Insights From Warren Buffett’s 2023 Shareholder’s Letter

There’s much to learn from Warren Buffett’s latest letter, including his thoughts on oil & gas companies and the electric utility industry.

One document I always look forward to reading around this time of the year is Warren Buffett’s annual Berkshire Hathaway shareholder’s letter. Over the weekend, Buffett published the 2023 edition. This letter is especially poignant because Buffett’s long-time right-hand man, the great Charlie Munger, passed away last November. Besides containing a touching eulogy from Buffett to Munger, the letter also had some fascinating insights from Buffett that I wish to document and share. 

Without further ado (emphases are Buffett’s)…

The actions of a wonderful partner 

Charlie never sought to take credit for his role as creator but instead let me take the bows and receive the accolades. In a way his relationship with me was part older brother, part loving father. Even when he knew he was right, he gave me the reins, and when I blundered he never – never –reminded me of my mistake. 

It’s hard to tell a good business from a bad one

Within capitalism, some businesses will flourish for a very long time while others will prove to be sinkholes. It’s harder than you would think to predict which will be the winners and losers. And those who tell you they know the answer are usually either self-delusional or snake-oil salesmen. 

Holding onto a great business – one that can deploy additional capital at high returns – for a long time is a recipe for building a great fortune

At Berkshire, we particularly favor the rare enterprise that can deploy additional capital at high returns in the future. Owning only one of these companies – and simply sitting tight – can deliver wealth almost beyond measure. Even heirs to such a holding can – ugh! – sometimes live a lifetime of leisure…

…You may be thinking that she put all of her money in Berkshire and then simply sat on it. But that’s not true. After starting a family in 1956, Bertie was active financially for 20 years: holding bonds, putting 1⁄3 of her funds in a publicly-held mutual fund and trading stocks with some frequency. Her potential remained unnoticed. 

Then, in 1980, when 46, and independent of any urgings from her brother, Bertie decided to make her move. Retaining only the mutual fund and Berkshire, she made no new trades during the next 43 years. During that period, she became very rich, even after making large philanthropic gifts (think nine figures). 

Berkshire’s size is now a heavy anchor on the company’s future growth rates

This combination of the two necessities I’ve described for acquiring businesses has for long been our goal in purchases and, for a while, we had an abundance of candidates to evaluate. If I missed one – and I missed plenty – another always came along.

Those days are long behind us; size did us in, though increased competition for purchases was also a factor.

Berkshire now has – by far – the largest GAAP net worth recorded by any American business. Record operating income and a strong stock market led to a yearend figure of $561 billion. The total GAAP net worth for the other 499 S&P companies – a who’s who of American business – was $8.9 trillion in 2022. (The 2023 number for the S&P has not yet been tallied but is unlikely to materially exceed $9.5 trillion.) 

By this measure, Berkshire now occupies nearly 6% of the universe in which it operates. Doubling our huge base is simply not possible within, say, a five-year period, particularly because we are highly averse to issuing shares (an act that immediately juices net worth)…

…All in all, we have no possibility of eye-popping performance…

…Our Japanese purchases began on July 4, 2019. Given Berkshire’s present size, building positions through open-market purchases takes a lot of patience and an extended period of “friendly” prices. The process is like turning a battleship. That is an important disadvantage which we did not face in our early days at Berkshire.  

Are there a dearth of large, great businesses outside of the USA? 

There remain only a handful of companies in this country capable of truly moving the needle at Berkshire, and they have been endlessly picked over by us and by others. Some we can value; some we can’t. And, if we can, they have to be attractively priced. Outside the U.S., there are essentially no candidates that are meaningful options for capital deployment at Berkshire.

Markets can occasionally throw up massive bargains because of external shocks

Occasionally, markets and/or the economy will cause stocks and bonds of some large and fundamentally good businesses to be strikingly mispriced. Indeed, markets can – and will – unpredictably seize up or even vanish as they did for four months in 1914 and for a few days in 2001.

Stock market participants today exhibit even more gambling-like behaviour than in the past

Though the stock market is massively larger than it was in our early years, today’s active participants are neither more emotionally stable nor better taught than when I was in school. For whatever reasons, markets now exhibit far more casino-like behavior than they did when I was young. The casino now resides in many homes and daily tempts the occupants.

Stock buybacks are only sensible if they are done at a discount to business-value

All stock repurchases should be price-dependent. What is sensible at a discount to business-value becomes stupid if done at a premium.

Does Occidental Petroleum play a strategic role in the long-term economic security of the USA?

At yearend, Berkshire owned 27.8% of Occidental Petroleum’s common shares and also owned warrants that, for more than five years, give us the option to materially increase our ownership at a fixed price. Though we very much like our ownership, as well as the option, Berkshire has no interest in purchasing or managing Occidental. We particularly like its vast oil and gas holdings in the United States, as well as its leadership in carbon-capture initiatives, though the economic feasibility of this technique has yet to be proven. Both of these activities are very much in our country’s interest.

Not so long ago, the U.S. was woefully dependent on foreign oil, and carbon capture had no meaningful constituency. Indeed, in 1975, U.S. production was eight million barrels of oil-equivalent per day (“BOEPD”), a level far short of the country’s needs. From the favorable energy position that facilitated the U.S. mobilization in World War II, the country had retreated to become heavily dependent on foreign – potentially unstable – suppliers. Further declines in oil production were predicted along with future increases in usage. 

For a long time, the pessimism appeared to be correct, with production falling to five million BOEPD by 2007. Meanwhile, the U.S. government created a Strategic Petroleum Reserve (“SPR”) in 1975 to alleviate – though not come close to eliminating – this erosion of American self-sufficiency.

And then – Hallelujah! – shale economics became feasible in 2011, and our energy dependency ended. Now, U.S. production is more than 13 million BOEPD, and OPEC no longer has the upper hand. Occidental itself has annual U.S. oil production that each year comes close to matching the entire inventory of the SPR. Our country would be very – very – nervous today if domestic production had remained at five million BOEPD, and it found itself hugely dependent on non-U.S. sources. At that level, the SPR would have been emptied within months if foreign oil became unavailable.

Under Vicki Hollub’s leadership, Occidental is doing the right things for both its country and its owners. 

Nobody knows what the price of oil would do in the short-term and the long-term

No one knows what oil prices will do over the next month, year, or decade.

Nobody can predict the movement of major currencies

Neither Greg nor I believe we can forecast market prices of major currencies. We also don’t believe we can hire anyone with this ability. Therefore, Berkshire has financed most of its Japanese position with the proceeds from ¥1.3 trillion of bonds.

Rail is a very cost-efficient way to move products around America, and railroads should continue to be an important asset for the USA for a long time to come

Rail is essential to America’s economic future. It is clearly the most efficient way – measured by cost, fuel usage and carbon intensity – of moving heavy materials to distant destinations. Trucking wins for short hauls, but many goods that Americans need must travel to customers many hundreds or even several thousands of miles away…

…A century from now, BNSF will continue to be a major asset of the country and of Berkshire. You can count on that.

Railroad companies gobble up capital, such that its owners have to spend way more on annual maintenance capital expenditure than depreciation – but this trait allowed Berkshire to acquire BNSF for far less than its replacement value

BNSF is the largest of six major rail systems that blanket North America. Our railroad carries its 23,759 miles of main track, 99 tunnels, 13,495 bridges, 7,521 locomotives and assorted other fixed assets at $70 billion on its balance sheet. But my guess is that it would cost at least $500 billion to replicate those assets and decades to complete the job.

BNSF must annually spend more than its depreciation charge to simply maintain its present level of business. This reality is bad for owners, whatever the industry in which they have invested, but it is particularly disadvantageous in capital-intensive industries.

At BNSF, the outlays in excess of GAAP depreciation charges since our purchase 14 years ago have totaled a staggering $22 billion or more than $11⁄2 billion annually. Ouch! That sort of gap means BNSF dividends paid to Berkshire, its owner, will regularly fall considerably short of BNSF’s reported earnings unless we regularly increase the railroad’s debt. And that we do not intend to do.

Consequently, Berkshire is receiving an acceptable return on its purchase price, though less than it might appear, and also a pittance on the replacement value of the property. That’s no surprise to me or Berkshire’s board of directors. It explains why we could buy BNSF in 2010 at a small fraction of its replacement value.

Railroad companies are having trouble with hiring because of tough working conditions

An evolving problem is that a growing percentage of Americans are not looking for the difficult, and often lonely, employment conditions inherent in some rail operations. Engineers must deal with the fact that among an American population of 335 million, some forlorn or mentally-disturbed Americans are going to elect suicide by lying in front of a 100-car, extraordinarily heavy train that can’t be stopped in less than a mile or more. Would you like to be the helpless engineer? This trauma happens about once a day in North America; it is far more common in Europe and will always be with us.

American railroad companies are at times at the mercy of the US government when it comes to employees’ wages, and they are also required to carry products they would rather not

Wage negotiations in the rail industry can end up in the hands of the President and Congress. Additionally, American railroads are required to carry many dangerous products every day that the industry would much rather avoid. The words “common carrier” define railroad responsibilities.

Last year BNSF’s earnings declined more than I expected, as revenues fell. Though fuel costs also fell, wage increases, promulgated in Washington, were far beyond the country’s inflation goals. This differential may recur in future negotiations.

Has the electric utility industry in the USA become uninvestable because of a change in the authorities’ stance toward electric utilities?

For more than a century, electric utilities raised huge sums to finance their growth through a state-by-state promise of a fixed return on equity (sometimes with a small bonus for superior performance). With this approach, massive investments were made for capacity that would likely be required a few years down the road. That forward-looking regulation reflected the reality that utilities build generating and transmission assets that often take many years to construct. BHE’s extensive multi-state transmission project in the West was initiated in 2006 and remains some years from completion. Eventually, it will serve 10 states comprising 30% of the acreage in the continental United States. 

With this model employed by both private and public-power systems, the lights stayed on, even if population growth or industrial demand exceeded expectations. The “margin of safety” approach seemed sensible to regulators, investors and the public. Now, the fixed-but-satisfactoryreturn pact has been broken in a few states, and investors are becoming apprehensive that such ruptures may spread. Climate change adds to their worries. Underground transmission may be required but who, a few decades ago, wanted to pay the staggering costs for such construction?

At Berkshire, we have made a best estimate for the amount of losses that have occurred. These costs arose from forest fires, whose frequency and intensity have increased – and will likely continue to increase – if convective storms become more frequent.

It will be many years until we know the final tally from BHE’s forest-fire losses and can intelligently make decisions about the desirability of future investments in vulnerable western states. It remains to be seen whether the regulatory environment will change elsewhere.

Other electric utilities may face survival problems resembling those of Pacific Gas and Electric and Hawaiian Electric. A confiscatory resolution of our present problems would obviously be a negative for BHE, but both that company and Berkshire itself are structured to survive negative surprises. We regularly get these in our insurance business, where our basic product is risk assumption, and they will occur elsewhere. Berkshire can sustain financial surprises but we will not knowingly throw good money after bad.

Whatever the case at Berkshire, the final result for the utility industry may be ominous: Certain utilities might no longer attract the savings of American citizens and will be forced to adopt the public-power model. Nebraska made this choice in the 1930s and there are many public-power operations throughout the country. Eventually, voters, taxpayers and users will decide which model they prefer. 

When the dust settles, America’s power needs and the consequent capital expenditure will be staggering. I did not anticipate or even consider the adverse developments in regulatory returns and, along with Berkshire’s two partners at BHE, I made a costly mistake in not doing so. 


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. I currently have no vested interest in any company mentioned. Holdings are subject to change at any time.

Shorting Stocks Is Hard, Really Hard

It’s far easier to recognise poor underlying business fundamentals in a stock and simply avoid investing in it.

In investing parlance, to “short a stock” is to make an investment with the view that a stock’s price will decline. On the surface, shorting seems like a fairly easy thing to do for an investor who has skill in “going long”, which is to invest with the view that a stock’s price will rise – you just have to do the opposite of what’s working.

But if you peer beneath the hood, shorting can be a really difficult way to invest in the stock market. Nearly four years ago in April 2020, I wrote Why It’s So Difficult To Short Stocks, where I used the story of Luckin Coffee to illustrate just how gnarly shorting stocks can be:

In one of our gatherings in June 2019, a well-respected member and deeply accomplished investor in the club gave a presentation on Luckin Coffee (NASDAQ: LK)…

…At the time of my club mate’s presentation, Luckin’s share price was around US$20, roughly the same level from the close of its IPO in May 2019. He sold his Luckin shares in January 2020, around the time when Luckin’s share price peaked at US$50. Today, Luckin’s share price is around US$4. The coffee chain’s share price tanked by 76% from US$26 in one day on 2 April 2020 and continued falling before stock exchange operator NASDAQ ordered a trading halt for Luckin shares…

…The wheels came off the bus only on 2 April 2020. On that day, Luckin announced that the company’s board of directors is conducting an internal investigation. There are fraudulent transactions – occurring from the second quarter of 2019 to the fourth quarter of 2019 – that are believed to amount to RMB 2.2 billion (around US$300 million). For perspective, Luckin’s reported revenue for the 12 months ended 30 September 2019 was US$470 million, according to Ycharts. The exact extent of the fraudulent transactions has yet to be finalised. 

Luckin also said that investors can no longer rely on its previous financial statements for the nine months ended 30 September 2019. The company’s chief operating officer, Liu Jian, was named as the primary culprit for the misconduct. He has been suspended from his role…

…it turns out that fraudulent transactions at Luckin could have happened as early as April 2019. From 1 April 2019 to 31 January 2020, Luckin’s share price actually increased by 59%. At one point, it was even up by nearly 150%.

If you had shorted Luckin’s shares back in April 2019, you would have faced a massive loss – more than what you had put in – even if you had been right on Luckin committing fraud. This shows how tough it is to short stocks. Not only must your analysis on the fundamentals of the business be right, but your timing must also be right because you could easily lose more than you have if you’re shorting. 

Recent developments at a company named Herbalife (NYSE: HLF) present another similar illustration of the onerous task of shorting. High-profile investor Bill Ackman first disclosed that he was short Herbalife in December 2012. Back then, the company was a “global network marketing company that sells weight management, nutritional supplement, energy, sports & fitness products and personal care products” in 79 countries, according to its 2011 annual report. Today, Herbalife is a “global nutrition company that provides health and wellness products to consumers in 95 markets,” based on a description given in its 2023 annual report. So the company has been in pretty much the same line of business over this span of time.

Ackman’s short-thesis centred on his view that Herbalife was a company running an illegal pyramid scheme, and so the business model was simply not sustainable. When Ackman announced that he was short Herbalife’s shares, the company was reporting consistent and strong growth in its business. From 2006 to 2011, Herbalife’s revenue compounded at an annualised rate of 13% from US$1.9 billion to US$3.5 billion while its profit grew from US$143 million to US$415 million, representing a compounded annual growth rate of 24%.

Although Herbalife has to-date never officially been found to be operating an illegal pyramid scheme, its business results since Ackman came public with his short has been poor. The table below shows Herbalife’s revenue, net income, and net income margins from 2011 to 2023. What’s notable is the clear downward trend in both Herbalife’s net income and net income margin in that time frame. 

Source: Tikr

According to a Bloomberg article published at the end of February 2018, Ackman had effectively ended his short position on Herbalife by the time the piece came to print. I think most investors who are made to guess Ackman’s returns from his Herbalife short by looking only at the trajectory of the company’s financials from 2011 to 2017 would have noted the stark deterioration – the company’s net income declined by nearly 40% and its net income margin shrank from 12.0% to 4.8% – and conclude that Ackman had probably made a decent gain. 

But the stock market had other ideas. Herbalife’s stock price closed at US$23.16 on the day just prior to Ackman’s first public declaration of his short position. It closed at US$46.05 – a double from US$23.16 – when the aforementioned Bloomberg article was published. From December 2012 to today, the highest close for Herbalife’s stock price was US$61.47, which was reached on 4 February 2019. Right now, Herbalife’s stock price is at US$8.07. This comes after Herbalife’s stock price fell by 32% to US$8.03 on 15 February 2024 after the company reported its 2023 fourth-quarter results. Following the sharp decline, Ackman proclaimed on X (previously known as Twitter) that “it is a very good day for my psychological short on Herbalife.” 

The market eventually reflected the deterioration in Herbalife’s fundamentals, but the interim journey was a wild ride. In a similar manner to Luckin’ Coffee (and borrowing the prose from the last paragraph of the excerpts above from Why It’s So Difficult To Short Stocks), if you had shorted Herbalife’s shares back in December 2012 and held onto the position till now, you would have faced a massive loss in the interim – more than what you had put in – even if you were right on Herbalife’s collapsing fundamentals and eventual stock price decline.  

The investing sage Philip Fisher once wrote that “it is often easier to tell what will happen to the price of a stock than how much time will elapse before it happens.” This explains why shorting stocks is hard – really hard. To be successful at shorting, you need to correctly read both the stock’s underlying business fundamentals and the timing of the stock’s price movement. In contrast, it’s far easier to recognise poor underlying business fundamentals in a stock and simply avoid investing in it.


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. I currently have no vested interest in any company mentioned. Holdings are subject to change at any time.

How Innovation Happens

Innovation can appear from the most unexpected places, take unpredictable paths, or occur when supporting technologies improve over time.

There are a myriad of important political, social, economic, and healthcare issues that are plaguing our globe today. But Jeremy and I are still long-term optimistic on the stock market.

This is because we still see so much potential in humanity. There are nearly 8.1 billion individuals in the world right now, and the vast majority of people will wake up every morning wanting to improve the world and their own lot in life. This – the desire for progress – is ultimately what fuels the global economy and financial markets. Miscreants and Mother Nature will occasionally wreak havoc but we have faith that humanity can clean it up. To us, investing in stocks is ultimately the same as having faith in the long-term ingenuity of humanity. We will remain long-term optimistic on stocks so long as we continue to have this faith.

There may be times in the future when it seems that mankind’s collective ability to innovate is faltering (things are booming now with the AI rush). But here are three stories I learnt recently that would help me – and I hope you, too – keep the faith.

The first story is from Morgan Housel’s latest book Same As Ever. In it, he wrote: 

“Author Safi Bahcall notes that Polaroid film was discovered when sick dogs that were fed quinine to treat parasites showed an unusual type of crystal in their urine. Those crystals turned out to be the best polarizers ever discovered. Who predicts that? Who sees that coming? Nobody. Absolutely nobody.”

What the quinine and polarizers story shows is that the root of innovative ideas can show up completely unexpectedly. This brings me to the second story, which is also from Same As Ever. This time, it is Housel’s recounting of how the invention of planes moved in an unpredictable path that led to the invention of nuclear power plants (nuclear power is a zero-emission, clean energy source, so it could play a really important role in society’s sustainable energy efforts), and how a 1960s invention linking computers to manage Cold War secrets unpredictably led to the photo-sharing social app Instagram:

“When the airplane came into practical use in the early 1900s, one of the first tasks was trying to foresee what benefits would come from it. A few obvious ones were mail delivery and sky racing.

No one predicted nuclear power plants. But they wouldn’t have been possible without the plane. Without the plane we wouldn’t have had the aerial bomb. Without the aerial bomb we wouldn’t have had the nuclear bomb. And without the nuclear bomb we wouldn’t have discovered the peaceful use of nuclear power. Same thing today. Google Maps, TurboTax, and Instagram wouldn’t be possible without ARPANET, a 1960s Department of Defense project linking computers to manage Cold War secrets, which became the foundation for the internet. That’s how you go from the threat of nuclear war to filing your taxes from your couch—a link that was unthinkable fifty years ago, but there it is.”

This idea of one innovation leading to another, brings me to my third story. There was a breakthrough in the healthcare industry in November 2023 when the UK’s health regulator approved a drug named Casgevy – developed by CRISPR Therapeutics and Vertex Pharmaceuticals – for the treatment of blood disorders known as sickle cell disease and  beta thalassaemia. Casgevy’s greenlight is groundbreaking because it is the first drug in the world to be approved that is based on the CRISPR (clustered regularly interspaced short palindromic repeats) gene editing technique. A few weeks after the UK’s decision, Casgevy became the first gene-editing treatment available in the USA for sickle cell disease (the use of Casgevy for beta thalassaemia in the USA is currently still being studied). Casgevy is a huge upgrade for sickle cell patients over the current way the condition is managed. Here’s Sarah Zhang, writing at The Atlantic in November 2023:

When Victoria Gray was still a baby, she started howling so inconsolably during a bath that she was rushed to the emergency room. The diagnosis was sickle-cell disease, a genetic condition that causes bouts of excruciating pain—“worse than a broken leg, worse than childbirth,” one doctor told me. Like lightning crackling in her body is how Gray, now 38, has described the pain. For most of her life, she lived in fear that it could strike at any moment, forcing her to drop everything to rush, once again, to the hospital.

After a particularly long and debilitating hospitalization in college, Gray was so weak that she had to relearn how to stand, how to use a spoon. She dropped out of school. She gave up on her dream of becoming a nurse.

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.” 

The manufacturing technologies behind Casgevy include electroporation, where an electric field is used to increase the permeability of a cell’s membrane. This enables molecules, such as genetic material and proteins, to be introduced in a cell for the purposes of gene editing. According to an expert-call on electroporation that I reviewed, the technology has been around for over four decades, but only started gaining steam in recent years with the decline in genetic sequencing costs; without affordable genetic sequencing, it was expensive to know if a gene editing process done via electroporation was successful. The relentless work of Illumina has played a huge role in lowering genetic sequencing costs over time.

These show how one innovation (cheaper genetic sequencing) supported another in a related field (the viability of electroporation) that then enabled yet another in a related field (the creation of gene editing therapies).    

The three stories I just shared highlight the different ways that innovation can happen. It can appear from the most unexpected places (quinine and polarizers); it can take unpredictable paths (from planes to nuclear power plants); and it can occur when supporting technologies improve over time (the development of Casgevy). What they signify is that we shouldn’t lose hope in mankind’s creative prowess when it appears that nothing new of significance has been built for a while. Sometimes, what’s needed is just time


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.  I currently have no vested interest in any company mentioned. Holdings are subject to change at any time.

An Attempt To Expand Our Circle of Competence

We tried to expand the limits of our investing knowledge.

Jeremy and I have not invested in an oil & gas company for years. The reason can be traced to the very first stocks I bought when I started investing. Back then, in October 2010, I bought six US-listed stocks at one go, two of which were Atwood Oceanics and National Oilwell Varco (or NOV). Atwood was an owner of oil rigs while NOV supplied parts and equipment that kept oil rigs running. 

I invested in them because I wanted to be diversified according to sectors. I thought that oil & gas was a sector that was worth investing in since the demand for oil would likely remain strong for a long time. My view on the demand for oil was right, but the investments still went awry. By the time I sold Atwood and NOV in September 2016 and June 2017, respectively, their stock prices were down by 77% and 31% from my initial investments. 

It turned out that while global demand for oil did indeed grow from 2010 to 2016 – the consumption of oil increased from 86.5 million barrels per day to 94.2 million barrels – oil prices still fell significantly over the same period, from around US$80 per barrel to around US$50. I was not able to predict prices for oil and I had completely missed out on the important fact that these prices would have an outsized impact on the business fortunes of both Atwood and NOV.

In its fiscal year ended 30 September 2010 (FY2010), Atwood’s revenue and net income were US$650 million and US$257 million, respectively. By FY2016, Atwood’s revenue had increased to US$1.0 billion, but its net income barely budged, coming in at US$265 million. Importantly, its return on equity fell from 21% to 9% in that period while its balance sheet worsened dramatically. For perspective, Atwood’s net debt (total debt minus cash and equivalents) ballooned from US$49 million in FY2010 to US$1.1 billion in FY2016.

As for NOV, from 2010 to 2016, its revenue fell from US$12.2 billion to US$7.2 billion and its net income collapsed from US$1.7 billion to a loss of US$2.4 billion. This experience taught me to be wary of companies whose business results have strong links to commodity prices, since I had no ability to foretell their movements. 

Fast forward to the launch of the investment fund that Jeremy and I run in July 2020, and I was clear that I still had no ability to divine oil prices – and neither did Jeremy. Said another way, we were fully aware that companies related to the oil & gas industry were beyond our circle of competence. Then 2022 rolled around and during the month of August, we came across a US-listed oil & gas company named Unit Corporation. 

At the time, Unit had three segments that spanned the oil & gas industry’s value chain: Oil and Natural Gas; Mid-Stream, and Contract Drilling. In the Oil and Natural Gas segment, Unit owned oil and natural gas fields in the USA – most of which were in the Anadarko Basin in the Oklahoma region – and was producing these natural resources. The Mid-Stream segment consisted of Unit’s 50% ownership of Superior Pipeline Company, which gathers, processes, and treats natural gas, and owns more than 3,800 miles of gas pipelines (a private equity firm, Partners Group, controlled the other 50% stake). The last segment, Contract Drilling, is where Unit owned 21 available-for-use rigs for the drilling of oil and gas.

When we first heard of Unit in August 2022, it had a stock price of around US$60, a market capitalisation of just over US$560 million, and an enterprise value (market capitalisation minus net-cash) of around US$470 million (Unit’s net-cash was US$88 million back then). But the company’s intrinsic value could be a lot higher. 

In January 2022, Unit launched a sales process for its entire Oil and Natural Gas segment, pegging the segment’s proven, developed, and producing reserves at a value of US$765 million. This US$765 million value came from the estimated future cash flows of the segment – based on oil prices we believe were around US$80 per barrel – discounted back to the present at 10% per year. Unit ended the sales process for the Oil and Natural Gas segment in June 2022 after selling only a small portion of its assets for US$45 million. Nonetheless, when we first knew Unit, the Oil and Natural Gas segment probably still had a value that was in the neighbourhood of the company’s estimation during the sales process, since oil prices were over US$80 per barrel in August 2022. Meanwhile, we also saw some estimates in the same month that it would cost at least US$400 million for someone to build the entire fleet of rigs that were in the Contract Drilling segment. As for the Mid-Stream segment, due to Superior Pipeline’s ownership structure and the cash flows it was producing, the value that accrued to Unit was not significant*.

So here’s what we saw in Unit in August 2022 after putting everything together: The value of the company’s Oil and Natural Gas and Contract-Drilling segments (around US$765 million and US$400 million, respectively) dwarfed its enterprise value of US$470 million.

But there was a catch. The estimated intrinsic values of Unit’s two important segments Oil and Natural Gas, and Contract Drilling – were based on oil prices in the months leading up to August 2022. This led Jeremy and I to attempt to expand our circle of competence: We wanted to better understand the drivers for oil prices. There were other motivations. First, Warren Buffett was investing tens of billions of dollars in the shares of oil & gas companies such as Occidental Petroleum and Chevron in the first half of 2022. Second, we also came across articles and podcasts from oil & gas investors discussing the supply-and-demand dynamics in the oil market that could lead to sustained high prices for the energy commodity. So, we started digging into the history of oil prices and what influences it.

Here’s a brief history on major declines in the price of WTI Crude over the past four decades:

  • 1980 – 1986: From around US$30 to US$10
  • 1990 – 1994: From around US$40 to less than US$14
  • 2008 – 2009: From around US$140 to around US$40
  • 2014 – 2016: From around US$110 to less than US$33
  • 2020: From around US$60 to -US$37 

Since oil is a commodity, it would be logical to think that differences in the level of oil’s supply-and-demand would heavily affect its price movement – when demand is lower than supply, prices would crash, and vice versa. The UK-headquartered BP, one of the largest oil-producing companies in the world, has a dataset on historical oil production and consumption going back to 1965. BP’s data is plotted in Figure 1 below and it shows that from 1981 onwards, the demand for oil (consumption) was higher than the supply of oil (production) in every year. What this means is the price of oil has surprisingly experienced at least five major crashes over the past four decades despite its demand being higher than supply over the entire period

Figure 1; Source: BP

We shared our unexpected findings with our network of investor friends, which included Vision Capital’s Eugene Ng. He was intrigued and noticed that the U.S. Energy Information Administration (EIA) maintained its own database for long-term global oil consumption and production. After obtaining similar results from EIA’s data compared to what we got from BP, Eugene asked the EIA how it was possible for oil consumption to outweigh production for decades. The EIA responded and Eugene kindly shared the answers with us. It turns out that there could be errors within EIA’s data. The possible sources of errors come from incomplete accounting of Transfers and Backflows in oil balances: 

  • Transfers include the direct and indirect conversion of coal and natural gas to petroleum.
  • Backflows refer to double-counting of oil-streams in consumption. Backflows can happen if the data collection process does not properly account for recycled streams.

The EIA also gave an example of how a backflow could happen with the fuel additive, MTBE, or methyl tert-butyl ether (quote is lightly edited for clarity):

“The fuel additive MTBE is an useful example of both, as its most common feedstocks are methanol (usually from a non-petroleum fossil source) and Iso-Butylene whose feedstock likely comes from feed that has already been accounted for as butane (or iso-butane) consumption. MTBE adds a further complexity in that it is often exported as a chemical and thus not tracked in the petroleum trade balance.”

Thanks to the EIA, we realised that BP’s historical data on the demand and supply of oil might contain errors and how they could have happened. But despite knowing this, Jeremy and I still could not tell what the actual demand-and-supply dynamics of oil were during the five major price crashes that happened from the 1980s to today**. We tried expanding our circle of competence to creep into the oil & gas industry, but were stopped in our tracks. As a result, we decided to pass on investing in Unit. 

I hope that my sharing of how Jeremy and I attempted to enlarge our circle of competence would provide any of you reading this ideas on how you can improve your own investing process. 

*In April 2018, Unit sold a 50% stake in Superior Pipeline to entities controlled by Partners Group – that’s how Partners Group’s aforementioned 50% control came about. When we first studied Unit in August 2022, either Unit or Partners Group could initiate a process after April 2023 to liquidate Superior Pipeline or sell it to a third-party. If a liquidation or sale of Superior Pipeline were to happen, Partners Group would be entitled to an annualised return of 7% on its initial investment of US$300 million before Unit could receive any proceeds; as of 30 June 2022, a sum of US$354 million was required for Partners Group to achieve its return-goal. In the first half of 2022, the cash flow generated by Superior Pipeline was US$24 million, which meant that Unit’s Mid-stream segment was on track to generate around US$50 million in cash flow for the whole of 2022. We figured that a sale of Superior Pipeline in April 2023, with around US$50 million in 2022 cash flow, would probably fetch a total amount that was in the neighbourhood of the US$354 million mentioned earlier that Partners Group was entitled to. So if Superior Pipeline was sold, there would not be much proceeds left for Unit after Partners Group has its piece. 

**If you’re reading this and happen to have insight on the actual historical levels of production and consumption of oil during the past crashes, we would deeply appreciate it if you could get in touch with us. Thanks in advance!


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.  I currently have no vested interest in any company mentioned. Holdings are subject to change at any time.

What The USA’s Largest Bank Thinks About The State Of The Country’s Economy In Q4 2023

Insights from JPMorgan Chase’s management on the health of American consumers and businesses in the fourth quarter of 2023.

JPMorgan Chase (NYSE: JPM) is currently the largest bank in the USA by total assets. Because of this status, JPMorgan is naturally able to feel the pulse of the country’s economy. The bank’s latest earnings conference call – for the fourth quarter of 2023 – was held two weeks ago and contained useful insights on the state of American consumers and businesses. The bottom-line is this: The US economy remains resilient, but there are significant risks that are causing JPMorgan’s management team to be cautious.  

What’s shown between the two horizontal lines below are quotes from JPMorgan’s management team that I picked up from the call.


1. The US economy and consumer remains resilient, and management’s base case is that consumer credit remains strong, although loan losses (a.k.a net charge-off rate) for credit cards is expected to be “<3.5%” in 2024 compared to around 2.5% for 2023

The U.S. economy continues to be resilient, with consumers still spending, and markets currently expect a soft landing…

…We continue to expect the 2024 card net charge-off rate to be below 3.5%, consistent with Investor Day guidance…

…In terms of consumer resilience, I made some comments about this on the press call. The way we see it, the consumers find all of the relevant metrics are now effectively normalized. And the question really in light of the fact that cash buffers are now also normal, but that, that means that consumers have been spending more than they’re taking in is how that spending behavior adjusts as we go into the new year, in a world where cash buffers are less comfortable than they were. So one can speculate about different trajectories that, that could take, but I do think it’s important to take a step back and remind ourselves that consistent with that soft landing view, just in the central case modeling, obviously, we always worry about the tail scenarios is a very strong labor market. And a very strong labor market means, all else equal, strong consumer credit. So that’s how we see the world.

2.  Management thinks that inflation and interest rates may be higher than markets expect…

It is important to note that the economy is being fueled by large amounts of government deficit spending and past stimulus. There is also an ongoing need for increased spending due to the green economy, the restructuring of global supply chains, higher military spending and rising healthcare costs. This may lead inflation to be stickier and rates to be higher than markets expect.

3. …and they’re also cautious given the multitude of risks they see on the horizon

On top of this, there are a number of downside risks to watch. Quantitative tightening is draining over $900 billion of liquidity from the system annually, and we have never seen a full cycle of tightening. And the ongoing wars in Ukraine and the Middle East have the potential to disrupt energy and food markets, migration, and military and economic relationships, in addition to their dreadful human cost. These significant and somewhat unprecedented forces cause us to remain cautious.

4. Management is seeing a deterioration in the value of commercial real estate

The net reserve build was primarily driven by loan growth in card and the deterioration in the outlook related to commercial real estate valuations in the commercial bank.

5. Auto loan growth was strong

And in auto, originations were $9.9 billion, up 32% as we gained market share, while retaining strong margins.

6. Overall capital markets activity is picking up, but merger & acquisition (M&A) activity still remains weak…

We are starting the year with a healthy pipeline, and we are encouraged by the level of capital markets activity, but announced M&A remains a headwind and the extent as well as the timing of capital markets normalization remains uncertain…

…Gross Investment Banking and Markets revenue of $924 million was up 32% year-on-year primarily reflecting increased capital markets and M&A activity…

…So as you know, all else equal, this more dovish rate environment is, of course, supportive for capital markets. So if you go into the details a little bit, if you start with ECM [Equity Capital Markets], that helps higher — and the recent rally in the equity markets helps. I think there have been some modest challenges with the 2023 IPO vintage in terms of post-launch performance or whatever. So that’s a little bit of a headwind at the margin in terms of converting the pipeline, but I’m not too concerned about that in general. So I would expect to see rebound there. In DCM [Debt Capital Markets], again all else equal, lower rates are clearly supportive. One of the nuances there is the distinction between the absolute level of rates and the rate of change. So sometimes you see corporates seeing and expecting lower rates and, therefore, waiting to refinance in the hope of even lower rates. So that can go both ways. And then M&A, it’s a slightly different dynamic. I think there’s a couple of nuances there. One, as you obviously know, announced volume was lower this year. So that will be a headwind in reported revenues in 2024, all else equal. And of course, we are in an environment of M&A regulatory headwinds, as has been heavily discussed. But having said that, I think we’re seeing a bit of pickup in deal flow, and I would expect the environment to be a bit more supportive. 

7. …and appetite for loans among businesses is muted

C&I loans were down 2%, reflecting lower revolver utilization and muted demand for new loans as clients remain cautious…

…We expect strong loan growth in card to continue but not at the same pace as 2023. Still, this should help offset some of the impact of lower rates. Outside of card, loan growth will likely remain muted. 

8. Management is not seeing any changes to their macro outlook for the US economy

So the weighted average unemployment rate and the number is still 5.5%. We didn’t have any really big revisions in the macro outlook driving the numbers, and our skew remains as it has been, a little bit skewed to the downside. 

9. Management’s outlook for 2024 includes six rate-cuts by the Fed, but that outlook comes from financial market data, and not from management’s insights

[Question] Coming back to your outlook and forecast for net interest income for the upcoming year with the 6 Fed fund rate cuts that you guys are assuming. Can you give us a little insight why you’re assuming 6 cuts? 

[Answer] I wish the answer were more interesting, but it’s just our practice. We just always use the forward curve for our outlook, and that’s what’s in there.


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. I don’t have a vested interest in any company mentioned. Holdings are subject to change at any time.

The Everlasting Things In Human Affairs

Knowing the things that are stable over time can be incredibly useful in all areas of life.

Morgan Housel is one of my favourite writers in finance. In November 2023, he published his second book, Same as Ever: A Guide to What Never Changes. As the title suggests, the book is about mankind’s behavioural patterns and ways of thinking that do not seem to change over time.

Jeff Bezos, Amazon’s founder, once said: 

“I very frequently get the question: “What’s going to change in the next 10 years?” And that is a very interesting question; it’s a very common one. I almost never get the 14 question: “What’s not going to change in the next 10 years?” And I submit to you that that second question is actually the more important of the two — because you can build a business strategy around the things that are stable in time. … [I]n our retail business, we know that customers want low prices, and I know that’s going to be true 10 years from now. They want fast delivery; they want vast selection.”

Similarly, I believe that knowing the things that are stable over time can be incredibly useful in all areas of life – business, investing, relationships, and more. While reading Same as Ever, I made notes of the striking things I learnt from the book. I thought it would be useful to share this with a wider audience, so here they are:

The USA could have lost the Revolutionary War to Britain were it not for something as capricious as the wind

The Battle of Long Island was a disaster for George Washington’s army. His ten thousand troops were crushed by the British and its four-hundred-ship fleet. But it could have been so much worse. It could have been the end of the Revolutionary War. All the British had to do was sail up the East River and Washington’s cornered troops would have been wiped out. But it never happened, because the wind wasn’t blowing in the right direction and sailing up the river became impossible.

Historian David McCullough once told interviewer Charlie Rose that “if the wind had been in the other direction on the night of August twenty-eighth [1776], I think it would have all been over.”

“No United States of America if that had happened?” Rose asked.

“I don’t think so,” said McCullough.

“Just because of the wind, history was changed?” asked Rose.

“Absolutely,” said McCullough. 

Risk is what you don’t see

As financial advisor Carl Richards says, “Risk is what’s left over after you think you’ve thought of everything.” That’s the real definition of risk—what’s left over after you’ve prepared for the risks you can imagine. Risk is what you don’t see.

When a past event looks inevitable to us today, we may be fooled by hindsight bias

Two things can explain something that looks inevitable but wasn’t predicted by those who experienced it at the time: 

  • Either everyone in the past was blinded by delusion.
  • Or everyone in the present is fooled by hindsight.

We are crazy to think it’s all the former and none of the latter.

The level of uncertainty in the economy rarely fluctuates, just people’s perceptions

There is rarely more or less economic uncertainty; just changes in how ignorant people are to potential risks. 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 would make it less risky. What your imagination can’t fathom is the dangerous stuff, and it’s why risk can never be mastered

Even when the Great Depression of the 1930s happened, unemployment was not thought to be an issue by people with high posts

The Depression, as we know today, began in 1929. But when the well-informed members of the National Economic League were polled in 1930 as to what they considered the biggest problem of the United States, they listed, in order:

1. Administration of justice

2. Prohibition

3. Disrespect for law

4. Crime

5. Law enforcement

6. World peace

And in eighteenth place . . . unemployment.

A year later, in 1931—a full two years into what we now consider the Great Depression—unemployment had moved to just fourth place, behind prohibition, justice, and law enforcement. That’s what made the Great Depression so awful: No one was prepared for it because no one saw it coming. So people couldn’t deal with it financially (paying their debts) and mentally (the shock and grief of sudden loss).

Having expectations instead of forecasts is important when trying to manage risk

It’s impossible to plan for what you can’t imagine, and the more you think you’ve imagined everything the more shocked you’ll be when something happens that you hadn’t considered. But two things can push you in a more helpful direction.

One, think of risk the way the State of California thinks of earthquakes. It knows a major earthquake will happen. But it has no idea when, where, or of what magnitude. Emergency crews are prepared despite no specific forecast. Buildings are designed to withstand earthquakes that may not occur for a century or more. Nassim Taleb says, “Invest in preparedness, not in prediction.” That gets to the heart of it. Risk is dangerous when you think it requires a specific forecast before you start preparing for it. It’s better to have expectations that risk will arrive, though you don’t know when or where, than to rely exclusively on forecasts— almost all of which are either nonsense or about things that are well-known. Expectations and forecasts are two different things, and in a world where risk is what you don’t see, the former is more valuable than the latter.

Two, realize that if you’re only preparing for the risks you can envision, you’ll be unprepared for the risks you can’t see every single time. So, in personal finance, the right amount of savings is when it feels like it’s a little too much. It should feel excessive; it should make you wince a little. The same goes for how much debt you think you should handle—whatever you think it is, the reality is probably a little less. Your preparation shouldn’t make sense in a world where the biggest historical events all would have sounded absurd before they happened.

Geniuses are unique in BOTH good and bad ways

Something that’s built into the human condition is that people who think about the world in unique ways you like almost certainly also think about the world in unique ways you won’t like…

…John Maynard Keynes once purchased a trove of Isaac Newton’s original papers at auction. Many had never been seen before, as they had been stashed away at Cambridge for centuries. Newton is probably the smartest human to ever live. But Keynes was astonished to find that much of the work was devoted to alchemy, sorcery, and trying to find a potion for eternal life. Keynes wrote:

I have glanced through a great quantity of this at least 100,000 words, I should say. It is utterly impossible to deny that it is wholly magical and wholly devoid of scientific value; and also impossible not to admit that Newton devoted years of work to it.

I wonder: Was Newton a genius in spite of being addicted to magic, or was being curious about things that seemed impossible part of what made him so successful? I think it’s impossible to know. But the idea that crazy geniuses sometimes just look straight-up crazy is nearly unavoidable…

…Take Elon Musk. What kind of thirty-two-year-old thinks they can take on GM, Ford, and NASA at the same time? An utter maniac. The kind of person who thinks normal constraints don’t apply to them—not in an egotistical way, but in a genuine, believe-it-in-your-bones way. Which is also the kind of person who doesn’t worry about, say, Twitter etiquette.

A mindset that can dump a personal fortune into colonizing Mars is not the kind of mindset that worries about the downsides of hyperbole. And the kind of person who proposes making Mars habitable by constantly dropping nuclear bombs in its atmosphere is not the kind of person worried about overstepping the boundaries of reality.

The kind of person who says there’s a 99.9999 percent chance humanity is a computer simulation is not the kind of person worried about making untenable promises to shareholders. The kind of person who promises to solve the water problems in Flint, Michigan, within days of trying to save a Thai children’s soccer team stuck in a cave, within days of rebuilding the Tesla Model 3 assembly line in a tent, is not the kind of person who views his lawyers signing off as a critical step.

People love the visionary genius side of Musk, but want it to come without the side that operates in his distorted I-don’t-care-about-your-customs version of reality. But I don’t think those two things can be separated. They’re the risk-reward trade-offs of the same personality trait.

What gets you to the top also brings you down

What kind of person makes their way to the top of a successful company, or a big country? Someone who is determined, optimistic, doesn’t take no for an answer, and is relentlessly confident in their own abilities. What kind of person is likely to go overboard, bite off more than they can chew, and discount risks that are blindingly obvious to others? Someone who is determined, optimistic, doesn’t take no for an answer, and is relentlessly confident in their own abilities. Reversion to the mean is one of the most common stories in history. It’s the main character in economies, markets, countries, companies, careers—everything. Part of the reason it happens is because the same personality traits that push people to the top also increase the odds of pushing them over the edge.

Outrageous things can easily happen if the sample size is big enough

Evelyn Marie Adams won $3.9 million in the New Jersey lottery in 1986. Four months later she won again, collecting another $1.4 million. ‘‘I’m going to quit playing,’’ she told The New York Times. ‘‘I’m going to give everyone else a chance.’’ It was a big story at the time, because number crunchers put the odds of her double win at a staggering 1 in 17 trillion.

Three years later two mathematicians, Persi Diaconis and Frederick Mosteller, threw cold water on the excitement. If one person plays the lottery, the odds of picking the winning numbers twice are indeed 1 in 17 trillion. But if one hundred million people play the lottery week after week— which is the case in America—the odds that someone will win twice are actually quite good. Diaconis and Mosteller figured it was 1 in 30. That number didn’t make many headlines. ‘‘With a large enough sample, any outrageous thing is apt to happen,” Mosteller said

Why something bad happens nearly every year

If next year there’s a 1 percent chance of a new disastrous pandemic, a 1 percent chance of a crippling depression, a 1 percent chance of a catastrophic flood, a 1 percent chance of political collapse, and on and on, then the odds that something bad will happen next year—or any year—are . . . not bad.

The demise of local news, because of the internet, altered our perception on the frequency of bad news

The decline of local news has all kinds of implications. One that doesn’t get much attention is that the wider the news becomes the more likely it is to be pessimistic. Two things make that so: 

  • Bad news gets more attention than good news because pessimism is seductive and feels more urgent than optimism.
  • The odds of a bad news story—a fraud, a corruption, a disaster—occurring in your local town at any given moment is low. When you expand your attention nationally, the odds increase. When they expand globally, the odds of something terrible happening in any given moment are 100 percent.

To exaggerate only a little: Local news reports on softball tournaments. Global news reports on plane crashes and genocides. 

The internet’s existence means we’re more aware of bad things happening – but bad things are not necessarily happening more today

In modern times our horizons cover every nation, culture, political regime, and economy in the world. There are so many good things that come from that. But we shouldn’t be surprised that the world feels historically broken in recent years and will continue that way going forward. It’s not—we just see more of the bad stuff that’s always happened than we ever saw before.

A contemporary of Ben Graham seemed to know more about investing but was not as good a writer, so he is today much more obscure than Graham

Professor John Burr Williams had more profound insight on the topic of valuing stocks than Benjamin Graham. But Graham knew how to write a good paragraph, so he became the legend and sold millions of books.

US forces suffered against German forces during WWII because American leaders failed to account for Hitler going mad

Historian Stephen Ambrose notes that Eisenhower and General Omar Bradley got all the war-planning reasoning and logic right in late 1944, except for one detail—the extent to which Hitler had lost his mind. An aide to Bradley mentioned during the war: “If we were fighting reasonable people they would have surrendered long ago.” But they weren’t, and it—the one thing that was hard to measure with logic—mattered more than anything.

Lehman Brothers actually had strong financial ratios – better than even Goldman Sachs and Bank of America – in 2008 just before it went bankrupt; what went wrong for Lehman was that investors lost faith in the bank

A few examples of how powerful this can be: Lehman Brothers was in great shape on September 10, 2008. Its tier 1 capital ratio—a measure of a bank’s ability to endure loss—was 11.7 percent. That was higher than the previous quarter. Higher than Goldman Sachs. Higher than Bank of America. It was more capital than Lehman had in 2007, when the banking industry was about as strong as it had ever been. 

Seventy-two hours later Lehman was bankrupt. The only thing that changed during those three days was investors’ faith in the company. One day they believed in the company and bought its debt. The next day that belief stopped, and so did its funding. That faith is the only thing that mattered. But it was the one thing that was hard to quantify, hard to model, hard to predict, and didn’t compute in a traditional valuation model. GameStop

Hyman Minsky’s economic theory of stability leading to instability can be found in nature too

California was hit with an epic drought in the mid-2010s. Then 2017 came, dropping a preposterous amount of moisture. Parts of Lake Tahoe received—I’m not making this up—more than sixty-five feet of snow in a few months. The six-year drought was declared over.

You’d think that would be great. But it backfired in an unexpected way. Record rain in 2017 led to record vegetation growth that summer. It was called a superbloom, and it caused even desert towns to be covered in green. A dry 2018 meant all that vegetation died and became dry kindling. That led to some of the biggest wildfires California had ever seen.

So record rain directly led to record fires. There’s a long history of this, verified by looking at tree rings, which inscribe both heavy rainfall and subsequent fire scars. The two go hand in hand. “A wet year reduces fires while increasing vegetation growth, but then the increased vegetation dries out in subsequent dry years, thereby increasing the fire fuel,” the National Oceanic and Atmospheric Administration wrote. That’s hardly intuitive, but here again—calm plants the seeds of crazy. 

Why financial markets will always overshoot on both ends of the optimism and pessimism spectrum

The only way to know we’ve exhausted all potential opportunity from markets—the only way to identify the top —is to push them not only past the point where the numbers stop making sense, but beyond the stories people believe about those numbers. When a tire company develops a new tire and wants to know its limitations, the process is simple. They put it on a car and run it until it blows up. Markets, desperate to know the limits of what other investors can endure, do the same thing. Always been the case, always will be.

Markets going beyond the point of crazy is a normal thing 

One is accepting that crazy doesn’t mean broken. Crazy is normal; beyond the point of crazy is normal. Every few years there seems to be a declaration that markets don’t work anymore—that they’re all speculation or detached from fundamentals. But it’s always been that way. People haven’t lost their minds; they’re just searching for the boundaries of what other investors are willing to believe

Many things in life have a “most convenient size”

“For every type of animal there is a most convenient size, and a change in size inevitably carries with it a change of form,” Haldane wrote. A most convenient size. A proper state where things work well but break when you try to scale them to a different size or speed. It applies to so many things in life…

…Starbucks had 425 stores in 1994, its twenty-third year in existence. In 1999 it opened 625 new stores. By 2007 it was opening 2,500 stores per year—a new coffee shop every four hours. One thing led to another. The need to hit growth targets eventually elbowed out rational analysis. Examples of Starbucks saturation became a joke. Same-store sales growth fell by half as the rest of the economy boomed. 

Howard Schultz wrote to senior management in 2007: “In order to go from less than 1,000 stores to 13,000 stores we have had to make a series of decisions that, in retrospect, have led to the watering down of the Starbucks experience.” Starbucks closed six hundred stores in 2008 and laid off twelve thousand employees. Its stock fell 73 percent, which was dreadful even by 2008 standards.

Schultz wrote in his 2011 book Onward: “Growth, we now know all too well, is not a strategy. It is a tactic. And when undisciplined growth became a strategy, we lost our way.” There was a most convenient size for Starbucks—there is for all businesses. Push past it and you realize that revenue might scale but disappointed customers scale faster, in the same way Robert Wadlow became a giant but struggled to walk.

Different management skills are needed as a company changes in size

A management style that works brilliantly at a ten-person company can destroy a thousand-person company, which is a hard lesson to learn when some companies grow that fast in a few short years. Travis Kalanick, the former CEO of Uber, is a great example. No one but him was capable of growing the company early on, and anyone but him was needed as the company matured. I don’t think that’s a flaw, just a reflection that some things don’t scale. 

Militaries are really good at innovating because the problems they deal with are so important

Militaries are engines of innovation because they occasionally deal with problems so important—so urgent, so vital—that money and manpower are removed as obstacles, and those involved collaborate in ways that are hard to emulate during calm times. You cannot compare the incentives of Silicon Valley coders trying to get you to click on ads to Manhattan Project physicists trying to end a war that threatened the country’s existence. You can’t even compare their capabilities. The same people with the same intelligence have wildly different potential under different circumstances.

How the harsh conditions of the 1930s forced USA to innovate

The 1930s were a disaster, one of the darkest periods in American history. Almost a quarter of Americans were out of work in 1932. The stock market fell 89 percent. Those two economic stories dominate the decade’s attention, and they should. But there’s another story about the 1930s that rarely gets mentioned: it was, by far, the most productive and technologically progressive decade in U.S. history.

The number of problems people solved, and the ways they discovered how to build stuff more efficiently, is a forgotten story of the ’30s that helps explain a lot of why the rest of the twentieth century was so prosperous. Here are the numbers: total factor productivity—that’s economic output relative to the number of hours people worked and the amount of money invested in the economy—hit levels not seen before or since. Economist Alex Field wrote that by 1941 the U.S. economy was producing 40 percent more output than it had in 1929, with virtually no increase in the total number of hours worked. Everyone simply became staggeringly more productive.

A couple of things happened during this period that are worth paying attention to, because they explain why this happened when it did. Take cars. The 1920s was the era of the automobile. The number of cars on the road in America jumped from one million in 1912 to twenty-nine million by 1929. But roads were a different story. Cars were sold in the 1920s faster than roads were built. That changed in the 1930s when road construction, driven by the New Deal’s Public Works Administration, took off. Spending on road construction went from 2 percent of GDP in 1920 to over 6 percent in 1933 (versus less than 1 percent today). The Department of Highway Transportation tells a story of how quickly projects began: 

Construction began on August 5, 1933, in Utah on the first highway project under the act. By August 1934, 16,330 miles of new roadway projects were completed.

What this did to productivity is hard to overstate. The Pennsylvania Turnpike, as one example, cut travel times between Pittsburgh and Harrisburg by 70 percent. The Golden Gate Bridge, built in 1933, opened up Marin County, which had previously been accessible from San Francisco only by ferryboat. Multiply those kinds of leaps across the nation and the 1930s was the decade that transportation blossomed in the United States. It was the last link that made the century-old railroad network truly efficient, creating last-mile service that connected the world.

Electrification also surged in the 1930s, particularly to rural Americans left out of the urban electrification of the 1920s. The New Deal’s Rural Electrification Administration (REA) brought power to farms in what may have been the decade’s only positive development in regions that were economically devastated. The number of rural American homes with electricity rose from less than 10 percent in 1935 to nearly 50 percent by 1945. It is hard to fathom, but it was not long ago—during some of our lifetimes and most of our grandparents’—that a substantial portion of America was literally dark.

Franklin Roosevelt said in a speech on the REA:

Electricity is no longer a luxury. It is a definite necessity. . . . In our homes it serves not only for light, but it can become the willing servant of the family in countless ways. It can relieve the drudgery of the housewife and lift the great burden off the shoulders of the hardworking farmer.

Electricity becoming a “willing servant”—introducing washing machines, vacuum cleaners, and refrigerators—freed up hours of household labor in a way that let female workforce participation rise. It’s a trend that lasted more than half a century and is a key driver of both twentieth-century growth and gender equality.

Another productivity surge of the 1930s came from everyday people forced by necessity to find more bang for their buck. The first supermarket opened in 1930. The traditional way of purchasing food was to walk from your butcher, who served you from behind a counter, to the bakery, who served you from behind a counter, to a produce stand, who took your order. Combining everything under one roof and making customers pick it from the shelves themselves was a way to make the economics of selling food work during a time when a quarter of the nation was unemployed.

Laundromats were also invented in the 1930s after sales of individual washing machines fell; they marketed themselves as washing machine rentals.

Factories of all kinds looked at bludgeoned sales and said, “What must we do to survive?” The answer often was to build the kind of assembly line Henry Ford introduced to the world in the previous decade. Output per hour in factories had grown 21 percent during the 1920s. “During the Depression decade of 1930–1940— when many plants were shut down or working part time,” Frederick Lewis Allen wrote, “there was intense pressure for efficiency and economy—it had increased by an amazing 41 per cent.”

“The trauma of the Great Depression did not slow down the American invention machine,” economist Robert Gordon wrote. “If anything, the pace of innovation picked up.” Driving knowledge work in the ’30s was the fact that more young people stayed in school because they had nothing else to do. High school graduation surged during the Depression to levels not seen again until the 1960s.

All of this—the better factories, the new ideas, the educated workers— became vital in 1941 when America entered the war and became the Allied manufacturing engine. The big question is whether the technical leap of the 1930s could have happened without the devastation of the Depression. And I think the answer is no—at least not to the extent that it occurred. You could never push through something like the New Deal without an economy so wrecked that people were desperate to try anything to fix it.

Innovation takes time to be recognised, so it’s easy for people to think that innovation is lacking 

A lot of pessimism is fueled by the fact that it often looks like we haven’t innovated in years—but that’s usually because it takes years to notice a new innovation.

Economic progress has been incredible over long periods of time, but is unnoticeable over short periods

Real GDP per capita increased eightfold in the last hundred years. America of the 1920s had the same real per capita GDP as Turkmenistan does today. Our growth over the last century has been unbelievable. But GDP growth averages about 3 percent per year, which is easy to ignore in any given year, decade, or lifetime. Americans over age fifty have seen real GDP per person at least double since they were born. But people don’t remember the world when they were born. They remember the last few months, when progress is always invisible. Same for careers, social progress, brands, companies, and relationships. Progress always takes time, often too much time to even notice it’s happened.

Why progress happens slowly but bad news comes quickly 

Growth always fights against competition that slows its rise. New ideas fight for attention, business models fight incumbents, skyscrapers fight gravity. There’s always a headwind. But everyone gets out of the way of decline. Some might try to step in and slow the fall, but it doesn’t attract masses of outsiders who rush in to push back in the other direction the way progress does…

…The irony is that growth and progress are way more powerful than setbacks. But setbacks will always get more attention because of how fast they occur. So slow progress amid a drumbeat of bad news is the normal state of affairs. It’s not an easy thing to get used to, but it’ll always be with us. 

Good news is what did NOT happen whereas bad news is what did happen

A lot of progress and good news concerns things that didn’t happen, whereas virtually all bad news is about what did occur. Good news is the deaths that didn’t take place, the diseases you didn’t get, the wars that never happened, the tragedies avoided, and the injustices prevented. That’s hard for people to contextualize or even imagine, let alone measure. But bad news is visible. More than visible, it’s in your face. It’s the terrorist attack, the war, the car accident, the pandemic, the stock market crash, and the political battle you can’t look away from.

Why we underestimate big risks

Big risks are easy to overlook because they’re just a chain reaction of small events, each of which is easy to shrug off. So people always underestimate the odds of big risks…

…The Tenerife airport disaster in 1977 is the deadliest aircraft accident in history. The error was stunning. One plane took off while another was still on the runway, and the two Boeing 747s collided, killing 583 people on a runway on the Spanish island. In the aftermath authorities wondered how such an egregious catastrophe could occur. One postmortem study explained exactly how: “Eleven separate coincidences and mistakes, most of them minor . . . had to fall precisely into place” for the crash to occur. Lots of tiny mistakes added up to a huge one. It’s good to always assume the world will break about once per decade, because historically it has. The breakages feel like low-probability events, so it’s common to think they won’t keep happening. But they do, again and again, because they’re actually just smaller high-probability events compounding off one another. That isn’t intuitive, so we’ll discount big risks like we always have.

The fascinating history behind the phrase, “The American Dream”

“The American dream” was a phrase first used by author James Truslow Adams in his 1931 book The Epic of America. The timing is interesting, isn’t it? It’s hard to think of a year when the dream looked more broken than in 1931.

When Adams wrote that “a man by applying himself, by using the talents he has, by acquiring the necessary skills, can rise from lower to higher status, and that his family can rise with him,” the unemployment rate was nearly 25 percent and wealth inequality was near the highest it had been in American history.

When he wrote of “that American dream of a better, richer, and happier life for all our citizens of every rank,” food riots were breaking out across the country as the Great Depression ripped the economy to shreds.

When he wrote of “being able to grow to fullest development as men and women, unhampered by the barriers which had slowly been erected in older civilizations,” schools were segregated and some states required literacy tests to vote.

At few points in American history had the idea of the American dream looked so false, so out of touch with the reality everyone faced. Yet Adams’s book surged in popularity. An optimistic phrase born during a dark period in American history became an overnight household motto.

One quarter of Americans being out of work in 1931 didn’t ruin the idea of the American Dream. The stock market falling 89 percent—and bread lines across the country—didn’t, either. The American Dream actually may have gained popularity because things were so dire. You didn’t have to see the American Dream to believe in it—and thank goodness, because in 1931 there was nothing to see. You just had to believe it was possible and then, boom, you felt a little better.

In nature, species are never perfect in any one trait because perfection involves compromising in other areas

There is no perfect species, one adapted to everything at all times. The best any species can do is to be good at some things until the things it’s not good at suddenly matter more. And then it dies.

A century ago a Russian biologist named Ivan Schmalhausen described how this works. A species that evolves to become very good at one thing tends to become vulnerable at another. A bigger lion can kill more prey, but it’s also a larger target for hunters to shoot at. A taller tree captures more sunlight, but becomes vulnerable to wind damage. There is always some inefficiency. So species rarely evolve to become perfect at anything, because perfecting one skill comes at the expense of another skill that will eventually be critical to survival. The lion could be bigger and catch more prey; the tree could be taller and get more sun. But they’re not, because it would backfire. So they’re all a little imperfect. Nature’s answer is a lot of good enough, below-potential traits across all species.

Biologist Anthony Bradshaw says that evolution’s successes get all the attention, but its failures are equally important. And that’s how it should be: Not maximizing your potential is actually the sweet spot in a world where perfecting one skill compromises another.

The probability of a species going extinct is independent of its age

Leigh Van Valen was a crazy-looking evolutionary biologist who came up with a theory so wild no academic journal would publish it. So he created his own journal and published it, and the idea eventually became accepted wisdom. Those kinds of ideas—counterintuitive, but ultimately true—are the ones worth paying most attention to, because they’re easiest to overlook.

For decades, scientists assumed that the longer a species had been around, the more likely it was to stick around, because age proved a strength that was likely to endure. Longevity was seen as both a trophy and a forecast. In the early 1970s, Van Valen set out to prove that the conventional wisdom was right. But he couldn’t. The data just didn’t fit.

He began to wonder whether evolution was such a relentless and unforgiving force that long-lived species were just lucky. The data fit that theory better. You’d think a new species discovering its niche would be fragile and susceptible to extinction—let’s say a 10 percent chance of extinction in a given period—while an old species had proven its might, and has, say, a 0.01 percent chance of extinction.

But when Van Valen plotted extinctions by a species’ age, the trend looked more like a straight line. Some species survived a long time. But among groups of species, the probability of extinction was roughly the same whether it was 10,000 years old or 10 million years old.

In a 1973 paper titled “A New Evolutionary Law,” Van Valen wrote that “the probability of extinction of a taxon is effectively independent of its age.” If you take a thousand marbles and remove 2 percent of them each year, some marbles will remain in the jar after twenty years. But the odds of being picked out are the same every year (2 percent). Marbles don’t get better at staying in the jar. Species are the same. Some happen to live a long time, but the odds of surviving don’t improve over time. Van Valen argued that’s the case mainly because competition isn’t like a football game that ends with a winner who can then take a break. Competition never stops. A species that gains an advantage over a competitor instantly incentivizes the competitor to improve. It’s an arms race.

Evolution is the study of advantages. Van Valen’s idea is simply that there are no permanent advantages. Everyone is madly scrambling all the time, but no one gets so far ahead that they become extinction-proof.

An example of the unpredictable path of innovations: how planes made nuclear power plants possible

When the airplane came into practical use in the early 1900s, one of the first tasks was trying to foresee what benefits would come from it. A few obvious ones were mail delivery and sky racing. No one predicted nuclear power plants. But they wouldn’t have been possible without the plane. Without the plane we wouldn’t have had the aerial bomb. Without the aerial bomb we wouldn’t have had the nuclear bomb. And without the nuclear bomb we wouldn’t have discovered the peaceful use of nuclear power. Same thing today. Google Maps, TurboTax, and Instagram wouldn’t be possible without ARPANET, a 1960s Department of Defense project linking computers to manage Cold War secrets, which became the foundation for the internet. That’s how you go from the threat of nuclear war to filing your taxes from your couch—a link that was unthinkable fifty years ago, but there it is

The fascinating backstory behind the invention of Polaroid film

Author Safi Bahcall notes that Polaroid film was discovered when sick dogs that were fed quinine to treat parasites showed an unusual type of crystal in their urine. Those crystals turned out to be the best polarizers ever discovered. Who predicts that? Who sees that coming? Nobody. Absolutely nobody. 

The power of incentives can explain extreme events, unsustainable events occuring for prolonged periods of time, and warped beliefs

When good and honest people can be incentivized into crazy behavior, it’s easy to underestimate the odds of the world going off the rails. Everything from wars to recessions to frauds to business failures to market bubbles happen more often than people think because the moral boundaries of what people are willing to do can be extended with certain incentives. That goes both ways. It’s easy to underestimate how much good people can do, how talented they can become, and what they can accomplish when they operate in a world where their incentives are aligned toward progress.

Extremes are the norm. Unsustainable things can last longer than you anticipate. Incentives can keep crazy, unsustainable trends going longer than seems reasonable because there are social and financial reasons preventing people from accepting reality for as long as they can. A good question to ask is, “Which of my current views would change if my incentives were different?” If you answer “none,” you are likely not only persuaded but blinded by your incentives.

It’s hard to predict our behaviour during downturns because the environment changes so much

In investing, saying “I will be greedy when others are fearful” is easier said than done, because people underestimate how much their views and goals can change when markets break. The reason you may embrace ideas and goals you once thought unthinkable during a downturn is because more changes during downturns than just asset prices.

If I, today, imagine how I’d respond to stocks falling 30 percent, I picture a world where everything is like it is today except stock valuations, which are 30 percent cheaper. But that’s not how the world works. Downturns don’t happen in isolation. The reason stocks might fall 30 percent is because big groups of people, companies, and politicians screwed something up, and their screwups might sap my confidence in our ability to recover. So my investment priorities might shift from growth to preservation. It’s difficult to contextualize this mental shift when the economy is booming. And even though Warren Buffett says to be greedy when others are fearful, far more people agree with that quote than actually act on it. The same idea holds true for companies, careers, and relationships. Hard times make people do and think things they’d never imagine when things are calm.

Why humans prefer complexity over simplicity

The question then is: Why? Why are complexity and length so appealing when simplicity and brevity will do? A few reasons: 

Complexity gives a comforting impression of control, while simplicity is hard to distinguish from cluelessness. 

In most fields a handful of variables dictate the majority of outcomes. But paying attention to only those few variables can feel like you’re leaving too much of the outcome to fate. The more knobs you can fiddle with—the hundred-tab spreadsheet, or the Big Data analysis—the more control you feel you have over the situation, if only because the impression of knowledge increases. The flip side is that paying attention to only a few variables while ignoring the majority of others can make you look ignorant. If a client says, “What about this, what’s happening here?” and you respond, “Oh, I have no idea, I don’t even look at that,” the odds that you’ll sound uninformed are greater than the odds you’ll sound like you’ve mastered simplicity.

Things you don’t understand create a mystique around people who do. 

If you say something I didn’t know but can understand, I might think you’re smart. If you say something I can’t understand, I might think you have an ability to think about a topic in ways I can’t, which is a whole different species of admiration. When you understand things I don’t, I have a hard time judging the limits of your knowledge in that field, which makes me more prone to taking your views at face value.

Length is often the only thing that can signal effort and thoughtfulness. 

A typical nonfiction book covering a single topic is perhaps 250 pages, or something like 65,000 words. The funny thing is the average reader does not come close to finishing most books they buy. Even among bestsellers, average readers quit after a few dozen pages. Length, then, has to serve a purpose other than providing more material.

My theory is that length indicates the author has spent more time thinking about a topic than you have, which can be the only data point signaling they might have insights you don’t. It doesn’t mean their thinking is right. And you may understand their point after two chapters. But the purpose of chapters 3–16 is often to show that the author has done so much work that chapters 1 and 2 might have some insight. Same goes for research reports and white papers.

Simplicity feels like an easy walk. Complexity feels like a mental marathon.

If the reps don’t hurt when you’re exercising, you’re not really exercising. Pain is the sign of progress that tells you you’re paying the unavoidable cost of admission. Short and simple communication is different. Richard Feynman and Stephen Hawking could teach math with simple language that didn’t hurt your head, not because they dumbed down the topics but because they knew how to get from A to Z in as few steps as possible. An effective rule of thumb doesn’t bypass complexity; it wraps things you don’t understand into things you do. Like a baseball player who—by keeping a ball level in his gaze—knows where the ball will land as well as a physicist calculating the ball’s flight with precision.

The problem with simplicity is that the reps don’t hurt, so you don’t feel like you’re getting a mental workout. It can create a preference for laborious learning that students are actually okay with because it feels like a cognitive bench press, with all the assumed benefits.

Why people will always disagree

The question “Why don’t you agree with me?” can have infinite answers. Sometimes one side is selfish, or stupid, or blind, or uninformed. But usually a better question is, “What have you experienced that I haven’t that makes you believe what you do? And would I think about the world like you do if I experienced what you have?”

It’s the question that contains the most answers about why people don’t agree with one another. But it’s such a hard question to ask. It’s uncomfortable to think that what you haven’t experienced might change what you believe, because it’s admitting your own ignorance. It’s much easier to assume that those who disagree with you aren’t thinking as hard as you are.

So people will disagree, even as access to information explodes. They may disagree more than ever because, as Benedict Evans says, “The more the Internet exposes people to new points of view, the angrier people get that different views exist.” Disagreement has less to do with what people know and more to do with what they’ve experienced. And since experiences will always be different, disagreement will be constant. Same as it’s ever been. Same as it will always be. Same as it ever was


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. I currently have a vested interest in Amazon. Holdings are subject to change at any time.

Ben Graham’s Q&A

Ben Graham appeared in a news clip in the 1950s, answering questions and assuaging people’s worries about the stock market.

I recently came across an old US TV news clip from the 1950s that featured Ben Graham, the mentor of Warren Buffett, and the author of the highly influential investing texts, The Intelligent Investor and Security Analysis. In the clip, Graham was leading a seminar at Columbia University together with Dean Courtney Brown. The two men gave a short speech and answered questions from the crowd. 

The news clip also featured a short interview of Senator William Fulbright, who at the time, was commissioning a study on the US stock market after stock prices had advanced near the heights of the 1929 peak just before the Great Depression of the 1930s reared its ugly head. (The study was conducted and published in 1955.)

I was fascinated by the news clip, because Fulbright and the people asking questions to Graham and Brown, had worries about the stock market that are similar to today. For example, Fulbright was concerned that stock prices were too high and might collapse drastically yet again, similar to the great crash that happened during the Great Depression. In another example, the question at the 21:09 mark was concerned about inflation that was driven by “deficits spending”, “easy money policy”, “increased union wages”, “increased minimum wage”, and a “rogue [spending] programme of US$101 billion which the government has just announced” – these are worries in the 1950s that would absolutely fit in today. And importantly, the Dow Jones Industrial Average (I’m using the Dow because it is the index that is referenced in the news clip) is up from around 400 points in 1955 to over 37,000 currently. 

I decided to create a transcript of the news clip for my own reference in the future, and thought of sharing it with the possibility that it might be useful for any of you reading this. Enjoy!

Transcript

TV presenter (10:00): There is no shortage of experts on the market. As for us we’re barely able to tell the difference between a bull and a bear. So we sat in on part of a seminar at The Graduate School of Business at Columbia University. After all it’s older than the stock exchange and we thought professors familiar with the language of the street might treat the market with detachment. Dean Courtney Brown and Professor Benjamin Graham were instructing future brokers and customersmen. Here is See It Now’s short course in the market.

Courtney Brown (10:36): First let me give a caution. I hardly need give it to a group of informed students such as you. No one knows precisely why the market behaves as it behaves, either in retrospect, or in prospect. The best we can do as you well know is express informed judgments. But it is important that those judgments be informed. We do know that there has been a substantial rise. That rise has been going on for a number of years, particularly since the middle of 1953. And we do know that the rate of that rise has been very rapid, uncomfortably like that of the 1928-29 period. It has resulted in a lot of comparisons being made in the press. Moreover the present level of stock prices, as measured by the Dow Jones Averages, is about equal to, indeed a little above the peaks of 1929.

A number of explanations have been advanced regarding the stock market’s rise that suggests it may reflect a return to inflationary conditions. This doesn’t seem to me to be very convincing. First because there is no evidence of inflation in the behaviour of commodity prices, either at the wholesale or at the retail level and there hasn’t been over the past a year and a half – extraordinary stability in the behaviour of both indexes. There is so much surplus capacity around in almost every direction that it’s hard to conceive of a strong inflationary trend reasserting itself at this time.

Still another explanation is that the stock market has gone up because there has been a return of that kind of speculative fever that has from time to time in the past gripped the country – the Florida land boom, the 1929 stock boom. They’ve occurred in history as you know, all the way back from the Tulip speculations in Holland. I suspect there’s a certain element of truth in this one. However, it doesn’t seem to me that it gives us too much concern because there has been no feeding of this fever by the injection of credit. I think it is important for us to observe that the amount of brokers’ loans – loans made to brokers for the financing of securities of their customers that have been bought on margin – are less and then US$2 billion at present. In 1929, they were in excess of US$8.5 billion and there is now a larger volume of securities on the stock exchange. Now gentlemen, Professor Graham will pick up the story at that point.

Ben Graham (13:37): One of the comparisons is interesting is one not between 1929, which is so long ago but 1950 which is only a few years ago. It would be very proper to ask why a price is twice as much as they are now when the earnings of companies both in ‘54 and probably in 1955 are less than they were in 1950. Now that is an extraordinary difference and the explanation cannot be found in any mathematics but it has to be found in investor psychology. 

Ben Graham (14:10): You can have an extraordinary difference in the price level merely because not only speculators but investors themselves are looking at the situation through rose-coloured glasses rather than dark-blue glasses. It may well be true that the underlying psychology of the American people has not changed so much and that what the American people have been waiting for for many years has been an excuse for going back to the speculative attitudes which used to characterize them from time to time. Now if that is so, then the present situation can carry a very large degree of danger to people who are now becoming interested in common stocks for the first time. It would seem if history counts for anything, that the stock market is much more likely than not to advance to a point where of real danger.

Unknown questioner (15:03): You said that stock prices now are not too high but that you fear they will go higher. Well then are you recommending the decline?

Courtney Brown (15:09) Well here I’ll defend you on that [laughs].

Ben Graham (15:10): [Laughs] Yeah, go right ahead.

Courtney Brown (15:17): Those who have watched the security market’s behaviour over the years have become more and more impressed with the fact that stocks always go too high on the upside and tend to go too low on the downside. The swings in other words are always more dramatic and more – the amplitude of change is greater than might normally be justified by an analytical appraisal of the values that are represented there. I think what Professor Graham had to say was that his analysis of a series of underlying values would indicate that the stock prices are just about in line with where they might properly be.

However, from experience that would be the least likely thing to happen that stocks would just stabilise right here. Now if it’s the least likely thing to happen, and you have to select a probability between going up further or down further because of the strong momentum that they have had, I think I would be inclined to agree with him [referring to Graham] that the more probable direction would be towards a somewhat higher level.

Unknown questioner (16:24) When stockholders believed the market was too high, they switched from stocks to cash. Now, many people feel that due to capital gains tax they are not free to act. They are, what you might say, locked in. What effect does this have on the stock market in general?

Courtney Brown (16:41): No question about the fact that it does discourage some sales that might otherwise be made because one selling stocks trying to replace them would have to replace them at substantially lower prices and to come out even after paying the capital gains tax. However, that’s not the only reason people are reluctant to sell stocks and buy bonds. Stocks are still yielding about 4.5% on the basis of current dividend payments whereas bonds of prime quality are closer to 3%. Here again we find a contrast with the situation in 1929, when stocks were yielding about 3.5% and prime bonds closer to 5%.

Unknown questioner (17:24): In addition to raising margin requirements, should the federal government take other measures to check a speculative boom in the stock market, and which method is the better?

Ben Graham (17:34): My own opinion would be that the Federal Reserve should first exhaust the possibilities of raising the margin requirements to 100% and then consider very seriously before they imposed other sanctions if needed 

Unknown questioner (17:47): What is the significance of the broadening public participation in stock purchasing and ownership? 

Courtney Brown (17:58): There are probably two elements there that are important. One, the broadening participation of the public in stock purchases is one measure of the degree of speculative fever that we were talking about before. However, subject to that being controlled – and I believe that it can be controlled as Professor Graham has indicated. But over and above that, there is a broad social significance to that, it seems to me. What in essential terms means is that the ownership of American industry is being more widely dispersed among more and more people. This has very favourable repercussions in terms of our political and social life.

Unknown questioner (18:45): This question concerns the so-called Wall Street professional. Our Wall Street professionals, usually more accurate in their near or long-term market trends – forecasts of stock market trends. If not, why not?

Ben Graham (19:03): I said you say that they are more often wrong than right on their forecasts?

Unknown questioner (19:08): What I mean is are they more accurate in the shorter term than the long-term forecasts?

Ben Graham (19:11): Well we’ve been following that interesting question for a generation or more and I must say frankly that our studies indicate that you have your choice between tossing coins and taking the consensus of expert opinion. And the results are just about the same in each case. Your question as to why they are not more dependable – it’s a very good one and interesting one. My own explanation for that is this: That everybody in Wall Street is so smart, that their brilliance offsets each other, and that whatever they know is already reflected in the level of stock prices pretty much. And consequently what happens in the future represents what they don’t know.

Unknown questioner (19:56): Would you kindly comment on an item appearing in the newspapers to the effect that while 45% of buying today is on margin, the money borrowed is equal to only 1% of the value of listed stock.

Courtney Brown (20:12): The amount of trading on the stock exchange is a very small part of the total value of all the securities that are listed there on. And when you say that the total amount of borrowing on margins financed by brokerage loans is only 1% of the value, it is a reconcilable figure. You can’t reconcile it unless you have the detailed data with you, but it isn’t incompatible in any way.

Ben Graham (20:34): I might add a point on that Dean Brown and that is the slow increase in brokers loans as compared with 45% marginal trade, would indicate that a good deal of the marginal trading is between people who are taking in each other’s washing – that is the marginal buyers are buying from sellers who are previously on margin. And that’s why the rate of growth of brokers’ loans is so much smaller now than it had been in the 1920s, when I think a good deal of the selling had come from long-term owners and really smart people who were selling out to the suckers.

Unknown questioner (21:09): I want to raise a point of argument here on this question of inflation. Seems to me that you’re correct in stating that there’s been no inflation in ‘54 but there also appears to be several long-term inflationary points in the economy today. These I think are the deficits spending that’s supposed to be continued by the government, the easy money policy which is expected to continue, the question of increased union wages, the talk about increased minimum wage, and the talk about a guaranteed wage. All these and on top of this, the rogue program of US$101 billion which the government has just announced. These seem to me to be long-term inflationary things in the US economy and I wish you’d talk about these.

Courtney Brown (21:57): That’s a question that has a good many angles on it. Perhaps we both better try it. Prof Graham, why don’t you take the first crash?

Ben Graham (22:00): I think there are two answers to that in my mind. The first is that acknowledging that there are inflationary elements in governmental policy as it’s now being carried out, it may be argued that those are just necessary to keep things on an even keel because without them, we might have some inbuilt deflationary factors in the way business operates through increased productivity capacity and so forth.

Courtney Brown (22:27): I’ve been impressed with the possibility of labour costs as an inflationary factor. But a rise in wages does not necessarily mean a rise in labour costs. It depends upon the relationship of the rate of change in wages and the rate of change in output  per man-hour, or productivity. Now if wages are related to productivity, as you know they were in the General Motors contract, there is no necessary inflationary consequence to be anticipated. However, apart from that, it’s entirely possible that if wages go ahead faster than changes in productivity there could be a seriously inflationary factor. 

Unknown questioner (23:13): On the basis of your recent answer with regard to the psychological impact of the present condition of the market on the small investor, do you discount the entire theory of dollar averaging? 

Ben Graham (23:30): I think there’s no doubt for this, accepting your premise the man will put the same amount of money in the market year after year for the next 20 years, let’s say, there is a great chance of coming out ahead regardless of when he begins and particularly regardless we should begin now. You have to allow for the human nature factor that no man can really say definitely just how he’s going to behave over the next 10 to 20 years. And there is danger that people start with the idea of being systematic investors over the next 10 to 20 years, may change their attitude as the market fluctuates – in the first instance, put more money into the market because they become speculators, and secondly, get disgusted and scared and don’t buy at all later on when prices get low. It’s a psychological danger – the fault is not in the stars or in the system but in ourselves I think. 

TV presenter (24:27): That was a glimpse of a seminar examining the stock market at Columbia University. We move now to Washington, where Democratic Senator William J Fulbright has announced that his Banking and Currency committee will conduct an investigation of the market.

Unknown questioner (24:40): Senator Fulbright, why is your committee going to investigate the stock market?

William Fulbright (24:43): Well Mr Mayor, there are two principal reasons. One is that my committee has jurisdiction over the subject matter through its control and responsibility for the SEC. The second reason is that the unusual increase during the last 12 to 18 months in the level of prices would seem to warrant a study at this time. 

Unknown questioner (25:04): Are you worried about another 1929?

William Fulbright (25:06): But of course there’s certainly a possibility of it. This situation is reminiscent of 1929. We know the Great Depression in the early ‘30s was heralded by the tremendous increase, the great rise in the stock market and then the great drop. That’s unsettling to the whole economy and it frightens people. It causes great harm to people on fixed incomes and so on. And another thing about it is that the greatest criticism of our system and our economy by our enemies – especially the Communists – is the instability of our economy and the why of our fluctuations and we should endeavour to minimise those fluctuations. Now I don’t know all the reasons involved in this. That’s why we’re going to have the study. But the objective is is to inform the Congress and inform the people as far as we can about the conditions that now exist and we would then hope to be able to develop some remedy for it, some way to control these wild fluctuations. 

I confess with what limited knowledge I have, it does disturb me because it has gone up for such a long time and to such a great extent – I think far beyond what the conditions in the country itself warrant. I happen to know of my own knowledge that in the agricultural areas in the southwest, we are having a very severe depressed period. There is no boom in the agricultural areas, the rural areas of the West, and the Southwest. So that most of this boom is concentrated in the market and I think it is unhealthy but I’m unwilling to take a dogmatic stand now. That’s why as I say, we’ll have the study. 

Unknown questioner (26:52): Well Senator Fulbright, I think you have referred to this as a friendly investigation. What exactly is a friendly investigation?

William Fulbright (27:00): Well what I meant to convey is that I have no knowledge nor even suspicion of wrongdoing, manipulation, or anything of that kind in this increase. And I approach it in a friendly spirit in the spirit of trying to find out for the information of the country and of our committee and the Congress, what has been taking place. I’m not approaching it with the idea that we’re going to reveal a lot of wrongdoing.

TV presenter (27:27): The stock exchange hasn’t been investigated for 20 years, but it remains the subject of curiosity and concern as to whether what is good for the exchange is good for the country and the people who live here. There have been no official charges that it has been rigged or manipulated but rather the question of whether or not the market is healthy. There is wide disagreement amongst the experts as to why the market behaves as it does. But there is considerable agreement that it behaves the way it does because people behave the way they do. 

Good night and good luck. 


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. I do not have a vested interest in any companies mentioned. Holdings are subject to change at any time.

More Of The Latest Thoughts From American Technology Companies On AI (2023 Q3)

A collection of quotes on artificial intelligence, or AI, from the management teams of US-listed technology companies in the 2023 Q3 earnings season.

Nearly a month ago, I published The Latest Thoughts From American Technology Companies On AI (2023 Q3). In it, I shared commentary in earnings conference calls for the third quarter of 2023, from the leaders of technology companies that I follow or have a vested interest in, on the topic of AI and how the technology could impact their industry and the business world writ large. 

A few more technology companies I’m watching hosted earnings conference calls for 2023’s third quarter after the article was published. The leaders of these companies also had insights on AI that I think would be useful to share. This is an ongoing series. For the older commentary:

With that, here are the latest comments, in no particular order:

Adobe (NASDAQ: ADBE)

Adobe’s management believes that generative AI is a generational opportunity to deliver new products and services

We believe that every massive technology shift offers generational opportunities to deliver new products and solutions to an ever-expanding set of customers. AI and generative AI is one such opportunity, and we have articulated how we intend to invest and differentiate across data, models and interfaces. 

The integration of Adobe’s generative AI Firefly models with the company’s Creative Cloud’s suite of products have led to more than 4.5 billion generations since their launch in March

The general availability of our generative AI Firefly models and their integrations across Creative Cloud drove tremendous customer excitement with over 4.5 billion generations since launch in March.

Adobe’s management has released three new Firefly models for different functions

The release of 3 new Firefly models, Firefly Image 2 model, Firefly Vector model and Firefly Design model, offering highly differentiated levels of control with effects, photo settings and generative match

Adobe’s Creative Cloud subscription plans now include generative credits; Adobe’s management introduced generative credits to Adobe’s paid plans to drive adoption of the plans and drive usage of the generative AI functions; management does not expect the generative credits (or packs) to have a large impact on Adobe’s financials in the short term beyond driving more customer sign-ups

We also introduced generative credits as part of our Creative Cloud subscription plans…

…Secondly, we priced the generative packs — sorry, we integrated the generative capabilities and credits directly into our paid plans with the express intent of driving adoption of the paid subscription plans and getting broad proliferation of the ability to use those…

… I don’t personally expect generative packs to have a large impact in the short term other than to drive more customers to our paid existing subscription plans.

Photoshop Generative Fill and Generative Expand are now generally available and are seeing record adoption, with them being among the most used features in the Photoshop product

The general availability of Photoshop Generative Fill and Generative Expand, which are seeing record adoption. They’re already among the most used features in the product.

Adobe’s management believes that Adobe Express’s generative AI capabilities are driving adoption of the product

 The family of generative capabilities across Express, including text to image, text effects, text to template and generative fill are driving adoption of Express and making it even faster and more fun for users of all skill levels.

Adobe’s management is seeing high level of excitement among customers for the Firefly integrations across Adobe’s product suite

Customer excitement around Firefly integrations across our applications has been great to see with community engagement, social interactions and creative marketing campaigns driving organic brand search volume, traffic and record demand. 

Adobe’s management expects generative AI features to deliver additional value and attract new customers to Adobe’s Document Cloud suite of products; generative AI capabilities for Document Cloud is now in private beta, with a public beta to come in the next few months and general availability (GA) to arrive later in 2024

Much like the Creative business, we expect generative AI to deliver additional value and attract new customers to Document Cloud. Acrobat’s generative AI capabilities, which will enable new creation, comprehension and collaboration functionality have already been rolled out in a private beta. We expect to release this in a public beta in the coming months…

…What we’re really excited about as we bring the AI assistant to market, which, by the way, as I mentioned, is now in private beta. Expect it to come out in the next few months as a public beta and then GA later in the year.

Adobe’s management is focusing Adobe’s generative AI efforts within its Experience Cloud suite of products in three areas: (1) Building an AI assistant, (2) reimagining Experience Cloud’s existing applications, and (3) creating new generative AI solutions

Generative AI accelerates our pace of innovation across the Experience Cloud portfolio, enabling us to build on our capabilities to deliver personalized digital experiences. Our efforts are focused in 3 areas: one, augmenting our applications with an AI assistant that significantly enhances productivity for current users and provides an intuitive conversational interface to enable more knowledge workers to use our products; two, reimagining existing Experience Cloud applications like we did with Adobe Experience Manager; and three, developing entirely new solutions built for the age of generative AI like Adobe GenStudio.

Adobe’s management recently released Adobe GenStudio, a solution with generative AI capabilities that combines Creative Cloud, Express, and Experience Cloud, to help brands create content; Adobe GenStudio is seeing tremendous customer interest

Release of Adobe GenStudio, an end-to-end solution that brings together best-in-class applications across Creative Cloud, Express and Experience Cloud with Firefly generative AI at the core to help brands meet the rising demand for content. GenStudio provides a comprehensive offering spanning content ideation, creation, production and activation. We are seeing tremendous interest in GenStudio from brands like Henkel, Pepsi and Verizon and agencies like Publicis, Omnicom and Havas as they look to accelerate and optimize their content supply chains.

Adobe now has a pilot program where some customers are able to bring their own assets and content to extend Adobe’s Firefly models in a custom way; Adobe is exposing Firefly through APIs to that customers can build Firefly into their workflows; Adobe is enabling users to integrate Firefly-generated-content into a holistic Adobe workflow

So with Firefly and Express, very excited about the momentum that we continue to see. You heard that we crossed 4.5 billion generations now so we continue to see really, really strong adoption and usage of it, partially as a stand-alone business but also integrated into our Photoshop and Illustrator and these existing workflows.

And we’re starting to see a lot of interest not just in the context of using it as part of the existing products but also using it as part of the ecosystem within enterprises. So we’ve been working with a number of customers to not just enable them with Firefly, which is the predominance of the growth that we’re seeing in Q4 for enterprise adoption but also have a number of pilot customers already engaged around custom model extensions so that they can bring their own assets and their own content into what Firefly generates.

Second, we’re also enabling the ability to expose it through APIs so they can build it into their existing workflows. And third, we’re, of course, connecting it and tying it all into Adobe Express, which now also has its own Firefly and additional capabilities like things so that you can not just sort of create content using Firefly but then start to assemble it, start to schedule social posts around it, start to do multi-language translations, that those are all features that are already in there and then create a stakeholder workflow from people working in Photoshop to the marketers that are trying to post externally. So that’s where things get very interesting and exciting in terms of the connection we have with GenStudio and everything that Anil is doing.

Adobe’s management intends to improve the generative capabilities over time, which might be more expensive in terms of the generative credits consumed, and management believes this will help drive Adobe’s growth over time

But what will happen over the course of the year and the next few years is that we will be integrating more and more generative capabilities into the existing product workflows. And that will drive — and we’ll be integrating capabilities like video generation, which will cost more than 1 generation, and that will drive a natural inflation in that market and that will become a driver for growth subsequently. 

Adobe’s management believes that Firefly is a great on-ramp for Adobe Express, and a great catalyst for all of Adobe’s products across the spectrum (the same underlying generative AI technology is also a great catalyst for Adobe’s Document Cloud business)

And that sort of brings them as an on-ramp into Express, which would be the other part. Express is certainly the introductory pricing, the ability to get millions more into the fold. And the ability right now, it used to be that Express and other offerings in that is to all worry about do I have the right templates? Well, AI is going to completely change that. We have our own models. And so Firefly will allow anybody to take whatever creative idea that they have and make that available. So I think Firefly really helps with the Express offering.

On the Creative Cloud, David mentioned this. I mean, if you look at the adoption of that functionality and usage that’s being driven, whether it’s in Photoshop right now, Illustrator, as we add video, both in terms of providing greater value, and we certainly will, therefore, have the uplift in pricing as well as the retentive ability for Firefly, that’s where I think you’re going to see a lot of the really interesting aspects of how Firefly will drive both adoption as well as monetization.

And then if you go at the other end of the spectrum to the enterprise, GenStudio, every single marketer that I know and CFO and CMO are all worried about how much am I spending on data? How do I get agility in my campaigns? And the fact that Firefly is integrated into both Express as well as when we do the custom models for them so they can upload their own models and then have the brand consistency that they want. So Firefly really is the fact that we have our own models, a great catalyst for business all across the spectrum…

… And then you take the same technology that we have in Creative and think about its impact in both Document Cloud when we do that and the ability to have summaries and have conversational interfaces with PDF, thereby making every single PDF, as David again said, both for communication, collaboration and creation far more compelling. I think you’re going to see that same kind of uplift in usage and therefore, monetization on the Acrobat side.

DocuSign (NASDAQ: DOCU)

DocuSign’s management will be introducing generative AI enhancements to its CLM (Contract Lifecycle Management) platform; Veeco was an eSignature customer that has started using CLM, and DocuSign’s AI CLM features will help Veeco with surfacing actionable insights from customer contracts

CLM continues to grow well, particularly with North American enterprise customers. And for the fourth year in a row, our CLM solution was recognized as a leader by Gartner in contract life cycle management, noting our strong market understanding, product strategy and road map vision, including upcoming Generative AI enhancements. This quarter, we expanded a relationship that began more than 5 years ago with Veeco USA. Who’s the leader in workplace innovation. Veeco began using DocuSign eSignature and has added CLM as part of this transformation into a digital services company. Our AI solution will help Veeco streamline and enhance search and review of executed customer contracts with actionable insights to better serve its customers

MongoDB (NASDAQ: MDB)

MongoDB’s management held a customer feedback session recently and they saw four themes that emerged from the conversations, one of which was that customers of all sizes are interested in AI

This quarter, we held our most recent global Customer Advisory Board meeting where customers across various geographies and industries came together to share feedback and insight about the experience using MongoDB. From these discussions as well as our ongoing C-suite dialogue with our customers, a few themes emerge. First, AI is in nearly every conversation with customers of all sizes.

MongoDB’s management is seeing great early feedback from MongoDB’s partnership with AWS CodeWhisperer; MongoDB’s management also thinks that Microsoft Github Copilot is capable of generating useful code

We’re seeing great early feedback from our partnership with AWS’ CodeWhisperer, the AI-powered footing companion that is now trained on MongoDB data to generate codesuggestions based on MongoDB’s best practices from over 15 years of history. Microsoft GitHub Copilot is also proficient at generating code suggestions that reflect best practices in developers to build highly performant applications even faster on MongoDB.

MongoDB’s management is seeing software developers being asked to also build AI functionalities into their applications

And with the recent advances in Gen AI, building applications is no longer the sole domain of AI/ML experts. Increasingly, it’s software developers who are being asked to build powerful AI functionality directly into their applications. We are well positioned to help them do just that.

MongoDB’s Atlas Vector Search – the company’s AI vector search feature – recently received the highest NPS (net promoter score) among vector databases from developers; crucially, the NPS survey was done on the preview version of Vector Search and not even on the generally available version, which is better

In a recent state of AI survey reported by Retool, Atlas Vector Search received by far the highest Net Promoter Score from developers compared to all other vector databases available…

……As I said in the prepared remarks, there was a recent analysis done by a consultancy firm called [ Retool ] that really spoke to lots of customers, and we came out of top on — in terms of NPS. And by the way, our product was a preview product. It wasn’t even the GA product. 

MongoDB’s Atlas Vector Search allows developers to combine vector searches with another kind of search capabilities available in MongoDB, resulting in the ability to run very complex queries

Moreover, developers can combine vector search with any other query capabilities available in MongoDB, namely analytics, tech search, geospatial and time series. This provides powerful ways of defining additional filters on vector-based queries that other solutions just cannot provide. For example, you can run complex AI and rich queries such as “find pants and shoes in my size that look like the outfit in this image within a particular price range and have free shipping” or “find real estate listings with houses that look like this image that were built in the last 5 years and are in an area within 7 miles west of downtown Chicago with top-rated schools.”

MongoDB’s Atlas Vector Search allows customers to scale nodes independently, which gives customers the ability to achieve the right level of performance at the most efficient cost, so management thinks this is a very compelling value proposition for customers

One of the announcements we also made was that you can now do workload isolation. So for search or vector search functionality, you can scale those nodes independently of your overall cluster. So what that really does is allow customers to really configure their clusters to have the right level of performance at the most efficient cost. So we’ve been very sensitive on making sure that based on the different use cases, you can scale up and down different nodes based on your application needs. So by definition, that will be a very compelling value proposition for customers…

…[Question] With Vector Search comes quite a bit more data. So how are you making sure that customers don’t receive a surprise bill and end up unhappy?

[Answer] In terms of your question around the amount of data and the data builds, obviously, vectors can be memory-intensive. And the amount of vectors you generate will obviously drive the amount of usage on those nodes. That’s one of the reasons we also introduced dedicated search nodes so you can asymmetrically scale particular nodes of your application, especially your search nodes without having to increase the overall size of your cluster. So you’re not, to your point, soft for the big bill for underlying usage, for nonusage right? So you only scale the nodes that are really need that incremental compute and memory versus nodes that don’t, and that becomes a much more cost-effective way for people to do this. And obviously, that’s another differentiator for MongoDB.

MongoDB’s management believes that customers are aware that their legacy data infrastructure is holding them back from embracing AI (legacy data infrastructure do not allow customers to work with real-time data for AI purposes) but the difficulty in modernising the infrastructure is daunting for them; MongoDB’s management thinks that the modernisation of data infrastructure for AI is still a very early trend but it will be one of the company’s largest long-term opportunities

They are aware that their legacy platforms are holding them back from building modern applications designed for an AI future. However, customers also tell us that they lack the skills and the capacity to modernize. They all want to become modern, but daunted by the challenges as they are aware it’s a complex endeavor that involves technology, process and people. Consequently, customers are increasingly looking to MongoDB to help them modernize successfully…

… There is a lot of focus on data because with AI. Data in some way, it becomes a new code, you can train your models with your proprietary data that allows you to really drive much more value and build smarter applications. Now the key thing is that it’s operational data because with applications, this data is always constantly being updated. And for many customers, most of those applications are right now running on legacy platforms so that operational data is trapped in those legacy platforms. And you can’t really do a batch process of e-tailing all that data into some sort of warehouse and then still able to leverage the real-time use of that data. That’s why customers are now much more interested in potentially modernizing these legacy platforms than they ever have before…

…I would say it’s still very, very early days, we definitely believe that this will be one of the largest long-term opportunities for our business. we’re in the very early days.

MongoDB’s management has launched Query Converter, which uses AI to convert a customer’s existing SQL-related workflows to work with MongoDB’s NoSQL database platform, and customers have tried it out successfully

We launched Relational Migrator earlier this year to help customers successfully migrate data from their legacy relational databases to MongoDB. Now we’re looking beyond data migration to the full life cycle of application modernization. At our local London event, we unveiled the query converter, which uses genetic AI to analyze existing SQL queries and store procedures and convert them to work with MongoDB’s query API. Customers already tooled successfully to convert decades-old procedures to modernize their back-end with minimal need for manual changes.

MongoDB’s management thinks it’s too early to tell how the usage of MongoDB’s AI features by customers will impact MongoDB’s gross margin at maturity

[Question] And then the follow-up is more it’s around AI. So if I look at the demos that you guys have around vector search and how search is getting a lot better, that seems very compelling. And it seems like really straightforward for our clients to improve their the customer experience that they use it for a customer facing up, for example. What is the — what are the implications for gross margins for you, Michael, like do you have to do a lot more computer to be able to handle it?

[Answer] So I think it’s a little too early to tell. There’s obviously plenty of variability in the workloads depending on the nature what the underlying application is. So I think it’s a little early to give a strong direction to that… But I think too early to make a specific call or quantification on the gross margin impacts of AI.

MongoDB’s management thinks that Atlas Vector Search will be a big opportunity for MongoDB, but it’s early days and they find it hard to exactly quantify the revenue opportunity

We’ve seen a lot of demand from customers. And we feel like this is a big, big opportunity. Again, it’s early days. It’s going to take time to materialize, but this is, again, one of the other big growth opportunities for our business. That being said, in terms of the revenue opportunity, it’s really hard to quantify now because the use cases that customers are starting with are still kind of, I would say, early intent because people are still playing around with the technology. But we are seeing, as I mentioned, in UKG is using it to essentially provide an AI-powered assistant for its people. One Energy, European energy company is using terabytes of geospatial data and is using vectors to basically get better insights in terms of the images that they’re getting from the work they’re doing in terms of drilling for oil. So it’s still very, very early days. So hard to give you like an exact numbers.

When it comes to copilot tools for software coding, MongoDB’s management is seeing varying levels of productivity improvement for software developers based on the tools they are using; MongoDB’s management also sees the software written with copilots as being mostly for internal use currently

[Question] As customers began to trial some of these copilot code tools will say. What type of feedback have you gotten from them as it relates to the pace with which they’ve been able to reduce net new workload time to market, how much faster or efficient are customers getting using these tools?

[Answer] We get different answers from a lot of different customers. It really depends on which tool they’re using. Without commenting on who’s better, who’s worse, we definitely see a difference in the quality of the output between the different tools. I think it’s going to take some time for these tools to mature. So I think you’re seeing a lot of customers do a lot of testing and prototyping. I would also tell you that they’re doing a lot of this on internal-facing applications because there’s still lots of questions about IP rights and what is potentially copyrightable and then help to be licensable if they offer this as a shrink-wrap software or service to their end customers. So we’re seeing more of this work on internally facing applications but the productivity gains really do vary by tool and all the very do vary by the sophistication of the app being built. So it’s hard for me to give you a real number. I know there’s people out there quoting 30% or 40% improvement. But it really depends on the customer and the use case and tool that they’re trying to use.

MongoDB’s CEO, Dev Ittycheria, thinks his views – that (1) vector search would become just another functionality in a more holistic database platform, and (2) the database platform that can integrate vector search functionality well into developers’ workflow will win – has played out

I would say that I think 6, 9 months ago, there was a lot of interest in vector databases and there were some point solutions that got a lot of name recognition and a lot of people are wondering, is there a risk that we could be disrupted by them? And at that point in time, we made it clear that we believe vectors, we’re really another form of an index and that every database platform would ultimately incorporate vectors into their architecture. And the winner really would be the technology that made the vector functionality very integrated and cohesive as part of the developer workflow. I would argue that it’s really played out. 

MongoDB’s management saw customers having to work with two databases when performing vector searches for AI purposes; these customers were asking MongoDB to bring vector search capabilities into its database platform because working with one platform helps customers speed up their work and reduce costs

One of the reasons we actually built search is because we got feedback from our customers in many instances, a lot of our customers were dual homing data to MongoDB and to some sort of search database. So consequently, not only had to manage 2 databases, keep that data in sync, but also manage the plumbing that connected those 2 database platforms and customers told us they much would — this is like we don’t understand why you’re not offering a solution because we much rather have it all in one platform with one API. And that ultimately drove our desire to build out our search functionality, which is really becoming more and more popular. So the point for customers is that if you can remove friction in terms of how they can use the platform leverage the platform, have one set of kind of semantics in terms of — to address a broad set of use cases, it really simplifies the data architecture. And the more you simplify data architecture, the more nimble you can be and the more cost-effective you can be, and that’s what’s really resting with customers.

Okta (NASDAQ: OKTA)

Okta’s management introduced Okta AI during the company’s Oktane event in October; Okta AI is powered by the data that Okta has collected over the years from its 18,800 customers and 7,000+ integrations, and is infused into several of Okta’s products

The headline of the event was the introduction of Okta AI, the identity solution for the next era of computing. Okta AI is AI for Identity. It’s powered by the massive amounts of data the company has accumulated over the years, including anonymized insights crowdsourced from our 18,800 customers and the 7,000+ integrations in the Okta Integration Network, as well as data on usage, policies, threats, and risk signals. Okta AI uses that data to perform powerful, real-time security, developer, and policy actions. Okta AI is also infused into several of our products. It makes our existing products more valuable and new products possible — all while expanding what it means to be integrated and protected.

An example of Okta AI at work is Identity Threat Protection, which enables companies to automatically log users out of apps during a security issue

Identity Threat Protection with Okta AI, a new product that will enable businesses to prevent and respond to threats faster than ever before. It empowers organizations to automate the detection and remediation of Identity threats across the tech ecosystem. It extends adaptive risk evaluation from the point of authentication to any time a user is logged in and helps you quickly prevent and respond to threats. Identity Threat Protection allows for an array of powerful new actions like Universal Logout. For the first time in our industry, it’s possible to automatically log users out of their apps during a security issue. Threat actors might be getting more sophisticated, but we are using the power of AI and our ecosystem to keep our customers safe and a step ahead.

Salesforce (NYSE: CRM)

Salesforce’s management thinks Data Cloud’s introduction was great timing because it coincided with the boom in generative AI and a company can’t make AI useful without data

And Data Cloud, this hyperscale, this real-time customer data platform that is performing incredibly well for us, it’s the foundation of every AI transaction, but it’s the foundation of every large deal that we did this quarter. That is what is so exciting. And in just our third quarter, Data Cloud has ingested an astonishing 6.4 trillion records, 6.4 trillion records. That’s 140% year-over-year increase. It triggered 1.4 trillion activations, a 220% increase year-over-year. This is a monster product. I could not be more excited. And it’s the perfect time, we didn’t really understand that it was going to line up so well with this generative AI revolution. It’s a product we’ve been working on for a couple of years. Just the timing of it has been incredible because listen, if you don’t have your data together, in a company, you’re not going to deliver AI. It’s not like companies are going to run their AI off of Reddit or off of some kind of big public data set. They have to have their data set together to make AI work for them, and that is why the Data Cloud is so powerful for them

Salesforce’s management believes that Salesforce is the No.1 AI CRM and is leading the industry in the current AI innovation cycle; they also believe that the current cycle is unlike anything they have ever seen and it’s a view that’s shared widely

We are the #1 AI CRM. If that isn’t clear already, we’re leading the industry through the unprecedented AI innovation cycle. It’s unlike anything I’ve seen and most of the people that I talk to all over the world feel the same way. 

Salesforce’s management believes that trust is going to be important in the AI era and Salesforce will be protecting customer data with a trust layer so that the data can’t be easily accessed by 3rd-party foundation models

Now as I’ve said before, this AI revolution is going to be a trust revolution. It’s not just about CRM, data or AI. It’s also about trust. And I think the trust layer and the way that we’ve architected our platform so that our customers are not basically taking — getting taken advantage of these next-generation large language models, these foundation models, they are so hungry for all of this data, and they want our customers’ data so that they can grow. We’re not going to let them have it. We’re going to separate ourselves from those models through a trust layer so customers can be protected. This is going to be so important for the future of how Salesforce architects itself with artificial intelligence.

Salesforce’s management is seeing customers across the world wanting to invest in AI for more productivity; management also travelled the world and noticed that customers are very excited about AI but at the same time, they are confused about AI’s capabilities – this excitement was not in place a year ago because generative AI apps had not surfaced yet

I’ve been on the road pretty much nonstop especially over the last month. I’ve been in — throughout Europe. I’ve been now in Asia. I’ve been throughout the United States. And I just continue to see these same trends, which is customers are investing for the future and they’re investing and inspired by AI to give them more productivity. Look, they realize unemployment is just so low. Where are they going to hire more people? It’s so hard for them to hire, they’re going to have to get more productivity from their employees. They’re going to do that through this great new technology, and we’re going to help them make that happen…

…And on a global basis, and like I said, in some of these customers in the last 30 days, I was in — I can give you my direct experience. I was in San Francisco, Los Angeles, Las Vegas, Stuttgart, Germany, I was in Nice, Monaco. I visited with our customers throughout that area. And also, I went up to Amsterdam, to France. I had a large customer dinner in the U.K. in London. I went to the U.K. Safety Summit. I then came back and went to Japan. I think I see something very consistently, which is customers are extremely excited about AI everywhere we go. It could be government, it could be commercial organizations. It could be technologists. Everyone is excited about AI. At the same time, there is a lot of confusion about what AI can and cannot do…

… And this excitement, this energy, these ideas of innovation of AI were not in place a year ago. Because don’t forget, a year ago, I don’t think any of us have used ChatGPT or Bard or Anthropic or Cohere or Adapt or any of the new AI companies. None of us had really had our hands on or envisioned what it really meant to us or that we would have Copilots, and that those Copilots would give us the ability to do all kinds of next-generation capabilities. But a year later, it’s a technology revolution. 

Salesforce has been deploying its own generative AI tools at a quick pace and management thinks the results have been excellent

I’ve been impressed with how quickly we deployed our own trusted generative AI tools and applications internally. We’ve launched Sales, GPT and Slack Sales, Elevate internally, and our global support team is live with Service GPT, and we’re seeing incredible results. We’ve streamlined our quoting process with automation, eliminating over 200,000 manual approvals so far this year. And since the introduction in September, our AI-driven chatbot has autonomously resolved thousands of employee-related queries without the need for human involvement.

Salesforce’s management thinks that every customer’s AI transformation is going to begin and end with data 

What I’ll tell you is you’re seeing something that we have been seeing and calling out for the last few quarters, but we probably have not been able to illuminate it to the level that you see now in the numbers, which is that every customer and every customer transformation and every customer AI transformation is going to begin and end with data. And for us to achieve that goal, those customers are going to have to get to another level of excellence with their data. 

Salesforce’s management thinks that there’s still a lot that AI-companies need to do to make AI safe for customers, but it’s getting better over time

We have — we still have a lot of work, as everyone does in our industry, on AI and making it safe for our customers. This is going to be incredibly important. I think for a lot of customers, they realize that they’d like to just let this AI unleashed autonomously but it still hallucinates a huge amount and it also is quite toxic. So we’re not quite ready for that revolution. But every day, it’s getting a little better. 

Salesforce’s management thinks that the movie Minority Report contains a good scene on how AI can be used to automate the personalised customer experience – management also thinks that this is something that many of Salesforce’s customers want to achieve for their own customer experience

And when I — going through the streets of Tokyo, it’s not quite the minority report, which is a movie that was partly written by our futurist, Peter Schwartz, but it’s getting closer to that idea. And when I walked into some of these stores, there’s definitely a lot more automation based on my customer record but not quite the level of automation that Tom Cruise felt when he walked into that Gap store, if you remember that scene, which was so amazing, which is very much front of mind for a lot of our customers because they want to have that capability and they want us to deliver that for them.

Salesforce’s management explained how Data Cloud can be very useful for companies that are deploying AI: Companies can use their own data, via Data Cloud, to augment generative AI models to produce personalised and commercially-useful output that otherwise could not be done

But they’re going to get frustrated when the Copilot that they are given from other companies don’t have any data. They just have data grounded to maybe the application that’s sitting in front of them, but it doesn’t have a normalized data framework on — integrated into the Copilot. So while I think Copilots on productivity applications are exciting because you can tap into these kind of broad consumer databases that we’ve been using. So as an example, the Copilot is I’m writing an e-mail. So now my — I’m saying to the copilot, hey, now can you rewrite this email for me or some — make this 50% shorter or put it into the words of William Shakespeare. That’s all possible and sometimes it’s a cool party trick.

It’s a whole different situation when we say, “I want to write an e-mail to this customer about their contract renewal. And I want to write this e-mail, really references the huge value that they receive from our product and their log-in rates. And I also want to emphasize how the success of all the agreements that we have signed with them have impacted them, and that we’re able to provide this rich data to the Copilot and through the prompt and the prompt engineering that is able to deliver tremendous value back to the customer.” And this date, this customer value will only be provided by companies who have the data. And we are just very fortunate to be a company with a lot of data. And we’re getting a lot more data than we’ve ever had. And a lot of that is coming from the Data Cloud because it’s amplifying the capabilities of all the other data we have. 

Salesforce’s management thinks that there will be significant improvements to Salesforce’s AI features in the near future

I think the demonstrations at Dreamforce were outstanding. The demonstrations that we’ll deliver in our February release will be mind-boggling for our customers of what they will be able to get done. And I think that by the time we get to Dreamforce ’25 or ’24 in September ’24, what we’ll see is nothing that we could have possibly imagined just 24 months earlier before these breakthroughs in generative AI have really taken hold through the whole industry.

Salesforce’s management thinks that no single company will control the development of AI because they think that open source AI models are now as strong as proprietary models and will lead the way; management also thinks that unlike the development of mobile operating systems which is controlled by 2 companies, there are thousands of companies that are working on open-source AI and this will lead to rapid innovation

No one company has a hold on this. I think it’s pretty clear at this point that because of the way AI is built through open source, that these models are very much commodity models, and these responses are very much commodity responses. So we’ve always felt that way about AI for more than a decade. We said that its growth has really been amplified by open source development. Because these open source models now are as strong as commercial models are or proprietary models, I think that what we really can see is that, that is going to accelerate this through every customer. There’s not going to be any kind of restrictions because of the proprietariness or the cost structures of these models. We’re going to see this go much faster than any other technology.

The reference point, as I’ve been using as I travel around, is really mobile operating systems. Mobile operating systems are very important, and we all have one on our desk or in our pocket right now. But really, the development of mobile operating systems has been quite constrained because they’re really held mostly by 2 companies and 2 sets of engineering teams. That’s not how this technology is being built. This technology is highly federated across thousands of companies and thousands of engineering teams who are sharing this technology. And because of that, you’re ending up with a rate of innovation unlike anything we’ve seen in the history of our industry and is moving us into areas very quickly that could become uncomfortable. So this is an exciting moment.

Veeva Systems (NYSE: VEEV)

Veeva’s management has not seen a big impact on the clinical side of Veeva’s business from generative AI

In terms of the generative AI, honestly, I haven’t seen a big impact in clinical. There was good experimentation and projects around helping to write or evaluate protocols, for example, but not using things like generative AI to do statistical analysis or predict where the patients are. I think there, the more appropriate tool which people are using and continue to use more and more data science. Really having the right data, running the right algorithms, being systematic about it. So yes, I just haven’t seen that impact of generative AI. You see it more in other areas that relate to content creation and asking of questions, writing safety narratives, things like 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. I have a vested interest in Adobe, DocuSign, MongoDB, Okta, Salesforce, and Veeva Systems. Holdings are subject to change at any time.

The Opportunities and Risks In The US Stock Market

Earlier this week, on 12 December 2023, I was invited for a short interview on Money FM 89.3, Singapore’s first business and personal finance radio station. My friend Willie Keng, the founder of investor education website Dividend Titan, was hosting a segment for the radio show and we talked about a few topics concerning the US stock market:

  • Context on the US stock market’s strong performance so far in 2023 (Hint: Investors should not be surprised by the 20%-plus year-to-date gain in the S&P 500 because the index has historically been more likely to produce a gain of 20% or more in a calendar year than to experience a loss)
  • The impact on US stocks from a potential interest rate cut by the Federal Reserve (Hint: US stocks have historically tended to fall over a 1-year period after interest rate cuts, but it’s hard to say if a similar decline will happen again if the Fed does cut rates in 2024, since how stocks react will also depend on the reason for any interest rate cuts)
  • The risks of investing in the US stock market right now (Hint: The world we live in today is no less risky compared to yesterday, or a month ago, or a year ago, or even 10 years ago – the only thing that changes is our perception on the level and the types of risk that the world is facing. Instead of thinking about specific risks, it’s far more important to introduce elements of anti-fragility into our portfolios)
  • The opportunities I see in US stocks (Hint: Meta Platforms has overcome the key problems that were plaguing its business over the past year, and currently has an undemanding valuation) 

You can check out the recording of our conversation below!

Notes (where my data on US market history was sourced from):


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. I have a vested interest in Meta Platforms. Holdings are subject to change at any time.

Lessons From The Immortal Charlie Munger

Neuroscientist David Eagleman once wrote: “There are three deaths: the first is when the body ceases to function. The second is when the body is consigned to the grave. The third is that moment, sometime in the future, when your name is spoken for the last time.”

Along Eagleman’s line of reasoning, Charlie Munger, who passed away peacefully last night, would be immortal since he would never experience the third death – his accomplishments, and the wisdom he has shared throughout his life, would see to it. 

Munger is one of my investing heroes. In remembrance of his life, I would like to share my favourite lessons from him.

On the importance of thinking in reverse, or inverting

“Another idea that I discovered was encapsulated by that story Dean McCaffery recounted earlier about the rustic who wanted to know where he was going to die, so he wouldn’t go there. The rustic who had that ridiculous sounding idea had a profound truth in his possession. The way complex adaptive systems work, and the way mental constructs work, problems frequently become easier to solve through inversion. If you turn problems around into reverse, you often think better. For instance, if you want to help India, the question you should consider asking is not: How can I help India? Instead, you should ask: How can I hurt India? You find what will do the worst damage, and then try to avoid it. Perhaps the two approaches seem logically the same thing. But those who have mastered algebra know that inversion will often and easily solve problems that otherwise resist solution. And in life, just as in algebra, inversion will help you solve problems that you can’t otherwise handle.”

On the importance of being equanimous when investing

“If you’re not willing to react with equanimity to a market price decline of 50% two or three times a century you’re not fit to be a common shareholder and you deserve the mediocre result you’re going to get compared to people who do have the temperament, who can be more philosophical about these market fluctuations.”

On the importance of incentives

“From all business, my favourite case on incentives is Federal Express. The heart and soul of their system – which creates the integrity of the product – is having all their airplanes come to one place in the middle of the night and shift all the packages from plane to plane. If there are delays, the whole operation can’t deliver a product full of integrity to Federal Express customers. And it was always screwed up. They could never get it done on time. They tried everything – moral suasion, threats, you name it. And nothing worked. Finally, somebody got the idea to pay all these people not so much an hour, but so much a shift – and when it’s all done, they can go home. Well, their problems cleared up overnight.”

On great career advice

“Three rules for a career: (1) Don’t sell anything you wouldn’t buy yourself; (2) Don’t work for anyone you don’t respect and admire; and (3) Work only with people you enjoy.”

On the importance of admitting mistakes

“There’s no way that you can live an adequate life without many mistakes. In fact, one trick in life is to get so you can handle mistakes. Failure to handle psychological denial is a common way for people to go broke.”

On the importance of not letting rare events completely shape how you approach life

“Ben Graham had a lot to learn as an investor. His ideas of how to value companies were all shaped by how the Great Crash and the Depression almost destroyed him… It left him with an aftermath of fear for the rest of his life, and all his methods were designed to keep that at bay.”

On the importance of handling problems from many different angles

“Most people are trained in one model – economics, for example – and try to solve all problems in one way. You know the saying: “To the man with a hammer, the world looks like a nail.” This is a dumb way of handling problems.”

On the importance of getting a little wiser each day

“I constantly see people rise in life who are not the smartest, sometimes not even the most diligent, but they are learning machines. They go to bed every night a little wiser than they were when they got up, and boy, does that help, particularly when you have a long run ahead of you.”

On how to invest

Over the long term, it’s hard for a stock to earn a much better return than the business which underlies it earns. If the business earns 6% on capital over 40 years and you hold it for that 40 years, you’re not going to make much different than a 6% return—even if you originally buy it at a huge discount. Conversely, if a business earns 18% on capital over 20 or 30 years, even if you pay an expensive looking price, you’ll end up with a fine result. So the trick is getting into better businesses. And that involves all of these advantages of scale that you could consider momentum effects.”

On how to get others to agree with you

“Well, you’ll end up agreeing with me because you’re smart and I’m right.”

On the secret to a happy life

“I always say the same thing: realistic expectations, which is low expectations. If you have unreasonable demands on life, you’re like a bird that’s trying to destroy himself by bashing his wings on the edge of the cage. And you really can’t get out of the cage. It’s stupid. You want to have reasonable expectations and take life’s results good and bad as they happen with a certain amount of stoicism.”

On courage and perseverance

I saved the most poignant lesson I’ve learned from Munger for the last. Not many may know this, but the first decade-plus of Munger’s adulthood was tragic. 

Munger got married when he was 21, but the marriage ended when he was 29. He “lost everything in the divorce”, according to his daughter Molly Munger. Shortly after the divorce, Munger’s son, Teddy Munger, was diagnosed with leukaemia. “In those days, there was no medical insurance – I just paid all the expenses” Munger once said. But more importantly, there was absolutely nothing doctors back then could do for leukaemia. When Munger was 31, Teddy passed on. Munger recounted the heart-wrenching episode: “I can’t imagine any experience in life worse than losing a child inch by inch. By the time he died, my weight was down 10 to 15 pounds from normal.” One of Munger’s friends, Rick Guerin, said that “when his [Munger’s] son was in the bed and slowly dying, he’d go in and hold him for awhile, then go out walking the streets of Pasadena crying.”

So by the time Munger was 31, he had already gone through a divorce, experienced the painful death of his son from an incurable disease, and was broke. 

But when Munger left the world last night, he was a billionaire, and was widely revered around the world for his wit, wisdom, and character. He taught me that with courage and perseverance, we can eventually build a better life for ourselves. “You should never, when faced with one unbelievable tragedy, let one tragedy increase into two or three because of a failure of will,” he admonished. 

See you on the other side, Mr Munger.