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What We’re Reading (Week Ending 07 January 2024)

The best articles we’ve read in recent times on a wide range of topics, including investing, business, and the world in general.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

But since our readership-audience for The Good Investors is wider than our subscriber base, we think sharing the reading list regularly on the blog itself can benefit even more people. The articles we share touch on a wide range of topics, including investing, business, and the world in general.

Here are the articles for the week ending 07 January 2024:

1. What the Solow Model can teach us about China – Noah Smith

The question of why economies grow, and why they stop growing, is perhaps the most important in all of economics. It’s also an incredibly difficult question, both because growth is such a complicated thing, and because it’s very hard to compare different countries’ experiences. The Solow model is an incredibly simple thing — so simple that a bright junior high school student can learn it. It has only a few variables and a few parameters. There’s no possible way that such a simple model can tell us most of what we need to know about how and why economies grow.

And yet the amazing thing about the Solow model is that it does tell us a few incredibly important things about growth…

…The Solow model assumes that economic output — also called “production” or “GDP” — comes from three things:

Labor (human work effort)
Physical capital (machines, buildings, vehicles, etc.)
A mysterious quantity called “total factor productivity” (TFP), usually abbreviated as “A”, which some people associate with technology

The Solow model deals mostly with the question of how physical capital affects growth. Physical capital is everything you can build that helps you build other stuff or create economic value. It includes machine tools, factories, office buildings, delivery vans, highways, port infrastructure, trains, and so on. In my mind, the easiest type of physical capital to imagine is a machine tool — a sewing machine, or a drill press, or a lathe, or a nanolithography machine. So I’ll usually use machine tools as my examples of physical capital…

…Solow’s model makes three very reasonable assumptions about how physical capital works. It assumes:

You can build more physical capital by saving and investing.
Physical capital depreciates over time (at a constant rate).
On its own, physical capital has diminishing returns.

The first of these assumptions is actually the most subtle. The basic intuition is that you can set aside a certain amount of your GDP every year to build physical capital — like a farmer choosing to reserve a certain percentage of the annual corn harvest as seed corn for planting next year’s crop. But most real types of physical capital don’t work like seed corn — a sewing machine can’t be used to create new sewing machines, etc. So what Solow is actually assuming is that we set aside a certain percent of our financial income and use it to pay people to build more capital. It basically assumes a market where sewing machines, and any kind of capital, can be constructed for a price.

The second and third assumptions are pretty straightforward. If you’ve ever owned a car or a house, you know that it needs regular maintenance, upkeep, and renovation over time. If you have an economy with a lot of capital, some portion of it wears out every year and has to be replaced. (In the Solow model, the portion that wears out every year is just some constant percentage — 5% or 7% or whatever.) Replacing or maintaining your old worn-out capital costs money.

Finally, on its own, capital has diminishing returns. That means if you hold the number of people constant, eventually building more machines and buildings and such won’t help you produce more. To see why, just imagine one person trying to operate 100 sewing machines at once. They definitely wouldn’t produce 100 times as much as one person operating one sewing machine!…

…So what does this tell us about how economies grow? It tells us one incredibly important thing. It tells us that because of depreciation and diminishing returns, a country simply can’t build its way to infinitely high standards of living. If you just keep trying to build more and more, at some point depreciation overwhelms you. and you just can’t build any more!

Let’s think about that in the context of China. Over the last four decades, China has built an absolutely incredible amount of physical capital — in absolute terms, the most any country has ever built in history. Think about the vast, sprawling factories filled with robots and machines, the forests of skyscrapers and apartment buildings, the rivers of highways and high speed rail, the fleets of cars and trucks and buses and ships and planes.

The Solow model gives a simple explanation for how China was able to build this much, this fast: It had a very high rate of savings and investment, far higher even than other Asian countries.

China dedicated everything it had to building massive amounts of physical capital, leaving relatively little of its economic output left over for its people’s consumption. As a result, it grew very very quickly.

But the Solow model says that this type of growth has a limit. Just as the model would predict, China started hitting diminishing returns. We started seeing “ghost cities” and massive overcapacity in all sorts of industrial sectors. China’s incremental capital-output ratio — the dollars of capital needed in order to generate an additional dollar of GDP — rose relentlessly from around 2007…

…And just as the Solow model foretold, China’s growth is slowing:

Slowing growth from physical capital accumulation is the Solow model’s first big insight. The second is that it’s actually possible for a country to save and invest so much of its income, and build so much physical capital, that it actually makes its citizens poorer.

The reason is, again, depreciation. If you save and invest a huge fraction of your income — as China has done — you will build an enormous amount of physical capital. But the more you build, the more you have to pay to upkeep in the future. There’s a point called the “golden rule”, above which saving and investing more of your national income just forces your citizens to forego more and more consumption in order to stave off capital depreciation.

Does China save and invest more than Solow’s “golden rule” would suggest? It’s hard to tell. But if any country is above the healthy limit, it’s China. Note that in the Solow model, the optimal savings rate is lower if population growth is lower; China’s population is now shrinking, and its working-age population is falling rapidly. So the Solow model serves as a warning to China’s leaders that they should consider encouraging their people to consume more…

..Of course, there is a vast amount that the Solow model can’t tell us about economic growth. Most of those unanswered questions are contained in that innocuous little letter “A”; as one of Solow’s contemporaries put it, total factor productivity is a measure of our ignorance. One factor exacerbating China’s growth slowdown is that TFP growth has slowed relentlessly over the last three decades:

2. China’s Japanification – Robin Wigglesworth

The biggest question in global macroeconomics at the moment is whether China is on the cusp of a “balance sheet recession”. This sexy bit of economic jargon was first coined by Nomura’s Richard Koo to describe Japan’s lost decade(s), but is most commonly known as “Japanification”.

It can be described simply as a protracted period of deflation, economic sluggishness, property market declines and financial stress as households/companies/governments unsuccessfully try to deleverage after a debt binge…

…JPMorgan doesn’t explore cinematic history in its report but notes that there are a few eerie other similarities between China’s current predicament and Japan’s in the early 90s.

First is similarity in housing market development. As we have argued, China’s housing market correction since 2021 is not only cyclical (or policy-induced), it is also structural reflecting major changes in demand vs. supply in the housing market. This is similar to Japan’s housing market correction in the 1990s.

Second is similarity in financial imbalance, i.e. the pace of increase and level of debt problem. According to the BIS, China’s total non-financial credit/GDP ratio approached 297% of GDP by end-2022, similar to Japan in the 1990s. Also similarly, debt is mainly domestic and domestic saving rate is high in both countries.

The problem of population aging is also similar. The share of aged population (65 and above) was 12.7% in 1991 in Japan, similar to China in 2019 (12.6%).

On the external front, Japan’s large trade surplus vs. the US led to trade conflict, as exemplified in the Plaza Accord in 1985 (5-6 years before the start of Japan’s lost decade) and US-China tariff war that started in 2018. From a broader perspective, the rise of Japan (30 years ago) and China (right now) to challenge the status of the US as the largest economy in the world is quite similar, leading to the fight-back from the US that initially focuses on reducing the bilateral trade imbalance…

…Let’s look at what JPMorgan thinks are the “good” differences, before turning to the ugly. First of them (and JPMorgan reckons perhaps the most important difference) is a much lower urbanisation ratio in China.

China’s urbanization ratio was 65% in 2022, and if excluding migrant workers who live in urban areas but do not have the same privileges as urban citizens, the hukou ratio was only 47%. In Japan, urbanization ratio exceeded 77% in 1988. Lower urbanization ratio points at larger potential for productivity increase associated with labor migration from agricultural to non-agricultural sectors…

…Second, China has a much larger domestic market, a larger pool of STEM graduates and comprehensive manufacturing sectors. While China may be facing a more challenging external environment than Japan in the 1990s, there is also hope that China can achieve technology upgrade and commercialization in some areas…

…Third, perhaps somewhat debatably, we think China’s housing price overvaluation is less severe than Japan in the 1990s. This is in part due to prolonged administrative control on new home prices and in part due to solid income growth. Our estimates show that housing affordability has continued to be a big problem in tier-1 cities: it took 21.1 years of household income to buy a 90-sqm apartment in 2010, and 16.6 years of household income in 2022. By contrast, housing affordability is much better in tier-2 and tier-3 cities that account for the majority of China’s housing market. Using the same house price/income measure, the ratio fell from 13.4 in 2010 to 8.3 in 2022 in tier-2 cities, and from 10.2 in 2010 to 6.1 in 2022 in tier-3 cities.

Fourth, China’s capital account is not fully liberalized. This will reduce the risk of fire sale of domestic assets (mainly housing) to invest overseas…

…Lastly, the Chinese government has stronger control of both asset and liability sides of the debt problem. This could be a double-edge sword: it implies that the probability of a sudden-stop debt crisis is smaller in China, but the zombie parts of the economy will continue to stay and likely further expand, intensifying the moral hazard problem and weakening incentives for structural reforms. This may crowd out more productive activities in the economy and lead to faster-than-expected slowdown in economic growth…

…JPMorgan’s main concern is that China is actually ageing more rapidly than Japan was, which has led to predictions that it will ‘grow old before it grows rich(opens a new window)’ — a kind of demographics-caused middle-income trap.

In Japan’s case, the share of population aged 65 and above exceeded 10% in 1983, and exceeded 14% in 1994. The birth rate fell from 12.7 (per 1000 people) to 10.0 during that period. In China’s case, it took only 7 years (from 2014 to 2021) for the 65 plus population to increase from 10% to 14% of total population, and the birth rate has fallen faster from 13.8 (per 1000 people) to 7.5 during that period (and further down to 6.77 in 2022, similar to Japan in 2020 at 6.80). In addition, China’s total population started to decline in 2022, while Japan’s total population started to decline in 2008, nearly two decades after the start of the lost decade.

Second, China’s GDP per capita was around US$12,800 in 2022, much lower than Japan in 1991 at US$29,470. While lower GDP per capita may imply higher growth potential, it suggests that China is becoming old and high-indebted before it becomes rich…

…JPMorgan’s economists also point out that the global economic backdrop is worse for China than it was for Japan in the 1990s, and thinks the Chinese government has less scope for stimulative fiscal measures than is commonly assumed:…

…In recent years, technology decoupling from the US has replaced the tariff war to become the major challenge for China. Beyond the bilateral relationship with the US, the globalization process has slowed down notably after 2008 (when the share of global trade as % of global GDP peaked), in sharp contrast to the golden days of globalization in the 1990s. The Russia-Ukraine war in 2022 further accelerated global supply chain relocation, which weighs on China’s potential growth.

Moreover, the room of macro policy stimulus is more limited in China nowadays than Japan in early 1990s. On the fiscal side, government debt was 61.9% of GDP in Japan in 1991, the start of the housing bust. Government debt rose to 131% of GDP by 2000 in Japan. In China’s case, although central government debt was only 20% of GDP, if adding local government debt and LGFV debt, total public debt reached 95% of GDP by end-2022…

…JPMorgan warns that “the room for fiscal stimulus for China in the next 10 years is much smaller than Japan in the 1990s”. Nor do its economists think that China has any more scope to combat the economic miasma with monetary policy.

Similarly, on the monetary policy front, the BOJ’s policy rate was 8.1% in January 1991. The BOJ moved quickly after the housing bubble burst: by end-1993, the policy rate was cut to 2.4%; and in 1999, the BOJ became the first central bank to adopt zero interest rate policy. By comparison, China’s policy rate (7-day reverse repo rate) is already as low as 1.9%. The room for policy rate cuts for the PBOC, if deemed necessary, is much smaller than the BOJ in early 1990s…

…So why then does JPMorgan think that China isn’t about to suffer a Japan-style long-term balance sheet recession? It boils to the differences between “ordinary” economic downturns and Koo’s diagnosis of Japan’s pretty unique travails.

When asset prices fall, firms face binding borrowing constraints with balance sheet deteriorating, forced asset sales can further push asset prices lower and form a self-reinforcing downward spiral between asset prices and economic activities. In other words, asset price decline is critical in understanding the phenomenon of balance sheet recession.

Following this argument, balance sheet recession is not a reality yet in China. The Chinese government has adopted the strategy of protecting house prices but letting volumes correct dramatically. This is in sharp contrast to the Japan’s episode, when prices and volume fell simultaneously. As a consequence, the macro cost (sharp decline in volume activity and slower real estate investment) is larger in China, but the benefit is that financial risk associated with asset price decline has stayed under control.

Also Japan’s balance sheet recession manifested itself in a huge deleveraging by households and companies, but a massive increase in the government’s debt burden.

Corporate debt fell from the peak of 144.9 per cent of Japan’s GDP in 1993 to 99.4 per cent in 2004, and household fell from 71 per cent in 1999 to 60 per cent in 2007, even as government debt ballooned, pushing the overall burden for the economy as a whole higher.

In contrast, China’s debts have been building up across the board with hardly any interruptions since 2008, and this is likely to continue, according to JPMorgan…

…But the fact that Chinese debts have continued to rise and are likely to do so for the next few years — and that the property market hasn’t imploded yet — is not really an argument against China’s Japanification. Indeed, it might only indicate that a full-scale version just hasn’t started yet…

…But there are enough broad similarities to think that the overall disease — a protracted period of declining demographics, economic sluggishness, deleveraging and deflationary pressures that defies fitful government efforts to dispel the miasma — might end up being pretty similar.

3. 36 quick thoughts to end 2023 – Thomas Chua

#3 There’s zero benefit in dwelling on how luck shapes a person’s success. Instead, focus on controllable factors that can increase the probability of your success.

#4 As we progress in life, how we perceive wealth changes based on who we compare ourselves to. Define your ‘enough’ to avoid living your life solely pursuing wealth.

#5 If you don’t eat food that nourishes your body, sooner or later you’ll have to eat your medicine as food.

#6 Fast growth and quick wins are sexy in business and investing. Sustainable growth and compounding, however, are key to long-term outperformance…

#7 Just as food affects your body, the information you consume shapes your thoughts…

…#19 If you pursue any endeavors with half heartedness, your mind will become like a magnet for fear and doubts. When you encounter difficulties, you’ll come up with various reasons to tell yourself why you shouldn’t do it.

#20 The fastest way to end your life is to retire and do nothing.

#21 The biggest wall separating high achievers from the rest is excuses.

#22 Knowledge isn’t power. It’s a potential power. Only when knowledge is applied, it becomes power…

…#24 For a list of book recommendations, check out the bibliography section of books written by your favorite authors.

#25 You seldom regret what you did. You often regret what you didn’t do.

#26 More is not always better when setting goals. Reduce, reduce, reduce.

#27 Advice from people who are older aren’t laws. They’re like clothes. If it doesn’t fit you, try others.

#28 It’s inevitable to avoid pain in life. But suffering is optional…

…#32 Ordinary returns over a long time period will give you an extraordinary result…

…#34 No book can substitute the experience of navigating a stock market downturn. The best way to learn is to start.

#35 It’s not enough that you believe in investing for the long term. This idea must also be embraced by your spouse, family, and friends.

#36 Complexity gives you a false blanket of accuracy and control. It is usually the person who is able to explain things simply who knows what they are talking about.

4. The Nine Breakthroughs of the Year – Derek Thompson

1. CRISPR’s Triumph: A Possible Cure for Sickle-Cell Disease

In December, the FDA approved the world’s first medicine based on CRISPR technology. Developed by Vertex Pharmaceuticals, in Boston, and CRISPR Therapeutics, based in Switzerland, Casgevy is a new treatment for sickle-cell disease, a chronic blood disorder that affects about 100,000 people in the U.S., most of whom are Black.

Sickle-cell disease is caused by a genetic mutation that affects the production of hemoglobin, a protein that carries oxygen in red blood cells. Abnormal hemoglobin makes blood cells hard and shaped like a sickle. When these misshapen cells get clogged together, they block blood flow throughout the body, causing intense pain and, in some cases, deadly anemia.

The Casgevy treatment involves a complex, multipart procedure. Stem cells are collected from a patient’s bone marrow and sent to a lab. Scientists use CRISPR to knock out a gene that represses the production of “fetal hemoglobin,” which most people stop making after birth. (In 1948, scientists discovered that fetal hemoglobin doesn’t “sickle.”) The edited cells are returned to the body via infusion. After weeks or months, the body starts producing fetal hemoglobin, which reduces cell clumping and improves oxygen supply to tissues and organs.

Ideally, CRISPR will offer a one-and-done treatment. In one trial, 28 of 29 patients, who were followed for at least 18 months, were free of severe pain for at least a year. But we don’t have decades’ worth of data yet.

Casgevy is a triumph for CRISPR. But a miracle drug that’s too expensive for its intended population—or too complex to be administered where it is most needed—performs few miracles. More than 70 percent of the world’s sickle-cell patients live in sub-Saharan Africa. The sticker price for Casgevy is about $2 million, which is roughly 2,000 times larger than the GDP per capita of, say, Burkina Faso. The medical infrastructure necessary to go through with the full treatment doesn’t exist in most places. Casgevy is a wondrous invention, but as always, progress is implementation.

2. GLP-1s: A Diabetes and Weight-Loss Revolution

In the 1990s, a small team of scientists got to know the Gila monster, a thick lizard that can survive on less than one meal a month. When they studied its saliva, they found that it contained a hormone that, in experiments, lowered blood sugar and regulated appetite. A decade later, a synthetic version of this weird lizard spit became the first medicine of its kind approved to treat type 2 diabetes. The medicine was called a “glucagon-like peptide-1 receptor agonist.” Because that’s a mouthful, scientists mostly call these drugs “GLP-1s.”…

…3. GPT and Protein Transformers: What Can’t Large Language Models Do?…

…This spring, a team of researchers announced in Science that they had found a way to use transformer technology to predict protein sequences at the level of individual atoms. This accomplishment builds on AlphaFold, an AI system developed within Alphabet. As several scientists explained to me, the latest breakthrough suggests that we can use language models to quickly spin up the shapes of millions of proteins faster than ever. I’m most impressed by the larger promise: If transformer technology can map both languages and protein structures, it seems like an extraordinary tool for advancing knowledge.

4. Fusion: The Dream Gets a Little Closer

Inside the sun, atoms crash and merge in a process that produces heat and light, making life on this planet possible. Scientists have tried to harness this magic, known as fusion, to produce our own infinite, renewable, and clean energy. The problem: For the longest time, nobody could make it work.

The past 13 months, however, have seen not one but two historic fusion achievements. Last December, 192 lasers at the Lawrence Livermore National Laboratory, in California, blasted a diamond encasing a small amount of frozen hydrogen and created—for less than 100 trillionths of a second—a reaction that produced about three megajoules of energy, or 1.5 times the energy from the lasers. In that moment, scientists said, they achieved the first lab-made fusion reaction to ever create more energy than it took to produce it. Seven months later, they did it again. In July, researchers at the same ignition facility nearly doubled the net amount of energy ever generated by a fusion reaction. Start-ups are racing to keep up with the science labs. The new fusion companies Commonwealth Fusion Systems and Helion are trying to scale this technology…

...5. Malaria and RSV Vaccines: Great News for Kids

Malaria, one of the world’s leading causes of childhood mortality, killed more than 600,000 people in 2022. But with each passing year, we seem to be edging closer to ridding the world of this terrible disease.

Fifteen months ago, the first malaria vaccine, developed by University of Oxford scientists, was found to have up to 80 percent efficacy at preventing infection. It has already been administered to millions of children. But demand still outstrips supply. That’s why it’s so important that in 2023, a second malaria vaccine called R21 was recommended by the World Health Organization, and it appears to be cheaper and easier to manufacture than the first one, and just as effective. The WHO says it expects the addition of R21 to result in sufficient vaccine supply for “all children living in areas where malaria is a public health risk.”…

…6. Killer AI: Artificial Intelligence at War…

…In the world’s most high-profile conflict, Israel has reportedly accelerated its bombing campaign against Gaza with the use of an AI target-creation platform called Habsora, or “the Gospel.” According to reporting in The Guardian and +972, an Israeli magazine, the Israel Defense Forces use Habsora to produce dozens of targeting recommendations every day based on amassed intelligence that can identify the private homes of individuals suspected of working with Hamas or Islamic Jihad. (The IDF has also independently acknowledged its use of AI to generate bombing targets.)…

…Meanwhile, the war in Ukraine is perhaps the first major conflict in world history to become a war of drone engineering. (One could also make the case that this designation should go to Azerbaijan’s drone-heavy military campaign in the Armenian territory of Nagorno-Karabakh.) Initially, Ukraine depended on a drone called the Bayraktar TB2, made in Turkey, to attack Russian tanks and trucks. Aerial footage of the drone attacks produced viral video-game-like images of exploded convoys…

…But Russia has responded by using jamming technology that is taking out 10,000 drones a month. Ukraine is now struggling to manufacture and buy enough drones to make up the difference, while Russia is using kamikaze drones to destroy Ukrainian infrastructure.

7. Fervo and Hydrogen: Making Use of a Hot Planet…

…Eleven years ago, engineers in Mali happened upon a deposit of hydrogen gas. When it was hooked up to a generator, it produced electricity for the local town and only water as exhaust. In 2023, enough governments and start-ups accelerated their search for natural hydrogen-gas deposits that Science magazine named hydrogen-gas exploration one of its breakthroughs of the year. (This is different from the “natural gas” you’ve already heard of, which is a fossil fuel.) One U.S.-government study estimated that the Earth could hold 1 trillion tons of hydrogen, enough to provide thousands of years of fuel and fertilizer.

8. Engineered Skin Bacteria: What If Face Paint Cured Cancer?…

…Some common skin bacteria can trigger our immune system to produce T cells, which seek and destroy diseases in the body. This spring, scientists announced that they had engineered an ordinary skin bacterium to carry bits of tumor material. When they rubbed this concoction on the head of mice in a lab, the animals produced T cells inside the body that sought out distant tumor cells and attacked them. So yeah, basically, face paint that fights cancer…

…The ability to deliver cancer therapies (or even vaccines) through the skin represents an amazing possibility, especially in a world where people are afraid of needles. It’s thrilling to think that the future of medicine, whether vaccines or cancer treatments, could be as low-fuss as a set of skin creams.

5. TIP595: Stock Market History & The AI Bubble w/ Jamie Catherwood – Clay Finck and Jamie Catherwood

[00:34:02] Clay Finck: And then this also brought to mind another solution that could be brought about and that’s to restructure the debt. Are there examples in history that you’ve looked at where debt restructurings have occurred?

[00:34:15] Jamie Catherwood: Yeah. So in the U.S, it’s not something that tends to get acknowledged but in the first few years of our nation, we restructured our debt.

[00:34:26] Jamie Catherwood: I mean, that’s what Hamilton was tasked with doing when he. Assumed office as the first secretary of the treasury. When he came into his role in 89, 1789, there was a dire financial state. At that point, I’ll take you back to US history class from high school but before we had the constitution, we had the Articles of Confederation, which were designed to severely curtail the central government authority because obviously Americans were very fearful after having fought a war with a British monarch that any type of new government in the U.S. would fall kind of victim to a similar. And so the articles of confederation essentially gave Congress no power.

[00:35:16] Jamie Catherwood: And so, for example, they did not have the authority to collect taxes, which is insane. And so that means that during those years, there was not a lot of revenue coming in. And so even after the constitution was passed and the government we have today was put into place, there was a real problem because there were.

[00:35:34] Jamie Catherwood: It was not a lot of revenue coming in, but there had been massive accumulation of debt incurred during the revolutionary war to fight the British. And I mean, we owed, I think, like 80 million, a lot of it to foreign governments and when Hamilton took office, he had to write to the French government asking.

[00:35:54] Jamie Catherwood: For a delay in payments because the U.S. was basically struggling to get on its feet. In fact, in the 1st year of his time in office, he had to write to Washington President Washington saying that, if we don’t get the exact amount, but a certain amount of money into the treasury’s coffers in the next month, then we’re not going to be able to pay congressmen their salaries. And there are going to be a lot of other departments and cabinet positions that won’t be able to receive their funds because. we’re just so on the whole and so what Hamilton’s novel kind of idea was, and it was politically very challenging and a difficult thread to needle was he had to essentially convince American debt holders to exchange their existing higher paying debt and U.S. bonds that they owned for a public loan. Package of new debt securities that he would issue, which would have a lower interest rate, but his premise to these investors was the only alternative for continuing to pay out these higher interest rates would be to introduce new taxes or, raise higher taxes, both of which we know would lead to probably armed rebellion, as you can see, in the case of the whiskey rebellion, when there’s a whiskey tax introduced.

[00:37:10] Jamie Catherwood: And so if you want to really avoid that, then the only way we can do so is if you accept the fact that instead of being paid 6% interest on these bonds, we’re going to give you 4% interest going forward. And that was obviously a tough sell, especially when the nation was very divided and people were still very wary of strong central government implementing new taxes or having too much control and, changing their commitments to pay out what they had promised originally at 6%. And so that was very difficult, but in a matter of, I think, 2 years or so, he had successfully converted something like 98 % of the outstanding debt into this package of new securities that were lower paying, lower interest bearing securities and it saved. Tens of millions for the government and so that was restructuring literally at the founding of our nation. That was very successful. And one of the ways that he also was able to retire a lot of the debt, just kind of as an interesting side note, is by allowing investors to purchase shares of the Bank of the United States, which was kind of like an early central bank esque institution in the U.S. And the bank IPO ed on July 4th, 1791, I believe very patriotic IPO date and he allowed investors that held U.S. government bonds to pay for shares of the Bank of the United States with these bonds. So it was kind of a win for the government because, it injected capital into this new bank, but also it reduced the amount of debt outstanding that they would have to pay interest on by allowing someone to use like three government bonds to purchase one share of the Bank of the United States stock and so interesting and often under referenced example of a restructuring in U.S. history, because when there’s talk of debt restructurings or defaults, et cetera, people tend to pull out the line that U.S. has never defaulted on its debt or something like that.

[00:39:14] Jamie Catherwood: The reality is that there have been these moments in U.S. history where we were in pretty dire times and some novel solutions were needed…

…[00:40:37] Clay Finck: But then another major factor I sort of think about in terms of market efficiency is the massive impact of passive flows on index funds. And you did a write up that referenced the telegraph looking all the way back and investors first getting access to this quick information. So talk to us about the efficiency of markets and how that’s changed over time.

[00:40:58] Jamie Catherwood: Yeah. So what prompted kind of my recent interest in this again was a quote from Cliff Asness in a recent financial times article, but he said something along the lines of people that think technology. It’s going to make asset pricing markets more efficient are the same ones who 20 years ago said that social media would make us all like each other more, which I think is just a fantastic way to put it because definitely social media does not make us like each other more and has increased the divisiveness in society.

[00:41:31] Jamie Catherwood: But also, I mean, it makes sense on its face throughout history that when you suddenly get these innovations and kind of communication and data. That markets have become more efficient because people have more information. And while that’s certainly true to a certain extent, there is. It’s definitely nowhere near kind of an elimination of mispricing and, inefficient markets, because I remember when the telegraph cable first took over the world and people could get information in India to London, for example, on something like 8 hours where it used to take much longer.

[00:42:07] Jamie Catherwood: Someone said that there would be no need for crises moving forward because now all the information would simply be known. And I just loved the kind of matter of factness with, I can’t remember his name is Arthur something, but he was a person of high authority and he just. I just put it so bluntly as if why would we have panics and crashes moving forward?

[00:42:28] Jamie Catherwood: Because now everybody will have access to information at the tips of their fingers, at least in their day, that was considered tips of their fingers. And so how could there be more panics and crashes? And obviously, if anything, the 19th century had more panics and crashes than any century and so there is this.

[00:42:46] Jamie Catherwood: Just the belief that technology will always make markets extremely efficient but throughout history, you see the introduction of these technologies and the opposite occurs where, ironically, you know, when the telegraph and the ticker were introduced there was a study done that showed how the states that as their ticker subscriptions increased.

[00:43:09] Jamie Catherwood: Within each state, people started gravitating towards companies listed in their state and so basically a home country bias but at the state level, if you can imagine it, and people started just hurting into the same kind of like top 10 stocks within their state and instead of. The ticker and telegraph broadening the speculation across a broader set of stocks, people just continue to concentrate into the same names.

[00:43:39] Jamie Catherwood: And you see this throughout history in the 1600s, when markets in London during the 1690s were kind of going through their first bubble is this IPO bubble and kind of the first technology mania you saw a list of securities in one of the kind of market write ups market commentaries that was published every two weeks by this guy, John Houghton, he had a list of 20 securities that he monitored the prices of and even though.

[00:44:08] Jamie Catherwood: There were a couple of hundred securities trading on the London exchange, the vast majority of all trading volume on the exchange was concentrated into the same list of securities that he provided prices for in his market commentary every two weeks, and so while that’s not necessarily technology by modern standards, it’s still just shows that even when investors are presented with A lot of different stocks to invest in, they tend to concentrate into the same ones that everybody else does.

[00:44:35] Jamie Catherwood: And so it’s just this interesting phenomenon throughout history that technology does not necessarily change our approach to investing and, cause us to expand our universe of stocks to select from. And I think during COVID, we saw that same phenomenon with the Robinhood tracker. I don’t know if you remember that, but it showed just the level of trading on Robinhood that was concentrated in the top 10 most popular stocks.

[00:45:01] Jamie Catherwood: And it was just crazy to see even in this modern age, when literally you have unparalleled access to information at the tips of your fingers. That’s still, we kind of just heard into these same names as everyone else, even though you could be looking at a really exciting micro-cap stock or something

[00:45:18] Jamie Catherwood: And I could be looking at mid-smith cap stock doing something exciting, the energy sector or something like that but instead people tend to just kind of hurt into the same us large cap stocks.

Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. We currently have a vested interest in Alphabet. Holdings are subject to change at any time.

What We’re Reading (Week Ending 31 December 2023)

The best articles we’ve read in recent times on a wide range of topics, including investing, business, and the world in general.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

Here are the articles for the week ending 31 December 2023:

1. How Not to Be Stupid About AI, With Yann LeCun – Steven Levy and Yann LeCun

Steven Levy: In a recent talk, you said, “Machine learning sucks.” Why would an AI pioneer like you say that?

Yann LeCun: Machine learning is great. But the idea that somehow we’re going to just scale up the techniques that we have and get to human-level AI? No. We’re missing something big to get machines to learn efficiently, like humans and animals do. We don’t know what it is yet.

I don’t want to bash those systems or say they’re useless—I spent my career working on them. But we have to dampen the excitement some people have that we’re just going to scale this up and pretty soon we’re gonna get human intelligence. Absolutely not…

…Why are so many prominent people in tech sounding the alarm on AI?

Some people are seeking attention, other people are naive about what’s really going on today. They don’t realize that AI actually mitigates dangers like hate speech, misinformation, propagandist attempts to corrupt the electoral system. At Meta we’ve had enormous progress using AI for things like that. Five years ago, of all the hate speech that Facebook removed from the platform, about 20 to 25 percent was taken down preemptively by AI systems before anybody saw it. Last year, it was 95 percent…

…The company you work for seems pretty hell bent on developing them and putting them into products.

There’s a long-term future in which absolutely all of our interactions with the digital world—and, to some extent, with each other—will be mediated by AI systems. We have to experiment with things that are not powerful enough to do this right now, but are on the way to that. Like chatbots that you can talk to on WhatsApp. Or that help you in your daily life and help you create stuff, whether it’s text or translation in real time, things like that. Or in the metaverse possibly…

…One company that disagrees with that is OpenAI, which you don’t seem to be a fan of.

When they started, they imagined creating a nonprofit to do AI research as a counterweight to bad guys like Google and Meta who were dominating the industry research. I said that’s just wrong. And in fact, I was proved correct. OpenAI is no longer open. Meta has always been open and still is. The second thing I said is that you’ll have a hard time developing substantial AI research unless you have a way to fund it. Eventually, they had to create a for-profit arm and get investment from Microsoft. So now they are basically your contract research house for Microsoft, though they have some independence. And then there was a third thing, which was their belief that AGI [artificial general intelligence] is just around the corner, and they were going to be the one developing it before anyone. They just won’t.

How do you view the drama at OpenAI, when Sam Altman was booted as CEO and then returned to report to a different board? Do you think it had an impact on the research community or the industry?

I think the research world doesn’t care too much about OpenAI anymore, because they’re not publishing and they’re not revealing what they’re doing. Some former colleagues and students of mine work at OpenAI; we felt bad for them because of the instabilities that took place there. Research really thrives on stability, and when you have dramatic events like this, it makes people hesitate. Also, the other aspect important for people in research is openness, and OpenAI really isn’t open anymore. So OpenAI has changed in the sense that they are not seen much as a contributor to the research community. That is in the hands of open platforms…

…But isn’t an open source AI really difficult to control—and to regulate?

No. For products where safety is really important, regulations already exist. Like if you’re going to use AI to design your new drug, there’s already regulation to make sure that this product is safe. I think that makes sense. The question that people are debating is whether it makes sense to regulate research and development of AI. And I don’t think it does.

Couldn’t someone take a sophisticated open source system that a big company releases, and use it to take over the world? With access to source codes and weights, terrorists or scammers can give AI systems destructive drives.

They would need access to 2,000 GPUs somewhere that nobody can detect, enough money to fund it, and enough talent to actually do the job.

Some countries have a lot of access to those kinds of resources.

Actually, not even China does, because there’s an embargo.

I think they could eventually figure out how to make their own AI chips.

That’s true. But it’d be some years behind the state of the art. It’s the history of the world: Whenever technology progresses, you can’t stop the bad guys from having access to it. Then it’s my good AI against your bad AI. The way to stay ahead is to progress faster. The way to progress faster is to open the research, so the larger community contributes to it.

How do you define AGI?

I don’t like the term AGI because there is no such thing as general intelligence. Intelligence is not a linear thing that you can measure. Different types of intelligent entities have different sets of skills.

Once we get computers to match human-level intelligence, they won’t stop there. With deep knowledge, machine-level mathematical abilities, and better algorithms, they’ll create superintelligence, right?

Yeah, there’s no question that machines will eventually be smarter than humans. We don’t know how long it’s going to take—it could be years, it could be centuries.

At that point, do we have to batten down the hatches?

No, no. We’ll all have AI assistants, and it will be like working with a staff of super smart people. They just won’t be people. Humans feel threatened by this, but I think we should feel excited. The thing that excites me the most is working with people who are smarter than me, because it amplifies your own abilities.

But if computers get superintelligent, why would they need us?

There is no reason to believe that just because AI systems are intelligent they will want to dominate us. People are mistaken when they imagine that AI systems will have the same motivations as humans. They just won’t. We’ll design them not to.

What if humans don’t build in those drives, and superintelligence systems wind up hurting humans by single-mindedly pursuing a goal? Like philosopher Nick Bostrom’s example of a system designed to make paper clips no matter what, and it takes over the world to make more of them.

You would be extremely stupid to build a system and not build any guardrails. That would be like building a car with a 1,000-horsepower engine and no brakes. Putting drives into AI systems is the only way to make them controllable and safe. I call this objective-driven AI. This is sort of a new architecture, and we don’t have any demonstration of it at the moment.

2. China’s debt isn’t the problem – Michael Pettis

IMF in its latest Global Debt Monitor highlighted how China’s overall debt-to-GDP ratio has increased fourfold since the 1980s. It has been particularly rapid over the past decade. Over half of the increase in the entire global economy’s debt-to-GDP ratio since 2008 is solely due to an “unparalleled” rise in China, according to the IMF.

That $47.5tn total debt pile has grown further in 2023, which might mean that China has now finally overtaken the US in debt-to-GDP terms…

…However, the surge in Chinese debt is not itself the problem but rather a symptom of the problem. The real problem is the cumulative but unrecognised losses associated with the misallocation of investment over the past decade into excess property, infrastructure and, increasingly, manufacturing.

This distinction is necessary because much of the discussion on resolving the debt has so far focused on preventing or minimising disruptions in the banking system and on the liability side of balance sheets.

These matter — the way in which liabilities are resolved will drive the distribution of losses to various sectors of the economy — but it’s important to understand that the problems don’t emerge from the liability side of China’s balance sheets. They emerge from the asset side…

…In proper accounting, investment losses are treated as expenses, which result in a reduction of earnings and net capital. If, however, the entity responsible for the investment misallocation is able to avoid recognising the loss by carrying the investment on its balance sheets at cost, it has incorrectly capitalised the losses, ie converted what should have been an expense into a fictitious asset.

The result is that the entity will report higher earnings than it should, along with a higher total value of assets. But this fictitious asset by definition is unable to generate returns, and so it cannot be used to service the debt that funded it. In an economy in which most activity occurs under hard-budget constraints, this is a self-correcting problem. Entities that systematically misallocate investment are forced into bankruptcy, during which the value of assets is written down and the losses recognised and assigned.

But, as the Hungarian economist János Kornai explained many years ago, this process can go on for a very long time if it occurs in sectors of the economy that operate under soft-budget constraints, for example state-owned enterprises, local governments, and highly subsidised manufacturers.

In these cases, state-sponsored access to credit allows non-productive investment to be sustained. And as economic activity shifts to these sectors, the result can be many years of unrecognised investment losses during which both earnings and the recorded value of assets substantially exceed their real values. Because the debt that funds this fictitious investment cannot be serviced by the investment, the longer it goes on, the more debt there is.

But once these soft-budget entities are no longer able — or willing — to roll over and expand the debt, they will then be forced to recognise that the asset side of the balance sheet simply doesn’t generate enough value to service the liability side. Put another way, they will be forced to recognise that the real value of the assets on their balance sheets are less than their recorded value.

That is the real, huge and intractable problem China faces…

…The third and most important impact is what finance specialists call “financial distress” costs. In order to protect themselves from being forced directly or indirectly to absorb part of the losses, a wide range of economic actors — workers, middle-class savers, the wealthy, businesses, exporters, banks, and even local governments — will change their behaviour in ways that undermine growth.

Financial distress costs rise with the uncertainty associated with the allocation of losses, and what makes them so severe is that they are often self-reinforcing. As we’ve seen with the correction in China’s property sector, financial distress costs are almost always much higher than anyone expected.

The point is that resolving China’s debt problem is not just about resolving the liability side of the balance sheet. What matters more to the overall economy is that asset-side losses are distributed quickly and in ways that minimise financial distress costs. That is why restructuring liabilities must be about more than protecting the financial system. It must be designed to minimise additional losses.

3. The pharma industry from Paul Janssen to today: why drugs got harder to develop and what we can do about it – Alex Telford

The biopharmaceutical industry expends huge sums shepherding drug candidates through the development gauntlet and satisfying regulatory requirements. In 2022, the industry spent around $200 billion on R&D, more than four times the US National Institute of Health’s (NIH) budget of $48 billion. Pharmaceuticals is the third most R&D intensive sector in the OECD countries.

The bulk of that spending goes towards clinical trials and associated manufacturing costs; roughly 50% of total large pharma R&D spend is apportioned to phase I, II, and III trials compared to 15% for preclinical work. While early phases may cull more candidate compounds in aggregate, the cost of failure is highest during clinical development: a late-stage flop in a phase III trial hurts far more than an unsuccessful preclinical mouse study. By the time a drug gets into phase III, the work required to bring it to that point may have consumed half a decade, or longer, and tens if not hundreds of millions of dollars.

Clinical trials are expensive because they are complex, bureaucratic, and reliant on highly skilled labour. Trials now cost as much as $100,000 per patient to run, and sometimes up to $300,000 or even $500,000 per patient for resource-intensive designs, trials using expensive standard of care medicines as controls or as part of a combination, or in conditions with hard-to-find patients (e.g., rare diseases). When these costs are added on top of other research and development expenditures, like manufacturing, a typical phase I program with 20-80 trial participants can be expected to burn around $30m. Phase III programs, involving hundreds of patients, often require outlays of hundreds of millions of dollars. Clinical trials in conditions where large trials with tens of thousands of patients are standard, such as cardiovascular disease or diabetes, can cost as much as $1 billion.

Because executing late stage clinical trials and manufacturing enough of the drug to cover them is so expensive, companies prefer to manage risk by conducting studies sequentially, even though many steps could in principle be done in parallel.

A major reason that COVID-19 vaccine development was so fast was not because shortcuts were taken, but that the funding from operation warp speed and advance purchase agreements allowed companies to parallelize much of the process, scale up manufacturing early, and jump quickly into phase IIIs because they were insulated from the financial risk of failure. Early trial phases were combined in multiphase designs, Pfizer commandeered existing manufacturing infrastructure and repurposed it for COVID-19 vaccine production, and employees and regulators worked around the clock. The FDA and other regulators took reviewers off of non-COVID-19 drugs and redeployed them to review the COVID-19 vaccines; there were essentially no delays in safety reviews that you would otherwise see in other clinical trials. The little delays that crop up in development were powered through with extra manpower and resources: at one point during Operation Warp Speed the military recovered a vital piece of equipment needed to manufacture Moderna’s vaccine from a stalled train, and put it on an aeroplane so it could arrive in time. While the vaccines were approved under expedited emergency use regulatory pathways, they were nevertheless rigorously tested. Allocating such extensive resources for every new drug, as was done during the pandemic, is unsustainable and comes with substantial opportunity cost.

In business-as-usual times, the industry’s expenditure on drug R&D nets us about 40 new US FDA drug approvals a year — and a similar number (though not always exactly the same drugs) approved by the equivalent agencies in other regions, as well as some new indications for existing drugs.

All that money spent by the industry on R&D appeared to go a lot further in the past10. Despite continued growth in biopharmaceutical R&D expenditure, we have not seen a proportionate growth in output. Industry R&D efficiency — crudely measured as the number of FDA approved drugs per billion dollars of real R&D spend — has (until recently) been on a long-term declining trajectory11. This trend has been sardonically named “Eroom’s law” – an inversion of Moore’s law. Accounting for the cost of failures and inflation, the industry now spends about $2.5 billion per approved drug, compared to $40 million (in today’s dollars) when Janssen was starting out in 1953…

…Even though we’re spending more money than ever before, historical statistics on drug candidate failure rates suggest that we haven’t really gotten much better at developing drugs that succeed where it counts — in clinical trials. The real bottleneck is not finding drug candidates that bind and modulate targets of interest, it’s finding ones that actually benefit patients. Almost paradoxically, despite huge improvements in the technologies of drug discovery, the rate of new drug launches has hardly shifted in 50 years. High-throughput screening, new model systems, machine learning, and other fancy modern techniques have done little to change the statistic that 9 in 10 drug candidates that start clinical trials will fail to secure approval.

What’s behind this ‘Red Queen’ effect, where we seem to be expending more and more resources to keep running at roughly the same speed?

For one, as we’ve seen across scientific fields, new ideas are getting harder to find. There are more academic researchers than ever — 80,000 in the 1930’s vs. 1.5 million today in the USA — yet we have not seen a proportionate growth in the rate of meaningful discoveries. This may be because ideas are getting inherently more difficult to find, or it may be that the institutions and processes of science have become less effective: bogged down in bureaucracy, sclerotic, chasing the wrong metrics, and thereby limiting the impact of individual researchers.

The biopharmaceutical business is built on top of basic discoveries, and so it is not immune from this general trend afflicting all of science. Without the discovery of methods to stabilise coronavirus spike proteins and enhance immunogenicity prior to the pandemic, it’s unlikely that we would have had effective vaccines for COVID-19 as fast as we did. Imatinib, a breakthrough targeted therapy for a rare blood cancer, was predicated on the discovery of the mutant protein produced by the “Philadelphia chromosome” rearrangement. In support of the ‘low hanging fruit’ argument is data showing changes in the landscape of drug targets over time: compared to past decades, drugs in development are now much more frequently going after targets that would have historically been viewed as intractable. Modern protein targets are more likely to be disordered, with shallow or non-existing pockets for small molecules to bind, or otherwise difficult to interact with.

The more important reason for the decline in R&D efficiency, however, is that it is not enough for drugs to simply be novel and safe, they must also improve meaningfully over the available standard of care, which may include a large armamentarium of effective and cheap older drugs.

This is the so-called ‘better than Beatles’ problem. Imagine if in order to release new music it needed to be adjudicated as better than ‘Hey Jude’, or ‘Here comes the sun’ in a controlled experiment. New experimental music might have a hard time getting past the panel, and wouldn’t have the chance to refine its sound in future iterations. The situation for new drugs is somewhat analogous…

…Yet, even though there are major forces pushing against drug developers, there is a sense that the industry is still underperforming, and that it could do more. One reason for optimism can be seen in the recent flattening of the slope of Eroom’s law following decades of declining productivity. It remains to be seen whether the recent uptick is a sustained turnaround or not. The pessimistic view is that it is illusory, a result of how drugmakers have side-stepped fundamental productivity issues by focusing on developing drugs for niche subpopulations with few or no options where regulators are willing to accept less evidence, it’s easier to improve on the standard of care, and payers have less power to push back on higher prices: rare disease and oncology in particular. It’s no coincidence that investment has flowed into areas where regulatory restrictions have been relaxed and accelerated approvals are commonplace: 27% of FDA drug approvals in 2022 were for oncology, the largest therapeutic area category, and 57% were for rare/orphan diseases.

There is however, a more charitable and optimistic take for the flattening and possible reversal of Eroom’s law. The first possibility is that advances in basic science are finally being widely adopted in the drug development process and bearing fruit. Historically, it takes upwards of 20 years for new drug targets to lead to new medicines. Consider that the sequencing of the human genome was completed in 2003; genomics research has by now improved our understanding of many relatively simple monogenic genetic disease, and has identified new targets for more common conditions through genome-wide association studies (GWAS) that look for associations between gene variants and disease phenotypes in large populations. The PCSK9 inhibitors alirocumab and evolucumab, as an archetypal example, were developed after screening for genetic mutations in families with elevated cholesterol levels identified the PCSK9 gene as a key driver of cholesterol regulation. Drug programs with genetic support are more likely to succeed, and we may have only recently truly started to benefit from our improved understanding of human genetics.

4. Peter Lynch 1994 National Press Club Lecture (transcript here)- Monroe Carmen and Peter Lynch

Peter Lynch: And if you can’t explain – I’m serious – you can’t explain to a 10 year old in two minutes or less why you own a stock, you shouldn’t own it. And that’s true, I think, about 80% of people that own stocks.

And this is the kind of stock people like to own. This is the kind of company people adore owning. This is a relatively simple company. They make a very narrow, easy to understand product. They make a 1 MB SRAM CMOS bipolar risk floating point data, I/O array processor with an optimising compiler, a 16-dual port memory, a double diffused metal oxide semiconductor monolithic logic chip with a plasma matrix vacuum fluorescent display. It has a 16 bit dual memory. It has a Unix operating system, four whetstone megaflop polysilicone emitter, a high bandwidth – that’s very important – six gigahertz metalization communication protocol, an asynchronous backward compatibility, peripheral bus architecture, four wave interweave memory, a token ring and change backplane. And it does in 15 nanoseconds of capability. Now, if you own a piece of crap like that, you will never make money. Never. Somebody will come along with more wetstones or less wetstones or a big omega flop or a small omega flop. You won’t have the foggiest idea what’s happened. And people buy this junk all the time.

I made money in Dunkin Donuts. I can understand it. When there was recessions, I didn’t have to worry about what was happening. I could go there and people were still there. I didn’t have to worry about low price Korean imports. I can understand it. And you laugh. I made 10 or 15 times my money in Dunkin’Donuts. Those are the kind of stocks I can understand. If you don’t understand, it doesn’t work…

…Peter Lynch: I’m trying to convince people there is a method. There are reasons for stocks that go up. Coca Cola, this is very magic. It’s a very magic number. Easy to remember. Coca Cola is earning 30 times per share what they did 32 years ago. The stock has gone up 30 fold. Bethlehem Steel is earning less than they did 30 years ago. The stock is half its price of 30 years ago. Stocks are not lottery tickets. There’s a company behind every stock. The company does well. The stock does well. It’s not that complicated…

…Peter Lynch: Considering there’s not that many billionaires on the planet, I had logic – so I had syllogism and studied these when I was at Boston College – there can’t be that many people who can predict interest rates because there’d be lots of billionaires and no one can predict the economy.

A lot of people in this room were around in 1981 and 82 when we had a 20% prime rate with double digit inflation, double digit digit unemployment. I don’t remember anybody telling me in 1981 about it. I didn’t read – I study all this stuff. I don’t remember anybody telling we’re going to have the worst recession since the Depression. So what I’m trying to tell you, it’d be very useful to know what the stock market is going to do. It’d be terrific to know that the Dow Jones average year from now would be X, that we’re going to have a full scale recession or interest rate is going to be 12%. That’s useful stuff. You never know it though. You just don’t get to learn it. So I’ve always said if you spend 14 minutes a year in economics, you’ve wasted 12 minutes. And I really believe that.

Now, I have to be fair. I’m talking about economics in the broad scale, predicting the downturn for next year or the upturn, or M1 and M2, 3B, and all these all these M’s. I’m talking about economics, to me, is you talk about scrap prices. When I own auto stocks, I want to know what’s happening to used car prices. When used car prices are going up, it’s a very good indicator. When I own hotel stocks, I want to know hotel occupancies. When I own chemical stocks, I want to know what’s happening to price of ethylene. These are facts. If aluminium inventories go down five straight months, that’s relevant. I can deal with that. Home affordability, I want to know about, when I own Fannie Mae or I own a housing stock, these are facts. There are economic facts and there’s economic predictions. And economic predictions are a total waste.

And interest rates. Alan Greenspan is a very honest guy. He would tell you that he can’t predict interest rates. He could tell you what short rates are going to do in the next six months. Try and stick him on what the long term rate will be three years from now. He’ll say, “I don’t have any idea.” So how are you, the investor, supposed to predict interest rates if the Head of the Federal Reserve can’t do it? So I think that’s – But you should study history, and history is the important thing you learn from.

What you learn from history is the market goes down. It goes down a lot. The math is simple. There’s been 93 years, a century. This is easy to do. The market’s had 50 declines of 10% or more. So 50 declines in 93 years, about once every two years the market falls 10%. We call that a correction. That means – that’s a euphemism for losing a lot of money rapidly, but we call it a correction. So 50 declines in 93 years, about once every two years the market falls 10%. Of those 50 declines, 15 have been 25% or more. That’s known as a bear market. We’ve had 15 declines in 93 years. So every six years the market’s going to have a 25% decline. That’s all you need to know…

…Peter Lynch: So you only need a few stocks in your lifetime. They’re in your industry. I think of people – if you’d worked in the auto industry, let’s say you’re an auto dealer the last 10 years. You would have seen Chrysler come up with the minivan. If you’re a Buick dealer, a Toyota dealer, Honda dealer, you would have seen the Chrysler dealership packed with people. You could have made 10 times your money on Chrysler. A year after the minivan came out, Ford introduces the Taurus Sable, the most successful line of cars in the last 20 years. Ford went up sevenfold on the Taurus Sable. So if you’re a car dealer, you only need to buy a few stocks every decade…

…Peter Lynch: And then I want to conclude with, there’s always something to worry about. If you own stocks, there’s always something to worry about. You can’t get away from it. What happens in the 50s, people were worried about the only reason we got out of the depression was World War II. We got another recession in the early 50s. We said, “We’re going to go right back into a depression.” People worried about a Depression in the 50s and were worried about nuclear war. Back then, the little warheads they had then, they couldn’t blow up McLean, West Virginia, or McLean, Virginia, or Charlestown. Now, all these countries that end in ‘stan – there’s nine of these ‘stan countries that have come out of Russia. They all have enough warheads to blow the world up, and no one worries about.

When I was a kid, people were building fallout shelters and we used to have this civil defense drill. Remember this one in high school? You get under your desk. I never thought even then that was a particularly good thing to do. They’d blow us and some people put a hat would, all get under our desk. But in the ‘50s, people wouldn’t buy stocks. Except for the ‘80s, the ‘50s was the best decade in the century of the stock market, and people wouldn’t buy stocks in the ‘50s because they’re worried about nuclear war and they’re worried about depression. Remember when oil went from $4 to $40 and it was going to go to $100 and we’re going to have a depression. Remember that one? Well, about three years later, the same experts, now higher paid, oil is now at $10. They said it was going to go to $4 and we’re going to have a depression…

…Monroe Carmen: Are you concerned about the volatility in the financial markets today? Do you think something needs to be done to reduce it?

Peter Lynch: I love volatility. I remember when in 1972, the market went down dramatically and Taco Bell went from $14 to $1. They had no debt, they never had a restaurant close. And I started buying at $7, but I kept onto it and it went to $1. And it was the largest position in Magellan in 1978 when it was bought out for $42 by PepsiCola. And I think it would have gone to $400 if they didn’t buy it out. I think volatility is terrific.

I think these collars are very important. I don’t think the market going up 80 points one day and down 80 the next is a good thing for the public. I think that’s not a very good thing, but I think all these collars and all these other things to keep the volatility down each day is important. But the market’s going to go up and down. Human nature hasn’t changed a lot in 25,000 years and some event will come out of left field and the market will go down. Or the market will go up. So volatility will occur. Markets will continue to have these ups and downs. I think that’s a great opportunity if people can understand what they own. If they don’t understand what they own, they can own mutual funds. Try and figure out mutual funds they own and keep adding to it.

Basically, corporate profits have grown about 8% a year historically. So corporate profits double about every nine years. The stock market ought to double about every nine years. So I think the next market is about 3,800 today, 3,700. I’m pretty convinced the next 3,800 points will be up, it won’t be down. The next 500 points, the next 600 points, I don’t know which way they’re going. So the market ought to double in the next eight or nine years, it ought to double again in the eight or nine years after that because profits will go up 8% a year and stocks will follow. That’s all there is to it…

…Peter Lynch: October has always been a special month. I remember in 1987 I was very convinced that the market was not in trouble and I didn’t worry about things. And Carol and I had planned this great golf vacation to Ireland. And we’re going to visit one course and stay in a little house and visit another. Go all along the west coast of Ireland and play golf. And we left on a Thursday night and the market went down 55 points that day, which was not too good. And the next day we got to Ireland. Because of the time difference, we’d completed our day and I got back to hotel and I called and the market had gone down 112 on Friday. I said to Carolyn, “I think if the market goes down on Monday, we’re going to have to go back.” We stayed there for the weekend and on Monday the market went down 508 points and my fund went from, I think, $12 billion to $8 billion and that gets your attention. In two working days. I said, by the end of this week, I’d have no funds.

Now, there wasn’t a lot I could do. I mean, here I was on Monday, because the market didn’t open by 12:00 – it was in Ireland, it was still 07:00 in New York. So we did spend that day and we played around golf in the morning. Then we went somewhere and sort of watched the market deteriorate. And I did come back. There wasn’t nothing I could do. I mean, just nothing I could do about it. But I think my shareholders, they called up and they said, “What’s Lynch doing?” They said, “Well, he’s on the 6th hole and he’s even par up to now, but he’s in a trap. This could be a triple bogey here. This could be a big inning.” And I don’t think that’s exactly what they want to hear. So I could do something about this damn thing. So I came back home and suffered with everybody else…

…Peter Lynch: I had this biggest position in my fund one time was Hanes, which owned Leggs and was a huge stock. And it was bought eventually by Consolidated Foods and it was the best division of Consolidated Foods. But it’s my biggest position. Made a monopoly on this Leggs. And Leggs is a really big hit. And I knew somebody would come along with a new product, and it was – Kaiser Roth introduced No Nonsense. I was worried that this thing was better and I couldn’t quite figure out what was going on. So I went to the supermarket and I bought 62 pairs of No Nonsense. Different colors, different shapes, different – they must have wondered what kind of house I had when I was going back. But I brought it in. I brought to the office and I passed that to anybody, male or female, anybody who wanted these things, just take them home and tell me how it is. And they came back in about three weeks and they said, it’s not as good. And that’s what research is. That’s all it was. And I held onto Hanes and the stock was a huge stock. So that’s what it’s about.

5. From Penny-Farthings to Pounds: The Great British Bicycle Bubble of 1896 – Nicholas Vardy

The bicycle’s humble beginnings can be traced back to the “dandy horse” – a pedal-less bike patented in Germany in 1818. Over the next half-century, inventors tweaked the design. In the 1860s, a French enthusiast added pedals and a rotary crank to the dandy horse, creating a rudimentary version of the modern bicycle.

However, the later penny-farthing design, with its oversized front wheel, proved hazardous and cumbersome. It wasn’t until the 1890s that the innovations of chain-driven transmission captured the British public’s imagination. It was also when John Boyd Dunlop invented the pneumatic tire in 1887, making it easy to ride bicycles on hard roads.

Overnight, the bicycle became a technological marvel and a revolutionary new mode of transportation.

What accounted for the bicycle’s remarkable early success?

First, the bicycle liberated the British public from the constraints of railway schedules. The bicycle became synonymous with the freedom to travel when you want, where you want.

Second, the bicycle was cheaper to buy and maintain than horses. It also provided a much-needed solution to the horse manure-laden streets of London.

Third, even women could ride bicycles. That alone doubled the size of its potential market. By 1895, the bicycle came to represent feminine independence.

The bicycle had a large effect on Britain’s infrastructure.

Much like their counterparts did for railroads 60 years before, cycling organizations began to lobby for a network of good roads to connect cities and rural communities. The first roads were built for commuters and travelers on cycles, not in cars.

With every successful new road, the pool of consumers and their need for a bicycle grew. Predictions of hypergrowth abounded. Companies were keen to meet the seemingly endless demand…

…The venture capitalists of their day in the United States and Britain quickly pounced. They bought up Bicycle companies. They bolstered balance sheets with vast amounts of intangible goodwill and patents. This financial sleight of hand allowed them to leverage companies up to invest in increased production.

As a result, the 1890s saw a tremendous boom in bicycle shares in the Birmingham stock exchange, not dissimilar to today’s EV boom.

In 1896, there were roughly 20 British bicycle companies. But demand was quickly outpacing supply. Enter Ernest Terah Hooley, a property dealer from Birmingham, who saw an opportunity. He bought a company called Pneumatic Tyre for a staggering 3 million pounds, a hefty premium given its modest profits.

Thanks to Hooley’s sales prowess, shares in the newly renamed Dunlop Pneumatic Tyre Company skyrocketed by 1,138% in the spring of 1896. Other British bicycle companies followed suit, with their share prices tripling. Speculators made fortunes overnight, and more and more people flocked to get in on future growth.

In 1896 alone, 363 cycle, tube, or tire firms were listed on the London Stock Exchange, with another 238 added in the first half of 1897. The British press hailed the bicycle as a revolutionary technology. The Financial Times even dedicated a daily page to the share prices of bicycle companies…

…Then, the narrative began gradually to shift.

Cycles were made not just in Birmingham but also in the United States.

Suddenly, advances in manufacturing meant new bicycles flooded the market.

Investors learned that expansion in the market did not necessarily translate into the same profit growth.

Competition soon drove prices down. Profit margins fell…

…The bicycle companies had become overleveraged. Vast orders anticipated that failed to come through. You only need to buy a new bicycle every five or ten years. The market became saturated. Sales growth entered a slow-motion collapse. Intense competition led to oversupply and plummeting prices.

Meanwhile, technology had advanced. Other competitors emerged. The automobile was even more of a game-changer than the bicycle. The fortunes associated with the bicycles’ promise of hypergrowth dissipated rapidly.

Only with the benefit of hindsight did it become clear that bicycles were a bubble…

…By December 1897, an index of bicycle-related stocks had plummeted by 40%. In 1898, bicycle stocks traded at an average of 71% below their peaks. More than 80% of the companies participating in the 1890s British bicycle boom went bust.

Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. We currently have a vested interest in Meta Platforms. Holdings are subject to change at any time.

What We’re Reading (Week Ending 24 December 2023)

The best articles we’ve read in recent times on a wide range of topics, including investing, business, and the world in general.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

Here are the articles for the week ending 24 December 2023:

1. Google DeepMind used a large language model to solve an unsolved math problem – Will Douglas Heaven

Google DeepMind has used a large language model to crack a famous unsolved problem in pure mathematics. In a paper published in Nature today, the researchers say it is the first time a large language model has been used to discover a solution to a long-standing scientific puzzle—producing verifiable and valuable new information that did not previously exist. “It’s not in the training data—it wasn’t even known,” says coauthor Pushmeet Kohli, vice president of research at Google DeepMind…

…Google DeepMind’s new tool, called FunSearch, could change that. It shows that they can indeed make discoveries—if they are coaxed just so, and if you throw out the majority of what they come up with.

FunSearch (so called because it searches for mathematical functions, not because it’s fun) continues a streak of discoveries in fundamental math and computer science that DeepMind has made using AI. First AlphaTensor found a way to speed up a calculation at the heart of many different kinds of code, beating a 50-year record. Then AlphaDev found ways to make key algorithms used trillions of times a day run faster.

Yet those tools did not use large language models. Built on top of DeepMind’s game-playing AI AlphaZero, both solved math problems by treating them as if they were puzzles in Go or chess. The trouble is that they are stuck in their lanes, says Bernardino Romera-Paredes, a researcher at the company who worked on both AlphaTensor and FunSearch: “AlphaTensor is great at matrix multiplication, but basically nothing else.”

FunSearch takes a different tack. It combines a large language model called Codey, a version of Google’s PaLM 2 that is fine-tuned on computer code, with other systems that reject incorrect or nonsensical answers and plug good ones back in.

“To be very honest with you, we have hypotheses, but we don’t know exactly why this works,” says Alhussein Fawzi, a research scientist at Google DeepMind. “In the beginning of the project, we didn’t know whether this would work at all.”

The researchers started by sketching out the problem they wanted to solve in Python, a popular programming language. But they left out the lines in the program that would specify how to solve it. That is where FunSearch comes in. It gets Codey to fill in the blanks—in effect, to suggest code that will solve the problem.

A second algorithm then checks and scores what Codey comes up with. The best suggestions—even if not yet correct—are saved and given back to Codey, which tries to complete the program again. “Many will be nonsensical, some will be sensible, and a few will be truly inspired,” says Kohli. “You take those truly inspired ones and you say, ‘Okay, take these ones and repeat.’”

2. How Energy Traders Left A Country In The Cold – Stephen Stapczynski and Faseeh Mangi

Within a few weeks, Alleyne’s colleagues identified a candidate: Gunvor’s deal with Pakistan, which depends heavily on LNG but is a far smaller customer than major importers such as China and Japan. After some internal debate, the traders ran the idea of scrapping it past the firm’s legal team and decided to proceed. When the Russian army invaded Ukraine on Feb. 24, 2022, gas prices soared more than 150% in 11 days. Around the same time, according to people familiar with the events, Gunvor stopped responding to communications from the Pakistani government. Then it terminated Pakistan’s deal, saying the country had underpaid for one of its LNG shipments. (Pakistan disputes this.)

Under the terms of the contract, Gunvor was supposed to supply Pakistan with five tankers’ worth of LNG over the next several months. Instead, ship-tracking data show, Gunvor sent the cargoes to countries including the UK and Italy, where buyers paid the “spot,” or market, price. If the gas had been delivered to Pakistan as originally planned, the value of the sales would have been about $200 million, according to calculations by Businessweek. By the same arithmetic, Gunvor’s traders unloaded it for more than $600 million. Some would receive seven-figure bonuses for the year, the highest of their careers.

Gunvor’s decision to redirect its supplies—and other canceled gas deliveries by Eni SpA, a state-controlled Italian energy group—helped prompt an energy crisis in Pakistan that continues today. The nation of 240 million people, which has a per capita gross domestic product of just over $1,500, uses natural gas to heat homes, power industry and even run cars and buses. When it ran short, factories were forced to shut or dramatically cut their output, throwing workers into poverty; so were fertilizer plants, threatening food production. As it scrambled to procure replacement LNG, Pakistan paid record spot-market prices, draining its modest foreign currency reserves and pushing it to the brink of default. Now its government is trying to implement economic reforms after receiving a bailout from the International Monetary Fund before elections scheduled in early 2024…

…There’s no suggestion that Gunvor or Eni acted illegally. Both appear to have operated within the bounds of their contracts—albeit in a way that’s all but unique in an industry where suppliers have traditionally done whatever they can to meet customers’ need for gas. Moreover, Pakistan’s woes are the result of much more than a fuel shortage. Successive governments—some installed through military coups—have mismanaged its economy for decades. Notably, politicians have long subsidized power and gas rates, providing little incentive for energy efficiency and forcing the government to pick up the difference between the true cost and what consumers pay.

The situation nonetheless provides a stark example of how traders in the cutthroat world of commodities can profit at the expense of some of the world’s least developed nations. When they agreed to long-term gas deals, Pakistani officials thought they were protecting their economy and citizens from the vagaries of commodity markets. Instead they learned just how quickly, and brutally, those markets could turn against them…

…For countries that can’t meet their energy needs domestically, LNG provides major benefits. Until it was commercialized in the 1960s, the most common way to ship large quantities of gas was through pipelines, which have obvious disadvantages for places that are isolated, far from reserves or both. By contrast, a tanker full of LNG can be sent to any port with a so-called regasification terminal, where the fuel is heated up into usable form. To ensure reliable supplies, governments and utilities try to make long-term LNG deals to guarantee deliveries at a relatively stable price, rather than take their chances on the spot market. Even a single shipment that arrives late—or, worse, not at all—can have a significant impact on local energy supply.

Pakistan’s entry into the LNG market was engineered by former Minister of Petroleum and Natural Resources Shahid Khaqan Abbasi, who’d worked in the Saudi energy industry before shifting to politics. (He later served as prime minister.) In 2016, Abbasi made a $15 billion, government-to-government deal for LNG imports from Qatar. The shipments made up for dwindling production from domestic gas fields and eased conditions for Pakistani companies almost overnight. GDP grew more than 5% in 2016, the biggest rise in more than a decade, in part because of stronger output from large manufacturers.

Abbasi wanted to do more, and he opened two additional requests for LNG contracts: one for a five-year supply deal, the other for as long as 15 years. Roughly two dozen companies expressed interest, including Gunvor and Eni. Some had concerns about dealing with such a poor country. According to a person who participated in the tenders, gas traders applied an unusually high degree of scrutiny to the proposed contracts, seeking terms that ensured Pakistan would pay in full and on time. Pakistani officials, who were focused on securing the best possible price, didn’t insist on strict penalties for failing to deliver gas; at the time, cancellations were rare. (The Gunvor spokesperson says the company was “required to sign up to terms stipulated” by Pakistan, without amendment. The Eni spokesperson says that the relevant agreements “were not the results of a bilateral negotiation,” and that Pakistan set out their contents.)…

…In December 2020, Pakistani officials received a curious email from Eni. The Italian company said it would deliver only part of its LNG shipment for the following month, explaining that an unnamed supplier had failed to make its own delivery. Eni’s head of LNG portfolio, Ilaria Azzimonti, apologized and said her team would try to send replacement gas later…

…Under the terms of Eni’s contract, it didn’t have to provide details about the supplier default. But even after telling Pakistan it lacked sufficient gas to meet its commitments, according to a person with direct knowledge of the transaction, Eni sold an LNG shipment elsewhere at the spot price of roughly $100 million.

Although it was just part of the expected cargo, representing less than 10% of the country’s monthly supply from long-term contracts, losing the Eni gas put Pakistan in a difficult position. Cold weather was coming, increasing the need for fuel, and domestic production had declined significantly, the result of years of underinvestment. The government tried to find a spot-market shipment to make up the shortfall, but it deemed all the options too expensive. It had no choice but to temporarily curtail supplies to some households and factories.

There are occasional cancellations in the LNG business, often when problems at an export terminal affect supplies, and at first the undersize Eni delivery looked like a one-off. Regular shipments resumed in February 2021, coinciding with a collapse in spot prices. But later that year, with the recovery from the Covid‑19 pandemic driving energy demand, more of the gas expected by Pakistan failed to arrive. In August, Eni blamed reduced output at an Egyptian LNG plant for a missed shipment…

…Then, in November 2021, both companies canceled their deliveries, documents reviewed by Businessweek show. Gunvor cited a “force majeure,” a legal term for an unavoidable event that makes it impossible to fulfill a contract. Specifically it blamed an outage at a plant in Equatorial Guinea, a tiny, hydrocarbon-rich Central African dictatorship. (Although Gunvor didn’t offer details, there had been technical problems at a facility at the country’s Alba gas field that September.)

That justification from Gunvor, as well as the earlier statement by Eni about production in Egypt, took advantage of another part of Pakistan’s contracts. Unlike other LNG deals, which stipulate where a supplier will obtain the gas it’s selling, the Pakistani agreements said shipments could come from anywhere within Gunvor’s and Eni’s global portfolios. Pakistani officials have said they believed this would insulate them from disruptions, by allowing the companies to provide any gas they could source.

In their communications with Pakistan, people with knowledge of the discussions say, Gunvor and Eni turned that logic on its head, arguing that because no source was specified, a disruption anywhere gave them the right to cancel delivery. Problems in Equatorial Guinea therefore qualified as a force majeure, even though Gunvor rarely shipped gas from the plant to Pakistan. Over the next several months, Gunvor declared force majeure on two additional shipments and only partially delivered one more. At the same time, it was continuing to sell large quantities of gas to wealthier countries at spot prices, according to traders who participated in the deals…

…The events of early 2022 provided Alleyne and her team with an opportunity for a once-in-a-lifetime payday. At the average price of LNG from 2010 through 2020, a single tanker cargo could be sold on the spot market for about $30 million. Suddenly the potential number was north of $150 million. Alleyne and her colleagues, people with knowledge of the matter say, were under significant pressure from Gunvor’s billionaire chief executive officer and controlling shareholder, Torbjörn Törnqvist, to find ways to capitalize. (Gunvor denies this.)

Poor and politically isolated, Pakistan was an easy target. Gunvor traders were also conscious of an incident that had occurred in 2020, when the pandemic caused gas prices to crash globally. At the time, Pakistan had threatened to pull out of its LNG contract, since it was cheaper to pay the cancellation penalty and source gas on the spot market. Now it was the traders who had the advantage…

…Decision-makers in Pakistan’s energy industry say they’ve learned a painful lesson about international commodity markets. “As a supplier, if you have the option to sell it to Germany over Pakistan, 99 times out of a hundred you sell it to Germany,” Maniar, the Sui Southern Gas executive, says in an interview at the company’s offices in Karachi. To conserve electricity, the hallways of the building are dark. “You cannot stop people from making money.”

3. Xi Jinping repeats imperial China’s mistakes – The Economist

The rigours of imperial China’s civil-service examination system—the keju, used to select scholar-officials for over 1,300 years—are described in a new book by Yasheng Huang called “The Rise and Fall of the east: How Exams, Autocracy, Stability, and Technology Brought China Success, and Why They Might Lead to Its Decline”. Arguing that the exams stifled innovation in ancient times, Professor Huang sees lessons for Xi Jinping’s China.

The keju became more doctrinaire over time. First instituted in 587, the exams progressively shed such subjects as mathematics and astronomy. Soon, they only tested candidates’ mastery of dense Confucian texts filled with injunctions to revere fathers, officials and monarchs. The curriculum narrowed again in the 14th century, requiring candidates to memorise ultra-conservative commentaries on Confucian classics. The commentaries advocated unquestioning obedience towards rulers. A final refinement was added during the Ming dynasty: answers had to follow a rigidly scripted format, the “eight-legged essay”, described as “the greatest destroyer of human talent” by Ch’ien Mu, a historian…

…But a dataset of 11,706 Ming-era keju candidates shows that exam-takers who reached the third and final stage of the keju got there in middle age, on average. Millions sat the exams and never passed. This focus on bureaucratic glory crowded out other paths to social mobility. It was handy for autocrats, as test preparation left scholars “no time for rebellious ideas or deeds”, the book argues. The keju’s Confucian values promoted conformity of thought and disdain for commerce. Over time, the exams smothered the scientific curiosity that saw ancient China develop many technologies before the West, including the compass, gunpowder, movable-type printing and paper, known in China as the country’s “four great inventions”.

The keju was scrapped in 1905, but its legacy lives on today, in civil-service tests and in the fearsome gaokao, the college-entrance examination which rewards relentless toil. In the book’s telling, the curse of the keju spirit was broken once in China’s history, when Communist Party leaders embraced market-based reforms after the disasters of Maoism and central planning (and revived the gaokao, abandoned during the Cultural Revolution). During that reform era, lasting for 40 years after 1978, the book credits the party with successfully balancing stability, economic growth and technological progress. As in imperial times, a strong state overshadowed a weak society. But the reform-era party also praised private entrepreneurs and allowed policy experiments by regional governments. To harness the world’s dynamism, officials sought out foreign capital and international academic exchanges.

Then, in 2018, Mr Xi abolished the only term limits that constrained him as leader. His China is increasingly autocratic, statist and inward-looking. Private businesses endure more meddling by party cadres, and youth unemployment is high. In a flight to safety, almost 2.6m people applied to sit civil-service exams this year, chasing 37,100 posts. Too often, in public institutions that once boasted of being meritocratic, “merit” means fealty to one man. Officials and university students must devote ever more hours to studying Xi Jinping Thought and other dogma.

4. The Revenge Of The Ottoman Empire – Louis-Vincent Gave

In recent years, we have seen:

1. The Western world attempt to trigger a collapse in the Russian economy by blocking access to the US dollar, euro, British pound and Swiss franc. Unsurprisingly, Russia immediately shifted to selling its commodities for renminbi, Indian rupees, Brazilian real or Thai baht, and trade between Russia and the world’s major emerging markets went parabolic…

…2.The United States encourage domestic producers to repatriate production from China which is a non-democratic Communist country. Or, alternatively, to move production to countries that happen to not be non-democratic and nominally communist—for example, Vietnam.

The end result? China’s trade surplus has essentially tripled over the past few years…

…China’s trade surplus did not triple due to North American or European consumers deciding to buy three times as many plastic toys for their kids. Necessity is the mother of invention, as the saying goes, and the surge in China’s surplus is linked to it opening up new markets for its products. Back in 2017, the value of Chinese exports to Asean economies amounted to 60% of China’s exports to the US. Today, China’s exports to Southeast Asia stand at roughly 120% of China’s exports to the US.

China did this by moving up the value chain and exporting decent quality, aggressively-priced capital goods and other higher value-added products. The most visible example of this is how China came from nowhere five years ago to become the world’s largest car exporter. These cars are typically not sold in the US or Europe, but have been snapped up by drivers in Southeast Asia, the Middle East and Latin America. Just as importantly, while the cars have captured the general public’s imagination (hard not to notice Chinese cars when every shopping mall, or airport, one enters in an emerging economy now has very attractive Chinese cars on display), one can draw parallel stories for power plants, earth-moving equipment, tractors, telecom switches, turbines, and machine tools—basically, all the capital goods that are heavily in demand across India, Indonesia, Brazil and Saudi Arabia…

…How could China withstand both a frontal attack from the US (a country that controls the pipes of global financial flows to an even greater degree than the Ottoman Empire controlled the Eastern Mediterranean), and a real estate slowdown? The answer, as with Columbus and Vasco da Gama, is that necessity is the mother of all discoveries and inventions. Trade will tend to flow, either where it is the most profitable; or alternatively, if walls and barriers are put up, then trade will flow around these walls and find new destinations.

All of which brings us back to the Gavekal foundational concepts of Ricardian growth and Schumpeterian growth.

From its infancy as a firm, Gavekal has identified economic development as deriving from one of two sources:

Ricardian growth that stems from falling trade barriers, new roads, and improvements to modes of transport and communication. Such developments pave the way for a more efficient use of existing resources, whether land, labor or capital.
Schumpeterian growth, when new inventions trigger sharp productivity improvements…

…In fact, in recent years, global trade has continued to grind higher, thanks mostly to a sudden acceleration of trade within emerging economies…

…hardly a month goes by without the announcement of some new road, railway, canal or free trade deal linking the economies of the Istanbul-to-Jakarta axis described in the above reports (draw a line from Istanbul to Jakarta and one finds a population of roughly 3.5bn people—excluding China—that is growing by 1% a year, and with some of the highest income growth in the world).

Construction of new roads, railways and canals are appearing all across emerging economies because countries across the “Global South” can now:

Purchase commodities in their local currencies, from Russia.
Purchase capital goods from China, either in their local currency (if they have good relations with China), or, alternatively, in renminbi.

The combination of these two factors is a game changer for emerging economies like Indonesia, India and Brazil, which can now break free from the tyranny of the US dollar funding constraint. This explains why, for the first time in living memory, we have just seen a significant Federal Reserve monetary tightening cycle without a single emerging market going bust. On the contrary, in recent years the US dollar returns offered by most emerging market bonds have trounced those of US treasuries, along with German bunds or Japanese government bonds.

Indeed, for the first time ever, the yield on investment-grade sovereign emerging market debt is now lower in aggregate than that on US treasuries…

…If an economy contains two cities, it requires one link (say a railway line) to connect them. If an economy contains three cities, it needs three links to connect each city with the other two. If an economy contains four cities, the number of required connections rises to six.

For any number of cities, N, the number of links needed to connect each city to the others, is stated by the formula N*(N-1)/2. As more cities/countries join the system, the number of links therefore rises at an accelerating rate. For example, from the early 2000s, global economic activity was massively boosted, not just by connecting China to the rest of the world, but also by connecting Chinese cities to each other, with all the associated construction of rail, air, road, telecommunications and power links this involved.

And what occurred in China is now occurring across the broader Eurasian continent. Obviously not at the same pace (no country will ever be able to match China in mobilizing land, labor capital and natural resources towards the delivery of infrastructure) but it is happening nonetheless. Take India as an example. Over the past few years, India has opened 70 new airports and currently has plans to start the construction of another 70. And as more cities start talking directly with each other, this should mean more growth, more productivity and lower prices. Such dynamics bring me back to another staple of Gavekal analytics, namely, the acceleration phenomenon.

The concept of “acceleration” was developed by Albert Aftalion, a French economist active in the inter-war years. It is most useful in abrupt adjustments but is not easily explained mathematically, which may explain why it has not secured the following it deserves. Here goes the CliffsNotes version:

Most socioeconomic variables are distributed according to the “normal” law, the famous Gaussian bell-shaped curve.
This is especially true of incomes: in a “normal” country, where a large share of people have an income close to the average, a few people have very low incomes and few very high incomes. At both ends of the curve (the tails), one finds a very small population in percentage terms.
As incomes grow over a period of a few years, the right side of the tail will grow much faster (the acceleration phenomenon) than the growth of income. This is where it gets complicated since our minds are accustomed to thinking in linear patterns, yet the number of people earning a certain amount actually grows exponentially.

This matters because when it comes to the purchase of certain goods and services, history points to the existence of key income “thresholds’’. For example, if the average income in a country is below US$1,000, nobody owns a television; when incomes move above US$1,000, almost everybody buys one. For smartphones, the level seems to be around US$2,500. For the automobile industry, the critical level seems to be US$10,000 a year. For university education, the level is US$15,000 and above. For financial products like life insurance, brokerage accounts and mutual funds, the level seems to be US$30,000…

…Now let us further imagine a few things, namely that:

Just as incomes grow, the prices of goods delivered to consumers—whether cars, or smartphones, or personal computers—actually go down
As incomes grow, interest rates charged to consumers actually go down (“on ne prête qu’aux riches” and all that)

Then all of a sudden, one could face a double-, or triple-charged acceleration phenomenon.

Unsurprisingly, as cars replaced bicycles on the streets of Beijing, Shanghai and Chengdu, China’s energy demand also accelerated, as shown in the chart below. Could similar events now unfold across Southeast Asia, India and the broader Middle East? Given the growth in incomes, the fact that China is now offering high-quality sub-US$10,000 cars, and the funding for such purchases, is this not the path of least resistance?

The fall of Constantinople did not trigger “the end of globalization”. Instead, it unleashed a sharp move higher in global trade. Could the same thing happen as a result of the sanctions against Russia and the US’s attempts to take China out of global supply chains? Actually, this is precisely what seems to be unfolding. Both of these events mean that the likes of Indonesia, Brazil, Saudi Arabia and India can now use their own currencies to pay for the commodities they need to power their growth and the machine tools they need to industrialize. At the very least, they no longer need US dollars. Last year, for the first time, China made more loans to EM economies in renminbi than in US dollars.

And this is before the recent announcement of Saudi Arabia signing a RMB50bn swap line equivalent with the People’s Bank of China and the possible sale by China of nuclear power plants to the kingdom.

Today, the notion that the world is deglobalizing would seem laughable to anyone living in Dubai, Singapore, São Paulo or Mumbai. Rather, the world is going through a new wave of globalization, which is different from its predecessors.

5. Car wars – Noah Smith

Over the past two years, China has gone from an also-ran in the auto industry to the world’s biggest car exporter. EVs are a huge chunk of those exports, and most of China’s EV sales go to Europe.

Some forecasts say that by 2025, about 15% of EVs bought in Europe will be made in China — some by Western automakers like Tesla and Volkswagen, some by Chinese companies like BYD.

It’s very easy to understand why this is happening. China massively subsidizes the production of electric vehicles, and Europe massively subsidizes the consumption of electric vehicles. When that happens, any Econ 101 model can easily predict the outcome — China will produce a lot of EVs that are sold in Europe…

…But China’s EV export surge is more recent, so let’s go over some of the reasons it’s happening.

First, here’s a good Bloomberg article about the EV subsidy regime in China. China pays manufacturers a subsidy worth more than $1400 per EV they produce, provides EV companies with cheap land and financing, and heavily subsidizes R&D in the sector. Both China and Europe pay people to buy EVs, and their governments buy EVs directly. But China subsidizes local production a lot more than Europe.

That’s one reason for China’s export dominance, but not the only one. Another is that China controls nearly the entire supply chain for EV batteries, except for the initial mining.

An electric vehicle is a much simpler machine than an internal combustion car — it’s basically just a battery with wheels. The battery in an EV represents about 40% of the car’s purchase price. Making EVs in large numbers is a lot easier when the supplier is right nextdoor; batteries are 33% more expensive in Europe than in China.

Batteries are also about a quarter of an EV’s weight. The fact that they’re all made in China cuts down on the amount of shipping cost you can save by locating car factories close to consumers.

Yet another reason is macroeconomic. As everyone knows, China is in the middle of a big economic slowdown, which has cut local demand for new EVs despite all the consumption subsidies. Europe’s economy is in the dumps as well, but China basically planned to produce enough EVs for a much faster-growing Chinese economy than the one they ended up with. So Chinese EV producers are stuck with massive inventory that they can’t sell domestically. So they’re slashing prices and dumping the inventory on Europe.

And finally, let’s not discount the ingenuity and innovation of Chinese auto and battery engineers and entrepreneurs. The industry shift toward EVs gave upstart carmakers a once-in-a-century opportunity to do an end run around the entrenched dominance of the old-line companies that knew internal combustion engineering backwards and forwards. European startups could have challenged Volkswagen and Renault and Mercedes-Benz. They did not. Instead it was Chinese companies like BYD and SAIC, along with one American company, Tesla, who seized the day…

…Losing the car industry could thus push Europe further along the path to deindustrialization. Cheap Chinese EVs are a boon to European consumers, and they help speed the green transition and reduce carbon emissions. But the competition also threatens to put a bunch of European workers out of a job — 7% of the region’s workforce work in the automotive sector. Traditionally, Europe has been much more concerned than the U.S. about protecting its industries from foreign competition; the EV spat with China will be a test of whether this is still the case, or whether Europe has embraced more of a “neoliberal” approach to trade.

But there could also be a national security angle here too…

…A domestic auto industry gives Europe much more ability to repurpose production lines and ramp up defense production when needed. If the auto industry flees to China, Europe will be that much more vulnerable to Russia. In fact, this is one reason the auto industry is so globally distributed today; during and after World War 2, lots of countries decided they needed car industries in order to maintain strong militaries.

So if Europe does decide to protect its car industry, what might it do?…

…tariffs don’t do much to help European carmakers become more competitive in the export markets they used to dominate. The fact is that Chinese-made EVs are mostly just better than European-made ones right now, and tariffs aren’t going to change that.

In order to address these issues, Europe would need more than tariffs. It would need an equivalent of the U.S.’ Inflation Reduction Act — a major program of production subsidies, not just for EVs themselves but for the batteries and the mineral processing facilities necessary to make them. Europe would also need to simplify and slash some of the overgrowth of regulation that it has piled up around the auto industry over the last few years. And it would need to subsidize R&D in the EV sector more heavily.

And another important step would be something Europe has shied away from doing in recent times: encouraging startups. It’s no coincidence that Tesla, a startup automaker, was able to run rings around the stodgy old giants of GM and Ford, with their deep reliance on legacy markets and legacy technology. Europe has no Tesla; if it really wants to compete with China, it needs at least one.

What We’re Reading (Week Ending 10 December 2023)

The best articles we’ve read in recent times on a wide range of topics, including investing, business, and the world in general.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

Here are the articles for the week ending 10 December 2023:

1. Charlie Munger – A Conversation with Charlie Munger & John Collison – Charlie Munger & John Collison

John: [00:15:25] So my question is, how do you think about the quality of the business when overarching tech changes are really going to shake it up?

Charlie: [00:15:32] You’ve got to recognize the tech changes do cause some new businesses to flourish and other businesses that looked impregnable to fail. And that’s one of the realities you have to understand.

John: [00:15:44] So you secretly are a tech investor because your reasoning about the effects of tech on Costco or on…

Charlie: [00:15:51] Yes, it’s just that — take, for instance, pharmaceuticals. The American pharmaceutical industry is better than any other pharmaceutical industry in the whole world. And number two is not remotely even close. So we have one of the great achievements in the whole history of the world in science and technology and so forth. At the same time, there’s a fair amount of sleaze in the way pharmaceuticals are distributed. Everybody rooks the government…

John: [00:16:16] The PBMs, yes.

Charlie: [00:16:17] Yes. And that’s just the system. By and large, we haven’t invested in pharmaceuticals because we’ve got no edge. I don’t know enough about biology and medicine and chemistry to have any edge in guessing which new pharmaceutical attempt is likely to succeed and other people who know those things, not that they have perfect knowledge, but it’s way better than mine. Why in the hell would I play against other people in a game where they’re much better at it than I am when I’m playing for something desperately important to me like a way of feeding my family. So of course, we didn’t go near it.

I would argue that they’re — in practical life, you want to succeed, you got to do two things. You got to have a certain amount of confidence. And you have to know what you know and what you don’t know. You have to know the edge of your competency. And if you know the edge of your competency, you’re a much safer thinker and a much safer investor than you are if you don’t know it. And I constantly meet people, better to have an IQ of 160 and think it’s 150 than an IQ of 160 and think it’s 200. That guy is going to kill you because he doesn’t know the edge of his own competence and he thinks he knows everything.

Partly, Warren and I, we pretty much know what we know and what we don’t know, what we’re good at, what we’re not good at. And one of the things we’re not good at is guessing which new pharmaceuticals. So we don’t even look at it. After all, it’s a big universe out there and if we have to leave a certain kind of investment behind because we lack the capacity to deal with it as well as some other people. That’s all right. We don’t need an infinite number of opportunities…

…John: [00:21:36] So what examples do you prefer of businesses driving capital efficiency without squeezing small suppliers?

Charlie: [00:21:43] Well, Costco is one.

John: [00:21:44] By turning the inventory quickly?

Charlie: [00:21:46] Yes and doing that because they have fewer stocking units and they’re way more efficient.

John: [00:21:51] You’re on the board, right?

Charlie: [00:21:53] Yes. I am somewhat the older member. But Costco, it’s an amazing culture. The whole damn culture of the place is so subtle and it just marches from triumph to triumph. It was smart to have a small number of stocking units flowing through with enormous speed. It was right to have a membership system.

There are three things that Costco didn’t want. Didn’t want people who stole merchandise. They didn’t want the people who used bad checks, and it didn’t want people cluttering up his goddamn parking lot without spending a hell of a lot of money in stores. So a membership system, where they accept only a certain kind of a member, all of a sudden now they’ve got nothing but people who buy a lot per trip.

Costco has always had the lowest shrink rate in the world. Tricks the inside too. So the net theft rate at Costco was always below 2/10 of 1%. That’s unheard of.

John: [00:22:46] I hadn’t thought of the parking lot efficiency with the membership system.

Charlie: [00:22:49] You can’t go to Costco just to buy bottle of iodine, just drop in. You got to be a member and then you got to pay enough, so to an ordinary person, they’re not going to pay an extra $100 to buy a bottle of iodine or something. We keep the peach pickers, the little buyers out.

Sol Price used to say “A business should be careful in the business it deliberately does without”. Of course, that’s straight out of a Munger book. You figure out what you want to avoid. And they want to avoid theft losses, embezzlements, bad checks and cluttering up the parking lot without buying much. And their system caused all those effects at once.

John: [00:23:27] It’s like your first speech in the book, start with the business you don’t want, work backwards.

Charlie: [00:23:30] I know, but it’s so simple.

John: [00:23:32] Any others? Of businesses driving capital efficiency without squeezing suppliers.

Charlie: [00:23:35] There are lots of others. Practically all of the aerospace businesses have learned to make very high returns on capital.

John: [00:23:42] How do they do it?

Charlie: [00:23:43] They specialize in being good at something and handling the government well as a paying customer.

John: [00:23:49] Did you ever look at TransDigm?

Charlie: [00:23:51] Sure. I don’t like that way of making money.

John: [00:23:54] Because the price increases.

Charlie: [00:23:56] It’s too brutal. They figure out something that has a little monopoly due to the defense department regulations, and they raise the price 10 times. And they’re famous for it. I regard that as immoral…

…John: [00:24:25] One of the things you raised in the book is this question of when you have a small number of players in the industry, say, two or three players in the industry, it is not always easy to predict who will earn good profits and who will not. And so the airlines lost money since the Wright brothers versus the cereal manufacturers, very durably profitable. If you’re looking at the business today and you know that the industry will consist of two or three players, how can you predict will those players make money?

Charlie: [00:24:50] I don’t think it’s possible to be 100% accurate in making these predictions. But certainly, we’re looking backward, the people who had branded profits like coffee and oatmeal and so forth, made very high profits and airlines basically made no profits at all for their shareholders.

John: [00:25:09] But the airlines were branded goods.

Charlie: [00:25:11] But everybody had big capital equipment if they didn’t use it, they obviously were losing a lot of money. So that everybody was almost forced into a very destructive competition by the logic of the individual situations. There are a lot of businesses that are very hard to make money in permanently.

If you want to go into the business like restaurants, most people fail, small percentage of restaurants even last long enough to make a living to the people who own them. Too competitive. That’s why they fail. Just like there are too many deer on an island and no predators, pretty soon there are too many deer. So all the deer suffer because there are too many of them.

John: [00:25:49] But again, to go back to this question, if I want to understand, will the business be like an airline or like a cereal company. Is this then the ongoing capital expenditure that’s required where airlines fundamentally, they have lots of CapEx on an ongoing basis, it’s like the original Berkshire textile mills?

Charlie: [00:26:02] The airlines are like a guy who builds a big hotel and it’s just sitting there and he makes some incremental profit from filling it. And if it’s got up and staff, that’s better than just letting it sit there vacant. It almost forces irrational intense competition. The same thing does not happen within cereals.

John: [00:26:19] BNSF was one of the biggest acquisitions you guys did. And my sense from the outside is that it’s maybe even been more successful than you would have expected. Is that accurate? Or did you expect it to be this successful?

Charlie: [00:26:31] The railroads were a lousy investment. There were a few people when they were first created that basically stole all the money by milking the government, bribing legislators and doing all kinds of terrible stuff. But by and large, most railroads are lousy investors, like the airlines for a long time. And finally, it got down after years of fighting unions and consolidations, so you get down to a few big systems.

Now there are just two big transcontinental systems, and we’ve got one of them. Of course, that’s a less competitive market than it was — than it existed earlier when there were 100 different railroads. But early railroads when they were terribly competitive, they were terrible places to invest money.

John: [00:27:12] But again, airlines, bad business, not a good investment.

Charlie: [00:27:16] Early railroads, bad business.

John: [00:27:19] Early railroads, yes. Railroads today still require a lot of ongoing CapEx.

Charlie: [00:27:23] Yes, but they’re so dominant. Once you have a railroad that can put shipping containers on that stack too high on tracks. It’s one of the most efficient ways of transferring assets all over the country. It’s way more efficient than trucking. So that they have a system that just accidentally happened. Nobody anticipated you’d be able to double the capacity of the railroad just by shoving containers one on top of the other. So they got very efficient finally. And now they’re so efficient. They’re more efficient than anything else. And of course, they do well…

…John: [00:32:38] You have been famous for criticizing gold earlier on and now cryptocurrency.

Charlie: [00:32:46] I like to gold a lot better than I like cryptocurrency.

John: [00:32:49] You’ve criticized both.

Charlie: [00:32:51] Before there was cryptocurrency, I never bought gold. So I didn’t like gold. But I don’t hate gold as an investment as much as I hate cryptocurrency. I think cryptocurrency ought to have been driven out as illegal.

John: [00:33:03] At the risk of maybe getting ejected from the premises, if I can try to defend cryptocurrency, isn’t the perspective you have where — I think you would say, invest in a productive business. Isn’t that a reasonably U.S.-centric perspective, where absolutely, we have a great currency here. We have a great respect for property rights here. If you’re in Turkey and their property rights aren’t as strong, the currency is inflating 80% a year as it has this year, then the ability to move your wealth…

Charlie: [00:33:34] Well, if I lived in Turkey, I might do something odd. Buy my gold if I were in Turkey, but I would never buy cryptocurrency.

John: [00:33:39] Even in Turkey?

Charlie: [00:33:40] No. I don’t think that buying a percentage of nothing is a good investment, even though it’s hard to create more nothing.

John: [00:33:47] But isn’t gold functionally an investment in the percentage of nothing?

Charlie: [00:33:50] It is similar, except it’s been established so long as a…

John: [00:33:57] An agreed upon store of wealth…

Charlie: [00:33:58] With the history we have and with the need for a currency and a currency that is backed by something and gold is hard enough to mine and so forth. Gold is a perfectly reasonable thing to use as a currency. And the evolution of use of gold as a currency was a very good thing for civilization. I don’t have the feeling that gold is evil. Gold helps civilization develop. But I think cryptocurrency is scumball activity. And I think by and large, the people who promoted it are scumballs or delusionary. And I don’t know which is worse, being a scumball or a delusionary. But I think they’re both pretty bad.

John: [00:34:31] Some people can manage to be both. There’s plenty of scams in crypto. That’s absolutely not up for debate. But are we talking about questions of degree here between gold and cryptocurrency, where they are societally agreed upon stores of value, which trade above…

Charlie: [00:34:46] Let’s put it this way. If we didn’t have gold, we might have invented something like cryptocurrency as a substitute. But once we have gold and fiat currencies that are now long established, we don’t need to add in cryptocurrency.

John: [00:34:59] But isn’t cryptocurrency handier? If you can work with it in just software, you don’t need to actually go get some physical gold, trade it, melt it down. It’s much harder to seize cryptocurrency than it is to seize gold in an autocratic regime.

Charlie: [00:35:10] You don’t have to bother with any physical inventories or anything has any intrinsic value. You can create system very efficiently dealing in it. I don’t want to officially deal in nothing and craziness. I want to make it illegal. All nations have had anti-counterfeiting laws. And I think the anti-counterfeiting laws ought to have been used to totally bar cryptocurrency.

John: [00:35:33] But nothing’s being counterfeit here.

Charlie: [00:35:34] Well, if I am a nation and I have a currency, I don’t want a new currency established.

John: [00:35:38] But it’s not really a new currency. It’s a new store of wealth.

Charlie: [00:35:42] You can call it a store of wealth, I call it a store of delusion. I don’t think it’s good to participate in delusion even when it gets quite common. A second medium of exchange widely used. It’s ideal for drug dealers, dope dealers, scam artists of various kinds. Every kind of criminal you can imagine. Very good in extortion, kidnapping.

Why would we want a wonderful crime facilitating new medium of exchange? Why wouldn’t we just say this is like counterfeiting? You’re coming into the government’s business and you’re trying to create a fiat currency and you can’t do that. It’s a feel they don’t…

John: [00:36:18] All right. Well, I will agree to disagree on crypto. But…

Charlie: [00:36:20] You don’t have to agree. I can handle it if you like crypto. I don’t like it, but I can handle it.

John: [00:36:25] We’re staring into a recession, potential stagflation. What advice do you have for people thinking about how to work their way through the…

Charlie: [00:36:35] I have one standard set of advice for all difficulties, suck it in and cope. That’s all any human being can do, suck it in and cope. Partly, you have to be shrewd. That’s one way of coping is to be as shrewd as you can possibly be. But that’s my recipe. And I must say it’s worked pretty well for me. It will work very well for any other person who uses my methods…

…John: [00:37:59] How do you feel about American society over the coming decades?

Charlie: [00:38:03] Old men have always tended to think that new generation is going to hell. The old Romans, o tempora, o mores. That goes back to the earliest civilizations we had. The old guys were saying when I get out of the world, it’s going to hell. And it really wasn’t going to hell net by and large. But I do not like the way politics has morphed in my lifetime in the United States. I don’t like democracy. The way it actually morphed into existence with these primaries and the dominance of two parties where only the most extreme members of each party have a lot of pulling power and therefore, they control the nominees and so forth.

I think our way of getting nominees is deeply flawed now. It may have worked pretty well up until now. It worked better when we had those old, crooked bosses in the cities then it’s working now with the primaries. I wish those old, crooked bosses would come back and replace the present primaries. Wanted to control the patronage so they actually nominated some pretty good people like Teddy Roosevelt. And these modern primary systems, the worst people often win…

…John: [00:39:10] How do you feel about declining birth rates?

Charlie: [00:39:11] It creates a different kind of a world. Well, I don’t see that mankind would be at all smarter if everybody had six children. I think that just jams up population way too much starting with 7 billion for the whole world. So I think it’s good that the population is growing more slowly. But do I think it is good for people to be quite self-centered below 35 and then get married compared to marrying at 21 or 22 and having a lot of children?

No, I think the people who married at 21 or 22 and grew up fast because they had to because they have those young children. In a sense, I think they were a luckier generation than the people who came along with all these different options and who delay marriage into late age and have one or two children, I’m not at all sure it’s good for the people who are having these new options, but it is good for the population…

…John: [00:43:15] Where do you think the world is getting worse?

Charlie: [00:43:17] I think we have a political game problem that’s probably as bad as we’ve ever had. We have some crazy dictators on the verge of creating a nuclear war. We’ve got lots to worry about. The world has never been a perfectly safe place and it isn’t now.

John: [00:43:32] Kind of a societal version of your avoiding mistakes framework from Poor Charlie’s Almanack, where societies need to avoid the major mistakes just like individuals do, avoiding nuclear war.

Charlie: [00:43:42] We’re lucky to have done it so far. But if enough crazy people have enough hydrogen bombs, there will eventually be enough hatred, we’ll have an atomic war of some kind someday. You can almost count on it. So you can say that our generation, it was quite unlikely, but I think it’s getting more likely and not less…

…John: [00:46:15] And what’s an example of where you are more multidisciplinary than the architects in some of the buildings you’ve designed?

Charlie: [00:46:19] If you take the building, the graduate residence at the University of Michigan. They had a magnificent site with a parking lot. They had no other site. They’d used up all the land in the dormitory. They have a second campus, but on their main campus, they’d used up all the sites. And there is one little parking lot left. And I realized that if they used their power of eminent domain and doubled the size of that parking lot, they’d get it with a big square building on the site tha would hold a lot of graduate students.

But there was no way to do that without creating a window shortage in some of the bedrooms. And I also knew that it didn’t matter that there was a window shortage in the bedrooms because I went around Ann Arbour and saw the private builders in Anna Arbour now have already created apartment rooms with no windows and relying on artificial light. And I walked side-by-side exactly identical bedroom, one with a real window and one with just a blank wall. And the one with just a bank wall renting for 10% less.

So it wasn’t much of a problem. I looked for the evidence and then once I realized that, I could do all kinds of wonderful things in that building once I got over this prejudice that it was absolutely required under any and all circumstances that every bedroom have a window. So it’s just an example of just the most elementary common sense. I looked at the evidence at Ann Arbor. I understood geometry well enough to know. And then too, I was well aware that every ship has exactly the same problem. Every ship has a window shortage automatically. Every cruise ship. Yeah, and they pay $20,000 a week to be on the ship and so forth.

And if they don’t want a little light, they walk out of the ship and go into one of the common rooms. And of course, that’s what I arranged they do in the dorm. So I was following correct precedents from marine architecture. But show me an architect that’s learned anything from marine architect. I think you could go into any school of architect in the country and you won’t find anybody studying marine architecture. They think it has nothing to do with it. It has a lot to do with what they’re doing. If you don’t look, you won’t find.

John: [00:48:27] I feel like another example of understanding the customer is giving the students in the dorms single rooms where most people design…

Charlie: [00:48:32] Oh, well, that — talking about insanity. Now, I have sent a lot of children through a lot of graduate education. And I’ve never had a child that liked being in a room with one or two other unrelated people sleeping in the same room…

…John: [00:49:19] Why did this shared delusion persist for so long?

Charlie: [00:49:22] What happened was that the fire codes, they worry that the fireman would need a ladder to go and look through the window and crawl in through the window and haul somebody who had passed out from smoke. So they required that every sleeping space have a window. So the fireman could crawl up on a ladder. There were two things wrong with that.

One, it never happened. Nobody could find a case were a fireman — they would crawl up by ladder and look through and they had found somebody lying in bed passed out of smoke. And two, of course, a modern building with automatic sprinklers, that’s why there was going to be zero.

And that’s why the fire codes changed. And when the fire codes changed because — but the people are used to doing it in a certain way. Of course, they keep doing it the same way they’ve always done. Isn’t it the Mayo Clinic is one of the best places on earth in terms of an admirable culture. They kept doing hip replacements by a procedure that the doctors knew how to do because the new one that was better for the patient was very hard for the doctor to learn. And so they just kept doing it the old way. Architects are no different. They do what they’re used to.

John: [00:50:32] Again, for say, someone who’s 25 or 30, is the lesson that there are a lot of $20 bills lying on the sidewalks? There’s a lot of inefficiency in the world to be rectified that people should not assume the world works efficiently?

Charlie: [00:50:45] Well, of course, there’s always a lot of things that can be improved, always a lot of people who are getting ahead by doing something new. And that’s one of the pleasures of modern civilization. And imagine a postal clerk in the United States can go to Hawaii on a 2-week vacation on a superjet and have a nice time. A postal worker could do that in the world that you’re up in.

You can learn a whole new profession just punching buttons on the Internet and so forth, so the possibilities of self-education is fairly enormous. So all kinds of things have been greatly improved. Of course, that causes new opportunities for some people, and it causes absolute economic destruction from certain people who get obsoleted.

Imagine the Kodak company, which hired all the PhD chemists, totally dominated the chemistry of film and so forth and had the most reliable trademarks in the whole world. Go through Africa when I was young, there are 2 things you always saw: a Coca-Cola and Kodak. That was the brands all over Africa, the poorest villages. And of course, Kodak went totally broke because somebody invented a new way of taking photographs and developing photographs. And it just obsoleted their whole damn business, and Kodak wiped out its common shareholders. That happens all the time, that kind of thing. And you can’t blame the management for it and say, “Well, didn’t Kodak invent its own destruction?” That’s hard to do.

I mean for human nature, you’ve got a business as big as Kodak, everybody’s lived over for years. They’re like the surgeons who didn’t want to learn a new trick that was lot harder to learn when they were old. People don’t welcome having to learn something new. It’s really hard to learn. Everybody would rather get ahead using what he already knows…

…John: [00:53:18] You spend a lot of time in the book talking about businesses that are win-win for both sides and the importance of this for their long term.

Charlie: [00:53:24] How can anything be more important? It isn’t just that it works better in terms of creating plenty for all. It’s better morality. Of course, both sides want both sides to win, that’s more moral than trying to take advantage of other people when it’s so obviously the right way to live and it’s the right way to do business…

…John: [00:55:56] So you wouldn’t invest in drugs, tobacco or the Grateful Dead?

Charlie: [00:55:59] No, that’s correct. I would not. When I sell you a tennis racket for $100, one side gets the tennis racket they’d rather have than a hundred dollars they’re partying. The other guy, he likes what he’s getting, too. It’s win-win.

That’s the beauty of capitalism. It makes win-win transactions very easy and almost automatic. That’s such a hugely important idea. And people like Bernie Sanders and Elizabeth Warren, both of whom I regard as quite talented in some ways, but they just don’t get it.

John: [00:56:27] But I think you mean that as a backhanded compliment.

Charlie: [00:56:29] It’s both a compliment and a criticism.

John: [00:56:32] Is the fundamental thing they don’t grasp that a lot of the win-win businesses are net positive and win-win for both sides and they…

Charlie: [00:56:40] It’s automatic in a capitalist transaction, unless one side is making a big mistake. And most people are pretty good at not making mistakes over and over again with their own money.

John: [00:56:49] It’s not fully automatic, right? We can…

Charlie: [00:56:51] No, it’s not. But a lot of good happens automatically.

John: [00:56:54] Do you worry about the rise of this faction of the political spectrum who don’t really believe in capitalism?

Charlie: [00:57:00] Of course, look at the misery that’s happened to the Russian people. They didn’t like their old system with a bunch of serfs serving a bunch of landlords and so forth, corruption and so forth, so they went to something worse.

They were rebelling against something that was awful, so they substituted something that turned out to be actually worse. It’s hard to create a new form of government worse than Russian serfdom, but Russia has managed to do it. And not only that. They’re proud of having done it. You should never be proud of your defects.

John: [00:57:30] What are Berkshire’s defects?

Charlie: [00:57:31] We haven’t eliminated all mistakes of judgment or even all mistakes of morality. So nobody gets anywhere near perfect ever in human affairs. It’s not exactly a defect. A lot of what worked for us in the early days, we can’t do anymore because the world is more competitive.

The low-hanging fruit has all been picked, and we can’t get fruit out of barren branches where the fruit has gone away. And so we have to go to something else. And of course, that’s harder. A lot of people have that problem, and they go to the new systems in new ways.

John: [00:58:01] I’ve always liked the quote capitalism is how we take care of people we don’t know.

Charlie: [00:58:05] It’s certainly remarkable how it works. I like a social safety net, but I’m different from other people. If I were running the government, the modern civilization, I would be quite liberal at rewarding everything that can’t be faked, like being blind or not blind or something. I’d just give a very blind person a lifetime pension, which goes up with inflation.

If life is tough enough for you, we can afford to do it, and you and your handlers can figure out how you use the money. So I would be very liberal. I would give anybody any education right through college, courtesy of the government, but it would be meritocratic. You have to be able to do the work or you don’t qualify for the benefit.

So I wouldn’t let people pretend to be learning things in some half-assed institution and send the bills to the government. But places like Caltech or MIT, anybody could get in and do the work, if I was the government I’d pay for it all the way through college and graduate school, which they do in places like New Zealand and Australia and so on.

Again, everything in medicine, that is almost automatic, I would pay for that, too. But would I pay for Freudian analysis? No. Stuff that can be gamed and it was crazy, I would not pay for. And I wouldn’t allow the people to get rewards for low back pain, even though they have real low back pain. And it’s easily faked. I wouldn’t pay. It just causes too much cheating and the cheating gets to the eventual and so forth.

I would just say we can’t do that. It’s not that we don’t sympathize with your low back pain and your poor life adjustment? But we can’t give lifetime pay just because you say, “My lower back hurts.” or, “my life adjustment is imperfect.” That’s the way I would organize the government. Nobody thinks the way I do. I feel lonely. I would be quite generous, but I will be quite tough on people with low back pain or psychological problems…

…John: [01:12:23] If Patrick and I came and put you on Stripe, what would you want to understand about the business? What would your concerns be?

Charlie: [01:12:30] That’s an interesting question, considering how much Berkshire Hathaway has made out of other payment systems, including American Express. We recognize the power of having a dominant position in payments in a way that’s very efficient. And of course, anything in modern payments that enables all this Internet stuff is very useful. So you’ve come into a field and made a contribution and made yourself very useful.

I’m for all these payment systems that get better and better. So I think you’ve made your money honorably and you’ve made a lot of it, and good for you. I admire what you people have done. Why wouldn’t I? I regard everything that you’re doing as a little bit threatening to American Express, but American Express actually has a position where it’s like Hermes or something, and so it won’t necessarily be ruined by Stripe.

John: [01:13:22] In evaluating a business like Stripe, what questions would you want to answer for yourself?

Charlie: [01:13:26] Is it likely to remain forever as a money generator? And that’s a more complicated subject. It’s hard to know how the world is going to evolve. If Kodak could suddenly be obsoleted away, maybe it’s not utterly unthinkable if Stripe could.

The company that dominates software for architects, terribly prosperous company, but some other companies come up in that field a lot and it no longer dominates as much as it did. So not everything in software always wins. So I do not have the feeling — the venture capitals tend to think everything in software is always going to win. I don’t believe that for a minute…

…John: [01:14:48] Why has NetJets done so well?

Charlie: [01:14:50] It’s better in its niche than anybody else. In NetJets, the whole culture, safety is first, customer service is second. And after that, we’ll start worrying about the capitalists who own NetJets. And of course, there’s enough fanaticism of that kind of a culture. We create a hell of a product for the person who can afford anything. And ours is better than anybody else in the country, and it’s now big. It’s a big business. And we have yet to kill our first passenger. All these many years, we’ve never killed a passenger…

…John: [01:15:33] I can feature the magazine ads. NetJets- “No one has died yet”.

You’re very bullish on China. Why?

Charlie: [01:15:41] Well, first reason is that their economy was growing faster than ours. That isn’t necessarily true as we consider this exact minute, but for a long time, that economy grew a lot faster than ours. Number two, we could get way better and stronger companies at a much lower price in China than we could get in the United States. Now on the other side, we had to take the political risk of buying into a peculiar system of government that’s not different from ours.

As long as we were getting enough bargains, I was willing to run the — as with part of our assets is we would never invest all of our money in China, for Gods’ sake. But we were certainly willing to invest part of it. That’s perfectly logical. And of course, we were investing through Li Lu, he was a very exceptional money manager. And we put all those 4 things together, the ones, of course, that made sense…

…John: [01:17:19] How does the current geopolitical hawkishness change your view on investing in China, if at all?

Charlie: [01:17:24] Obviously, I’m more uncomfortable now than I was. The guy who changed the whole system and said, “I don’t care if the cat is black or white as long as it catches mice.”, he wanted the goddamn economy of China to work like Singapore’s. Of course we love that guy. And the new guy isn’t quite as much like that guy as we would consider ideal. We think the political risk in China should be run, and I think we should go out of our way to have a lot of friendly relations with big atomic powers.

Both China and the United States ought to get along with one another as a matter of wholly duty because they’re 2 big atomic powers. And the way you get along best is we should carefully work out a bunch of win-win transactions between us and China and actually work to make them work even better. That is the right policy in the United States.

We should not be trying to discipline China by telling them like a nattering nanny how China ought to behave and say, “We know better. We’re a democracy and you’re not.” We have a lot to be ashamed of in our own form of government. We shouldn’t be going around lecturing everybody else. And we should organize win-win transactions with China. Anything else is madness.

And for a long time, we had that. You can argue that China came to modernity primarily in win-win transactions with the United States because we’re so open to their imports. That’s what enabled them to get ahead so fast. And I’m proud of that, and I’m glad we helped them. And I want to do more of it. I don’t want this hostility on both sides.

John: [01:18:53] Tom Wolfe wrote a short story about Bob Noyce. I’m a huge Tom Wolfe fan of his books, but he has a great short story about Bob Noyce. And you can read the short story as it’s really about Grinnell, Iowa and the effect of Midwestern culture in Silicon Valley.

Charlie: [01:19:11] It’s a huge success, of course. And the success is interesting, but I would argue that the failure of Intel was just as interesting a story. Intel was on the ground floor of modern chip making. Absolutely ground zero. They were at the absolute best place. And they just grew and grew and so forth. And they eventually lost all their leadership completely, and they’re just a little pissant company compared to the big guys now.

John: [01:19:40] Why did that happen?

Charlie: [01:19:41] Firstly, some of that’s inevitable. In competitions, somebody are going to lose. It’s — partly it demonstrates the inevitable even if you’re successful, so a little guy that really scrambles, be sure that there’s some accidents, but partly, they were so interested in always reporting more earnings. They didn’t go to the leap enough, just stay on top.

If you’re serving along the edge of a new development like that, you have to just absolutely be going flat out all the time, and you have to be leading all the time. Berkshire, we don’t have to invent new things, particularly, compared to most places. They’re in the business of inventing new things, and you have to be totally fanatic.

And the truth of the matter is that the people in China were way more fanatic than Intel. In China, you had one old guy that controlled the place and he was a fanatic, and Intel had an army of bureaucrats, and they were interested in their executive rewards and the way the price earnings ratios and the approval of Wall Street. A whole lot of other things. And they were powerful. Now they look good for a while just by using their power to make the earnings go up.

But they should have been using their power to make sure their goddamn chips stayed way ahead of everybody else. And they had to be a totally reliable supplier, which they weren’t. They disappointed a lot of customers, and you can’t disappoint customers if you wanted to have a Mayo system of trust. That’s the interesting part of that, not the Noyce story. The story of the failure of Intel was the great story there…

…John: [01:31:17] Is the secret of Berkshire’s culture just the anti-bureaucracy bend? Could you sum it up…

Charlie: [01:31:22] Berkshire is pretty extreme in culture. We are deeply aware of how bureaucracies tend to create their own internal dynamics so that everybody protects everybody else and nobody changes anything, ruffles any feathers. And the net result is that a lot of bureaucracies make some very stupid decisions and we try and avoid that.

But the way we’ve done it, mostly, is by not having anybody around. They can’t be bureaucratic if they’re not there. There is nobody in the head office. So we avoided the bureaucracy. We just don’t want other people to do it. Nobody else is as extreme as we are in that. It’s a huge advantage to us.

And another thing is, we like very trustworthy people. I’d rather have a brief telephone with somebody I trust than I would a 40-page contract prepared by the finest law firm in the world with somebody I don’t trust. And so we like to deal with trustworthy people and to be able to count on their oral promises.

If you look to go into a Mayo operating room is what I call a seamless web of deserved trust. The surgeons trusting the anesthesiologist, the anesthesiologists trusting the surgeon, the nurses are trusting — everybody trusts everybody else. There’s no bureaucracy at all. They don’t have time for bureaucracy.

It’s in patients’ interest to get it over as soon as possible. And so that seamless web of deserved trust can do these very complicated procedures. We like a business system that operates as much as possible like a Mayo operating room, and that requires having very good people who are experienced enough with one another to trust one another.

John: [01:32:55] And that trust is internally between the Berkshire folks or between the Berkshire folks and the managers?

Charlie: [01:33:00] Both. We want the internal and all the Berkshire people to trust one another internally, and we also want the customers to trust us. We’re all for trust. Trust is one of the greatest economic forces on earth.

2. Charlie Munger’s Life Was About Way More Than Money – Jason Zweig

It’s 1931, and a boy and girl, both about seven years old, are playing on a swing set on N. 41st St. in Omaha. A stray dog appears and, without warning, charges. The children try to fight the dog off. Somehow, the boy is unscathed, but the dog bites the girl.

She contracts rabies and, not long after, dies. The boy lives.

His name? Charles Thomas Munger.

Charlie Munger, the brilliant investing billionaire who died on Tuesday in a California hospital 34 days before his 100th birthday, told me that story when I interviewed him last month. I’d asked the vice chairman of Warren Buffett’s Berkshire Hathaway BRK.B -0.75%decrease; red down pointing triangle: What do you think of people who attribute their success solely to their own brilliance and hard work?

“I think that’s nonsense,” Munger snapped, then told his story, which I can’t recall him ever publicly recounting. “That damn dog wasn’t 3 inches from me,” he said. “All my life I’ve wondered: Why did it bite her instead of me? It was sheer luck that I lived and she died.”

He added: “The records of people and companies that are outliers are always a mix of a reasonable amount of intelligence, hard work and a lot of luck.”

I had the extraordinary good luck to get to know Charlie Munger in the past two decades. If you think his life was only about piling up money, think again. Few people have ever been wealthier, in all the senses of the word, than Munger was.

Those who know only a little about him think Munger was a paragon of how to pick stocks—which he was. But those who knew him well consider him a moral exemplar—someone who showed how to think clearly, deal fairly and live fully. He took nothing for granted.

More than almost anyone I’ve ever known, Munger also possessed what philosophers call epistemic humility: a profound sense of how little anyone can know and how important it is to open and change your mind…

…“Part of the reason I’ve been a little more successful than most people is I’m good at destroying my own best-loved ideas,” Munger told the Journal in 2019. “I knew early in life that that would be a useful knack and I’ve honed it all these years, so I’m pleased when I can destroy an idea that I’ve worked very hard on over a long period of time. And most people aren’t.”…

…Munger deliberately kept himself surrounded by people he liked. “Many of the richest people have holes inside of them that they’re always trying to fill,” Munger’s friend Peter Kaufman said last month. “But Charlie knows you can’t fill those holes with money. That’s why he spends so much time with friends and family.”…

…One lesson: the importance of what Munger called “a seamless web of deserved trust” in which a company deals fairly with employees, customers, competitors and other constituencies.

“If you’re structurally adversarial to those adjacent to you in the ecosystem, maybe you prosper for five years,” said Collison, “but not for 75 years!”…

…“You know how a lot of old people say, ‘At my age I don’t even buy green bananas’?” regular guest John Hawkins, co-founder of private-equity firm Generation Partners, said recently. “Well, Charlie is buying green bananas by the truckload. He’s making investments for the next 10, 20, 30 years. He has his foot on the gas and is not taking it off.”…

…He mocked the marketing of short-term investment performance by telling a story about a man who walks into a fishing-tackle store and sees a bunch of gaudy, iridescent lures. “My God, they’re purple and green!” he says to the owner. “Do fish really take these lures?” The store owner answers, “Mister, I don’t sell to fish.”…

…Then I asked what he might want for an epitaph of no more than 10 words.

His reply was immediate and full of epistemic humility: “I tried to be useful.”

Not “I was useful.” That would be for other people to judge. But “I tried.” That much he knew.

3. What Will It Take for China’s GDP to Grow at 4–5 Percent Over the Next Decade? – Michael Pettis

There are two different groups of economists in China that believe that with the right—albeit very different—set of economic policies, China’s economy will be able to grow sustainably by 4–5 percent for many more years. One group argues that China must maintain the investment-driven and manufacturing-intensive strategy it has followed during the past three to four decades. The other group argues instead that China can maintain high growth rates only if it sharply reduces the investment share of GDP and replaces it with a greater reliance on consumption, something which Beijing has been trying to do for over a decade…

…Can China maintain high GDP growth rates driven by high investment? Some simple arithmetic is useful here. Globally, according to the World Bank, investment represents on average 25 percent of each country’s GDP and has remained within a tight range of between 23 percent and 27 percent during this century…

…China, however, is a huge outlier. It currently invests 42–44 percent of its GDP. What’s more… for the past two decades China’s investment share of GDP has never been below 40 percent; it reached as high as 47 percent in 2010 and 2011. In the previous two decades, the investment share of GDP was lower, but it still exceeded 35 percent on average, leaving China during the past four decades with the highest investment share of GDP, and the fastest growth rate in investment, in history.

The obvious implication is that while China accounts for a disproportionately small share of global consumption, it accounts for a disproportionately large share of global investment… According to the World Bank, China’s $18 trillion economy accounts for just under 18 percent of global GDP, making it the world’s second-largest economy after the United States, which accounts for about 25 percent. But China comprises only 13 percent of global consumption and an astonishing 32 percent of global investment…

…if China maintained its high investment share of GDP—in other words, if investment continued to grow as fast as GDP—and GDP grew at rates of 4–5 percent for the next decade, China’s share of global GDP would rise by less than 3 percentage points, to 21 percent, while its share of global investment would rise by more than 5 percentage points, to 38 percent. Its share of global consumption, however, would rise by well under 2 percentage points, to less than 15 percent.

Can China really account for 38 percent of global investment while its economy comprises just 21 percent of global GDP and 15 percent of global consumption? Every $1 of investment has required approximately $3 of consumption globally to sustain it during this century. In China, however, $1 of investment is balanced by only $1.30 of consumption. If the global relationship between consumption and investment held over the next decade, an increase in the Chinese share of global investment from 32 percent today to 38 percent in a decade would require that the rest of the world disinvest to accommodate China’s domestic imbalances.

To give a sense of just how extreme this requirement is, it would mean that to prevent a global overproduction crisis (which would hit China especially hard), the rest of the world would have to agree to reduce the investment share of its GDP by roughly 1 full percentage point, to 19 percent of GDP, well under half of the Chinese level. Needless to say, this is very unlikely, especially with the United States, the EU, and India putting into place policies aimed at boosting domestic investment.

What’s more, to the extent that the surge in China’s debt burden is driven by its extraordinarily high investment share of GDP, it would require China’s debt-to-GDP ratio to rise from just under 300 percent today to at least 450–500 percent in a decade. Given the huge difficulties the Chinese economy is already facing at current debt levels, and the difficulties Beijing has had in its attempts to reduce the debt burden, it is hard to imagine that the economy could tolerate such a substantial increase in debt…

…Globally, according to World Bank data, manufacturing represents 16 percent of GDP and has ranged from 13 percent to 17 percent during this century.

China, once again, is an extreme outlier, with manufacturing representing 28 percent of the country’s GDP. This share had declined from 32 percent in the decade before 2020, but it has risen in the past two years. This recent increase is not surprising. As a consequence of the contraction since 2021 in China’s long-lasting property bubble, there has been a major, policy-driven shift in investment from the property sector to the manufacturing sector, even though the evidence suggests that investment in Chinese manufacturing has been constrained by weak demand—not by scarce capital—so that even more investment in the manufacturing sector implies a further growth in excess capacity (that is, growth in domestic capacity that exceeds growth in domestic demand)…

…While China accounts for 18 percent of global GDP and only 13 percent of global consumption, it currently accounts for an extraordinary 31 percent of global manufacturing. If China maintained annual GDP growth rates of 4–5 percent while also maintaining the role of manufacturing in its economy, its share of global GDP would rise by less than 3 percentage points in a decade, to 21 percent, even as its share of global manufacturing would rise by more than 5 percentage points, to 36 percent…

…To accommodate this and prevent a global overproduction crisis, the rest of the world would have to allow its manufacturing share of GDP to drop between 0.5 and 1.0 percentage points. It would also have to allow a surge in China’s trade surplus—currently equal to nearly 1 percent of the GDP of the rest of the world—as a 5–8-percentage-point increase in China’s share of global manufacturing would be backed by a 2-percentage-point increase in China’s share of global consumption.

Again, this is very unlikely, especially with the United States, the EU, and India enacting policies aimed at protecting and boosting domestic manufacturing. In fact, given China’s determination to increase its reliance on manufacturing to drive growth, I expect global trade relationships to deteriorate sharply in the next few years as the world’s major economies battle over their respective manufacturing sectors…

…The net result would be persistent downward pressure on global demand as major economies competed by subsidizing production at the expense of consumption. This would only worsen global trade relationships because, in the end, only economies that were willing to protect their manufacturing sectors, or maximize the subsidies they delivered to domestic manufacturers, would be able to prevent their manufacturing sectors from contracting as a share of total GDP…

…If they set off a global trade conflict involving the United States, the EU, India, and Japan, the results would be especially painful for countries such as China that rely on large trade surpluses to balance weak domestic demand with an overreliance on manufacturing to drive growth.

That’s because without sustained trade surpluses, there are only two ways a country can balance excess supply with weak domestic demand. One way involves a painful and potentially disruptive collapse in production, as occurred most famously in the United States in the early 1930s, when it had to try to resolve its huge trade surplus in a contracting world economy exacerbated by beggar-thy-neighbor trade and currency policies. The other way is to boost domestic demand as quickly as possible…

…To put it another way, if China wanted to maintain GDP growth rates of 4–5 percent, Beijing would have to engineer policies that caused consumption to grow by at least 6–7 percent a year, with investment growing at roughly 1 percent annually.[3] Any lower consumption growth rate would mean that China could not rebalance its economy in a decade and still maintain current GDP growth rates.

If China pulled this off, at the end of the ten-year period its GDP would comprise 21 percent of global GDP (up from 18 percent in 2022). Its economy would be far more balanced, with investment comprising 29 percent of global investment (down from 31 percent in 2022) and consumption comprising 18 percent of global consumption (up from 13 percent in 2022). In that case, as its share of global GDP would rise by nearly 3 percentage points, its share of global investment would decline by 2 percentage points and its share of global consumption would rise by 5 percentage points.

With consumption growing at roughly 4 percent a year before the pandemic (and much less since), is 6–7 percent growth in consumption possible? No country in history at this stage of the development model has been able to prevent consumption from dropping, let alone cause it to surge, but that doesn’t mean it’s impossible.

But it won’t be easy. With investment growth slowing, which means fewer jobs building bridges, train stations, and apartment complexes, the only way to accelerate consumption growth sustainably is to get household income growth to accelerate through transfers—either directly (such as through wages and other income) or indirectly (such as through a stronger social safety net).

The problem with transfers is that they must be paid for, and there are only three sectors that, in theory, can meaningfully pay for them. One sector that can pay is the rich, who consume a much lower share of their income than ordinary households…

…A second sector that can be forced to pay is the business sector. For example, businesses can pay for these transfers in the form of rising wages, higher taxes, a strengthening currency, or higher borrowing costs (if these are matched by higher deposit rates for household savers). The problem is that with China’s manufacturing competitiveness based primarily on the very low share of income Chinese workers retain relative to their productivity, this would seriously undermine Chinese manufacturing.

The only other sector that can pay is government. There are in fact two levels of government in China: Beijing and local governments. Given the structure of payments and social transfers in China, along with Beijing’s explicit refusal to absorb the various debt and adjustment costs, it is very unlikely that Beijing will be willing to take on the full costs of transfers, which would require mainly central government borrowing.

That leaves local governments as the sector most likely to absorb the costs. By my calculations, if Beijing forced local governments to transfer roughly 1.5 percent of GDP every year to households, it would be possible to drive the growth in both household income and household consumption to around 7 percent annually. This is not as hard as it might at first seem. In spite of terrible cash flow pressures in recent years, local governments may own assets worth as much as 20–30 percent of China’s GDP.

But transferring such a large share of local governments’ assets won’t be easy. Such substantial transfers would be politically contentious and require a transformation of a wide range of elite business, financial, and political institutions at the local and regional level…

…The arithmetic, however, is quite straightforward: unless the rest of the world is willing to reverse its strategic economic priorities to accommodate Chinese growth ambitions, global constraints imply that China cannot continue growing its share of global GDP without sharply reducing the growth rate of investment and manufacturing.

4. The CRISPR Era Is Here – Sarah Zhang

Four years ago, she joined a groundbreaking clinical trial that would change her life. She became the first sickle-cell patient to be treated with the gene-editing technology CRISPR—and one of the first humans to be treated with CRISPR, period. CRISPR at that point had been hugely hyped, but had largely been used only to tinker with cells in a lab. When Gray got her experimental infusion, scientists did not know whether it would cure her disease or go terribly awry inside her. The therapy worked—better than anyone dared to hope. With her gene-edited cells, Gray now lives virtually symptom-free. Twenty-nine of 30 eligible patients in the trial went from multiple pain crises every year to zero in 12 months following treatment.

The results are so astounding that this therapy, from Vertex Pharmaceuticals and CRISPR Therapeutics, became the first CRISPR medicine ever approved, with U.K. regulators giving the green light earlier this month; the FDA appears prepared to follow suit in the next two weeks. No one yet knows the long-term effects of the therapy, but today Gray is healthy enough to work full-time and take care of her four children…

…The approval is a landmark for CRISPR gene editing, which was just an idea in an academic paper a little more than a decade ago—albeit one already expected to cure incurable diseases and change the world. But how, specifically? Not long after publishing her seminal research, Jennifer Doudna, who won the Nobel Prize in Chemistry with Emmanuelle Charpentier for their pioneering CRISPR work, met with a doctor on a trip to Boston. CRISPR could cure sickle-cell disease, he told her. On his computer, he scrolled through DNA sequences of cells from a sickle-cell patient that his lab had already edited with CRISPR. “That, for me, personally, was one of those watershed moments,” Doudna told me. “Okay, this is going to happen.” And now, it has happened. Gray and patients like her are living proof of gene-editing power. Sickle-cell disease is the first disease—and unlikely the last—to be transformed by CRISPR.

All of sickle-cell disease’s debilitating and ultimately deadly effects originate from a single genetic typo. A small misspelling in Gray’s DNA—an A that erroneously became a T—caused the oxygen-binding hemoglobin protein in her blood to clump together. This in turn made her red blood cells rigid, sticky, and characteristically sickle shaped, prone to obstructing blood vessels. Where oxygen cannot reach, tissue begins to die…

…The basic technology is a pair of genetic scissors that makes fairly precise cuts to DNA. CRISPR is not currently capable of fixing the A-to-T typo responsible for sickle cell, but it can be programmed to disable the switch suppressing fetal hemoglobin, turning it back on. Snip snip snip in billions of blood cells, and the result is blood that behaves like typical blood.

Sickle cell was a “very obvious” target for CRISPR from the start, says Haydar Frangoul, a hematologist at the Sarah Cannon Research Institute in Nashville, who treated Gray in the trial. Scientists already knew the genetic edits necessary to reverse the disease. Sickle cell also has the advantage of affecting blood cells, which can be selectively removed from the body and gene-edited in the controlled environment of a lab. Patients, meanwhile, receive chemotherapy to kill the blood-producing cells in their bone marrow before the CRISPR-edited ones are infused back into their body, where they slowly take root and replicate over many months.

It is a long, grueling process, akin to a bone-marrow transplant with one’s own edited cells. A bone-marrow transplant from a donor is the one way doctors can currently cure sickle-cell disease, but it comes with the challenge of finding a matched donor and the risks of an immune complication called graft-versus-host disease. Using CRISPR to edit a patient’s own cells eliminates both obstacles. (A second gene-based therapy, using a more traditional engineered-virus technique to insert a modified adult hemoglobin gene into DNA semi-randomly, is also expected to receive FDA approval for sickle-cell disease soon. It seems to be equally effective at preventing pain crises so far, but development of the CRISPR therapy took much less time.)

In another way, though, sickle-cell disease is an unexpected front-runner in the race to commercialize CRISPR. Despite being one of the most common genetic diseases in the world, it has long been overlooked because of whom it affects: Globally, the overwhelming majority of sickle-cell patients live in sub-Saharan Africa. In the U.S., about 90 percent are of African descent, a group that faces discrimination in health care. When Gray, who is Black, needed powerful painkillers, she would be dismissed as an addict seeking drugs rather than a patient in crisis—a common story among sickle-cell patients…

…Doctors aren’t willing to call it an outright “cure” yet. The long-term durability and safety of gene editing are still unknown, and although the therapy virtually eliminated pain crises, Hsu says that organ damage can accumulate even without acute pain. Does gene editing prevent all that organ damage too? Vertex, the company that makes the therapy, plans to monitor patients for 15 years.

Still, the short-term impact on patients’ lives is profound. “We wouldn’t have dreamed about this even five, 10 years ago,” says Martin Steinberg, a hematologist at Boston University who also sits on the steering committee for Vertex. He thought it might ameliorate the pain crises, but to eliminate them almost entirely? It looks pretty damn close to a cure…

…The field is already looking at techniques that can edit cells right inside the body, a milestone recently achieved in the liver during a CRISPR trial to lower cholesterol. Scientists are also developing versions of CRISPR that are more sophisticated than a pair of genetic scissors—for example, ones that can paste sequences of DNA or edit a single letter at a time. Doctors could one day correct the underlying mutation that causes sickle-cell disease directly…

…We have opened the book on CRISPR gene editing, Frangoul told me, but this is not the final chapter. We may still be writing the very first.

5. Introducing Gemini: our largest and most capable AI model – Sundar Pichai and Demis Hassabis

I believe the transition we are seeing right now with AI will be the most profound in our lifetimes, far bigger than the shift to mobile or to the web before it. AI has the potential to create opportunities — from the everyday to the extraordinary — for people everywhere. It will bring new waves of innovation and economic progress and drive knowledge, learning, creativity and productivity on a scale we haven’t seen before…

…Millions of people are now using generative AI across our products to do things they couldn’t even a year ago, from finding answers to more complex questions to using new tools to collaborate and create. At the same time, developers are using our models and infrastructure to build new generative AI applications, and startups and enterprises around the world are growing with our AI tools…

…We’re approaching this work boldly and responsibly. That means being ambitious in our research and pursuing the capabilities that will bring enormous benefits to people and society, while building in safeguards and working collaboratively with governments and experts to address risks as AI becomes more capable…

…Now, we’re taking the next step on our journey with Gemini, our most capable and general model yet, with state-of-the-art performance across many leading benchmarks. Our first version, Gemini 1.0, is optimized for different sizes: Ultra, Pro and Nano. These are the first models of the Gemini era and the first realization of the vision we had when we formed Google DeepMind earlier this year…

…We’ve been rigorously testing our Gemini models and evaluating their performance on a wide variety of tasks. From natural image, audio and video understanding to mathematical reasoning, Gemini Ultra’s performance exceeds current state-of-the-art results on 30 of the 32 widely-used academic benchmarks used in large language model (LLM) research and development.

With a score of 90.0%, Gemini Ultra is the first model to outperform human experts on MMLU (massive multitask language understanding), which uses a combination of 57 subjects such as math, physics, history, law, medicine and ethics for testing both world knowledge and problem-solving abilities.

Our new benchmark approach to MMLU enables Gemini to use its reasoning capabilities to think more carefully before answering difficult questions, leading to significant improvements over just using its first impression.

Gemini Ultra also achieves a state-of-the-art score of 59.4% on the new MMMU benchmark, which consists of multimodal tasks spanning different domains requiring deliberate reasoning…

…Until now, the standard approach to creating multimodal models involved training separate components for different modalities and then stitching them together to roughly mimic some of this functionality. These models can sometimes be good at performing certain tasks, like describing images, but struggle with more conceptual and complex reasoning…

…Gemini 1.0 was trained to recognize and understand text, images, audio and more at the same time, so it better understands nuanced information and can answer questions relating to complicated topics. This makes it especially good at explaining reasoning in complex subjects like math and physics.

We designed Gemini to be natively multimodal, pre-trained from the start on different modalities. Then we fine-tuned it with additional multimodal data to further refine its effectiveness. This helps Gemini seamlessly understand and reason about all kinds of inputs from the ground up, far better than existing multimodal models — and its capabilities are state of the art in nearly every domain…

…Gemini Ultra excels in several coding benchmarks, including HumanEval, an important industry-standard for evaluating performance on coding tasks, and Natural2Code, our internal held-out dataset, which uses author-generated sources instead of web-based information.

Gemini can also be used as the engine for more advanced coding systems…

…Using a specialized version of Gemini, we created a more advanced code generation system, AlphaCode 2, which excels at solving competitive programming problems that go beyond coding to involve complex math and theoretical computer science.

When evaluated on the same platform as the original AlphaCode, AlphaCode 2 shows massive improvements, solving nearly twice as many problems, and we estimate that it performs better than 85% of competition participants — up from nearly 50% for AlphaCode. When programmers collaborate with AlphaCode 2 by defining certain properties for the code samples to follow, it performs even better…

…We trained Gemini 1.0 at scale on our AI-optimized infrastructure using Google’s in-house designed Tensor Processing Units (TPUs) v4 and v5e. And we designed it to be our most reliable and scalable model to train, and our most efficient to serve.

On TPUs, Gemini runs significantly faster than earlier, smaller and less-capable models. These custom-designed AI accelerators have been at the heart of Google’s AI-powered products that serve billions of users like Search, YouTube, Gmail, Google Maps, Google Play and Android. They’ve also enabled companies around the world to train large-scale AI models cost-efficiently.

Today, we’re announcing the most powerful, efficient and scalable TPU system to date, Cloud TPU v5p, designed for training cutting-edge AI models. This next generation TPU will accelerate Gemini’s development and help developers and enterprise customers train large-scale generative AI models faster, allowing new products and capabilities to reach customers sooner…

…Gemini has the most comprehensive safety evaluations of any Google AI model to date, including for bias and toxicity. We’ve conducted novel research into potential risk areas like cyber-offense, persuasion and autonomy, and have applied Google Research’s best-in-class adversarial testing techniques to help identify critical safety issues in advance of Gemini’s deployment.

To identify blindspots in our internal evaluation approach, we’re working with a diverse group of external experts and partners to stress-test our models across a range of issues.

To diagnose content safety issues during Gemini’s training phases and ensure its output follows our policies, we’re using benchmarks such as Real Toxicity Prompts, a set of 100,000 prompts with varying degrees of toxicity pulled from the web, developed by experts at the Allen Institute for AI. Further details on this work are coming soon.

To limit harm, we built dedicated safety classifiers to identify, label and sort out content involving violence or negative stereotypes, for example. Combined with robust filters, this layered approach is designed to make Gemini safer and more inclusive for everyone. Additionally, we’re continuing to address known challenges for models such as factuality, grounding, attribution and corroboration…

…Starting today, Bard will use a fine-tuned version of Gemini Pro for more advanced reasoning, planning, understanding and more. This is the biggest upgrade to Bard since it launched. It will be available in English in more than 170 countries and territories, and we plan to expand to different modalities and support new languages and locations in the near future.

We’re also bringing Gemini to Pixel. Pixel 8 Pro is the first smartphone engineered to run Gemini Nano, which is powering new features like Summarize in the Recorder app and rolling out in Smart Reply in Gboard, starting with WhatsApp — with more messaging apps coming next year.

In the coming months, Gemini will be available in more of our products and services like Search, Ads, Chrome and Duet AI.

We’re already starting to experiment with Gemini in Search, where it’s making our Search Generative Experience (SGE) faster for users, with a 40% reduction in latency in English in the U.S., alongside improvements in quality.

Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. We currently have a vested interest in Alphabet (the company behind Gemini) and Costco. Holdings are subject to change at any time.

What We’re Reading (Week Ending 03 December 2023)

The best articles we’ve read in recent times on a wide range of topics, including investing, business, and the world in general.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

Here are the articles for the week ending 03 December 2023:

1. Charlie Munger, Warren Buffett’s Partner and ‘Abominable No-Man,’ Dies at 99 – Jason Zweig and Justin Baer

No equal business partner has ever played second fiddle better than Charlie Munger.

Warren Buffett’s closest friend and consigliere for six decades, the billionaire vice chairman of Berkshire Hathaway died Tuesday at age 99 in a California hospital. A news release from Berkshire confirmed his death.

In public, especially in front of the tens of thousands of attendees at Berkshire’s annual meetings, Munger deferred to Buffett, letting the company’s chairman hog the microphone and the limelight. Munger routinely cracked up the crowd by croaking, “I have nothing to add.”

In private, Buffett, who is 93, often deferred to Munger. In 1971, Munger talked him into buying See’s Candy Shops for a price equivalent to three times the chocolate stores’ net worth—a “fancy price,” Buffett later recalled, far higher than he was accustomed to paying for businesses.

See’s would go on to generate some $2 billion in cumulative earnings for Berkshire over the coming decades…

…Buffett nicknamed Munger the “abominable no-man” for his ferocity in rejecting potential investments, including some that Buffett might otherwise have made. But Munger, who was fascinated by engineering and technology, also pushed the tech-phobic Buffett into big bets on BYD, a Chinese battery and electric vehicle maker, and Iscar, an Israeli machine-tool manufacturer.

Munger was a brilliant investor in his own right. He began managing investment partnerships in 1962. From then through 1969, the S&P 500 gained an average of 5.6% annually. Buffett’s partnerships returned an average of 24.3% annually. Munger’s did even better, averaging annualized gains of 24.4%.

In 1975, shortly before he joined Berkshire as vice chairman, Munger shut down his partnerships. Over their 14-year history, his portfolios gained an average of 19.8% annually; the S&P 500 grew at only a 5.2% rate…

…“I have been shaped tremendously by Charlie,” Buffett said in 1988. “Boy, if I had listened only to Ben [Graham], would I ever be a lot poorer.”

In 2015, Buffett wrote that Munger taught him: “Forget what you know about buying fair businesses at wonderful prices; instead, buy wonderful businesses at fair prices.”

Berkshire “has been built to Charlie’s blueprint,” Buffett added…

…Munger also confronted tragedy: In 1955, his son Teddy died of leukemia at age 9. Munger later recalled pacing the streets of Pasadena in tears at “losing a child inch by inch.” More than six decades later he would still choke up at the memory of his son’s suffering.

In 1978, a surgeon bungled a cataract surgery, leaving Munger blind in one eye, which later had to be surgically removed. The investor refused to blame the doctor, noting that complications occurred in 5% of such procedures. For him, as always, it was about the numbers.

Munger taught himself Braille, then realized he could still see well enough to read. He ended up driving his own car, often to the consternation of friends and family, until his early 90s…

…At Berkshire’s annual meeting in 2000, a shareholder asked how the speculation in Internet stocks would affect the economy. Buffett answered with nearly 550 words. Munger growled, “if you mix raisins with turds, they’re still turds.”

When a shareholder asked at the 2004 meeting how Berkshire sets pay for executives, Buffett spoke for more than five minutes. Munger drawled, “Well, I would rather throw a viper down my shirtfront than hire a compensation consultant.”…

…Munger never stopped preaching old-fashioned virtues. Two of his favorite words were assiduity and equanimity.

He liked the first, he said in a speech in 2007, because “it means sit down on your ass until you do it.” He often said that the key to investing success was doing nothing for years, even decades, waiting to buy with “aggression” when bargains finally materialized.

He liked the second because it reflected his philosophy of investing and of life. Every investor, Munger said frequently, should be able to react with equanimity to a 50% loss in the stock market every few decades.

Munger retained his sense of humor into his 90s, even though he was nearly blind, could barely walk, and his beloved wife, Nancy, had died years earlier. Around 2016, an acquaintance asked which person, in a long life, he felt most grateful to.

“My second wife’s first husband,” Munger said instantly. “I had the ungrudging love of this magnificent woman for 60 years simply by being a somewhat less awful husband than he was.”

2. How Geopolitical Risks Are Impacting Iranian Stocks – Tracy Alloway, Joe Weisenthal, Aashna Shah, and Maciej Wojtal

Maciej (04:03):

But what’s interesting and why we are doing this is that you mentioned that you were surprised how big Iran’s economy is and I would say that no, it’s actually very small compared to how big it could get because Iran, you know, it’s around 90 million people, the largest combined oil and gas reserves in the world, and a properly developed and diversified economy. Well, thanks to decades of sanctions, they didn’t have a choice. They had to develop all different parts of the economy.

And all this— in terms of GDP — is around, depending how you calculate it, but it’s around $200 billion. Now when you look at Turkey, which is a similar size country in terms of population and geographical size, but no natural resources, Turkey is around $800-$900 billion. If you look at Saudi Arabia, which has no other sectors except for oil and some petrochemicals, the GDP over there is around $1 trillion. So in some super optimistic, very positive scenario, if everything went well for Iran, Iran could become basically the combination of the two, which is anywhere between $1.8 to $2 trillion dollars.

So the upside for the economy is eight times from where it is right now. So this is the potential, this is the optionality that is in the market. On top of that, once the country starts to open up, obviously there is a long list of things that would have to come in place, then we expect to see a lot of capital flowing into the market and right now it’s only domestic capital and us, which means that because there is not enough capital the local assets are valued at very low levels.

So what we are seeing in the market is that we are buying stocks at four to five times forward net earnings and those earnings are growing, they are paying dividends. The average or the median dividend yield for the top 100 companies is probably close to 15%. So strong double digit dividend yields valuations at such levels that they cannot really fall further as long as those earnings are growing.

So investment risks are pretty small, pretty limited. You have different sorts of risks. You have geopolitics, exactly as you mentioned. I mean those equities basically are priced for war and obviously there is a reason, there might be a reason for that. It’s because it’s the Middle East and it’s amazing how the narrative, you know, the region reminded everyone that the situation and the perception of the region can make a u-turn overnight. Because a month ago, it was not only what you mentioned in the introduction that there was some sort of arrangement between Iran and the US which led to the prisoner exchange, which was very important because historically prisoner exchange was usually the first step to something bigger. Then on top of that, Iran is selling a lot of oil so obviously sanctions are probably not enforced very strictly and so on.

But the bigger story a month ago was in the whole Middle East where Iran basically signed what you can call a peace treaty with Saudi Arabia after many years of not having diplomatic relations. Then what followed were discussions and restoration of diplomatic ties with Iran and Egypt, Bahrain, all Saudi allies and so on…

…Maciej (12:22):

So on the seventh of October, I believe that it was the case for the whole region that the local currencies sold off and local stock markets went down. What happened was that initially everything went down. For the first three weeks, the local equity index measured in dollar terms was going down with the lowest point around 10% in terms of the correction.

Since then it started bouncing back. In local currency terms, the equity index is actually at the level from the seventh of October so it made up for all the losses. The currency is still down. So for a foreign investor who is measuring the P&L in dollar terms, you are still roughly 3% down. So it’s actually not that bad given the circumstances, given the risk for local markets and especially Iran which is involved in everything that is going on.

The worst case scenario is that potentially there is a military conflict war, and I don’t know, Iranian refineries or petrochemical plants are military targets and so on. And people were quite scared. We could see this. Some of the sectors went down in the meantime by about 20%, bounced back since then, but mainly that was happening due to very low liquidity.

So what was the biggest impact? Actually, we could see was on liquidity. Normal liquidity is around $150 million per day, and it went to as low as $30- 40 million. So what was going down the most was actually the most illiquid stocks or illiquid industries. So when I look at sectors that really were hit the most, it’s textile producers, confectionaries, so things that are not related to war or geopolitics at all, but they are basically illiquid.

And, oh. One thing important to remember, so the stock market is driven by retail investors. 90% of daily trading is done by retail. So, it’s very emotional, it’s very short term momentum, I would say. So they are selling or buying depending on the, you know, recent price action. So they were driving the share price direction basically…

…Maciej (15:36):

Yes, and the thing that is most volatile in Iran is the currency. So the stock market is much less volatile in the local currency than when measured in dollar terms. The local stock market is actually well hedged against currency depreciations because the majority of the biggest companies are actually exporters so they benefit from currency depreciation, but share prices react with a lag…

…Maciej (19:47):

There are two interesting facts about the performance of the market. So first of all, when I looked at the last 15 years and big geopolitical events for example, like previous conflicts with Hamas in Gaza, or there was a situation between Iran and the US where people were saying that this was close to a military conflict when Iranian general Soleimani was killed and then Iran retaliated by firing some missiles at an American base in Iraq. When I looked at the performance of the market, it never went down more than 10% in dollar terms, actually.

So what happened right now, I think the bottom was around almost 11% was pretty much in line with those historical geopolitical events that also presented a big risk for the local market. But another way of looking at the Iranian market is the historical performance. And this is very interesting because if you look at the performance of the benchmark equity index, it’s called TedPix Index, total return.

For the last 15 years, so since the inception in 2018, the annualized return in dollars is around 11%, which I think is quite amazing because it’s pretty much the same as for S&P 500, maybe 12% for S&P 500, so it’s in the same ballpark and the environment was completely different. I mean, couldn’t be more different because over the last 15 years in the US you had a technology revolution, those mega caps appearing on the market, interest rates initially going to zero, top of the cycle valuations and in Iran, you had two episodes of currency depreciation of more than 75%. You had some crazy presidents and you had US sanctions, UN sanctions and still, at the end of the day, when you compare performance over the last 15 years, it’s pretty much the same, obviously with much bigger volatility because in Iran, the volatility was probably around 40% or something.

But that shows you that when you’re buying assets at very, very low valuations, and I’m say talking about this four times net earnings, let’s say, and the economy and those companies are actually naturally hedged against the currency volatility or big depreciation, then even in those countries where things are going really bad you can still make money. But what is more important is that if in bad times you are still averaging 11% per year, just think what you can make, what you can expect, when things finally go the right way for Iran and the country opens up and so on? That’s the potential that we are obviously hoping for…

…Maciej (30:25):

There are several asset classes in Iran for retail investors. So real estate is the big one, the biggest one, but it’s a high ticket item so not everyone can trade in and out of apartments. It’s a well understood asset class as everywhere. That’s why it’s a bit less interesting for us. So if Iranians have any spare cash, they will buy real estate. From what I heard, 30% of apartments in Tehran are actually empty because they are basically used as a store of value just to park somewhere, assets, savings and they’re not even rented out, they’re just empty.

And also just bear in mind that in Tehran in the best places, the best neighborhoods of Tehran prices are quite expensive. So in the north of Tehran, if you want to buy an apartment, you have to pay around $10,000 per square meter. So a 100 square meter apartment, I don’t know three bedrooms will cost you a million dollars or something, in Iran, which is a poor country. So this is real estate. Real estate is the number one asset class.

Then a very important asset class are used cars. So people trade used cars because they are, again, a hedge against inflation against the currency depreciation, because car manufacturers will always adjust prices based on inflation. Some of the components have to be imported, which is not easy. They produce more than one million cars, or actually closer probably to 1.5 million cars per year, but this is not enough. So the demand is much higher.

So they’re trading used cars and there are platforms that help you trade used cars. It’s a proper asset class, and yes, every Iranian is actually a currency trader, because the currency has been so volatile historically. It’s very important that you know what’s happening to the dollar or the local currency against the dollar. So everyone is tracking the exchange rate and it’s not easy to buy and sell dollars. There are quotas for individual Iranians due to capital controls. So that’s why, instead of buying dollars or to get a bigger position, they go to those proxy asset classes, like used cars or real estate. Also interest rates so you can buy/sell Treasury bills, Treasury bills up to two years maturity. They pay around 25% yield to maturity, maybe a bit more right now so interest rates are high.

When you look at Iran, there is not enough capital there. There’s basically not enough money, credit doesn’t exist. I mean, you cannot get a mortgage at 25%, right? I mean, you cannot finance anything at 25%. And because of very volatile macro people also tend to postpone investment decisions, whether these are individuals or more importantly companies, right?

Everyone is looking like six months ahead, maybe 12 months ahead, right? And they are managing a crisis, because there is always some sort of a crisis, right? So when you think about it, for example, I don’t know, every company is running big inventories just in case, just so that they have enough material to manufacture their products. So they’re not optimized, organized in this very efficient, lean way. They are organized just to survive, basically, war conflict, currency depreciation, sanctions, trade disruptions, whatever…

…Maciej (35:41):

So when sanctions were reintroduced in 2018, they haven’t hurt manufacturing, they haven’t hurt exports, companies that much, to be honest. I mean, because people find a way. I mean, companies that export in the region, they’re not really affected by sanctions, big exporters that used to send products to Japan and so on, yes, they were affected, but they found other routes and manufacturers.

Sanctions caused one thing. I mean, sanctions caused currency volatility so the big depreciations of Rial and manufacturers who have costs in Rial, but they either sell in hard currency or at prices linked to some regional benchmarks that are in hard currency, their margins actually expanded.

Look, it’s an interesting thing that the highest earnings growth that we’ve seen over the last couple of years was one year after the 2018 sanctions. This is crazy because this is not intended, I would assume. And, who got hurt by sanctions? Well, households, because they are price takers. So when the inflation shut off because of the currency depreciation, their spending power went down massively, right? And they were able to survive and it was actually quite interesting that they were holding up quite well. And this is because of those savings, right?

Because of the savings that Iranian households had. I’m not sure what’s the situation right now, because they’ve been, I think, on a net basis, those savings have been decreasing over the last couple of years because they had just had to spend them. But yes, that’s what helped them survive the inflation basically.

3. Frugal vs. Independent – Morgan Housel

Frugal, by my definition, means depriving yourself of something you want and could afford.

Not wanting something to begin with because you get your pleasure and identity from sources that can’t be purchased is something entirely different. The best word for it is probably independent…

…The world tells you – even by a mere whisper – that everyone should want the same things: A big house, a nice car, advanced degrees, credentials, social clubs, etc.

I like most of those things. But you have to realize how much of their appeal is an attraction to status, which can be completely different from happiness.

There’s a recent example of someone understanding the difference in real time that I think is more fascinating than Holt or Read’s story.

Chuck Feeney, who founded Duty Free stores, died last month.

The well-known part of Feeney’s story is that he gave away 99.99% of his $8 billion fortune years ago, before he died. He and his wife kept $2 million, lived in a small apartment, flew coach, and gave the rest to charity.

The less well-known part of Feeney’s story is that he once gave the High Life an honest try. The Washington Post wrote of his life in 1980s, when he was newly rich:

He had luxury apartments in New York, London and Paris and posh getaways in Aspen and the French Riviera. He hobnobbed with the other mega-rich on yachts and private jets. If he wanted it, he could afford it.

He quickly realized it wasn’t for him. Society told him he should want those things. But it wasn’t what actually made him happy.

Giving money away was.

“I’m happy when what I’m doing is helping people and unhappy when what I’m doing isn’t helping people,” Feeney said…

…He didn’t follow a typical path of what other people told him to like or how to live.

He found what made him happy.

He may have looked frugal, but he was actually the freest, most independent person you’ll ever hear of.

4. Value Investing with Legends: Nicolai Tangen – Decision-Making and Intuition in Investing (transcript here) – Michael Mauboussin, Tano Santos, and Nicolai Tangen

Mauboussin: What motivated you to do that? And a slightly odd question. Do you see parallels between the investing and the art worlds at all?

Tangen: So I had been very well paid at Egerton and so could afford to take a break. I wanted to do something which was very different. And so I studied German Expressionist Woodcuts, pretty black and white. And it’s wonderful to study with people who think differently and who really want to dig down. And of course, you get your attention span back up from like 2 seconds to 2 hours when you have to write a dissertation and so on. So that was good.

Are there any similarities between art and investing? Well, I don’t think so. Some people claim there is. It’s not for me. I love art because it’s very different from what I do on a daily basis. But perhaps it’s good for creativity. It’s certainly good for the soul. It’s fun, it’s beautiful, interesting.

Santos: You know, when I was telling that we had this point of connection, it’s because I came very close to studying art history when I was a young man. I became completely obsessed with our history. And I spent every summer during my teenage years travelling around France and Italy, trying to absorb as much as I could, you know. And at some point I learned that I also like teaching, so that’s when I decided to go in a different direction. But you’re absolutely right, it’s something that sustains you throughout life.

Tangen: A big difference is you study art, it’s something dead, it’s on the wall. Finance, it’s alive, it’s incredible. I just think finance is just an amazing thing to study because it’s everything that you eat, wear, drive, consume, all these kind of things. It’s about the people, it’s about the psychology, it’s about corporate culture, it’s about – in the market, greed and fear, it’s related to macro. Security, wars, geopolitics and it changes all the time. All the time. And if you’re good at it, you make money. And so it is just the most interesting thing you can ever spend your time doing…

…Tangen: Now, we started off as a mid cap firm and then gradually went a bit larger cap because we thought we could add value also there. Also gradually we gravitated towards the higher quality spectrum of stocks and now that’s all I care about. It’s the high quality end. It’s companies which can grow earnings, high return on capital and solid moats. A lot of these things we look for. The rest of it is basically a waste of time. The fewer decisions you can make, the better they become. So if you can just sit there and compound, I just think it’s such a wonderful idea. Is it easy? No, it’s super tough. It’s super tough.

And why is that? Well, I kind of think, you come home from work, your husband or wife asks you, “What have you been doing today?” “Well, I’ve done nothing.” Next day, Tuesday, “What have you been doing today?” Nothing. Wednesday, nothing. Thursday nothing, Friday nothing. You just feel like a failure. So therefore you feel you have to trade a bit, but it’s mostly not very profitable…

…Mauboussin: Do you guys know this book came out this year called How Big Things Get Done? Do you know this, Nicolai? Bent Flyvbjerg and Dan Gardner?

Tangen: Yeah, I read it. It’s very good.

Mauboussin: But I think Chapter One is called Think Slow, Act Fast. And I really like that because the “think slow” part is, a lot of it is contemplation and from time to time you do have to act quickly. But for the most part it’s just sitting around and thinking and trying to line things up. You mentioned that finance is wondrous. I clearly agree with that. But I do want to come back to one of the educational items on your CV and that’s a Master’s in social psychology from the London School of Economics. And I believe you’ve suggested that social psychology is something that everyone should study. I think we spend a little bit of time on it in our finance curriculum, but probably not as much as we should. So tell us a little bit about your takeaways from studying behavior and how that applies to markets, both in good times and in challenging times.

Tangen: I think everybody should study it. And I saw that increasingly everything I read was within the social psychology area and I did it actually part time when I still ran AKO. I did my dissertation on looking at gut feel versus analysis and I interviewed the 15, who I thought were the best performing fund managers in Europe, and analyzed how were they actually going about making decisions. And it’s quite interesting because psychologists don’t typically have access to these well paid hedge fund managers and so on. So it was kind of gold dust kind of sample that I had there.

And what you see is that people, if you call it gut feel, nobody believes in it. If you call it pattern recognition, everybody believes in it, even though it’s the same thing. You don’t believe in anybody else’s gut feel, only your own. And you can mainly use it if you are quite senior in the firm, because you can’t come and say, listen, hey, I’m 22 years old, I really believe I have a gut feel that this and that. Now you’re 55, you’re the boss, everybody listens to you and you have more data points and more experience. So your gut feel is basically better or pattern recognition. That’s interesting. Then you use it when you have very little time, when things are urgent, and you use it when the problems are really complex and difficult to analyze.

My impression was that the best ones go from one to the other, so it depends on the situation. But that was really interesting…

…Tangen: I also spent time on people’s risk appetite. Now it’s very, very important when you run an asset management company, is to understand people’s risk appetite. Risk appetite is linked to different things, such as gender. So women take less risk than men. And you only look at the drowning statistics from Norway. Nine out of 10 people who drown are men, so they take more risks. You see it in traffic accidents and so on. Has to do with age, has to do with geographies, introvert, extrovert. So introverts take less risk. And you need to know that, because if an introvert woman aged 50 comes to you and want to take risk, that means something different from an extrovert guy, 22, from America. You need to dial it up and down. The noise level is really, really important.

The last thing I spent time on in social psychology was just to how to unbias your decisions. Extremely important that you’re able to question your own decision making and change your mind when the facts change. So really interesting, everybody, you just have to study it. It’s just the best thing to study.

Mauboussin: So, Nicolai, on that last one, are there a couple guides you would give to folks to debias as they go through their process, or there are tools that you would pull out?

Tangen: Well, the biggest bias people have is the fact that you don’t think you’re biased. Adam Grant’s book, Think Again, the whole mindset there of confident humility, that’s where you need to be as an investor. You need to be confident and you need to be really stubborn, because where you make money is, of course, where you do the opposite of everybody else. But when things change, you just need to change your mind. So that combination of being stubborn and agile is rare. But those are the guys who make the most money. I mean, look at Stan Druckenmiller, who is very confident about his decisions, but then, bang, something changes and he changes tact…

…Tangen: I sail. And at that stage, I sailed quite a bit of competition and I sailed with some spectacularly good sailors, some Olympic people. And I asked, why are you so good? And the whole debrief process was key. So two things which were key to their success. It was the bounce back ability – so how you get back on your horse after a loss, which you also, of course, need in investing. But then the debrief process was really important. And so we started to work with sports psychologists in terms how to improve these kind of things.

And one of the important thing when you look at high achievers in sport is that they focus in on the process rather than the results. And if your process is right, the results will come. And of course, in investing, this is more important than anywhere else, because in investing in the short term, there is just no correlation between process and outcome, whilst in the long term, that’s what it’s all about. And so you need to judge your process. And we kind of split the investment process into different categories and then we graded each analyst on each part of that process with regular intervals. And that’s a really good thing to do because if you go through a period of underperformance, as long as you see that your process is improving, you shouldn’t be too depressed about it…

…Tangen: I probably spend more time now on corporate culture than I did in the past. It’s so unbelievably important. And you have two companies which from the outside look exactly the same, right? They pretty much have the same product and so on. And then one of them is doing extremely well, and the other one is just not doing well. Gee, look at the banking. Look at the banking sector. On my podcast, I interviewed James Gorman, 14-year CEO of Morgan Stanley, and how Morgan Stanley has really done well compared to other banks. So it’s just intriguing how important corporate culture is. And that is also something that CEOs are very keen to talk about but the analysts generally are not so keen because the result of corporate culture work you see only in the long term, and most of the analysts are very short term.

And another interesting thing is that when you are young, you’re 25 years old, you are so in a hurry, despite having the whole life ahead of you. Now, when you are like 57, like me, and about to die, you suddenly get this long term time horizon. It makes no sense. But I think that’s just interesting. And I just met this 85 year old Spanish guy the other day and he was just planting some pistachio trees and he couldn’t wait. I can’t remember how long time it took for them to bear fruit, but it was certainly – I mean, he would probably not be alive then. He was really excited about it. I thought that was so cool…

…Tangen: Norway found oil in 69, on the very last attempt, on the very last well, they were drilling. If they hadn’t found oil on that last one, they would have just packed up the toys and gone home. So pretty amazing. Now, this was told to the Norwegian people on the day before Christmas Eve, 69, and wow, what a Christmas gift.

But the thing was that was it really? Because in a lot of other countries it had been a curse and it had led to corruption and crowding out effects and so on. And then some very clever politicians decided, you know what, let’s put the money into a fund. So they did, 27 years ago, started with a deposit of 2 billion Norwegian kroner, and that has now grown to more than 15,000 billion. So it’s been just an unbelievable success…

…Tangen: Now we are also generally pretty vocal on ESG because we think it’s very very important. We do think the link between climate and finance is strong and getting stronger. Climate is driving food inflation through bad harvests and food price increases. It’s also not driving it through productivity. So that link is strong and established…

…Mauboussin: So, Nicolai, when you end up hanging up your cleats, finally, how will you define success for the fund? I’m sure returns are obviously very important, but what other factors you think will be important to judge your success, as CEO of Norges?

Tangen: We have a clear goal in our strategy document. We want to be the best large investment fund in the world. How do you define that? Well, one thing is performance, but it has to do with process, reputation, risks. And also, I would judge it, just how happy are people working there? Are they using their full potential? Are they thriving? Do they have a good life? Very, very important. And are they having fun? Fun – completely underestimated. People who get fun, they’re more creative. It’s a great leveller. It’s kind of, in a way, the goal of everything we do. You want to have fun and you want to be fulfilled…

…Tangen: I do think a lot about productivity and the lack of productivity growth. And in particular, I’m thinking about Europe versus the US. Because in the US, there is more innovation, there is more speed, and Europe is pretty slow.

And what is it with Europe? Why don’t we have great technology companies? Why is growth pretty pedestrian? And it’s just a combination of so many things. It’s a mindset thing. In Europe, we think 2% growth is fine. Well, perhaps it should be five, perhaps it should be 10. We have very few kind of hairy goals. And you read the Elon Musk book and you understand what a hairy goal is. The speed, the speed by which you move. It just struck me here. I’m in New York now, and just the speed by which they pack a sandwich, right? It’s just like five times quicker than they do it in Europe. The depth of capital market, the lack of depth in the corporate bond market, you’ve got more risky capital here, or risk-seeking capital, you’ve got more venture capital. You can fail. And now in Europe, it’s not good to fail. Much bigger public sector, which probably slows down the thing. I really think union is a great thing, but it does something with structure of businesses. So you have a whole range of things which make Europe slower than America, then that worries me. But I’m doing more work here. This is my next thinking project. Really interesting.

5. Parallel Bets, Microsoft, and AI Strategies – Matthew Ball

Parallel bets strategies are best suited to (1) cash-rich companies . . . that are (2) pursuing “must-win” categories” . . . in which (3) their assets and strategies are a good fit . . . but (4) may not be configured correctly . . . and (5) there is a high rate of change . . . and (6) many uncertainties . . . and (7) many players . . . with (8) progress often occurring out of sight. Deployed correctly, a company can cover all of the bases while also neutralizing the existential threat of a new competitor. Parallel bets are therefore likely the right strategy generally for “Big Tech” and during this phase of AI, during which there are many unresolved and interconnected hypotheses.

Will closed or open models be more capable? If closed models are technically superior, will open models nevertheless be considered “superior” on a cost-adjusted basis? What is the trade-off between the quality of a generative AI response and its cost? How does this vary by vertical?
How many of the potential uses of generative AI will result in new companies/applications, rather than new or improved functionality in the products of existing market leaders? Put another way, is the technology or distribution more important? Is there a hybrid model in which users access existing applications, such as PhotoShop or Microsoft Office, but while logging into a third-party AI service, such as OpenAI?
Which AI products or integrations will warrant additional revenue from the user, rather than just be baked into the core product as a new table-stakes feature?
To what extent are the answers to these questions path-dependent, that is, subject to specific decisions by specific companies and the quality of their specific products—as was the case with Meta open-sourcing its Llama 2 LLM). And how, again, do the answers differ by vertical

Eventually, though, it will be necessary for parallel bets to be winnowed; all strategy is eventually about execution. Note how quickly Microsoft focused its OS strategy on Windows after the success of Windows 3.0 in 1990 (the company was later accused of following an “Embrace, Extend, Extinguish” model where one-time partners would be crushed once emerging markets stabilized). The questions here, of course, are “When,” “How Much,” and “How do you know?”

Microsoft never halted its investments in applications and productivity tools, nor Internet services, and is better off as a result. Sometimes parallel bets lead to growth in new adjacent markets, rather than displace a current one (to that end, Microsoft’s more direct OS-bets were eventually paired). It’s possible that Amazon’s Alexa device footprint will still yet enable the company to regain market leadership. Indeed, OpenAI’s CEO, Sam Altman has confirmed reports that it is considering its own foray into consumer hardware (led, according to rumours, by Apple’s long-time design chief, Jony Ive).

And sitting alongside all of the above considerations is the biggest question: how might the focus on current AI architectures and opportunities distract from the development of artificial general intelligence? John Carmack, who is considered the “father of 3D graphics” due his pioneering work at Id Software, which he co-founded in 1991, and joined Oculus VR as its first CTO in 2013, founded his own AI start-up in 2022, Keen Technologies, which is exclusively focused on developing artificial general intelligence. According to Carmack, the number of [contemporary] “billion-dollar off-ramps” for AI technologies has become a de facto obstacle to achieving true AGI. “There are extremely powerful things possible now in the narrow machine-learning stuff,” Carmack told Dallas Innovates in his first major interview after founding Keen, “[but] it’s not clear those are the necessary steps to get all the way to artificial general intelligence.”

Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. We currently have a vested interest in Microsoft. Holdings are subject to change at any time.

What We’re Reading (Week Ending 26 November 2023)

The best articles we’ve read in recent times on a wide range of topics, including investing, business, and the world in general.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

Here are the articles for the week ending 26 November 2023:

1. 11 Signs to Avoid Management Meltdowns – Todd Wenning

Pressure to maintain those numbers

Anyone who’s made it to the C-suite understands that missing Wall Street estimates can result in a stock price drop. There’s natural pressure to satisfy investors, particularly when the stock price drives a big part of employee compensation.

Some of that pressure can be good, but it can also lead to unethical decisions when a company can’t achieve those numbers in the ordinary course of business. A company may, for example, stuff a channel with inventory to pull forward demand. That can work for a while, but eventually, all the customers’ warehouses are full.

Companies might also make an acquisition, alter segment reporting, or take some type of restructuring initiative to reset investor expectations. These moves should be viewed with skepticism…

…Young’uns and bigger-than-life CEOs

An iconic CEO who surrounds themselves with young, ambitious employees can be a warning sign. Jennings argues that’s because:

“These young’uns don’t have enough experience or wisdom to challenge the CEO, and the CEO has roped them in with executive success. They are hooked on the cash and its trappings and cannot speak up about obvious ethical and legal issues because they might lose the homes, the boats, the cars, and, yes, the prestige that comes with astronomical financial success at a young age.”

In contrast, when a CEO has an experienced team who – critically – have financial and professional options other than working at the company, it’s far less likely (though not impossible) for misbehavior to persist for long…

…Innovation like no other

As technological advances accelerate, we’re more frequently dazzled by their potential impacts. Jennings warns that companies behind these technologies may consider themselves “as being above the fray, below the radar, and generally not subject to the laws of either economics or gravity.”

Founders and executives of tremendously successful companies often receive accolades from the business and financial media, as well as their local communities. In turn, this feedback can create an inflated sense of self-importance.

To illustrate, here’s a clip from a December 2000 press release announcing that Fortune magazine named Enron one of the 100 best companies to work for in America.

Enron adds the “100 Best Companies to Work For in America” distinction to its “Most Innovative Company in America” accolade, which it has received from Fortune magazine for the past five years. The magazine also has named Enron the top company for “Quality of Management and the second best company for “Employee Talent.”

When a company gets this type of public reinforcement, it can provide mental cover for justifying other actions.

As an antidote to this red flag, Jennings suggests being on the lookout for how management responds to external questions about the company, its performance, or its tremendous growth. If rather than thoughtfully respond to a tough question, management launches an ad hominem attack against the questioner, be on your guard…

…Obsession with short sellers: If the company has been the target of a well-distributed short thesis, there are two appropriate responses for the types of companies we want to own. One is ignore it and focus on the business. In 1992, when Fastenal founder Bob Kierlin was asked about the huge short interest in his stock, he replied: “I’ve got nothing against short sellers…They have a role in the market place, too. My own portfolio has a couple of short positions. In the long run, the truth will always come out.” The second is to calmly and thoughtfully respond to short seller concerns like Netflix’s Reed Hastings did in reply to Whitney Tilson. Any other type of response – particularly when it’s driven by emotion – is a warning sign.

2. Waking up science’s sleeping beauties – Ulkar Aghayeva

Some scientific papers receive very little attention after their publication – some, indeed, receive no attention whatsoever. Others, though, can languish with few citations for years or decades, but are eventually rediscovered and become highly cited. These are the so-called ‘sleeping beauties’ of science.

The reasons for their hibernation vary. Sometimes it is because contemporaneous scientists lack the tools or practical technology to test the idea. Other times, the scientific community does not understand or appreciate what has been discovered, perhaps because of a lack of theory. Yet other times it’s a more sublunary reason: the paper is simply published somewhere obscure and it never makes its way to the right readers…

…The term sleeping beauties was coined by Anthony van Raan, a researcher in quantitative studies of science, in 2004. In his study, he identified sleeping beauties between 1980 and 2000 based on three criteria: first, the length of their ‘sleep’ during which they received few if any citations. Second, the depth of that sleep – the average number of citations during the sleeping period. And third, the intensity of their awakening – the number of citations that came in the four years after the sleeping period ended. Equipped with (somewhat arbitrarily chosen) thresholds for these criteria, van Raan identified sleeping beauties at a rate of about 0.01 percent of all published papers in a given year.

Later studies hinted that sleeping beauties are even more common than that. A systematic study in 2015, using data from 384,649 papers published in American Physical Society journals, along with 22,379,244 papers from the search engine Web of Science, found a wide, continuous range of delayed recognition of papers in all scientific fields. This increases the estimate of the percentage of sleeping beauties at least 100-fold compared to van Raan’s.

Many of those papers became highly influential many decades after their publication – far longer than the typical time windows for measuring citation impact. For example, Herbert Freundlich’s paper ‘Concerning Adsorption in Solutions’ (though its original title is in German) was published in 1907, but began being regularly cited in the early 2000s due to its relevance to new water purification technologies. William Hummers and Richard Offeman’s ‘Preparation of Graphitic Oxide’, published in 1958, also didn’t ‘awaken’ until the 2000s: in this case because it was very relevant to the creation of the soon-to-be Nobel Prize–winning material graphene.

Both of these examples are from ‘hard’ sciences – and interestingly, in physics, chemistry, and mathematics, sleeping beauties seem to occur at higher rates than in other scientific fields.

Indeed, one of the most famous physics papers, Albert Einstein, Boris Podolsky, and Nathan Rosen (EPR)’s ‘Can Quantum-Mechanical Description of Physical Reality Be Considered Complete?’ (1935) is a classic example of a sleeping beauty. It’s number 14 on one list that quantifies sleeping beauties by how long they slept and how many citations they suddenly accrued…

…The EPR paper wasn’t hidden in a third-tier journal, unread by the scientific community. Indeed, it generated intense debate, even a New York Times headline. But in terms of its citations, it was a sleeper: it received many fewer citations than one would expect because it needed testing, but that testing wasn’t feasible for a long time afterward…

…In some cases, a sleeping beauty comes without the kind of great mystery attached to the EPR paper. In some cases, scientists understand something well enough – but just don’t know what to do with it.

The first report of the green fluorescent protein (GFP) – a crucial ingredient in many modern biological experiments because of its ability glow brightly under ultraviolet light, and thus act as a clear indicator of cellular processes like gene expression and protein dynamics – was published in 1962 in the Journal of Cellular and Comparative Physiology. GFP had been discovered in the jellyfish Aequorea victoria in research led by the marine biologist Osamu Shimomura.

Over the summers of the following 19 years, 85,000 A. victoria jellyfish were caught off Friday Harbor in Washington state in attempts to isolate sufficient amounts of GFP that allowed for a more thorough characterization. This resulted in a series of papers between 1974 and 1979. But as Shimomura admitted in one of the interviews many years later, ‘I didn’t know any use of . . . that fluorescent protein, at that time.’

In 1992, things changed. The protein was cloned, and the relevant genetic information was passed on to the biologist Martin Chalfie. Chalfie was first to come up with the idea of expressing GFP transgenically in E. coli bacteria and C. elegans worms. He demonstrated that GFP could be used as a fluorescent marker in living organisms, opening up new worlds of experimentation. GFP is now a routinely used tool across swathes of cell biology…

…With that caveat on the record, we can look at a final example of a true sleeping beauty – one that perhaps has the most to teach us about how to awaken dormant knowledge in science.

In 1911, the pathologist Francis Peyton Rous published a paper in which he reported that when he injected a healthy chicken with a filtered tumor extract from a cancerous chicken, the healthy chicken developed a sarcoma (a type of cancer affecting connective tissue). The extract had been carefully filtered to remove any host cells and bacteria, which might be expected to cause cancer, so another factor must have been at play to explain the contagious cancer.

It turned out that the cause of the tumor in the injected chicken was a virus – but Rous wasn’t able to isolate it at the time.

The importance of his study, and the paper reporting it, wasn’t recognized until after 1951, when a murine leukemia virus was isolated. This opened the door to the era of tumor virology – and to many citations for Rous’s initial paper. The virus Rous had unknowingly discovered in his 1911 paper became known as the Rous sarcoma virus (RSV), and Rous was awarded the Nobel Prize in Medicine in 1966, 55 years after publishing…

…Another lesson is related to collaboration. It could be that the techniques and knowledge required to fully exploit a discovery in one field lie, partly or wholly, in an entirely different one. A study from 2022 showed empirically how the ‘distance’ between biomedical findings – whether they were from similar subfields or ones that generally never cite each other – determines whether they tend to be combined to form new knowledge.

‘Biomedical scientists’, as the paper’s author, data scientist Raul Rodriguez-Esteban, put it, ‘appear to have a wide set of facts available, from which they only end up publishing discoveries about a small subset’. Perhaps understandably, they tend to ‘reach more often for facts that are closer’. Encouraging interdisciplinary collaboration, and encouraging scientists to keep an open mind about who they might work with, could help extend that reach.

That, of course, is easier said than done. Perhaps the most modern tools we have available – namely, powerful AI systems – could help us. It is possible to train an AI to escape the disciplinary lines of universities, instead generating ‘alien’, yet scientifically plausible, hypotheses from across the entire scientific literature.

These might be based, for example, on the identification of unstudied pairs of scientific concepts, unlikely to be imagined by human scientists in the near future. It’s already been shown in research on natural language processing that a purely textual analysis of published studies could potentially glean gene-disease associations or drug targets years before a human, or a human-led analysis, would discover them.

3. An Interview with Intel CEO Pat Gelsinger About Intel’s Progress Towards Process Leadership – Ben Thompson and Pat Gelsinger

Well, tell me more about that. Why is advanced packaging the future? I know this has been a big focus for Intel, it’s something you want to talk about, and from everything I know you have good reason to want talk about it, your technology is leading the way. Why is that so important in addition to the traditional Moore’s Law shrinking transistors, et cetera? Why do we need to start stacking these chiplets?

PG: Well, there’s about ten good reasons here, Ben.

Give me the top ones.

PG: I’ll give you the top few. One is, obviously, one of your last pieces talked about the economics of Moore’s Law on the leading edge node, well now you’re able to take the performance-sensitive transistors and move them to the leading edge node, but leverage some other technologies for other things, power delivery, graphics, IP sensitive, I/O sensitive, so you get to mix-and-match technologies more effectively this way.

Second, we can actually compose the chiplets to more appropriate die sizes to maximize defect density as well, and particularly we get to some of the bigger server chips, if you have a monster server die, well, you’re going to be dictated to be n-2, n-3, just because of the monster server die size. Now I get to carve up that server chip and leverage it more effectively on a 3D construct. So I get to move the advanced nodes for computing more rapidly and not be subject to some of the issues, defect density, early in the life of a new process technology. Additionally, we’re starting to run into some different scaling aspects of Moore’s Law as well.

Right.

PG: SRAMs in particular, SRAM scaling will become a bigger and bigger issue going forward. So I actually don’t get benefit by moving a lot of my cache to the next generation node like I do for logic, power, and performance. I actually want to have a 3D construct where I have lots of cache in a base die, and put the advanced computing on top of it into a 3D sandwich, and now you get the best of a cache architecture and the best of the next generation of Moore’s law so it actually creates a much more effective architectural model in the future. Additionally, generally, you’re struggling with the power performance and speed of light between chips.

Right. So how do you solve that with the chiplet when they’re no longer on the same die?

PG: Well, all of a sudden, in the chiplet construct, we’re going to be able to put tens of thousands of bond connections between different chiplets inside of an advanced package. So you’re going to be able to have very high bandwidth, low latency, low power consumption interfaces between chiplets. Racks become systems, systems become chips in this architecture, so it becomes actually a very natural scaling element as we look forward, and it also becomes very economic for design cycles. Hey, I can design a chiplet with this I/O…

…The yield advantages of doing smaller dedicated chiplets instead of these huge chips is super obvious, but are there increased yield challenges from putting in all these tens of thousands of bonds between the chips, or is it just a much simpler manufacturing problem that makes up for whatever challenges there might be otherwise?

PG: Clearly, there are challenges here, and that’s another area that Intel actually has some quite unique advantages. One of these, we can do singulated die testing. Literally, we can carve up and do testing at the individual chiplet level before you actually get to a package, so you’re able to take very high yielding chiplets into the rest of the manufacturing process. If you couldn’t do that, now you’re subject to the order of effects of being able to have defects across individual dies, so you need to be able to have very high yielding individual chiplets, you need to be able to test those at temperature as well, so you really can produce a good, and then you need a high yielding manufacturing process as you bring them into an advanced substrate.

Why is Intel differentiated in this? What is your advantage that you think is sustainable? You’ve talked about it already being the initial driver of your Foundry Service.

PG: Yeah, it’s a variety of things. We’ve been building big dies and servers for quite a while, so we have a lot of big die expertise. Our advanced packaging with Foveros and EMIB (Embedded Multi-Die Interconnect Bridge) and now hybrid bonding and direct copper-to-copper interface, we see ourself as years ahead of other technology providers in the industry. Also, as an integrated IDM, we were developing many of these testing techniques already. So we have our unique testers that we have that allow us to do many of these things in high yield production today at scale, and we’re now building factories that allow us to do wafer level assembly, multi-die environment.

So it really brings together many of the things that Intel is doing as an IDM, now bringing it together in a heterogeneous environment where we’re taking TSMC dies. We’re going to be using other foundries in the industry, we’re standardizing that with UCIe. So I really see ourself as the front end of this multi-chip chiplet world doing so in the Intel way, standardizing it for the industry’s participation with UCIE, and then just winning a better technology…

…And then RibbonFET and number one, explain them to me and to my readers. And number two, why are they so important? And number three, which one is more important? Are they inextricably linked?

PG: Yeah, PowerVia, let’s start with the easier one first. Basically, when you look at a metal stack up and a modern process, leading edge technology might have fifteen to twenty metal layers. Metal one, metal two…

And the transistors all the way at the bottom.

PG: Right, and transistors down here. So it’s just an incredible skyscraper design. Well, the top level of metals is almost entirely used for power delivery, so now you have to take signals and weave them up through this lattice. And then you want big fat metals and why do you want them fat? So you get good RC characteristics, you don’t get inductance, you’re able to have low IR drop right across these big dies.

But then you get lots of interference.

PG: Yeah and then they’re screwing up your metal routing that you want for all of your signals. So the idea of taking them from the top and using wafer-level assembly and moving them to the bottom is magic, right? It really is one of those things, where the first time I saw this laid out, as a former chip designer, I was like, “Hallelujah!”, because now you’re not struggling with a lot of the overall topology, die planning considerations, and you’re going to get better metal characterization because now I can make them really fat, really big and right where I want them at the transistor, so this is really pretty powerful. And as we’ve done a lot of layout designs now we get both layout efficiency because all of my signal routing get better, I’m able to make my power delivery and clock networks far more effectively this way, and get better IR characteristics. So less voltage drops, less guard banding requirements, so it ends up being performance and area and design efficiency because the EDA tools —

Right. It just becomes much simpler.

PG: Everybody loves this. That’s PowerVia, and this is really an Intel innovation. The industry looked at this and said, “Wow, these guys are years ahead of anything else”, and now everybody else is racing to catch up, and so this is one where I say, “Man, we are ahead by years over the industry for backside power or PowerVia, and everybody’s racing to get their version up and running, and we’re already well underway and in our second and third generation of innovation here”.

On the transistor, that’s the gate-all-around (GAA) or we call it RibbonFET, our particular formulation for that. Samsung and TSMC have their variation of that, so I’ll say on PowerVia, well ahead, while everybody’s working on GAA and you can say, “Why is Intel better?”, well hey, when you’ve done every major transistor innovation for the last twenty-five years…

…Just to step back and look back over your two to three years, in our previous interview we talked about the importance of the Foundry business being separate from the product business. This is something that I was very anchored on looking at your announcement, and it’s why I was excited about Meteor Lake for example, because to me that was a forcing function for Intel to separate the manufacturing and design parts. At the same time, you are not actually unveiling a separate P&L for it until early next year. What took so long? Was that the area where maybe you actually were moving too slowly?

PG: Well, when you say something like separate the P&L, it’s sort of like Intel hasn’t done this in almost our 60-year history. The idea that we’re going to run fully separate operations with fully separate financials, with fully separate allocation systems at ERP and financial levels, I joke internally, Ben, that the ERP and finance systems of Intel were old when I left, that was thirteen years ago and we are rebuilding all of the corporate systems that we sedimented into IDM 1.0 over a five-decade period.

Tearing all of that apart into truly separate operational disciplines as a fabless company and as a foundry company, that’s a lot of work. Do I wish it could have gone faster? Of course I do, but I wasn’t naive to say, “Wow, I can go make this happen really fast.” It was five decades of operational processes, and internally we’ll be by the time we publish the financials in Q1 of next year, we’ll have gone through multiple quarters of trial running those internally, and now that’ll be the first time that we present it to the Street that way.

As we talk to Foundry customers we’re saying, “Come on in, let’s show you what we’re doing, test us.” And MediaTek, one of our early Foundry customers, “Hey, give us the feedback, give me the scorecard. How am I doing? What else do you need to see?”, start giving us the NPS scores for us as a Foundry customer, there’s a lot of work here. Yeah, I wish it would go faster but no, I’m not disappointed that it’s taken this long…

…I mean, you’ve pushed vigorously, I would say, for the CHIPS Act and there was actually just a story in the Wall Street Journal, I saw it as I was driving in, that said Intel is the leading candidate for money for a national defense focused foundry, a secure enclave I think they called it, potentially in Arizona. But you mentioned the money aspect of being a foundry, and you have to be the first customer, but you’re the first customer with an also-threatened business that has— you talked about your earnings, you’re not filling your fabs currently as it is, and you don’t have trailing edge fabs spinning off cash to do this, you don’t have a customer base. Is this a situation where, “Look, if the US wants process leadership, we admit we screwed up, but we need help”?

PG: There are two things here. One is, hey, yeah, we realize that our business and our balance sheet, cash flows are not where they need to be. At the same time, there’s a fundamental economic disadvantage to build in US or Europe and the ecosystem that has emerged here (Taiwan), it’s lower cost.

Right. Which TSMC could tell you.

PG: Right. And hey, you look at some of the press that’s come out around their choice of building in the US, there’s grave concerns on their part of some of those cost gaps. The CHIPS Act is designed to close those cost gaps and I’m not asking for handouts by any means, but I’m saying for me to economically build major manufacturing in US and Europe, those cost gaps must be closed, because if I’m going to plunk down $30 billion for a major new manufacturing facility and out of the gate, I’m at a 30%, 40% cost disadvantage —

Even without the customer acquisition challenges or whatever it might be.

PG: At that point, no shareholders should look at me and say, “Please build more in the US or Europe.” They should say, “Well, move to Asia where the ecosystem is more mature and it’s more cost-effective to build.” That’s what the CHIPS Act was about: if we want balanced, resilient supply chains, we must close that economic gap so that we can build in the US and Europe as we have been. And trust me, I am fixing our issues but otherwise, I should go build in Asia as well, and I don’t think that’s the right thing for the world. We need balanced supply chains that are resilient for the Americas and for Europe and in Asia to have this most important resource delivered through supply chains around the world. That’s what the CHIPS Act was about.

I am concerned though. My big concern, just to put my cards on the table, is the trailing edge, where it’s basically Taiwan and China, and obviously China has its own issues, but if Taiwan were taken off the map, suddenly, part of what motivated the CHIPS Act was we couldn’t get chips for cars. Those are not 18A chips, maybe those will go into self-driving cars, I don’t want to muddy the waters, but that’s an issue where there’s no economic case to build a trailing edge fab today. Isn’t that a better use of government resources?

PG: Well, I disagree with that being a better use of resource, but I also don’t think it’s a singular use of resource on leading edge. And let me tease that apart a little bit. The first thing would be how many 28 nanometer fabs should I be building new today?

Economically, zero.

PG: Right, yeah, and I should be building zero economically in Asia as well.

Right. But China is going to because at least they can.

PG: Exactly. The economics are being contorted by export policy, not because it’s a good economic investment as well.

Right. And that’s my big concern about this policy, which is if China actually approaches this problem rationally, they should flood the market like the Japanese did in memory 40 years ago.

PG: For older nodes.

For older nodes, that’s right.

PG: Yeah because that’s what they’re able to go do and that does concern me as well. At the same time, as we go forward, how many people are going to be designing major new designs on 28 nanometers? Well, no. They’re going to be looking at 12 nanometers and then they’re going to be looking at 7 nanometers and eventually they will be moving their designs forward, and since it takes seven years for one of these new facilities to both be built, come online, become fully operational in that scale, let’s not shoot behind the duck.

And so your sense is that you are going to keep all these 12, 14 nanometer fabs online, they’re going to be fully depreciated. Even if there was a time period where it felt like 20 nanometer was a tipping point as far as economics, a fully depreciated 14 nanometer fab—

PG: And I’m going to be capturing more of that because even our fab network, I have a whole lot of 10 nanometer capacity. I’m going to fill that with something, I promise you, and it’s going to be deals like we just did with Tower. We’re going to do other things to fill in those as well because the depreciated assets will be filled. I’m going to run those factories forever from my perspective, and I’ll find good technologies to fill them in.

Let’s talk about AI. I know we’re running short on time, but there’s the question. I feel like AI is a great thing for Intel, despite the fact everyone is thinking about it being GPU-centric. On one hand, Nvidia is supply constrained and so you’re getting wins. I mean, you said Gaudi is supply constrained, which is not necessarily as fast as an Nvidia chip, I think, is safe to say. But I think the bull case, and you articulated this in your earnings call, is AI moving to the edge. Tell me this case and why it’s a good thing for Intel.

PG: Well, first I do think AI moves to the edge and there are two reasons for that. One is how many people build weather models? How many people use weather models? That’s training versus inference, the game will be in inference. How do we use AI models over time? And that’ll be the case in the cloud, that’ll be the case in the data center, but we see the AI uses versus the AI training becoming the dominant workload as we go into next year and beyond. The excitement of building your own model versus, “Okay, now we build it. Now what do we do with it?”

And why does Intel win that as opposed to GPUs?

PG: For that then you say, in the data center, you say, “Hey, we’re going to add AI capabilities.” And now gen four, Sapphire Rapids is a really pretty good inferencing machine, you just saw that announced by Naver in Korea. The economics there, I don’t now have to port my application, you get good AI performance on the portion of the workload where you’re inferencing, but you have all the benefits of the software ecosystem for the whole application.

But importantly, I think edge and client AI is governed by the three laws. The laws of economics: it is cheaper to do it on the client versus in the cloud. The laws of physics: it is faster to do it on the client versus round tripping your data to the cloud. And the third is the laws of the land: do I have data privacy? So for those three reasons, I believe there’s all going to be this push to inferencing to the edge and to the client and that’s where I think the action comes. That’s why Meteor Lake and the AIPC is something—

4. Slicing and Dicing: How Apollo is Creating a Deconstructed Bank – Marc Rubinstein

Securitisation as a technology changed finance. By allowing loans to be repackaged for resale, it paved the way for the disintegration of the traditional value chain that cleaved loan origination to funding sources.

The basic form of an asset-backed security goes back a long time, but the modern-day version was born 40 years ago when First Boston, Salomon Brothers and Freddie Mac divided up residential mortgage pools into different tranches that allowed bondholders to be paid at different rates. Investors could choose between buying more expensive, higher rated bonds backed by tranches with first claim on payment flows, or purchasing subordinated bonds that were less expensive, lower rated and riskier. This technique helped the mortgage-backed securities market grow from $30 billion in 1982 to $265 billion in 1986.

The market soon spread, moving beyond mortgages in the 1980s to include student loans, auto loans and credit card receivables. Eventually, issuers securitised more exotic revenue streams, creating, for example, Bowie bonds securitised by revenues from David Bowie’s back catalogue and even Bond bonds securitised by revenues from James Bond movies. Market growth was aided by a friendly regulatory environment, improvements in computing power and new information technologies. With increasing precision, the risks and revenues associated with debts could be identified, catalogued, isolated and sold.

The securitisation process involves a chain of participants. In a stylised version, a borrower sits at one end and takes out a loan from an originator. The originator then sells the loan into a special purpose entity which issues bonds against it, with the help of an underwriter. To provide originators with liquidity, banks offer warehouse facilities which act as a kind of institutional credit card, allowing them to finance pre-agreed eligible assets. The underwriter manages the sale of bonds to investors. To ensure payment flows continue uninterrupted, a servicer sits underneath the process, collecting cash from the borrower and passing it through to the investor…

…In its 13 years of experience investing in asset-backed securities, Apollo has deployed over $200 billion of capital. Its annualised loss rate: just 1.3 basis points.

But Apollo reckons that it could deploy more if only it had access to more origination. “There is no shortage of capital,” said CEO Marc Rowan at an investor day two years ago. “What there is, is a shortage of assets.”

Hence, the firm has reversed back down the value chain into direct origination. And because it’s not necessarily able to invest in everything its origination platforms throw off, it has built up a capital solutions group as well, to distribute asset-backed loans to other market participants. Apollo also recently lifted a business from Credit Suisse which it has renamed Atlas SP that offers warehouse facilities, securitisation and syndication to other originators. So, like a deconstructed bank, it now operates right across the value chain in a fairly unique way.

Apollo currently operates 16 different origination engines. They operate as stand-alone companies focused on their particular niche, independently capitalised and with their own management and board of directors. In total, the firm has invested around $8 billion of equity capital into these businesses; they collectively manage $130 billion of assets and employ 3,900 staff. The companies are at different stages of maturity: Seven manage less than $2 billion of assets, including two that Apollo launched de-novo; six manage between $2 billion and $10 billion of assets; and three manage in excess of $20 billion…

…The problem with operating a range of origination platforms is that their track record – at least as public businesses – is not very good. Origination businesses need to manage two risks: liquidity risk and credit risk.

Historically, liquidity risk has brought many down. Their reliance on market funding sources entwines their fortunes with market sentiment, and markets can be skittish. Following the Russian debt crisis in 1998, market disruption led to a steep fall in demand among investors for risky assets, including subprime securitizations, even before a recession took hold three years later. Subprime originators saw their own borrowing costs skyrocket. In the two years following the crisis, eight of the top 10 subprime lenders declared bankruptcy, ceased operations or sold out to stronger firms…

…Apollo argues that its long-term insurance liabilities are a better match for asset financing than commercial paper, money markets or even a bank’s deposits. The firm may have a point. Deposit outflows at Silicon Valley Bank, Signature Bank and First Republic highlight that bank funding isn’t what it was and that its realised duration may be lower than anticipated.

The second risk is credit risk. Apollo reckons its diversification helps – across originators and across asset types. Its platforms operate over 30 product lines and each deploys a large funnel. Since being founded in 2008, MidCap has closed only 2,000 deals out of around 29,000 identified opportunities, on which it issued 6,800 term sheets. Overall, the group’s platforms target a conversion of between 5% and 10% of opportunities. Such a large funnel avoids adverse selection.

5. Everything You Can’t Predict – Jack Raines

You would be hard-pressed to find a technological development from the last 20 years that is more important than “the cloud.”…

…Interestingly, the first company to launch an enterprise cloud solution wasn’t Amazon, Microsoft, or Google.

It was IBM.

Yes, IBM, whose stock price appreciated by a whopping 2.39% between August 2000 and April 2023, was the first entrant to the cloud space.

So, what went wrong?

IBM was the face of the computer industry for most of the 20th century, and in July 2002, they unveiled a service called Linux Virtual Services, which offered customers a radical new payment structure.

Historically, IBM had locked customers into long-term, fixed-price contracts in exchange for access to different hardware and software products. In contrast, Linux Virtual Services would allow customers to run their own software applications through IBM mainframes and pay based on their usage.

According to IBM, this usage-based payment model would result in savings of 20% – 55%.

Linux Virtual Services should have kickstarted a proliferation of cloud-based services, but instead, it was shut down a few years later…

…In 2002, IBM, a $130B computing giant with unlimited resources and a multi-decade head start, launched an enterprise cloud offering aimed at commoditizing computing power.

In 2002, Amazon, a $10B e-commerce store, was solving an internal engineering bottleneck.

In 2006, IBM shut down its cloud storage service.

In 2006, Amazon launched its cloud storage service.

In 2023, IBM is still worth $130B.

In 2023, Amazon is worth 10 IBMs, largely due to the success of AWS.

What went wrong at IBM? No one really knows, but Corry Wang, a former equity researcher at Bernstein, speculates that IBM’s sales team may have had misaligned incentives. In 2002, sales teams would have earned larger commissions on higher-priced, fixed contracts than on cheaper, usage-based contracts, and the new offerings would have cannibalized current customers as well. Why, as a salesperson, would you sell a service that made you less money?

Meanwhile, Amazon realized, almost by accident, that their internal solutions to infrastructure bottlenecks could be exported and sold as services. And Amazon didn’t have current SaaS customers to worry about cannibalizing, so their salespeople were free to sell the service to anyone.

16 years later, Amazon is the market leader in cloud, and IBM is stuck in 2006…

…Because it shows that predicting the future is easy, but predicting who wins in that future is much, much more difficult. By 2001, plenty of tech experts could have told you that cloud computing was going to emerge as an important technological development in a decade.

But how many of those experts would have predicted that an online bookstore would dominate the cloud market?

Picking trends is easy. Picking winners is hard.

Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. We currently have a vested interest in Alphabet (parent of Google), Amazon, Microsoft, Netflix, and TSMC. Holdings are subject to change at any time.

What We’re Reading (Week Ending 19 November 2023)

The best articles we’ve read in recent times on a wide range of topics, including investing, business, and the world in general.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

Here are the articles for the week ending 19 November 2023:

1. Strange Ways AI Disrupts Business Models, What’s Next For Creativity & Marketing, Some Provocative Data – Scott Belsky

Increasing perversion of certain business models that are liable to be gamed or constrained by AI: We’re shifting from a world where data analysis required long cycles (analysts need lots of time to run queries, analyze, and then present findings in a way that people understand) to a new world of real-time optimization and insights (AI will mine the data to surface insights and make optimization decisions in real-time). But when businesses start optimizing themselves, all sorts of crazy things might start happening (or at least be suggested by the AI). What wild examples can we think of here? For dating apps, where the perfect match of two people increases churn, will Tinder or Bumble constrain the efficiency of AI so the product doesn’t become too “unsustainably effective”? Or in the world of music streaming: Since Spotify pays artists per song, will Spotify automatically optimize its algorithms to favor longer songs, taking into account the number of minutes each customer listens per day? As AI gets really good at optimization, some industries and business models will need to change…

…AI will threaten subjectivity in purchase decisions, and with it the sway of brand and marketing. As we gain trust in the guidance of agent-assisted experiences, will the impact of brand, referral, and relationships in purchase decisions be diminished? Whether we’re buying batteries, sneakers, potato chips, or kitchen appliances, we are often influenced more than we care to admit by brand perceptions as opposed to factual comparisons. However, as your “AI Agent” gets to know you better – infused by every personal preference and previous purchase as well as every online review and consumer reports determination – you may start trusting the guidance of your agent more than any other signal. Perhaps the stakes are even more pronounced in the enterprise, where a procurement process tainted by human emotions, laziness, and previous relationships is the persistent fear of any CFO. How many purchase decisions are made for the wrong reasons – like relationships strengthened by football games and steak dinners with salespeople as opposed to the value and quality of a solution? Companies like Globality (in my portfolio, tackling enterprise procurement) and many others are leveraging AI to radically transform every function of a company. And if you look at this wave of companies overall, they are tackling the tremendous costs of subjectivity in decision making and are designed to yield better and more cost-effective solutions. Ultimately, elevating product meritocracy solves problems in both the worlds of consumer and enterprise purchasing. AI threatens subjective decision making tainted by human error and bias and will usher in an era where the best product at the best value may in fact win. This is a win for buyers, but may be quite disruptive to sellers who fail to innovate and endlessly optimize.

2. 15-Year Anniversary of the Business Owner Fund – Robert Vinall

On Monday the Biden administration released an Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence. This Executive Order goes far beyond setting up a commission or study about AI, a field that is obviously still under rapid development; instead it goes straight to proscription…

If the wrong mental model or a lack of intellectual acumen is not why people fail to beat the market, what is? In my view, it is the sheer difficulty of remaining rational – i.e., buying businesses for less than they are worth and selling them for more than they are worth – when being constantly bombarded with market gyrations, news flow, social media, expert opinions, and any number of other influences. This is not something that I or, likely, anyone is immune to. Over the last five years, I likely became too optimistic in some of my assumptions as the bull market approached its peak in 2021.

That the emotions interfere with rational thought is not an original idea. The definitive book on psychological biases has already been written – “Thinking, Fast and Slow,” by Israeli-American Nobel Prize winner Daniel Kahneman…

…In practice, there are two main failings resulting from emotional biases that an investor needs to eliminate – turning overly pessimistic when markets or investments are down and turning overly optimistic when they are up. Perhaps it could even be argued that turning overly pessimistic when markets are down is the key risk to be cognizant of. Assuming markets trend upwards over time – albeit in a lumpy fashion – the single most important attribute in an investor is the ability to remain steadfast when the outlook temporarily looks bleak. However, given how damaging to wealth it can be to be caught up in a bubble, I will leave the list at two…

…I cannot overstate the importance of being independent. It is far easier to reach a rational conclusion about any topic if your thought process is unclouded by the opinions of others.

In the 1950s, psychologist Solomon Asch conducted a series of psychological experiments known as the Asch conformity experiments. A group of eight participants engaged in a simple perceptual task, whereby all but one of the participants were actors. Each participant was shown a card with one line on it followed by another card with three lines of differing lengths on it… The task was to state which line was of similar length, a simple task that everyone got right when left to their own devices. The catch is that in some trials, the actors gave the wrong response. When this happened, the study’s subject was far more likely to give the wrong response as well. The research suggests people are more likely to conform than they might expect.

Furthermore, the study found that people are more likely to conform when a) more people are present; b) the task is more difficult; and c) the other members of the group are of higher social status. The study found they are less likely to conform when able to respond privately.

This suggests to me four ways to increase your chances of thinking independently: avoid large groups, stick to simple investment opportunities, avoid experts and gurus, and make investment decisions in private, i.e., not in a committee. It is fascinating to me that three of these four measures suggest working alone is better than in a team, and the fourth (keeping it simple) is independent of team size. All the evidence suggests that the smaller the team size, the better the decision-making…

…Given that a good investment idea should be obvious, but the analysis before investing needs to be detailed, it stands to reason that the optimal approach is to analyse many ideas superficially and a handful (the ones considered for investment) in depth. In other words, it is necessary to kiss lots of frogs until you find a prince.

The investment blog, value and opportunity, occasionally takes an entire stock market and analyses every company in it. I am a big fan of the idea. The blogger’s reasons for rejecting an investment sometimes amount to just a single sentence, so these entries will not win any prizes for their intricacy. However, to the end of creating as many free options as possible, it is great…

…If the name of the game is to keep an even keel despite what is happening around you, I cannot for the life of me imagine how having a prominent social media presence can improve investment returns. Social media tends to amplify whatever emotions are prevalent at the time. When returns are good, you are likely to be celebrated as the next Warren Buffett. When they are bad, you will be pummelled mercilessly. An ideal environment is the exact opposite – one where you receive gentle encouragement when things are going badly and a reality check when things are going well. I realise that building a prominent social media presence is an effective way to raise capital fast. But if you live by the sword, expect to die by the sword…

…The single best way I have found to evaluate whether something is important or not is to consider whether I will care about it or even remember it in 10 years’ time. Changes in interest rates, disappointing quarters and even recessions are things that people will likely not care about in ten years’ time. A customer exodus, the breach of debt covenants, and a disruptive new entrant potentially are. Looking through the lens of how things will appear in the future helps to separate signal from the noise. Note though, it is only possible to practice long-term thinking if you have capital providers who take a similarly long-term perspective.

The final point is the importance of humility. Markets occasionally do unexpected things and the best investment strategies ultimately fail as competitors imitate them. Anyone who thinks they have everything figured out is riding for a fall. It is important to be humble.

You have read on two occasions in this memo that it is not clear to me whether I will beat the market in the long-term. This is not false humility. I believe it – not just because of the sobering experience of the last five years, but for the simple reason that so few investors do beat the market over the long-term. Why should I be the chosen one? I hope this is not too disconcerting to my investors. It should not be. Even Buffett is circumspect about Berkshire’s ability to continue to beat the market given its enormous scale, though he would no doubt fancy his chances with a smaller capital base. Anyone who is certain they are going to beat the market belongs in the marketing department, not the investment department.

3. Attenuating Innovation (AI) – Ben Thompson

…To rewind just a bit, last January I wrote AI and the Big Five, which posited that the initial wave of generative AI would largely benefit the dominant tech companies. Apple’s strategy was unclear, but it controlled the devices via which AI would be accessed, and had the potential to benefit even more if AI could be run locally. Amazon had AWS, which held much of the data over which companies might wish to apply AI, but also lacked its own foundational models. Google likely had the greatest capabilities, but also the greatest business model challenges. Meta controlled the apps through which consumers might be most likely to encounter AI generated content. Microsoft, meanwhile, thanks to its partnership with OpenAI, was the best placed to ride the initial wave generated by ChatGPT.

Nine months later and the Article holds up well: Apple is releasing ever more powerful devices, but still lacks a clear strategy; Amazon spent its last earnings call trying to convince investors that AI applications would come to their data, and talking up its partnership with Anthropic, OpenAI’s biggest competitor; Google has demonstrated great technology but has been slow to ship; Meta is pushing ahead with generative AI in its apps; and Microsoft is actually registering meaningful financial impact from its OpenAI partnership.

With this as context, it’s interesting to consider who signed that letter Allen referred to, which stated:

Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war.

There are 30 signatories from OpenAI, including the aforementioned CEO Sam Altman. There are 15 signatories from Anthropic, including CEO Dario Amodei. There are seven signatories from Microsoft, including CTO Kevin Scott. There are 81 signatories from Google, including Google DeepMind CEO Demis Hassabis. There are none from Apple or Amazon, and two low-level employees from Meta.

What is striking about this tally is the extent to which the totals and prominence align to the relative companies’ current position in the market. OpenAI has the lead, at least in terms of consumer and developer mindshare, and the company is deriving real revenue from ChatGPT; Anthropic is second, and has signed deals with both Google and Amazon. Google has great products and an internal paralysis around shipping them for business model reasons; urging caution is very much in their interest. Microsoft is in the middle: it is making money from AI, but it doesn’t control its own models; Apple and Amazon are both waiting for the market to come to them.

In this ultra-cynical analysis the biggest surprise is probably Meta: the company has its own models, but no one of prominence has signed. These models, though, have been gradually open-sourced: Meta is betting on distributed innovation to generate value that will best be captured via the consumer touchpoints the the company controls.

The point is this: if you accept the premise that regulation locks in incumbents, then it sure is notable that the early AI winners seem the most invested in generating alarm in Washington, D.C. about AI. This despite the fact that their concern is apparently not sufficiently high to, you know, stop their work. No, they are the responsible ones, the ones who care enough to call for regulation; all the better if concerns about imagined harms kneecap inevitable competitors…

…I wrote at the time in an Update:

In 1991 — assuming that the “dawn of the Internet” was the launch of the World Wide Web — the following were the biggest companies by market cap:

$88 billion — General Electric
$80 billion — Exxon Mobil
$62 billion — Walmart
$54 billion — Coca-Cola
$42 billion — Merck

The only tech company in the top 10 was IBM, with a $31 billion market cap. Imagine proposing a bill then targeting companies with greater than $550 billion market caps, knowing that it is nothing but tech companies!

What doesn’t occur to Senator Klobuchar is the possibility that the relationship between the massive increase in wealth, and even greater gain in consumer welfare, produced by tech companies since the “dawn of the Internet” may in fact be related to the fact that there hasn’t been any major regulation (the most important piece of regulation, Section 230, protected the Internet from lawsuits; this legislation invites them). I’m not saying that the lack of regulation is causal, but I am exceptionally skeptical that we would have had more growth with more regulation.

More broadly, tech sure seems like the only area where innovation and building is happening anywhere in the West. This isn’t to deny that the big tech companies aren’t sometimes bad actors, and that platforms in particular do, at least in theory, need regulation. But given the sclerosis present everywhere but tech it sure seems like it would be prudent to be exceptionally skeptical about the prospect of new regulation; I definitely wouldn’t be celebrating it as if it were some sort of overdue accomplishment.

Unfortunately this week’s Executive Order takes the exact opposite approach to AI that we took to technology previously…

…I fully endorse Sinofsky’s conclusion:

This approach to regulation is not about innovation despite all the verbiage proclaiming it to be. This Order is about stifling innovation and turning the next platform over to incumbents in the US and far more likely new companies in other countries that did not see it as a priority to halt innovation before it even happens.

I am by no means certain if AI is the next technology platform the likes of which will make the smartphone revolution that has literally benefitted every human on earth look small. I don’t know sitting here today if the AI products just in market less than a year are the next biggest thing ever. They may turn out to be a way stop on the trajectory of innovation. They may turn out to be ingredients that everyone incorporates into existing products. There are so many things that we do not yet know.

What we do know is that we are at the very earliest stages. We simply have no in-market products, and that means no in-market problems, upon which to base such concerns of fear and need to “govern” regulation. Alarmists or “existentialists” say they have enough evidence. If that’s the case then then so be it, but then the only way to truly make that case is to embark on the legislative process and use democracy to validate those concerns. I just know that we have plenty of past evidence that every technology has come with its alarmists and concerns and somehow optimism prevailed. Why should the pessimists prevail now?

They should not. We should accelerate innovation, not attenuate it. Innovation — technology, broadly speaking — is the only way to grow the pie, and to solve the problems we face that actually exist in any sort of knowable way, from climate change to China, from pandemics to poverty, and from diseases to demographics. To attack the solution is denialism at best, outright sabotage at worst. Indeed, the shoggoth to fear is our societal sclerosis seeking to drag the most exciting new technology in years into an innovation anti-pattern.

4. Bad Office – Marc Rubinstein

On the very same avenue, there have been multiple examples of borrowers handing back keys to lenders on office properties:

Between 55th and 56th Streets, Blackstone gave up on a $308 million loan on 26-storey 1740 Broadway after tenants L Brands and law firm Davis & Gilbert relocated.
Between 49th and 50th, Brookfield surrendered the deeds to the 11-storey Brill Building at 1619 Broadway in a transfer valued at $216 million, six years after buying it.
At Times Square, CIM Group and Australian pension fund QSuper handed back the keys on 1440 Broadway after being unable to pay a $399 million loan. They had bought the building in 2017 and had it valued at $540 million when they took the loan out two years ago.

Such stress in the office market stems from a combination of lower occupancy and higher interest rates. Over three years on from the start of the pandemic, occupancy in major US office markets remains depressed. Latest turnstile swipe data from Kastle indicates that office occupancy stands at 49.8% of pre-pandemic levels, a figure which has remained stable for eighteen months. And data from XY Sense, which uses sensor data to measure physical office presence, points to office utilisation of around 30% compared with around 60% pre-pandemic, consistent with a roughly 50% drop in occupancy. Whatever incentives companies deploy to get employees back into the office, they’re not working.

For a team of New York-based academics, this doesn’t bode well. In a recent paper, they established a clear connection between companies’ remote work policies and their actual reductions in leased office space. Because only a third of pre-pandemic office leases have come up for renewal, the impact has yet to fully flow through even with vacancy rates at 30-year highs (22.1% in Manhattan). They estimate that on the basis of current working behaviours, New York office stock is worth 42% less than it was in December 2019. At that level, even 60% loan-to-value financing deals are at risk.

In the meantime, higher interest rates are also squeezing borrowers. A lot of debt in the commercial real estate market is floating rate. When times were good, floating rate loans gave borrowers the flexibility to prepay early and sell assets. A typical structure is a five year loan, with the rate hedged for the first two years. With rates up, borrowers have to decide whether to buy new rate protection or alternatively, what to do with the asset. To finance its downtown Los Angeles portfolio, Brookfield took on a lot of floating-rate debt and when an interest-rate hedge expired on one of its properties last year, it opted not to get a new one, leading to it defaulting on a $319 million loan.

Not all of the office debt is with banks. For commercial real estate overall – encompassing hotels, retail, industrial and multifamily as well as office – banks sit on around 50% of debt outstanding. The rest is in commercial mortgage-backed securities structures (16%), government and government sponsored enterprise pools (13%), insurance companies (13%) and Real Estate Investment Trusts (5%).

In some of these segments, stress has been evident for some time. Office REIT stock prices are down 60% since the end of 2019 and commercial mortgage-backed securities spreads have widened. For banks, though, the pressures have been slower to build.

This week, Bawag, another Europe-based commercial real estate lender, took a €20 million provision against a specific US office exposure as part of its third quarter earnings. The bank underwrote the loan in 2019 based on a rent roll that failed to materialise and has now written down the value of the collateral (to “an 8.5% cap rate, which I think is quite conservative, if you kind of benchmark that to where other people are valuing assets,” said the CEO on his earnings call). The write-down reflects a concern the European Central Bank recently expressed, that bank property valuers may be slow to update estimates. “Despite its importance, collateral valuation is a blind spot for many of the banks reviewed,” ECB supervisors warned last year.

Other banks are trying to get ahead of the curve. Among the largest US banks, PNC has the highest exposure to office (2.7% of total loans). Although it has barely seen any losses in its portfolio, it has begun to classify many of the loans as non-performing. In total, it views 23% of its office portfolio as “criticised” and in the third-quarter, it shifted $373 million of those onto non-performing status. “I think they’re actually all still accruing. We just kind of get there because we don’t think they’re refinanceable in the current market,” explained CEO Bill Demchak on his earnings call. “The move to non-performing from already being criticised comes about as you just watch cap rates creeping higher and adjust the underlying value of the properties accordingly.”

PNC has now set aside reserves to cover 8.5% of its total office loans and within that 12.5% of multi-tenant office loans. Other banks have provisioned at similar levels. Wells Fargo is at 10.8% in the large corporate office segment (although only at 2.2% for small offices); US Bancorp is at 10%.

For many, the crunch will come when borrowers look to refinance. Bank of America has disclosed that around a half of its office loans mature before the end of 2024. As long as they are still paying, many banks may be tempted to roll out the maturity rather than force a loss. Willy Walker, CEO of commercial real estate finance company Walker & Dunlop, calls it “extend and pretend” (emphasis added):

“What the regulator is allowing the banks to do is to take provisions for loan losses and then go and renegotiate those loans and extend and pretend. And given that the banking system is so overcapitalised right now, very much unlike the great financial crisis, a lot of this paper is just going to get rolled. Because the banks are sitting there going: I don’t want to foreclose on this; there’s no sale market for me to get rid of it. Do I want 60 cents on the dollar today or hope that maybe I get 80 or 90 cents on the dollar if I allow them to hold the asset, or I get worked out? The only place where this obviously causes some problems is in the CMBS world where you don’t have the flexibility because you have a special servicer who has a fiduciary responsibility to the bondholders to seize the asset.”

5. RWH034: The High Road To Riches w/ Peter Keefe – William Green and Peter Keefe

[00:17:43] Peter Keefe: And I think if you, opened up the minds of a lot of people in this business. You discover that their motivations may not be exactly what they think they are. And I think money is an incredibly powerful motivator and people may not be willing to admit just how powerful of a motivator it is. And I think it was Henry Kissinger who said money’s the ultimate aphrodisiac and it just can accomplish all kinds of things.

[00:18:11] Peter Keefe: And I think we all know that subconsciously. And so, and of course, am I interested in the rewards, the financial rewards of this business? Absolutely. I don’t know anybody in this business who isn’t, and I’d worry about you a little bit if you said that you weren’t, but having said that, This business is a calling and I think that when I’m talking to people about why they want to be in this business or when I’m mentoring younger investors, I do, this is sort of, it’s sort of an ominous statement says we’re all think that we’re in service to others.

[00:18:50] Peter Keefe: But sometimes you’re serving yourself. So, I sort of ask this question, it’s gently, you’re serving someone, but who are you serving? Make sure you understand who you’re serving. So, you know, we’re all in service to others, but. Make sure you understand who you’re serving.

[00:19:07] William Green: I wonder if it changes as we get older, because I often find when I interview great investors, it seems like early in their lives, there’s a sort of, I have no factual basis for this, it’s more impressionistic, but I have this sense that there’s a real hunger, often, for money, a kind of ill-defined hunger for money, whether it’s to get out of straightened circumstances, if you’re someone like Bill Miller or Mario Gabelli who grew up with nothing or desire to sort of impress people and get, you know, be noticed, you know, which I think, you know, if you were someone like Bill Ackman, who came from a very successful family, you know, you needed to make your mark. And then at a certain point, it shifts, maybe one, at least for a lot of people. I don’t know.

[00:19:54] William Green: And then also there’s a sense of just loving the game, right? I remember you, one thing that I heard you would ask the people you were interviewing for jobs was you would say to them, would you do this on a teacher’s salary for five years? And I think that’s a really important issue as well. Like, you know, actually having to enjoy the game enough the actual craft. Sorry, I’m going on. Well, do you have any thoughts?

[00:20:17] Peter Keefe: You’ve got to enjoy the game, but you’ve really got to appreciate the craft, and you do have to, the reason I asked that question, would you do this on a teacher’s salary it’s serious, but it’s also a trick question, because anybody who’s good at this is not going to have to live on a teacher’s salary for very long.

[00:20:34] Peter Keefe: I don’t want to be involved professionally with people who are doing this solely for the money. You are serving someone, and you should be serving those who need your skills. If you are good at this business, then you have an obligation to give those skills to those who need it. And they’re desperately needed.

[00:20:57] Peter Keefe: They’re desperately needed by hospitals, schools, retirees, poor people. Wealthy people who simply don’t care about investing, so the need is enormous, so I think it’s important to approach this business from a standpoint of service, and if you’re any good at it, you know, the money is going to rain down upon you more money than you ever imagined and more money than you’re ever going to need.

[00:21:23] Peter Keefe: So, you need to take the money out of the equation. Cause if you’re any good, you’re going to make a lot of it. If you’re not, you still might make a lot of it, but I think the principal motivation has to be to serve. Now, when you’re a young man, young woman, you know, we’ve all been there. You just want to go out and slay the world.

[00:21:41] Peter Keefe: I think that’s just part of the natural deal of you know, being young and moving to a new city like I did and wanting to do something. I mean, I tell people I had no idea what I wanted to do, but I wanted to do something, and I wanted to make an impact on people’s lives, a favorable impact on people’s lives.

[00:21:59] Peter Keefe: I’m not sure I even cared about making a favorable impact. I think I wanted to be noticed and I wanted my life to amount to something. You know, there was just a sort of ill-defined desire, this yearning to make some kind of mark. It was very ego filled, definitely. I think we’re saying exactly the same thing.

[00:22:18] Peter Keefe: I mean, I think that over time, my objectives evolved. Yeah. You know, on day one, you’ve got to pay the rent. You know, on day two, you know, you’re thinking about building a family. Day three, you’re thinking about the legacy. So, your way you approach your life evolves over time. And but yeah, I mean, I just, like I said, I got here in DC and I thought I was going to be a lawyer and then decided that was a really bad idea and I just wanted to do something, you know, I had a lot of energy and I was curious about everything, you know, which can be a problem because if you’re curious about everything, it’s hard to focus on one thing…

…[00:31:49] William Green: Yeah, I wanted to dwell for a moment on that idea of the biggest mistakes you’ve made, because you said recently that my biggest mistakes have been early sales of great businesses, and you described that as the silent killer, where you sell compounders too soon, and while we’re dwelling on your mistakes, can I cause you heart palpitations by asking you about Pool Corp, which is a pretty good example of this.

[00:32:14] Peter Keefe: Sure. Yeah. I think Pool Corporation’s the biggest mistake I’ve ever made in my investment career. And like you said, you know, selling early is the high blood pressure of the investment business. It’s a silent killer. And you know, people will always talk about the business they bought that went to zero, or the one that went down 50% or 75%.

[00:32:32] Peter Keefe: Yes, that’s bad. You want to avoid that but the business that you sold too early, that went on the compound tenfold, or 20-fold after that in my career, has been a real killer. I bought Pool Corp at the right price. Interesting story that I tell you about going down to visit management in Covington, Louisiana, which is not exactly a business mecca, but in any event, you know, it checked all our boxes.

[00:32:58] Peter Keefe: Manny Perez de la Mesa, who was still the chairman of the board, I think, was the CEO then, he’d been in GE, he had a great background, he was, understood capital allocation beautifully, and Pool Corp was a terrific business, and for those of your listeners who aren’t familiar with it, I’ll tell them in a breath.

[00:33:18] Peter Keefe: It’s a distributor of pool supplies and equipment, and it gets margins in the mid-single digits, most distributors, margins in the low single digits, but Pool Corp has this unique franchise that permits it to get these ridiculously high returns for a distributor. And those ridiculously high returns multiplied by frequent inventory turnover mean they get huge returns on capital and do everything that you want a compounder to do.

[00:33:50] Peter Keefe: Well, I bought it right and sold it after depreciating four or five times. In our portfolio, because I allowed some thinking about erroneous thinking about evaluation and probably about the economy didn’t creep into my thinking and full construction is somewhat like to the construction cycle. And so, I probably let all these things influence my thinking and went up selling the position in its entirety and having made, like I said, four or five times our capital on the business. Well, I think it’s appreciated about tenfold since then. So, what that taught me was that you either have to be an investor or an economist. Not many people can be both, and I don’t know any wealthy economists, so I’d rather be an investor.

[00:34:38] Peter Keefe: And I, so I just try to tune out some of this economic stuff that can infect your thinking unusually negatively.

[00:34:46] William Green: Yeah, I was reading your letters to shareholders yesterday, and there was one from, I guess, August 2020, so in the middle of the COVID pandemic, and you wrote, We have no predictions about the direction of the economy or markets, and certainly not the virus.

[00:35:01] William Green: The trajectory of the virus and its ultimate duration and impact on the economy are unknowable. What is knowable? is that on occasion the unthinkable happens, unforeseen acts of terrorism occur, real estate bubbles burst, or a pandemic emerges. This means we must own businesses with both bulletproof balance sheets and outstanding and durable business models that can withstand unthinkable economic hardship, which are run by ethical managers whom we can trust to act in our best interests.

[00:35:26] William Green: And that strikes me as such an important insight that you, I mean, in a way it gets back to stoicism, right? It’s like controlling what we can control and letting go of what we can’t control and just recognizing the fact that the direction of the economy and the market and viruses and stuff is just not really knowable unless maybe you’re Soros or Druckenmiller or someone like that, I don’t know. And so just that recognition, having the humility to recognize that’s not knowable strikes me as a really important first step-in long-term investment success.

[00:35:58] Peter Keefe: Yeah, so I, one of the things I tell young investors when I’m mentoring them is, make a choice, you’re either an economist or an investor, unless you’re one of those five people you mentioned.

[00:36:10] Peter Keefe: And I just rhetorically say there’s probably five people on the planet who can consistently tell you what the dollar is going to do, what the price of gypsum is going to be, what oil might be, or the price of money. I know none of those things, and I simply don’t have enough mental bandwidth to be able to allocate any room at all to these things.

What We’re Reading (Week Ending 05 November 2023)

The best articles we’ve read in recent times on a wide range of topics, including investing, business, and the world in general.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

Here are the articles for the week ending 05 November 2023:

1. Lessons from Charlie Munger’s podcast interview – Thomas Chua

2. Why algo driven trading firms like Renaissance technology are taking excessive risk

“The easiest trade is to front run what you know, what the average is, what the index funds have to buy, and you know what it is. Exactly. They all know that. And the way they get their returns year after year is taking the leverage, the midday leverage, up higher and higher and higher and higher.

So they’re making smaller and smaller profits on more and more volume, which gives them this big peak leverage risk, which I would not run myself. And that’s the only way they make these big returns, is to have this huge leverage that would make you crazy if you were already rich.”

3. How Warren and Charlie changed their mind quickly with Diversified Retailing after they realized it was too competitive

(and how they made a ton of money after changing their mind)

Some context: On January 30, 1966, Buffett, Munger, and Gottesman formed a holding company, Diversified Retailing Company, Inc., to “acquire diversified businesses, especially in the retail field.”

Buffett and Munger then went to the Maryland National Bank and asked for a loan to make the purchase. The lending officer looked at them goggle-eyed and exclaimed, “Six million dollars for little old Hochschild-Kohn?” Even after hearing this, Buffett and Munger—characteristically—did not question their own judgment and run screaming out the door.

“We thought we were buying a second-class department store at a third-class price” is how Buffett describes little old Hochschild-Kohn.

“We made nothing but money at Diversified. We didn’t exactly make it in retailing, but we made a lot of money.

What happened was very simple. We bought this little department store chain in Baltimore. Big mistake. Too competitive.

As the ink dried on the closing papers we realized we’d made a terrible mistake. So we decided just to reverse it and take the hits to look foolish rather than go broke. You just told us how to get us out of this. By that time we’d already financed half of it on covenant free debt and so forth. And they had all this extra cash and our own stocks got down to selling an enormous (discounts).

In the middle of one of those recessions, we just bought, bought and bought and bought and all that money went right into those stocks and of course we tripled it.”…

...11. Why Warren’s investment in Japan was a no-brainer

“If you’re as smart as Warren Buffett, maybe two, three times a century, you get an idea like that. The interest rates in Japan were half a percent per year for ten years. And these trading companies were really entrenched old companies, and they had all these cheap copper mines and rubber foundations, and so you could borrow for ten years ahead, all the money, and you could buy the stocks, and the stocks paid 5% dividends.

So there’s a huge flow of cash with no investment, no thought, no anything. How often do you do that? You’ll be lucky if you get one or two a century. We could do that [because of Berkshire credit]. Nobody else could.”…

…14. His view on China

“Well, my position in China has been that the Chinese economy has better future prospects over the next 20 years than almost any other big economy.

That’s number one. Number two, the leading companies of China are stronger and better than practically any other leading companies anywhere, and they’re available at a much cheaper price. So naturally I’m willing to have some China risk in the Munger portfolio.

How much China risk? Well, that’s not a scientific subject. But I don’t mind. Whatever it is, 18% or something.”…

…15. What about BYD that captivated Munger?

“Guy (Wang Chuanfu) was a genius. He was at a PhD in engineering and he could look at somebody part, he could make that part, look at the morning and look at it in the afternoon. He could make it. I’d never seen anybody like that. He could do anything. He is a natural engineer and get it done type production executive.

And that’s a big thing. It’s a big lot of talent to have in one place. It’s very useful. They’ve solved all these problems on these electric cars and the motors and the acceleration, braking, and so on.”

Comparing Elon with Wang Chuanfu

“Well, he’s a fanatic that knows how to actually make things with his hands, so he has to he’s closer to ground zero. In other words, the guy at BYD is better at actually making things than Elon is.”

2. The Crash Callers Won’t Save You – Ben Carlson

Here’s something Henry Blodget wrote about notorious stock market bear John Hussman:

Every historical indicator Hussman is looking at is suggesting that the stock market is wildly overvalued and headed for a period of lousy returns. How lousy? John Hussman thinks there’s a good chance the stock market will soon crash 40-50 percent.

And even if the market doesn’t crash, Hussman thinks stocks are priced to produce returns of only a couple of percentage points per year over the next decade–far below the 7 percent inflation-adjusted long-term return that everyone is used to and the double-digit returns of the last few years. If you want to feel comfortable and happy, go ahead and ridicule John Hussman with everyone else. If you want to prepare yourself for what seems like a likely possible stock-market future, however, read on.

Sounds scary, right?…

…Here’s the problem with Blodget and Hussman’s predictions — this piece was written in the summer of 2013!… In the 10 years following Hussman’s prediction of a 40-50% crash or lousy returns for a decade, the S&P 500 was up more than 230% in total or 12.8% on an annual basis:…

…Did Hussman relent from his crash-calling ways? No. He’s still out there calling for a crash, only this time it’s going to be even bigger!…

…When Hussman called for a 40-50% crash in August 2013, he said the Dow could fall somewhere in the 7,500-8,500 range. From current levels at around 32,800 the Dow would need to fall 55% just to get back to the point where Hussman made his initial prediction in 2013 and then another 50% from there to hit that target range…

…I looked at the daily returns on the S&P 500 going back to 1950 to see how often the market was in a state of drawdown at different levels of losses… We’ve had 40% and 50% crashes but it’s pretty rare. You don’t spend all that much time there as an investor. Sometimes you’re going to get your face ripped off in the markets and learn to live with it but you can’t shouldn’t expect it to happen all the time…

…I looked at the rolling 10 year returns for the S&P 500 going back to 1950 to find the distribution of annual returns at various levels… More than 3% of the time returns have been negative over 10 year time frames. Annual returns have been 5% or worse 14.1% of the time. That’s not great. However, annual returns have been 10% or higher 55% of the time. Annual returns of 8% or more have occurred in nearly 70% of all rolling 10 year windows since 1950…

…The people who predict a crash every single year will be “right” eventually. The same is true for those who are constantly forecasting a recession. But they will be wrong the majority of the time. The stock market has been up roughly 75% of the time over one year periods and nearly 97% of the time over 10 year time frames over the past 70+ years.

3. The Long, Long View of Interest Rates – Byrne Hobart

The single most important variable in economics is the risk-free interest rate, i.e. the price of money. Over time, the available data indicate that money has gotten much, much cheaper…

…First things first: a loan to the Duke of Burgundy in the 15th century and a loan to the US treasury in 2023 are completely different things. In the latter case, it’s a loan to a global hegemon that issues the world’s most-accepted reserve currency, a currency in which that loan will be repaid. The Duke, by contrast, is a person, not a country. He collects taxes, but perhaps intermittently, and some fraction of Burgundy consists of his personal property. His big source of uncertain expenses is military campaigns, which are also one of the few legible investments that can produce some theoretical return. But they’re usually a bad deal…

…So for the tiny set of people (like the Duke) who regularly borrowed large sums, their big lumpy expenses were probably ransoms, which means ransoms were potentially a big lumpy source of income as well. In other words, they took part in a physical contest which would lead to an unpredictable positive or negative payoff. 12% is expensive for a sovereign credit, but pretty cheap for a loan to an athlete whose primary source of income is wagering on the outcome of their own matches.

The process of replacing personal relationships with institutional ones has been gradual. Over time, though, it’s created more low-risk or even essentially risk-free lending opportunities. It’s hard to draw a dividing line here, especially because some countries move in and out of risk-free status depending on the market’s general fears and the specifics of their political situation (the spread between German and Italian rates, for example, is a good proxy for the market’s view of how stable Europe is). In the case of the US, we really do have a stable, low-risk borrower—but even the US likes to periodically stress-test the market with debt ceiling fights.

There were lower-risk bonds in the early period of the chart; the paper mentions people earning 5% lending to the governments of Florence and Venice, for example. But in practice, the only risk-free investment at the time was taking hard currency and literally burying it; a risk-free asset with a positive yield is a 19th-century innovation.

Adjust for that, and you’d end up with a new chart: the rate of return on a risk-free investment was on average slightly negative (the inconvenience of hiding it, the risk of losing it, and the possibility, for some currencies, of devaluation). Then it jumped some time in the 19th century despite the fact that governments still needed to borrow, they were now larger and better at tax collection than their predecessors, but their bonds now competed with high-return private sector opportunities). And then we see a decline, or a reversion to the mean, starting in the 1980s: growth declined, rates declined, and the real rate of return on risk-free assets dropped. That’s recently been disrupted again, with the resurgence in inflation since 2021.

But the other big driver of that secular-decline chart is still in place, and it pushes the equilibrium interest rate relentlessly lower. The biggest factor is the existence of retirement…

…The key difference in modernity is that we took a luxury previously available only to the elite, i.e. the ability to live well entirely off the labor of others, and made it an option for anyone who chose to sock away enough money in their 401(k). (The “labor of others” is now some miniscule share of the profits from every company in whatever index the retiree in question has invested in, and their capital comes from forgone consumption when they themselves had a job, but the fundamentals are unchanged.) Longer lifespans that mostly lead to longer retirement rather than more working years will necessarily increase global savings; whether this old-age saving is mediated through private sector investments or through public pensions like social security, it creates an implicit asset on the retiree’s (or future retiree’s) economic balance sheet, a corresponding liability on the part of whoever is offering that income, and thus a demand for income-producing assets that match that liability…

…Technology is also a driver of rates. But the direction is noisy. The more sophisticated the financial system, the more likely it is that deploying new technology will be inflationary. There are two forces at work: in the long run, new technology is deflationary over time, since we’re getting more from less—the number of labor-hours required for illuminating a room for an hour, traveling across the country, or getting a nutritious meal has continuously declined. But when technology is being deployed, it’s inflationary, because there’s more demand for investment and labor. So asking whether the impact of a given technological development is net inflationary or deflationary over, say, the next decade, amounts to asking: how quickly is it getting deployed? If we developed some radically transformative new technology, like a way to generate low-cost, low-emissions energy from trivial amounts of a fairly abundant natural resource, taking advantage of this would require spending money on construction labor, equipment, and raw materials, but would lead to energy abundance over time…

…Last big feature in the real rates model is the existence of a reserve currency. Early in the time series, there were reserve-like currencies; some kinds of money were good for transacting or paying taxes in a specific place, but a ducat or florin was useful just about anywhere, because Venetian and Florentine merchants were almost everywhere, and people who did business with them were everywhere else. But these were small, open economies, of the sort that can’t absorb significant inflows. They’re closer to the Swiss franc than to the dollar: everyone knew they were safe, but it wasn’t possible for everyone in the world to denominate savings in the same currency.

What the dollar as a reserve currency does is to create demand for dollar-denominated savings from exporters, who a) want to keep their currency from appreciating too quickly, and b) want to have local dollar liquidity to ensure that they don’t have a ruinous financial crisis if their exports slow down. The relevant exporters, and the policy consequences, have varied over time; sometimes the petrodollar is the dominant form, and sometimes it’s manufacturing economies. But the direction persists, and as long as the dollar has such strong network effects, there will be foreign demand for dollar-denominated savings with minimal interest rate sensitivity.

Extremely long-term trends are important, because they’re the closest thing we have to true economic fundamentals. If something was true under feudalism and democracy, in wartime and peacetime, in an agrarian economy, a manufacturing economy, and a services-based one, it’s probably just a fact of economic life. The decline in real rates is noisy in the chart and noisier still in reality, but it’s something we should accustom ourselves to: if people live longer than they work, and provide for their old age by saving money; if technological advances are deflationary over time and haven’t been happening as often as they did at the peak; and if countries still grudgingly rely on the dollar; then the long-term set point for rates will decline over time.

4. How Does the World’s Largest Hedge Fund Really Make Its Money? – Rob Copeland

Since founding Bridgewater in his Manhattan apartment in 1975, Mr. Dalio has been said to have developed prodigious skill at spotting, and making money from, big-picture global economic or political changes, such as when a country raises its interest rates or cuts taxes. That made both a lot of sense and none at all; what was it about Bridgewater that made it so much better at predictions than any other investor in the world trying to do the exact same thing?

Bridgewater earned worldwide fame for navigating the 2008 financial crisis, when the firm’s main fund rose 9 percent while stocks dropped 37 percent, making Mr. Dalio a sought-after adviser for the White House and Federal Reserve and attracting new deep-pocketed clients to his fund. Yet the hedge fund’s overall descriptions of its investment approach could be maddeningly vague. Mr. Dalio often said he relied on Bridgewater’s “investment engine,” a collection of hundreds of “signals,” or quantitative indicators that a market was due to rise or fall. Bridgewater rarely revealed any details of these signals, citing competitive pressure, but if they pointed to trouble ahead or even to uncertainty, Bridgewater said it would buy or sell assets accordingly — even if Mr. Dalio’s own gut might have told him otherwise…

…What confused rivals, investors and onlookers alike was that the world’s biggest hedge fund didn’t seem to be much of a Wall Street player at all. Much smaller hedge funds could move the markets just by rumors of one trade or another. Bridgewater’s heft should have made it the ultimate whale, sending waves rolling every time it adjusted a position. Instead, the firm’s footprint was more like that of a minnow.

What if the secret was that there was no secret?…

…In early 2015, Bill Ackman, the endlessly opinionated hedge fund manager, took the first whack. The billionaire founder of Pershing Square Capital had long found Mr. Dalio’s public pronouncements about his quantitative investment style to be generic and even nonsensical. At a charity event in February that year, Mr. Ackman grilled Mr. Dalio during an onstage interview about how Bridgewater handled the assets it managed.

Mr. Dalio responded: “Well, first of all, I think it’s because I could be long and short anything in the world. I’m basically long in liquid stuff. And I can be short or long anything in the world, and I’m short or long practically everything.” He also noted that some 99 percent of Bridgewater trading was automated, based on longtime, unspecified rules. “They’re my criteria, so I’m very comfortable,” Mr. Dalio said.

Mr. Ackman tried another tack. He gave Mr. Dalio a layup, the sort of question asked six times an hour on business television. “Let’s say you were to buy one asset, or one stock, or one market, or one currency. Where would you put your money?” There was a pause, then Mr. Dalio said, “I don’t do that.” He went on to lay out how Bridgewater’s hundreds of investment staff members spent their days, describing a data-driven approach.

Onstage, Mr. Ackman would remark that it was “one of the most interesting conversations I’ve ever had.” But he walked away shaking his head.

“What was he even talking about?” he vented afterward…

…This all piqued the interest of a Boston financial investigator, Harry Markopolos, who had been a no-name analyst in the late 1990s when his boss asked him to reproduce a rival’s trading strategy that seemed to pay off handsomely. Mr. Markopolos couldn’t, but he figured out enough that he began chatting with the Securities and Exchange Commission. Six years later, when his warnings about Bernie Madoff proved right, Mr. Markopolos earned national fame.

To Mr. Markopolos, what was happening in Westport, Conn., where Bridgewater has its headquarters, raised serious questions, according to people who worked with him. Here lay another giant hedge fund famed for an investment approach that no competitors seemed to understand. He got his hands on Bridgewater’s marketing documents, including a summary of the firm’s investment strategy and a detailed chart of fund performance. Bridgewater described itself as a global asset manager, yet these documents didn’t name a single specific asset that had made or lost the firm money. An investment-performance chart indicated the firm seldom had a down year — even when Mr. Dalio’s public predictions proved off, Bridgewater’s main fund, Pure Alpha, consistently seemed to end the year around flat.

As he looked over the documents, Mr. Markopolos felt a familiar flutter in his heart…

…Mr. Markopolos also went to see David Einhorn of Greenlight Capital, the hedge fund billionaire famed for spotting frauds. Mr. Einhorn welcomed Mr. Markopolos into his Manhattan office, and they sat down with a team of Greenlight analysts who Mr. Einhorn said were interested in investigating Bridgewater themselves, two people present recalled.

After hearing Mr. Markopolos’s talk, Mr. Einhorn said it tracked with his suspicions, too. That was all the encouragement Mr. Markopolos needed. Bridgewater, he wrote to the S.E.C., was a Ponzi scheme.

Bridgewater was not a Ponzi scheme. Which is not to say that all was as Mr. Dalio so often described it.

The S.E.C. and other regulators dutifully took meetings with Mr. Markopolos and his team. The whistle-blowers’ report was passed through the organization, and a team at the agency looked into it. (The S.E.C. declined to comment.)

According to a person briefed on the investigation, what they concluded, in part, was that the world’s biggest hedge fund used a complicated sequence of financial machinations — including relatively hard-to-track trading instruments — to make otherwise straightforward-seeming investments. It made sense to the S.E.C. that rivals couldn’t track them…

…As it turned out, by the time the S.E.C. received Mr. Markopolos’s submission, the regulators had already looked into Bridgewater. In the wake of the Madoff fraud, and never having really dug into the world’s biggest hedge fund, S.E.C. staff spent a stretch in Westport, deeply studying the firm’s operations. The S.E.C. did not much bother with how Bridgewater made money, just that it did indeed invest its clients’ accounts…

…Of Bridgewater’s roughly 2,000 employees at its peak — and hundreds more temporary contractors — fewer than 20 percent were assigned to investments or related research. (The rest worked on operations tasks, including the expansion of Mr. Dalio’s “Principles.”) And of those investment staff members, many held responsibilities no more complicated than those of the average college student. They worked on economic history research projects and produced papers that Mr. Dalio would review and edit. As for whether those insights made it into Bridgewater’s trading, most research employees knew not to ask, current and former investment employees said.

Only a tiny group at Bridgewater, no more than about 10 people, enjoyed a different view. Mr. Dalio and his longtime deputy, Greg Jensen, plucked the members from the crew of Bridgewater investment associates and offered them entry to the inner sanctum. In exchange for signing a lifetime contract — and swearing never to work at another trading firm — they would see Bridgewater’s inner secrets…

…There were two versions of how Bridgewater invested hundreds of billions of dollars in the markets. One version, Mr. Dalio told the public and clients about. The other version, current and former investment employees said, happened behind closed doors.

In the first version, Bridgewater’s hedge funds were a meritocracy of ideas. Every investment staff member or researcher could suggest an investment notion, and the Bridgewater team would debate the merits of the thesis dispassionately, incorporating a broad study of history. Ideas from investment employees with a record of accurate predictions would over time carry more weight and earn backing with more client money. Investors flocked to the approach, assured that Bridgewater — unlike other hedge funds — would not rise or fall off a single trade or prediction from the firm founder. It was the Wall Street equivalent of Darwinism, with a thick wallet…

…The bottom line: Mr. Dalio was Bridgewater and Mr. Dalio decided Bridgewater’s investments. True, there was the so-called Circle of Trust. But though more than one person may have weighed in, functionally only one investment opinion mattered at the firm’s flagship fund, employees said. There was no grand system, no artificial intelligence of any substance, no holy grail. There was just Mr. Dalio, in person, over the phone, from his yacht, or for a few weeks many summers from his villa in Spain, calling the shots.

Lawyers for Mr. Dalio and Bridgewater said the hedge fund “is not a place where one man rules because the system makes the decision 98 percent of the time.” They said that “the notion that Mr. Dalio ‘call[ed] the shots’ on Bridgewater’s investments is false.”…

…On Wall Street, the phrase “information advantage” often carries an unseemly implication, suggesting that one is engaged in insider trading. Mr. Dalio’s information advantage, however, was as legal as it was vast.

Bridgewater’s target was information about entire nations. According to employees involved with the effort, Mr. Dalio heavily courted well-connected government officials from whom he might divine how they planned to intervene in their economies — and Bridgewater used these insights to make money in its funds.

Anywhere seemed fair game, even Kazakhstan. The Central Asian nation was not on the first page in any Wall Street manual. Ruled by an authoritarian government, it is the globe’s largest landlocked country yet sparsely populated. In 2013, Kazakhstan began developing what was then the most expensive oil project — a giant field in the Caspian Sea — helping it grow a $77 billion sovereign wealth fund. That money would have to be invested somewhere, and Bridgewater’s client services squad put a meeting on Mr. Dalio’s calendar with Berik Otemurat, the fund’s chief, a bureaucrat who had begun his career barely 10 years earlier…

…Inside Bridgewater, a relationship meant access. The country’s new oil field had taken more than a decade to develop, with near-constant delays. Anyone who knew how the project was proceeding could adjust bets on oil accordingly. Bridgewater’s representatives told the delegation that their firm would be happy to offer free investing advice, and Bridgewater’s team would likewise appreciate the opportunity to ask questions about industries of local expertise…

…The longest-term project for Mr. Dalio was in China, where he made frequent trips. Mr. Dalio hired China Investment Corporation’s former chairman to a cushy job as head of a Dalio charity in China, and he became close with Wang Qishan, who would later become China’s vice premier and widely considered the second most powerful person in the country. Mr. Dalio would occasionally tell Chinese government representatives that when they invested with Bridgewater, their fees were not merely being sent back to America. “Whatever fees you pay, I will donate back to China personally,” he said in one meeting, according to a person present.

In media interviews, Mr. Dalio stuck to a fixed, laudatory line about the country’s leadership. It was “very capable,” he said, over and again, sometimes repeating the phrase more than once in an interview. Those same leaders, he would also say inside Bridgewater, were quick to ask him for advice.

To any reasonable observer — and even to the Chinese themselves — Mr. Dalio was the paradigm of a China booster. But there was also an advantage that could be played. He asked the Circle of Trust to help create a way for Bridgewater’s funds to place bets against Chinese assets, in an offshore way that China’s government couldn’t track. That way, when Bridgewater took the wrong side of China, no one would know…

…With the hope of turning around the firm’s investment performance, members of the Circle of Trust put together a study of Mr. Dalio’s trades. They trawled deep into the Bridgewater archives for a history of Mr. Dalio’s individual investment ideas. The team ran the numbers once, then again, and again. The data had to be perfect. Then they sat down with Mr. Dalio, according to current and former employees who were present. (Lawyers for Mr. Dalio and Bridgewater said that no study was commissioned of Mr. Dalio’s trades and that no meeting took place to discuss them.)

One young employee, hands shaking, handed over the results: The study showed that Mr. Dalio had been wrong as much as he had been right. Trading on his ideas lately was often akin to a coin flip.

5. Palmer Luckey – Inventing The Future Of Defense – Patrick O’Shaughnessy and Palmer Luckey

Patrick: [00:01:42] Palmer, I always like starting somewhere of recent passion, you started to give me some amazing materials, so we stopped and we restarted the recording here. And maybe we’ll just begin with this idea that you were telling me about I’m always interested by major changes that might happen in the world that nobody is really talking about.

And until you said the word synthetic long chain hydrocarbon fuel to me 5 minutes ago, I’d never heard that combination of words before. So maybe you can start there and explain why that topic is of interest to you today.

Palmer: [00:02:16] Well, it’s of interest because there’s a lot of money being bet by companies, but also governments on a handful of specific technological pads for electrifying vehicles, battery electric vehicles, hydrogen electric vehicles.

If you can make synthetic long chain hydrocarbon fuels, in other words, synthetic gasoline, synthetic diesel synthetic jet fuel using carbon from the atmosphere in particular, there’s a lot of ways to do it. Boiling it down, one of the ways to do it. You take water, you crack it into hydrogen and oxygen using some kind of energy source like a nuclear power plant and then you bond it with carbon to make hydrocarbons and then you’ve got artificial gasoline coming out the other end.

If someone can figure out how to do that, cheaply enough. First of all, it’s an incredible carbon capture mechanism. Two, if you can do it cheaply enough, let’s say, $1 per gallon, then all of these trillions of dollars in investment into battery electric vehicles and hydrogen electric vehicles become really a waste of money and a waste of time. There are, of course, some advantages to battery electrical vehicles, hydrogen electric vehicles that wouldn’t apply.

But for the most part, especially on the aviation side, the ability to make fuels to just plug into existing fully known, fully optimized, fully understood and even fully certified systems that are better than the ones that cost hundreds of billions of dollars to develop. That also aren’t as good electric planes spend most of their energy hauling around their energy storage, not people or payload, which, of course, means you need to put more energy into them in the first place than even synthetic fuels with a pretty low conversion efficiency.

The reason it’s so interesting to me is that the bet seems so mis-apportioned, you have so much money going into battery electric vehicles and electrification of electrical infrastructure that’s not moving. And almost nobody betting that you can build systems that make dollar per gallon hydrocarbon fuels using either biological processes like algae farms or mechanical processes, however you’re making the synthetic fuels.

And of course, if someone figures it out, they’re going to really knock a whole bunch of stuff sideways. And we talked about this before, but it’s especially interesting because lots of companies make poor technical decisions and they decide to go down a product path, it doesn’t make sense.

I personally feel like this is a case where you have dozens of governments around the world have decided to commit to a particular product path that isn’t optimal. It’s not the optimal end state or the optimal near term, and they’re dumping hundreds of billions, maybe trillions of dollars into that bet. It’s something that I’m worried about.

Patrick: [00:04:38] When you find an idea like this. First of all, I’m curious how you found this one in particular, but the world has just gone through the superconductor craze, which for a week there it was like, well, if this is real, it changes everything. And then very quickly realize, oh, it’s not real, and it seems like, again, a remote possibility and not terribly likely. So maybe there won’t be loads of dollars trying to create superconductors. With something like this, how do you weigh the potential against the odds of us being able to do it with your own time and investigation?

Palmer: [00:05:05] Well, in this case, it’s 1950s era Department of Energy documents regarding potential energy futures for the United States, accounting for what they assumed would be a nuclear future. I always find it interesting when I go into an area that I don’t understand to try and understand it better.

Even — if I want to understand what’s going on in the modern day, you want to go back to the future and say, what were people saying, back then, what are the ideas that people aren’t even discussing right now? Because I don’t want to be too pessimistic on present, but if you look through a lot of the academic literature and government literature today on energy solutions for the United States, they’re really, really narrow minded.

They are really, really politically driven, it’s all about what is aligned with the current debates going on between political parties. The people in these agencies are largely tied to the things that have already been deemed important. And if you go back on the other hand, to let’s say, post-World War II America, where we were really thinking from first principles, what do we want the world to look like? What do we want the United States to look like?

And what are all of the ways we could get there? They were thinking very expensively. And so this idea of extremely cheap synthetically manufactured biofuels that would get rid of strategic dependence on limited oil supply or allow us to sell off our oil supply to make money in the near term while still having a robust renewable base of energy to power our industrial machine, our war machine, you name it

That was an idea that was of interest to people in the ’40s, the ’50s, the ’60s. I think mostly all of this fell apart when it became clear that we were not going to be a nuclear economy mostly in for political reasons, not practical or technological reasons. So this was the case, right?

I didn’t actually have to be a big thinker. I just had to go say, what were people thinking when they were allowed to think whatever they wanted and when they could think really, really big things? And it’s not even just on fuel. There’s other interesting things they were thinking about back then, like today, if you say, what’s the best way to help the environment in the United States? It’s actually very calcified.

There’s very little consideration for things that are better than what currently exists. You kind of preserving the status quo as the ultimate good. There’s very little consideration for what is better for people, what would be better for more animals. And if you look back again the earlier parts of the United States history, there were serious proposals by the Department of Interior to say, what should the United States ecosystem look like if we could make it whatever we wanted?

What animals would we have? Would we have hippos? Would we have rhinos? Why not? Why don’t we put hippos in Louisiana? There was just this endless possibility, big thinking. But what’s crazy is it’s not even big thinking in the way that we would think of today. When people think a big thinking, they immediately jump to really hard ideas, fusion power and what if we could bio-engineer ourselves? The ideas they were having, they would have a big impact, but they’re actually easy ideas.

Just what if we brought some hippos, put them over there on that swamp? The big idea is what could we do economically? Would that be a good meat source? Could we use that as a better protein source that is less damaging to environments that we’re trying to preserve than what we’re currently doing with cows? And those types of ideas, they’re not taken seriously today. People treat you like a crank if you step outside the orthodoxy…

…Patrick: [00:22:27] When you approach those problems, I have heard you talk about those other two, which is totally fascinating how you approach things. Maybe even before I ask this question, I’m just curious what your method of invention is. So you find an interesting problem either that you want to work in this case, don’t want to work on necessarily. Is your method iterative? Is it more theoretical? Describe the way that you start to invent in a field when you approach something for the first time.

Palmer: [00:22:50] Well, it depends on if it’s a field that I know a lot about or don’t know a lot about. If you know a lot about something, it’s easier to get right into the iterative side of things and know that you’re probably on a pretty reasonable path. In that case, iteration is a valuable tool to move very quickly, find out what works, find out what doesn’t and then continuously make it better.

The risk with going with a strongly iterative approach in areas that you maybe don’t understand, and you might even think you do, but let’s say you truly don’t is that there might be much better approaches that you should have started iterating on. Or that you should have examined before you committed to one particular path. I talked about this earlier, but it’s really about going back to the future. I love to go and see what everyone else who solved this problem thinks about it, not in the recent times.

I don’t want to know what my competition looks like because when I started Oculus, I wasn’t looking at what existing companies were doing in VR because clearly, they were all doing it wrong. Whatever they were doing was not working. I was not going to look around at the handful of VR companies that existed in that time and learn anything except how to fail. So I wanted to look into the past, what were people thinking when they were thinking bigger, when they were willing to look at wackier paths.

When they were willing to consider things that have been eliminated often because technologies just weren’t ready. There’s a lot of technologies that have been discarded because they weren’t practical at the time, and nobody ever revisited them and said, “Hey, I actually think the time has come.” A good example is with the Rift. Doing real-time distortion correction is not a new idea. It existed in the 1980s and 1990s in the virtual reality community. They have been discarded even by NASA.

There’s a fascinating NASA paper where they talk about doing real-time geometry distortion correction on a virtual reality headset that made the optics lower distortion and allow them to, therefore, use wider field of view. Lighter weight optics than would have otherwise been required to have an optically perfect image. And the conclusion was, yes, this is a really good way to save money and to save weight, but it’s too computationally expensive. We’re using most of our processing power to warp the image in real time rather than render this wire frame image.

And so this is not a good approach. You should just do it optically, and then you don’t have to have a more expensive computer. But back then, compute was the expensive part and the optic transform used up a lot of your compute. Nobody reexamined this idea even as computers got better. Nobody went back until me and said, “Wait a second, you can do real-time transform on a modern graphics card for like 1% or 2% of your render horsepower.” And also your graphics card doesn’t cost $100,000 anymore. It costs a few hundred dollars.

And so if you’re worried about that 1% or 2% impact, just buy a graphics card that costs a few dollars more, so you can save hundreds or thousands of dollars on the VR headset itself by using optics that have geometric distortion or in chromatic aberration, for example. That was an idea that had been discarded and nobody ever came back to it.

And most of the things that made the Rift successful were ideas like that, there’s a few others where I was just going back to the future and realizing, “Wait a sec, these ideas, they were actually pretty good. They were just a little too early.”…

…Patrick: [00:35:55] Just trying to think about a framework to discuss the state of weapons technology or the history of weapons technology with you. And the cleanest I could come up with a stupid consultant 2×2, where on one axis, you have offensive versus defensive technologies dominating. And on another, you have democratic versus very non-democratic. Musket’s on one end, everyone has the same amount of power. And on nuclear weapons on the other, one person has a gazillion times as much as the Musket guy or something. Is that a good way to think about where we might pop through history and weapons technology? Is there some other way that you would approach thinking about an era and weapons technology?

Palmer: [00:36:29] Offensive and defensive is definitely the right scale. Distributed or not distributed, I’m not sure. That I actually think matters less by weapon system and more by the power dynamic of the nation. There’s a question here, are the people aligned with the government or are they opposed to the government and to what degree? If you have them where there are neutral parties that accept each other’s existence, that’s one thing.

Let’s say you have a country like Ukraine where implausibly to the Russians, they had formed a strong national identity, and there were people who were willing to die in large numbers for their country. That’s a case where there’s people who are very much aligned with the broader goals of their nation. On the other hand, if you look at a lot of African nations, even a lot of Middle Eastern nations, you have a huge mismatch between what the political class wants and what the every man wants.

And so I think a better access is actually more like democratic versus autocratic technologies. In that, there are a lot of technologies that are much more useful for controlling your own population than for preserving their rights against hostile actors. There’s a lot of countries whose military effectively is an internal peacekeeping force to crush dissent. That’s actually what it’s for.

And there’s a lot of tools made by companies like SenseTime in China that are fundamentally — they are not useful for going to other countries and preserving our rights. They’re not useful for defending yourself from an invader. They are only useful for controlling people in your nation. This is one of the reasons that China is exporting these technologies in the same way that the Soviet Union exported AK-47s, which you could say are on this distributed and offensive side, if you were to look at it that way.

But the reason they were actually doing that is they wanted to arm nations with the tools that they needed to keep their civilian population in check and keep them in power and they wanted to threaten them and say, “Hey, if you ever get out of line, we’re going to stop providing you with these arms and systems you need, and then you’re going to immediately get a violent revolution and you’re probably going to get killed.” It was a great motivation for people to stay stuck to the Soviet Union. This idea that, “We are the thing that allows you to keep your people in check, and without us, that is over.”

China is pursuing a similar strategy. They’re going to African nations and saying, “Hey, we’re going to help build out this infrastructure in your ports, on your roads, in your police force, in your military. We’re going to build AI camera systems that track dissidents for you. They track where they’re shopping, where they’re going, where they’re riding trains. We’re going to allow you to monitor all their communications on the telecommunications side. So let us sell you telecommunications gear, and you get all these back doors that allow you to control people who’re trying to come after you.”

But a bargain with the devil that they’re making is, “Oh, and by the way, if you ever do anything that’s counter to Chinese interests, we’re going to pull all of this and you’re going to lose all your tools for controlling your population and you’re going to be dead inside of a week.” And say SenseTime is on the autocratic, authoritarian side of that scale because it has almost no application in preserving freedom or in deterring an invasion. It’s only for controlling your own people…

…Patrick: [00:48:53] So you built Lattice. Now the world is catching up. Everyone wants to build an AI platform system. What have you learned about building one? What are the components of it? What do you think about AI at large, the cost associated with compute and AI? All of these big things you’ve been working in for a while, and now it matters to everybody. So what would you contribute as the lessons that you’ve learned there so far?

Palmer: [00:49:11] It’s been a double-edged sword, I think. We’ve been working on AI for defense since literally day one. That was the whole pitch. The second page of our pitch deck was a quote from Vladimir Putin. He was talking about artificial intelligence, and he said, “The country that wins in this sphere will become the ruler of the entire world,” which I love. It’s a very James Bond villain quote.

On the one hand, it sounded crazier at that time because AI wasn’t hot seven years ago. There were people who were interested in it, but it’s obviously not even a 0.01 of the attention that’s being dedicated to it today. The flip side of that is now that everyone is saying they’re AI, all of a sudden our message is getting diluted or, “Hey, we’ve actually been doing AI for defense for almost seven years now.” And now everyone is changing to say, “Yes, our systems are all powered by AI. It’s all AI-driven.” Some of that’s true, some of it’s not.

Now it actually is less differentiated than we were. You have to now get very clear about what the difference between a real usable, fieldable AI system looks like versus strapping together ChatGPT with whatever your quadcopter thing is and saying that it’s going to change the world. I do think what’s been helpful to us, though, with members of Congress, people in The Pentagon, even investors has been the explosion of firsthand understanding of how powerful AI can be that’s been driven by these large language models.

Obviously, the things that we are building that fuse data from thermal vision and radar and signals intelligence processors, that then calculate optimal weapons pairing against that target, very different use of AI than a thing that you tell to write a poem about your car.

But the fact that every member of Congress has been able to use ChatGPT, the fact that all these people in The Pentagon have seen and used systems, doing things that they never believed a computer could do has, I think, expanded people’s minds in general towards the possibility that maybe people can be replaced by AI in certain use cases, maybe there are areas where computers really can do a job as well or better than a person. A lot of skeptics, I think, have changed their minds because they type something into ChatGPT, it did something for them, and they said, “Wow, computers sure are amazing these days.

Patrick: [00:51:20] What has AI most unlocked?

Palmer: [00:51:22] The most important thing that it has unlocked for us is ability to scale. People focus on use cases where AI can do better than a person or even better than a team of 100 or 1,000 people at some one specific task. I think a lot of the more interesting use cases are where you can do as good of a person but without a person having to do it.

Let’s use an example. Let’s say that I’m going to deploy 1,000 autonomous cruise missiles. Those are going to be a lot more impactful than they would be if I had to have 1,000 people trying to remotely pilot 1,000 systems and tell them what to do, how to do it, have all those data links active. I guess it’s using AI to do things that would be impossible to do otherwise, either for real technical reasons like bandwidth or just for practical reasons. We don’t have thousands of pilots that we could dedicate to such a task. For me, I think that’s the biggest thing AI enables.

I’m less focused on the superhuman, super intelligent side of things and more, “Hey, this AI that’s running my autonomous helicopter, is it about as good as a pretty good helicopter pilot? Okay, that means that I can have one soldier managing a fleet of 25 airframes himself and just telling them, “Hey, I need you to clear this area. I need you to find this target I’m looking for. I need you to fly ahead of my convoy and watch for anything.” Now he doesn’t need 25 pilots and 25 helicopters to do that. That’s what I’m most excited about.

And it’s really important in a world where I think quantity is going to have a quality all of its own in these types of weapon systems. The best way to defeat a lot of our adversaries’ defenses is not through building a small number of exquisite systems. But quantities that are so large, they can’t possibly stop them.

And it’s especially important in a world where militaries are struggling to recruit. They’re trying to be more cost effective. They’re trying to put less money into salaries and disability payments and more into systems that are going to be fighting the adversary directly, robotic systems.

For example, the United Kingdom has said that they want to, over the next few years, reduce the size of their Navy by 30%, 30% personnel reduction. And because of that, they are doing things like dedicating one of their two aircraft carriers to being an autonomous aircraft launch system.

In other words, they want one of their carriers to only launch autonomous systems. You don’t have to have huge numbers of people to run and maintain these traditional manned systems. If that’s the world we’re going to live in where we need to ramp up the number of systems but also ramp down the number of people, the only thing that can fill the gap is automation.

Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. We currently do not have a vested interest in any companies mentioned. Holdings are subject to change at any time.

What We’re Reading (Week Ending 29 October 2023)

The best articles we’ve read in recent times on a wide range of topics, including investing, business, and the world in general.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

Here are the articles for the week ending 29 October 2023:

1. CEO/CIO’s Final Investment Note: The Best of Times and The Worst of Times – Chuin Ting Weber

While there is sadness in the hearts of all of us at MoneyOwl, we know that the ups and downs of our journey are but a faint reflection of our larger condition – as a human race, as countries, as societies and as individuals. We all face circumstances that we cannot control, try as we may to do so. The shock of the Israel-Hamas conflict and the accompanying humanitarian disaster, the ongoing Russia-Ukraine war, and the gyrations in big economies both East and West, threatens to shake us and tempt us to despair. On an individual level, some of us may face unexpected shocks, tough times, or just unsettling uncertainties as we move from one season of life to another.

Yet, there must always be some beliefs in our lives that anchor us, so that our core will not be shaken. And as it is with our lives, so it is with investing. Whatever is happening around you and in the world, please remember that the human spirit for recovery and progress, has never been quenched by wars, pandemics, natural disasters or man-made crises. COVID-19 was the most recent example, but it was neither the first crisis we have overcome, nor would it be the last. As J.S. Mill put it, writing in a period that Charles Dickens described as both the best and the worst of times:

“What has so often excited wonder, is the great rapidity with which countries recover from a state of devastation…… An enemy lays waste a country by fire and sword, and destroys or carries away nearly all the moveable wealth existing in it: all the inhabitants are ruined, and yet in a few years after, everything is much as it was before.”

John Stuart Mill, “Principles of Political Economy”, 1848

When you invest in a globally diversified portfolio of stocks and bonds – instruments that companies and countries issue to finance their economic activities – what you are really investing in, is the future of human enterprise. It is a vote of confidence in the human race. In the long run, stock prices are driven by earnings, and earnings, by the increase in global aggregate demand, which is in turn driven by a combination of global population growth and the quest for increase in standards of living. That is why no matter how bad the crisis, the stock market always recovers and goes up in the long run. This is the reason the stock market has a positive expected return. It is backed by logic and evidence.

The principle, however, does not apply to individual companies, sectors or even countries. It is also not so easy to read the tea-leaves to try to catch the short-term turns of ups and downs, to do better than the market’s long-term return. The best of times often follows the worst of times. We just don’t know when it turns. While being in a bad season is temporary, being out of the market because you timed it wrong, is the one sure way of missing out on the recovery.

2. Higher For Longer vs. the Stock Market – Ben Carlson

I don’t know what the bond market is thinking but it’s worth considering the potential for rates to remain higher than we’ve been accustomed to since the Great Financial Crisis. So I used various interest rate and inflation levels to see how the stock market has performed in the past.

Are returns better when rates are lower or higher? Is high inflation good or bad for the stock market?…

…Surprisingly, the best future returns have come from both periods of very high and very low starting interest rates while the worst returns have come during average interest rate regimes.

The average 10 year yield since 1926 is 4.8% meaning we are at that long-term average right now. Twenty years ago the 10 year treasury was yielding around 4.3%. Yields have moved a lot since then…

…In that 20 year period the S&P 500 is up nearly 540% or 9.7% per year. Not bad…

…The average inflation rate since 1926 was right around 3%.

These results might look surprising as well. The best forward long-term returns came from very high starting inflation levels. At 6% or higher inflation, forward returns were great. At 6% or lower, it’s still pretty good but more like average.

So what’s going on here? Why are forward returns better from higher interest rates and inflation levels?

The simplest explanation is we’ve only had one regime of high interest rates over the past 100 years or so and two highly inflationary environments. And each of these scenarios was followed by rip-roaring bull markets. The annual inflation rate reached nearly 20% in the late-1940s following World War II. That period was followed by the best decade ever for U.S. stocks in the 1950s (up more than 19% per year). And the 1970s period of high inflation and rising interest rates was followed by the longest bull market we’ve ever experienced in the 1980s and 1990s.

A simple yet often overlooked aspect of investing is a crisis can lead to terrible returns in the short-term but wonderful returns in the long-term. Times of deflation and high inflation are scary while you’re living through them but also tend to produce excellent entry points into the market…

…It’s also important to remember that while volatility in rates and inflation can negatively impact the markets in the short-run, a long enough time horizon can help smooth things out.

Regardless of what’s going on with the economy, you’ll fare better in the stock market if your time horizon is measured in decades rather than days.

3. Drawdowns – Chris Mayer

A drawdown is how much a stock price declines from its peak before it recovers.

Drawdowns are part of the life of every investor. Invariably, if you own a stock for a long time, you are going to have to sit through several…

…A few examples from the book, which was published in 2015:

Apple from its IPO in 1980 through 2012 was a 225-bagger. But you had to sit through a peak-to-trough loss of 80% — twice! And there were several 40% drops.
Netflix, which has been a 60-bagger since 2002, lost 25% of its value in a single day — four times! And there was a four-month stretch where it dropped 80 percent.
And Berkshire Hathaway, the best performing stock in the study, was cut in half four times.

What I found affirmed what Peter Lynch once said: “The real key to making money in stocks is not to get scared out of them.” …

…Not only do the best stocks suffer frequent (and lengthy) drawdowns, but the best investors also suffer drawdowns that would surprise most.

The aforementioned Peter Lynch, for example, had four severe drawdowns during his Hall of Fame run at Fidelity. Even though he returned a mind-boggling 29% annually, he had many drawdowns during those years, including three of more than 20% (one of which was a hair-raising 42% drop in 1987).

In summary: There is no defense against drawdowns if you are committed to a long-term, ownership approach to stocks. (Peter Lynch, by the way, was highly diversified and had a high turnover rate in his career – but still). In fact, I would go so far as to say that the ability to sit through drawdowns with equanimity is a source of outperformance. It is a competitive advantage over those that can’t.

4. NVIDIA CEO Jensen Huang – Ben Gilbert, David Rosenthal, Jensen Huang

David: I love this tee-up of learning but not imitating, and learning from a wide array of sources. There’s this unbelievable third element, I think, to what Nvidia has become today. That’s the data center.

It’s certainly not obvious. I can’t reason from AlexNet and your engagement with the research community, and social media feed […]. You deciding and the company deciding we’re going to go on a five-year all-in journey on the data center. How did that happen?

Jensen: Our journey to the data center happened, I would say almost 17 years ago. I’m always being asked, what are the challenges that the company could see someday?

I’ve always felt that the fact that Nvidia’s technology is plugged into a computer and that computer has to sit next to you because it has to be connected to a monitor, that will limit our opportunity someday, because there are only so many desktop PCs that plug a GPU into. There are only so many CRTs and (at the time) LCDs that we could possibly drive.

The question is, wouldn’t it be amazing if our computer doesn’t have to be connected to the viewing device? That the separation of it made it possible for us to compute somewhere else.

One of our engineers came and showed it to me one day. It was really capturing the frame buffer, encoding it into video, and streaming it to a receiver device, separating computing from the viewing.

Ben: In many ways, that’s cloud gaming.

Jensen: In fact, that was when we started GFN. We knew that GFN was going to be a journey that would take a long time because you’re fighting all kinds of problems, including the speed of light and—

Ben: Latency everywhere you look.

Jensen: That’s right.

David: To our listeners, GFN GeForce NOW.

Jensen: Yeah. GeForce NOW.

David: It all makes sense. Your first cloud product.

Jensen: That’s right. Look at GeForce NOW. It was Nvidia’s first data center product.

Our second data center product was remote graphics, putting our GPUs in the world’s enterprise data centers. Which then led us to our third product, which combined CUDA plus our GPU, which became a supercomputer. Which then worked towards more and more and more.

The reason why it’s so important is because the disconnection between where Nvidia’s computing is done versus where it’s enjoyed, if you can separate that, your market opportunity explodes.

And it was completely true, so we’re no longer limited by the physical constraints of the desktop PC sitting by your desk. We’re not limited by one GPU per person. It doesn’t matter where it is anymore. That was really the great observation.

Ben: It’s a good reminder. The data center segment of Nvidia’s business (to me) has become synonymous with how is AI going. And that’s a false equivalence. It’s interesting that you were only this ready to explode in AI in the data center because you had three-plus previous products where you learned how to build data center computers. Even though those markets weren’t these gigantic world-changing technology shifts the way that AI is. That’s how you learned.

Jensen: That’s right. You want to pave the way to future opportunities. You can’t wait until the opportunity is sitting in front of you for you to reach out for it, so you have to anticipate.

Our job as CEO is to look around corners and to anticipate where will opportunities be someday. Even if I’m not exactly sure what and when, how do I position the company to be near it, to be just standing near under the tree, and we can do a diving catch when the apple falls. You guys know what I’m saying? But you’ve got to be close enough to do the diving catch.

David: Rewind to 2015 and OpenAI. If you hadn’t been laying this groundwork in the data center, you wouldn’t be powering OpenAI right now.

Jensen: Yeah. But the idea that computing will be mostly done away from the viewing device, that the vast majority of computing will be done away from the computer itself, that insight was good.

In fact, cloud computing, everything about today’s computing is about separation of that. By putting it in a data center, we can overcome this latency problem. You’re not going to overcome the speed of light. Speed of light end-to-end is only 120 milliseconds or something like that. It’s not that long.

Ben: From a data center to—

Jensen: Anywhere on the planet.

Ben: Oh, I see. Literally across the planet.

Jensen: Right. If you could solve that problem, approximately something like—I forget the number—70 milliseconds, 100 milliseconds, but it’s not that long.

My point is, if you could remove the obstacles everywhere else, then the speed of light should be perfectly fine. You could build data centers as large as you like, and you could do amazing things. This little, tiny device that we use as a computer, or your TV as a computer, whatever computer, they can all instantly become amazing. That insight 15 years ago was a good one.

Ben: Speaking of the speed of light—David’s begging me to go here—you totally saw that InfiniBand would be way more useful way sooner than anyone else realized. Acquiring Mellanox, I think you uniquely saw that this was required to train large language models, and you were super aggressive in acquiring that company. Why did you see that when no one else saw that?

Jensen: There were several reasons for that. First, if you want to be a data center company, building the processing chip isn’t the way to do it. A data center is distinguished from a desktop computer versus a cell phone, not by the processor in it.

A desktop computer in a data center uses the same CPUs, uses the same GPUs, apparently. Very close. It’s not the processing chip that describes it, but it’s the networking of it, it’s the infrastructure of it. It’s how the computing is distributed, how security is provided, how networking is done, and so on and so forth. Those characteristics are associated with Melanox, not Nvidia.

The day that I concluded that really Nvidia wants to build computers of the future, and computers of the future are going to be data centers, embodied in data centers, then if we want to be a data center–oriented company, then we really need to get into networking. That was one.

The second thing is observation that, whereas cloud computing started in hyperscale, which is about taking commodity components, a lot of users, and virtualizing many users on top of one computer, AI is really about distributed computing, where one training job is orchestrated across millions of processors.

It’s the inverse of hyperscale, almost. The way that you design a hyperscale computer with off-the-shelf commodity ethernet, which is just fine for Hadoop, it’s just fine for search queries, it’s just fine for all of those things—

Ben: But not when you’re sharding a model across.

Jensen: Not when you’re sharding a model across, right. That observation says that the type of networking you want to do is not exactly ethernet. The way that we do networking for supercomputing is really quite ideal.

The combination of those two ideas convinced me that Mellanox is absolutely the right company, because they’re the world’s leading high-performance networking company. We worked with them in so many different areas in high performance computing already. Plus, I really like the people. The Israel team is world class. We have some 3200 people there now, and it was one of the best strategic decisions I’ve ever made….

…Ben: Let’s say you do get this great 10-year lead. But then other people figure it out, and you’ve got people nipping at your heels. What are some structural things that someone who’s building a business can do to stay ahead? You can just keep your pedal to the metal and say, we’re going to outwork them and we’re going to be smarter. That works to some extent, but those are tactics. What strategically can you do to make sure that you can maintain that lead?

Jensen: Oftentimes, if you created the market, you ended up having what people describe as moats, because if you build your product right and it’s enabled an entire ecosystem around you to help serve that end market, you’ve essentially created a platform.

Sometimes it’s a product-based platform. Sometimes it’s a service-based platform. Sometimes it’s a technology-based platform. But if you were early there and you were mindful about helping the ecosystem succeed with you, you ended up having this network of networks, and all these developers and customers who are built around you. That network is essentially your moat.

I don’t love thinking about it in the context of a moat. The reason for that is because you’re now focused on building stuff around your castle. I tend to like thinking about things in the context of building a network. That network is about enabling other people to enjoy the success of the final market. That you’re not the only company that enjoys it, but you’re enjoying it with a whole bunch of other people.

David: I’m so glad you brought this up because I wanted to ask you. In my mind, at least, and it sounds like in yours, too, Nvidia is absolutely a platform company of which there are very few meaningful platform companies in the world.

I think it’s also fair to say that when you started, for the first few years you were a technology company and not a platform company. Every example I can think of, of a company that tried to start as a platform company, fails. You got to start as a technology first.

When did you think about making that transition to being a platform? Your first graphics cards were technology. There was no CUDA, there was no platform.

Jensen: What you observed is not wrong. However, inside our company, we were always a platform company. The reason for that is because from the very first day of our company, we had this architecture called UDA. It’s the UDA of CUDA.

David: CUDA is Compute Unified Device Architecture?

Jensen: That’s right. The reason for that is because what we’ve done, what we essentially did in the beginning, even though RIVA 128 only had computer graphics, the architecture described accelerators of all kinds. We would take that architecture and developers would program to it.

In fact, Nvidia’s first business strategy was we were going to be a game console inside the PC. A game console needs developers, which is the reason why Nvidia, a long time ago, one of our first employees was a developer relations person. It’s the reason why we knew all the game developers and all the 3D developers.

David: Wow. Wait, so was the original business plan to…

Ben: Sort of like to build DirectX.

David: Yeah, compete with Nintendo and Sega as with PCs?

Jensen: In fact, the original Nvidia architecture was called Direct NV (Direct Nvidia). DirectX was an API that made it possible for the operating system to directly connect with the hardware.

David: But DirectX didn’t exist when you started Nvidia, and that’s what made your strategy wrong for the first couple of years.

Jensen: In 1993, we had Direct Nvidia, which in 1995 became DirectX.

Ben: This is an important lesson. You—

Jensen: We were always a developer-oriented company.

Ben: Right. The initial attempt was we will get the developers to build on Direct NV, then they’ll build for our chips, and then we’ll have a platform. What played out is Microsoft already had all these developer relationships, so you learned the lesson the hard way of—

David: […] did back in the day. They’re like, oh, that could be a developer platform. We’ll take that. Thank you.

Jensen: They did it very differently and did a lot of things right. We did a lot of things wrong.

David: You were competing against Microsoft in the nineties.

Ben: It’s like […] Nvidia today.

Jensen: It’s a lot different, but I appreciate that. We were nowhere near competing with them. If you look now, when CUDA came along and there was OpenGL, there was DirectX, but there’s still another extension, if you will. That extension is CUDA. That CUDA extension allows a chip that got paid for running DirectX and OpenGL to create an install base for CUDA.

David: That’s why you were so militant. I think from our research, it really was you being militant that every Nvidia chip will run CUDA.

Jensen: Yeah. If you’re a computing platform, everything’s got to be compatible. We are the only accelerator on the planet where every single accelerator is architecturally compatible with the others. None has ever existed.

There are literally a couple of hundred million—250 million, 300 million—installed base of active CUDA GPUs being used in the world today, and they’re all architecturally compatible. How would you have a computing platform if NV30 and NV35 and NV39 and NV40 are all different? At 30 years, it’s all completely compatible. That’s the only unnegotiable rule in our company. Everything else is negotiable.

David: I guess CUDA was a rebirth of UDA, but understanding this now, UDA going all the way back, it really is all the way back to all the chips you’ve ever made…

…Ben: Well, as we start to drift toward the end here, we spent a lot of time on the past. I want to think about the future a little bit. I’m sure you spend a lot of time on this being on the cutting edge of AI.

We’re moving into an era where the productivity that software can accomplish when a person is using software can massively amplify the impact and the value that they’re creating, which has to be amazing for humanity in the long run. In the short term, it’s going to be inevitably bumpy as we figure out what that means.

What do you think some of the solutions are as AI gets more and more powerful and better at accelerating productivity for all the displaced jobs that are going to come from it?

Jensen: First of all, we have to keep AI safe. There are a couple of different areas of AI safety that’s really important. Obviously, in robotics and self-driving car, there’s a whole field of AI safety. We’ve dedicated ourselves to functional and active safety, and all kinds of different areas of safety. When to apply human in the loop? When is it okay for a human not to be in the loop? How do you get to a point where increasingly human doesn’t have to be in the loop, but human largely in the loop?

In the case of information safety, obviously bias, false information, and appreciating the rights of artists and creators, that whole area deserves a lot of attention.

You’ve seen some of the work that we’ve done, instead of scraping the Internet we, we partnered with Getty and Shutterstock to create commercially fair way of applying artificial intelligence, generative AI.

In the area of large language models in the future of increasingly greater agency AI, clearly the answer is for as long as it’s sensible—and I think it’s going to be sensible for a long time—is human in the loop. The ability for an AI to self-learn, improve, and change out in the wild in a digital form should be avoided. We should collect data. We should carry the data. We should train the model. We should test the model, validate the model before we release it in the wild again. So human is in the loop.

There are a lot of different industries that have already demonstrated how to build systems that are safe and good for humanity. Obviously, the way autopilot works for a plane, two-pilot system, then air traffic control, redundancy and diversity, and all of the basic philosophies of designing safe systems apply as well in self-driving cars, and so on and so forth. I think there are a lot of models of creating safe AI, and I think we need to apply them.

With respect to automation, my feeling is that—and we’ll see—it is more likely that AI is going to create more jobs in the near term. The question is what’s the definition of near term? And the reason for that is the first thing that happens with productivity is prosperity. When the companies get more successful, they hire more people because they want to expand into more areas.

So the question is, if you think about a company and say, okay, if we improve the productivity, then need fewer people. Well, that’s because the company has no more ideas. But that’s not true for most companies. If you become more productive and the company becomes more profitable, usually they hire more people to expand into new areas.

So long as we believe that they’re more areas to expand into, there are more ideas in drugs, there’s drug discovery, there are more ideas in transportation, there are more ideas in retail, there are more ideas in entertainment, that there are more ideas in technology, so long as we believe that there are more ideas, the prosperity of the industry which comes from improved productivity, results in hiring more people, more ideas.

Now you go back in history. We can fairly say that today’s industry is larger than the world’s industry a thousand years ago. The reason for that is because obviously, humans have a lot of ideas. I think that there are plenty of ideas yet for prosperity and plenty of ideas that can be begat from productivity improvements, but my sense is that it’s likely to generate jobs.

Now obviously, net generation of jobs doesn’t guarantee that any one human doesn’t get fired. That’s obviously true. It’s more likely that someone will lose a job to someone else, some other human that uses an AI. Not likely to an AI, but to some other human that uses an AI.

I think the first thing that everybody should do is learn how to use AI, so that they can augment their own productivity. Every company should augment their own productivity to be more productive, so that they can have more prosperity, hire more people.

I think jobs will change. My guess is that we’ll actually have higher employment, we’ll create more jobs. I think industries will be more productive. Many of the industries that are currently suffering from lack of labor, workforce is likely to use AI to get themselves off their feet and get back to growth and prosperity. I see it a little bit differently, but I do think that jobs will be affected, and I’d encourage everybody just to learn AI…

…David: Well, and that being our final question for you. It’s 2023, 30 years anniversary of the founding of Nvidia. If you were magically 30 years old again today in 2023, and you were going to Denny’s with your two best friends who are the two smartest people you know, and you’re talking about starting a company, what are you talking about starting?

Jensen: I wouldn’t do it. I know. The reason for that is really quite simple. Ignoring the company that we would start, first of all, I’m not exactly sure. The reason why I wouldn’t do it, and it goes back to why it’s so hard, is building a company and building Nvidia turned out to have been a million times harder than I expected it to be, any of us expected it to be.

At that time, if we realized the pain and suffering, just how vulnerable you’re going to feel, and the challenges that you’re going to endure, the embarrassment and the shame, and the list of all the things that go wrong, I don’t think anybody would start a company. Nobody in their right mind would do it.

I think that that’s the superpower of an entrepreneur. They don’t know how hard it is, and they only ask themselves how hard can it be? To this day, I trick my brain into thinking, how hard can it be? Because you have to.

Ben: Still, when you wake up in the morning.

Jensen: Yup. How hard can it be? Everything that we’re doing, how hard can it be? Omniverse, how hard can it be?

David: I don’t get the sense that you’re planning to retire anytime soon, though. You could choose to say like, whoa, this is too hard.

Ben: The trick is still working.

David: Yeah, the trick is still working.

… Jensen: Yeah. The thing to keep in mind is, at all times what is the market opportunity that you’re engaging in? That informs your size. I was told a long time ago that Nvidia can never be larger than a billion dollars. Obviously, it’s an underestimation, under imagination of the size of the opportunity. It is the case that no chip company can ever be so big. But if you’re not a chip company, then why does that apply to you?

This is the extraordinary thing about technology right now. Technology is a tool and it’s only so large. What’s unique about our current circumstance today is that we’re in the manufacturing of intelligence. We’re in the manufacturing of work world. That’s AI. The world of tasks doing work—productive, generative AI work, generative intelligent work—that market size is enormous. It’s measured in trillions.

One way to think about that is if you built a chip for a car, how many cars are there and how many chips would they consume? That’s one way to think about that. However, if you build a system that, whenever needed, assisted in the driving of the car, what’s the value of an autonomous chauffeur every now and then?

Obviously, the problem becomes much larger, the opportunity becomes larger. What would it be like if we were to magically conjure up a chauffeur for everybody who has a car, and how big is that market? Obviously, that’s a much, much larger market.

The technology industry is that what we discovered, what Nvidia has discovered, and what some of the discovered, is that by separating ourselves from being a chip company but building on top of a chip and you’re now an AI company, the market opportunity has grown by probably a thousand times.

Don’t be surprised if technology companies become much larger in the future because what you produce is something very different. That’s the way to think about how large can your opportunity, how large can you be? It has everything to do with the size of the opportunity.

5. The 4 Billion Pieces of Paper Keeping Global Trade Afloat – Archie Hunter

They are relatively easy to fake. Frequently get lost. And can add huge amounts of time to any journey. Yet paper documents still rule in the $25 trillion global cargo trade with four billion of them in circulation at any one time.

It is a system that has barely changed since the nineteenth century. But that dependence on bits of paper being flown from one party to another has become a vulnerability for companies which move and finance the world’s resources around the globe.

In one high profile case, banks including ING Groep NV discovered in 2020 that they had been given falsified bills of lading — shipping documents that designate a cargo’s details and assign ownership — in return for issuing credit to Singapore’s Agritrade Resources. In another dispute, HSBC Holdings Plc and other banks have spent three years in legal wrangling to recover around $3.5 billion from collapsed fuel trader Hin Leong, which is accused by prosecutors of using “forged or fabricated documentation,” when applying for credit.

The International Chamber of Commerce estimates that at least 1% of transactions in the global trade financing market, or around $50 billion per year, are fraudulent. Banks, traders and other parties have lost at least $9 billion through falsified documents in the commodities industry alone over the past decade, according to data compiled by Bloomberg…

…Less than 2% of global trade is transacted via digital means, but that is set to change. Of the world’s top 10 container shipping lines, nine — which account for over 70% of global container freight — have committed to digitizing 50% of their bills of lading within five years, and 100% by 2030. Some of the world’s biggest mining companies including BHP Group Ltd., Rio Tinto Group, Vale SA and Anglo American Plc have voiced their support for a similar campaign in the bulk shipping industry.

The greatest barrier to that expansion has been legal. Banks, traders, insurers and shipping companies have had the means to go digital, but up to now a paper bill of lading has been the only document recognized by English law that gives the holder title ownership to a cargo. A bank or insurer won’t cover a deal that isn’t legally secure, and without financing, deals are unlikely to happen.

To address that, the UK passed the Electronic Trade Documents Act in July which enshrines digital documents with the same legal powers as paper ones. English law on trade documents goes back centuries. It underpins around 90% of global commodities and other trade contracts. So the UK law change represents a big step. Singapore, another center for maritime law, created a similar legal framework in 2021 conducting its first electronic bill of lading transactions in 2022. Similar legislation is expected in France later this year.

The next challenge will be getting companies to change processes that have been in place for hundreds of years. For all its faults, paper is something that everyone understands and while businesses are happy to join a critical mass of digital trade, few are keen to be the first to take steps in that direction…

…For now, when a cargo of coffee is shipped from Brazil to a roaster like Illycaffe SpA in Europe it sets off a flurry of printing. Three identical bills of lading need to be produced and gradually make their way between sellers, banks and buyers, stopping off at law firms and consultants in order to guarantee the rights to the cargo across its 20 day journey. There are also paper invoices, certificates of analysis, and additional documents to measure weight, origin, packing, and moisture content if it is ores that are being shipped.

It is impossible to accurately calculate how many documents are printed for a given trade route but Brazil exports over 900,000 tons of coffee to the European Union every year. And that represents a lot of paper — McKinsey estimated that at least 28,000 trees a year could be saved by reduced friction in the container trade.

As well as providing details of the cargo, its destination and origin, the documents give the holder ownership rights over whatever is being shipped, crucial for holding transport companies accountable for any damages or loss that might occur, or indeed to give banks and insurers some security when providing hundreds of millions of dollars to finance a single shipment…

…The multi-step process begins when an agent prepares the bill of lading and receives sign-off that all the details are correct from the seller, ship owner, trader and end-buyer. The ship is then loaded and original bills of lading are issued by the vessel’s owner and signed by its captain. The three original bills of lading are then released to the seller — in the Brazilian example, the coffee producer — which passes them on to its financing bank along with additional documents to receive payment. The coffee company’s bank will endorse the bill of lading by writing on the back of it.

In many cases a carrier will need to set sail before this process is complete, so the vessel’s captain will provide a shipping agent with a letter of authority to complete the documents on their behalf.

The next leg of the journey for the bill of lading is from the coffee company’s bank to the trading group’s equivalent via DHL Worldwide Express or FedEx Corp. The trader’s bank then makes the payment to the producer’s bank against the receipt of those documents. Assuming everything is okay at this stage the bank working for the trader endorses the bill of lading, signs, stamps, dates and delivers it to its counterpart representing the buyer of the cargo, which in turn pays the trader’s bank for the goods and hands the bill of lading to the master at the destination port to obtain the release of goods.

This pass-the-parcel style approach to the bureaucracy is happening in parallel with the physical goods being loaded, shipped around the world and delivered. Sometimes the documents may only need to move between a small cluster of offices in Geneva or Singapore — where companies across the supply and finance chain have set up offices to be close to one another. But often they are far more tortuous…

…Digital startups like Vakt and ICE Digital Trade offer the opportunity to transfer trade and other financial documents electronically. Bolero has been doing it since the 1990s. Oil majors, such as BP Plc and Shell Plc, traders like Gunvor Group and banks including Société Générale SA have stakes in Vakt, while Intercontinental Exchange bought essDOCS last year for an undisclosed sum, betting that the move online will accelerate.

But the lack of public examples highlights the uphill battle to full adoption of electronic bills of lading. Trafigura used essDOCS for an Australian iron ore shipment back in 2014. Taiwanese shipping line Wan Hai used Bolero’s electronic bill of lading for a polyester filament trade to China in 2018.

This low take-up is largely due to the continued lack of legal recognition in many jurisdictions and banks — which finance the cargoes in transit — but will not accept a digital bill of lading as collateral in most cases. Advocates say the UK law reform should change that.

Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. We currently have a vested interest in Apple, Microsoft, and Netflix. Holdings are subject to change at any time.

What We’re Reading (Week Ending 22 October 2023)

The best articles we’ve read in recent times on a wide range of topics, including investing, business, and the world in general.

We’ve constantly been sharing a list of our recent reads in our weekly emails for The Good Investors.

Do subscribe for our weekly updates through the orange box in the blog (it’s on the side if you’re using a computer, and all the way at the bottom if you’re using mobile) – it’s free!

Here are the articles for the week ending 22 October 2023:

1. Margin of safety: Most important words in investing – Chin Hui Leong

Warren Buffett once said that “margin of safety” has been the bedrock of his investing success for decades. But what do these three words mean?

Let’s use an analogy: imagine you are an engineer and you are tasked to build a bridge that can withstand cars weighing 1,000 kg every day. How strong would you make the bridge? Would it be able to support 1,000 kg or 1,500 kg?

If you chose the first option, you are cutting it close. But if you chose the second option, you have grasped the concept of margin of safety.

In investing, margin of safety is about leaving room for error because you’ll never know what will happen in the future.

For example, think about the pandemic which shook the world three years ago, a rare and unpredictable event that had a huge impact on businesses and industries. Few, if any, could have foreseen or prepared for it. That’s why margin of safety is important; it helps protect your stock portfolio from unexpected risks…

…As a growth investor, I view the concept of margin of safety differently.

For me, the value created by a business is my margin of safety. On the surface, my approach appears to be at odds with the concept of margin of safety. Why place your faith on a business which is inherently filled with uncertainties? Yet, I would argue my approach is easier to apply.

Consider the contrast between value and growth investing.

In a value investing approach, as you have seen earlier, your task is to figure whether a business which ran into trouble is not not doing as badly as it seems. You are compensated, in this case, with a lower stock price. In comparison, when you pick growing businesses which are already doing well, all you have to figure out is whether it can continue doing well in the future. This business puzzle, to me, is easier to solve. Sure, you will pay a higher price at the start as growing businesses rarely sell on a discount. But if done well, the value which builds up over time will compensate you for the risk taken.

To share an example, take Chipotle Mexican Grill (NYSE: CMG), a US-based, fast-casual Mexican food chain.

In 2006, the business was generating less than US$6.3 million in free cash flow (FCF). Today, the food chain churned out US$1.25 billion in FCF over the past 12 months, some 200 times more than its 2006 level. During this period, its share count also declined by 14 per cent. Thus, on a per share basis, the company’s current FCF per share is over 230 times higher than 2006’s FCF per share…

…At the end of 2006, the stock was trading at US$57 or around 295 times its 2006 free cash flow per share, a valuation that cannot be described as cheap.

Fast forward to today: at a share price of around US$1,822, the free cash flow per share multiple has declined to 40.5 times, over 86 per cent lower compared to 2006’s level.

Yet, despite the drastic fall in this multiple, eagle-eyed readers would have noticed that shares today are 32 times higher compared to the end of 2006…

…If you compare the share price at the end of 2006 (US$57) to today’s FCF per share (US$45 per share), you would get a valuation which is less than 1.3 times. This is an extremely low multiple for the stock, giving you plenty of room for error.

And what drove the creation of this margin of safety? That’s right, it was the value of the business, signified by the growth of its FCF per share.

2. The Risks No One Is Talking About – Brian Richards

Generally speaking, risky investments are well-known to be risky, and most market participants have an eyes-wide-open approach to the risks. Perhaps positions are kept smaller, or are hedged, as a buffer. Contrast that with anything deemed “safe”—whether deemed so because of overconfidence, naivete, a low-looking valuation, or a psychological illusion. Its presumed safety can lull investors into a sense of security that prevents appropriate diligence or analysis.

Think about the role of bond ratings in the Great Financial Crisis, when investment-grade ratings were given to paper that turned out not to be investment grade. The U.S. Financial Crisis Inquiry Commission’s published report does not mince words:

We conclude the failures of credit rating agencies were essential cogs in the wheel of financial destruction. The three credit rating agencies were key enablers of the financial meltdown. The mortgage-related securities at the heart of the crisis could not have been marketed and sold without their seal of approval. Investors relied on them, often blindly. In some cases, they were obligated to use them, or regulatory capital standards were hinged on them. This crisis could not have happened without the rating agencies. Their ratings helped the market soar and their downgrades through 2007 and 2008 wreaked havoc across markets and firms….

….As my friend Morgan Housel says:

Asking what the biggest risks are is like asking what you expect to be surprised about. If you knew what the biggest risk was you would do something about it, and doing something about it makes it less risky. What your imagination can’t fathom is the dangerous stuff, and it’s why risk can never be mastered.

It seems to me that managing risk is a process without an end, an art rather than a science. The key, I think, is to be humble about what risks exist (even in so-called safer assets); be upfront about the things you take as granted; to try to be mindful of your own behavioral biases (or the psychological illusions designed to trick your brain); and realize that the true risks are hard to recognize ahead of time. Equities that appear to be “safe”—such as the Nifty 50 in the 1970s, to many eyes—may be among the least safe of all; and those that appear risky may be among the most promising and potentially less risky than average.

3. Freight recession unlike any other in history – Craig Fuller

In 2000, freight brokerage was a cottage industry, representing a small percentage of the trucking industry — 6%. Fast forward to 2023, and freight brokers handle more than 20% of all trucking freight.

As freight brokerages have taken on a larger percentage of the market, they have reshaped the typical freight cycle.

In the early 2000s, it was uncommon to see a freight broker in the primary position of a shipper’s routing guide.

Back then, freight brokers usually handled freight that asset-based carriers didn’t want or that was priced too low for the carriers to make their margins. Freight brokers would also serve as a last resort if carriers had freight surges that they could not handle.

Since then, however, things have changed dramatically. As freight brokerages invested in technology and customer service, they began to offer a more compelling product than their asset-based competitors and took on a greater role in routing guides.

Today, it is common for multiple freight brokerages to be in primary positions in shippers’ routing guides, often as the top choice, beating out their asset-based competitors…

…As of April 2023, there were more than 531,000 active trucking fleets that own or lease at least one tractor in the U.S., according to Carrier Details, which provides trucking authority intelligence using data from the Federal Motor Carrier Safety Administration (FMCSA) and insurance registrations (available on SONAR).

Contrast that with 1980, when there were around 18,000 U.S. trucking companies…

…The current freight cycle has been different. In previous cycles when freight rates have been low, many of the weakest carriers exited the industry. While some of the companies that went out of business in 2019 — the last major down cycle — were quite large, such as Celadon and New England Motor Freight, most were small “mom-and-pop” companies that lacked the resources to stay in business.

In 2023, many people, including me, expected that as before, many small carriers would roll over and quickly exit the freight market as conditions became difficult. After all, we thought, when the freight economy slowed, high-quality loads for small carriers would dry up. It wasn’t just rates, but also load counts that dropped.

FreightWaves’ Rachel Premack reported in an April 28 article that the “number of authorized interstate trucking fleets in the U.S. declined by nearly 9,000 in the first quarter of 2023 …”

So while companies have certainly left the industry, small carriers overall have held on for far longer than many of us expected. The reason is that even as rates have declined — in many cases lower than 2019 rates — freight brokerages have kept many small truckers supplied with quality load opportunities…

…Newton’s law of gravity, a fundamental rule in physics, is commonly cited in commodity markets like trucking.

When capacity tightens and drives up rates, new entrants enter the market, flooding it with capacity and driving down rates.

The same carriers that entered the trucking industry to take advantage of high rates are now being forced to take much lower rates to keep their trucks moving.

In past cycles, when the freight market softened, we would see a massive purge in capacity. While there have been reductions, it has happened much slower than anticipated.

A key reason it has been so slow to churn out capacity is because of the proliferation of freight brokers.

In past down cycles, freight brokers would lose a large percentage of their volume, as shippers kept to a small number of core carriers in their routing guides.

But over the past decade, freight brokerages have positioned themselves in the role as a core carrier, enabling them to maintain load volumes, even in down markets.

So in this down market, most freight brokerages have maintained a high percentage of load volumes, even as rates fall.

The loads may not pay much, but brokers are able to supply carriers with loads that pay just enough to cover the monthly truck bill.

Carriers may be losing money, but that small amount of cash flow will keep them in the game longer than would be otherwise expected…

…According to SONAR‘s Carrier Details Total Trucking Authorities index, from 2010 to August 2020, the trucking industry added an average of 199 new trucking fleets per week.

From August 2020 to September 2022, the number of new trucking fleets exploded by an average of 1,124 new fleets per week.

The trucking market currently has 63,000 more fleets than the 2010-2020 trend line would suggest…

…Unless there is an acceleration in revocations (i.e. trucking companies shuttering their authorities), FreightWaves models suggest the trucking market has 78 weeks to go before capacity is back in balance with historical trends.

4. Where are all the defaults? – Greg Obenshain

A rapidly rising Fed funds rate has historically led to high levels of defaults as weaker borrowers get squeezed between higher borrowing costs and slowing growth. Just looking at the number of Chapter 11 bankruptcy filings, history would appear to be repeating itself in this rate-hiking cycle. Chapter 11 filings have increased even as the economy has thus far appeared to avoid a recession.

Usually, as the bankruptcy rate spikes, the high-yield spread also rises. But so far, the high-yield spread has barely moved.

If we just used bankruptcy rates to predict high-yield spreads, then we’d expect high-yield spreads to be 7.0%, not the 4.4% we see today. It’s not just small companies defaulting. Fourteen of the bankruptcies in 2023 have had over $1 billion of liabilities, including Mallinckrodt, Yellow Corp, Wesco Aircraft, Avaya, and Party City.

One reason we believe high-yield spreads haven’t spiked yet is the migration of lower-quality borrowers—those most likely to default—out of high yield and into the private credit market. According to Moody’s, the number of issuers with B3 debt has fallen as these issuers have departed for private credit. They do not mince words about this: “Ultimately, we believe the growth of the alternative asset managers will contribute to systemic risk. This group of lenders comprise both private equity and private credit segments and lack prudential oversight, as opposed to the highly regulated banking sector.”

The leveraged loan market, which can be thought of as the loan market rated by credit agencies, is now about as big as the high-yield market, at around $1.3 trillion. The private credit market, which can be thought of as the loan market not rated by credit agencies, is much harder to measure but is reported to also be over $1 trillion. And much of that growth has come from riskier borrowers…

…Where loan and bond amounts are available (54 of the 62), Moody’s has tracked $35 billion of loan defaults versus $26 billion of bond defaults. 30 were loan-only capital structures, 12 were bond-only capital structure, and 12 were capital structures with both loans and bonds. Of the 62 defaults listed, 37 were distressed exchanges and 19 of the distressed exchanges were for loan-only capital structures versus 10 for bond-only capital structures. Distressed exchanges, which are debt renegotiations conducted directly with lenders and outside the bankruptcy system, are often not captured by the default statistics and are not counted in the running count of Chapter 11s with which we started the article. This time is different in a way. Defaults are happening. They are just not happening where they used to, and they are happening in a different way (distressed exchanges) than they used to.

This does not mean that all loans are doing poorly. In fact, BKLN, a loan ETF with $4.4 billion of assets has returned 9.1% year to date as it benefits from higher underlying interest on its loans. But that fund holds more than half its funds in BB or BBB rated credit and less than 1% in CCC loans. It is not heavily exposed to the companies in the low single-B rating. That is where the most pain is likely to be. The rating composition of a market matters when considering defaults. And there has been a significant shift of low-rated credits to the private credit markets.

5. Buffett’s World War II Debut – Marcelo Lima

At this year’s Berkshire Hathaway annual meeting, Buffett did something I wish he did more often: he put up some very educational slides. The first showed the front page of the New York Times on Sunday, March 8, 1942, three months after Japan attacked Pearl Harbor. If you think today’s headlines are scary, you’re in for quite a shock…

…Buffett had his sights on Cities Service preferred stock, which was trading at $84 the previous year and had declined to $55 in January. And now, on March 10th, it was selling at $40.

That night, 11-year-old Buffett decided it was a good time to invest. As Buffett recounted, “Despite these headlines, I said to my dad, ‘I think I’d like to pull the trigger, and I’d like you to buy me three shares of Cities Service preferred’ the next day. And that was all I had. I mean, that was my capital accumulated over the previous five years or thereabouts. And so my dad, the next morning, bought three shares.”…

…Buffett successfully top-ticked the market at $38 ¼, with the shares closing at $37 (down 3.3 percent). This, he joked, “was really kind of characteristic of my timing in stocks that was going to appear in future years.”

The world’s greatest-investor-in-training would eventually see the shares called by the Cities Service Company for over $200 per share more than four years later…

… But the story doesn’t have a happy ending…

…From the 38 ¼ Buffett paid, the stock went on to decline to $27 (down nearly 30 percent from his cost!).

What Buffett didn’t say at the annual meeting is that he had enlisted his sister Doris as a partner in the idea of buying the shares. Every day on the way to school, Doris “reminded” him that her stock was down. (This story is recounted in the excellent book Snowball).

After enduring so much pain, he was happy to sell at a profit only a few months later, in July, for $40. “As they always say, ‘It seemed like a good idea at the time,’” Buffett joked.

Despite the ugly headlines, Buffett said everyone at the time knew that America was going to win the war. The incredible economic machine that had started in 1776 would see to it. So imagine, in the middle of this crisis, you had invested $10,000 in the S&P 500. There were no index funds at the time, but you could have bought the equivalent basket of the top 500 American companies.

Once you did that, imagine you never read another newspaper headline, never traded again, never looked at your investments.

How much would you have today? Buffett again: “You’d have $51 million. And you wouldn’t have had to do anything.”

Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. We currently have a vested interest in Chipotle Mexican Grill. Holdings are subject to change at any time.