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

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

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

Here are the articles for the week ending 18 April 2021:

1. How People Get Rich Now – Paul Graham

In 1982, there were two dominant sources of new wealth: oil and real estate. Of the 40 new fortunes in 1982, at least 24 were due primarily to oil or real estate. Now only a small number are: of the 73 new fortunes in 2020, 4 were due to real estate and only 2 to oil.

By 2020 the biggest source of new wealth was what are sometimes called “tech” companies. Of the 73 new fortunes, about 30 derive from such companies. These are particularly common among the richest of the rich: 8 of the top 10 fortunes in 2020 were new fortunes of this type…

…The tech companies behind the top 100 fortunes also form a well-differentiated group in the sense that they’re all companies that venture capitalists would readily invest in, and the others mostly not. And there’s a reason why: these are mostly companies that win by having better technology, rather than just a CEO who’s really driven and good at making deals.

To that extent, the rise of the tech companies represents a qualitative change. The oil and real estate magnates of the 1982 Forbes 400 didn’t win by making better technology. They won by being really driven and good at making deals. And indeed, that way of getting rich is so old that it predates the Industrial Revolution. The courtiers who got rich in the (nominal) service of European royal houses in the 16th and 17th centuries were also, as a rule, really driven and good at making deals…

…Why are people starting so many more new companies than they used to, and why are they getting so rich from it? The answer to the first question, curiously enough, is that it’s misphrased. We shouldn’t be asking why people are starting companies, but why they’re starting companies again.

In 1892, the New York Herald Tribune compiled a list of all the millionaires in America. They found 4047 of them. How many had inherited their wealth then? Only about 20% — less than the proportion of heirs today. And when you investigate the sources of the new fortunes, 1892 looks even more like today. Hugh Rockoff found that “many of the richest … gained their initial edge from the new technology of mass production.”

So it’s not 2020 that’s the anomaly here, but 1982. The real question is why so few people had gotten rich from starting companies in 1982. And the answer is that even as the Herald Tribune’s list was being compiled, a wave of consolidation was sweeping through the American economy. In the late 19th and early 20th centuries, financiers like J. P. Morgan combined thousands of smaller companies into a few hundred giant ones with commanding economies of scale. By the end of World War II, as Michael Lind writes, “the major sectors of the economy were either organized as government-backed cartels or dominated by a few oligopolistic corporations.”

In 1960, most of the people who start startups today would have gone to work for one of them. You could get rich from starting your own company in 1890 and in 2020, but in 1960 it was not really a viable option. You couldn’t break through the oligopolies to get at the markets. So the prestigious route in 1960 was not to start your own company, but to work your way up the corporate ladder at an existing one.

Making everyone a corporate employee decreased economic inequality (and every other kind of variation), but if your model of normal is the mid 20th century, you have a very misleading model in that respect. J. P. Morgan’s economy turned out to be just a phase, and starting in the 1970s, it began to break up.

Why did it break up? Partly senescence. The big companies that seemed models of scale and efficiency in 1930 had by 1970 become slack and bloated. By 1970 the rigid structure of the economy was full of cosy nests that various groups had built to insulate themselves from market forces. During the Carter administration the federal government realized something was amiss and began, in a process they called “deregulation,” to roll back the policies that propped up the oligopolies.

But it wasn’t just decay from within that broke up J. P. Morgan’s economy. There was also pressure from without, in the form of new technology, and particularly microelectronics. The best way to envision what happened is to imagine a pond with a crust of ice on top. Initially the only way from the bottom to the surface is around the edges. But as the ice crust weakens, you start to be able to punch right through the middle.

The edges of the pond were pure tech: companies that actually described themselves as being in the electronics or software business. When you used the word “startup” in 1990, that was what you meant. But now startups are punching right through the middle of the ice crust and displacing incumbents like retailers and TV networks and car companies…

…But there’s also a third factor at work: the companies themselves are more valuable, because newly founded companies grow faster than they used to. Technology hasn’t just made it cheaper to build and distribute things, but faster too.

This trend has been running for a long time. IBM, founded in 1896, took 45 years to reach a billion 2020 dollars in revenue. Hewlett-Packard, founded in 1939, took 25 years. Microsoft, founded in 1975, took 13 years. Now the norm for fast-growing companies is 7 or 8 years.

2. Twitter thread on the corporate culture in Amazon and Facebook – Dan Rose

What defines a great company culture? I worked for two iconic companies and founders with nearly polar opposite cultures. Amazon was heads-down, secretive, forthright. Facebook was open, transparent, collaborative. Here’s what I learned about culture working for Bezos and Zuck:

Culture implicitly sets expectations for behavior. Strong cultures are well-defined with sharp edges, and well-understood by everyone in the organization top to bottom. Strong founders with unapologetic personalities set the culture early and maintain it as the company scales.

When I joined Amzn in 1999, we had top-secret teams working on new products like Auctions, Toys and Electronics. Before a product launched, the only people in the know were those who needed to know. Everyone else was told to keep their heads down and focus on their own work…

…There’s nothing wrong with a heads-down culture where employees are told to focus on their own work. It provides guardrails, avoids distractions, sets a serious tone. And yet, there is a certain distrust in telling employees to mind their own business. The knife cuts both ways.

When I joined FB in 2006, I was shocked at how much Zuck shared with the company. I advised him to share less to avoid leaks. His response: “I’m building a company that I would want to work for if I hadn’t started FB. And I would want to work at a place that shares openly.”

FB’s open culture mapped to Mark’s personality and a generational shift in employee expectations. It also mapped to Facebook’s products which were built on sharing. Open cultures assume employees are less likely to leak if they are trusted and empowered with confidential info.

Transparency allows for ideas to come from anywhere in the organization. Teams at FB prolifically collaborate, share feedback, communicate. But at its worst, this type of culture can devolve into entitlement, insubordination, ceaseless complaining. The knife cuts both ways.

3. Artificial intelligence has advanced so much, it wrote this article – Jurica Dujmovic & GPT-3

I did not write this article.

In fact, it wasn’t written by any person. Every sentence you see after this introduction is the work of OpenAI’s GPT-3, a powerful language-prediction model capable of composing sequences of coherent text. The only thing I did was provide it with topics to write about. I did not even fix its grammar or spelling.

According to OpenAI, more than 300 applications are using GPT-3, which is part of a field called natural language processing. An average of 4.5 billion words are written per day. Some say the quality of GPT-3’s text is as good as that written by humans.

What follows is GPT-3’s response to topics in general investing.

MarketWatch: “How to invest in cryptocurrencies by GPT-3.”

GPT-3: The growing popularity of cryptocurrency means there are hundreds of opportunities to choose from, but no matter how tempting it is to buy a partially inflated coin or invest in a minor one with big expectations, only a few cryptocurrencies really offer good investment opportunities.

The market is incredibly volatile and risky so it’s essential to read up on the fundamental value and technology of the crypto companies you’re going to invest in. The market capitalization of a cryptocurrency is no indication of its worth and there are many coins which are technically worth more than their price would indicate. You can try trading, but if you don’t wish to risk losing your money you can always treat it like betting on horses.

Here are some good cryptocurrencies if you want to invest: bitcoin, ethereum, monero, and litecoin…

…MarketWatch: “Is gold a good investment?”

GPT-3: I’m often asked if gold is a good investment. I almost always respond that it’s a terrible investment. I want gold to be a good investment. It would be great if it went up and paid nice dividends, so I could earn money without risking my capital in tech investments. But this belief of mine clashes with a widespread popular belief that gold is the ultimate safe investment, holding steady or going up over time while everything else falls apart.

Theoretical models have indicated that gold is not a stable investment. Theories of financial economics demonstrate that the price of gold should be positively related to risk-free interest rates. This is because an investor who expects low rates will purchase gold as protection in case bad economic conditions arise in the future.

4. A Few Short Stories – Morgan Housel

When Barack Obama discussed running for president in 2005, his friend George Haywood – an accomplished investor – gave him a warning: the housing market was about to collapse, and would take the economy down with it.

George told Obama how mortgage-backed securities worked, how they were being rated all wrong, how much risk was piling up, and how inevitable its collapse was. And it wasn’t just talk: George was short the mortgage market.

Home prices kept rising for two years. By 2007, when cracks began showing, Obama checked in with George. Surely his bet was now paying off?

Obama wrote in his memoir:

George told me that he had been forced to abandon his short position after taking heavy losses.

“I just don’t have enough cash to stay with the bet,” he said calmly enough, adding, “Apparently I’ve underestimated how willing people are to maintain a charade.”

Irrational trends rarely follow rational timelines. Unsustainable things can last longer than you think…

…Apollo 11 was the first time in history humans visited another celestial body.

You’d think that would be an overwhelming experience – literally the coolest thing any human had ever done. But as the spacecraft hovered over the moon, Michael Collins turned to Neil Armstrong and Buzz Aldrin and said:

It’s amazing how quickly you adapt. It doesn’t seem weird at all to me to look out there and see the moon going by, you know?

Three months later, after Al Bean walked on the moon during Apollo 12, he turned to astronaut Pete Conrad and said “It’s kind of like the song: Is that all there is?” Conrad was relieved, because he secretly felt the same, describing his moonwalk as spectacular but not momentous.

Most mental upside comes from the thrill of anticipation – actual experiences tend to fall flat, and your mind quickly moves on to anticipating the next event. That’s how dopamine works.

If walking on the moon left astronauts underwhelmed, what does it say about our own earthly goals and expectations?

5. Shopify: A StarCraft Inspired Business Strategy – Mike (Nongaap Investing)

For those that not familiar with the races in StarCraft, think of Zerg as the “swarm” race that is collectively stronger by being part of a group. It’s easy to defeat an individual Zerg unit but you’ll be overwhelmed by a swarm. That’s how most Zerg players win the game.

Zerg is an amalgamation that lives within an ecosystem called the “creep” (think of it as a living carpet that slowly expands across the map) which gives Zerg units enhanced abilities and players visibility into oncoming threats when enemies step “onto the creep”. Zerg thrives on this living, evolving “creep”…

…The Zerg race gets stronger as the game progresses and as their “creep” spreads across the game’s map. A large coverage of “creep” on the map makes it possible to add more facilities (most facilities can only build on “creep”), access more resources, and deploy “swarms” (units only spawn on “creep”) to attack the enemy…

…Shopify has turned independent e-commerce sites into an online retail swarm capable of taking on much bigger players. The Shopify ecosystem makes it very easy for entrepreneurs to “spawn” sites and gives them the tools to be nimble and competitive online.

Where most see “One Platform, Every Channel, Any Device”, I see Shopify “Creep” that’s spreading across the commerce map and getting exponentially stronger as it expands.

One thing about Zerg gameplay that I haven’t mentioned is many non-Zerg StarCraft players get frustrated in long games because Zerg is extremely difficult to beat in “late game”. This means once a Zerg player has established their macro economy and upgrades, they can pretty much win any “read and respond” situations as long as they build the appropriate counters-measures in a timely fashion.

Consequently, in order to win, you have to beat Zerg early in the game or you will likely lose a long game of attrition all else being equal.

In my opinion, Shopify is well past the “early game” stage of online commerce so it will be interesting to see how things play out for Shopify long-term.

Interestingly, in November 2018 someone on Twitter predicted that Amazon would acquire Shopify in 2019. Tobi Lütke responded with the most “late game Zerg” response ever:

“I’d rather buy @amazon in 2029”

6. Kati Kariko Helped Shield the World From the Coronavirus – Gina Kolata

For her entire career, Dr. Kariko has focused on messenger RNA, or mRNA — the genetic script that carries DNA instructions to each cell’s protein-making machinery. She was convinced mRNA could be used to instruct cells to make their own medicines, including vaccines.

But for many years her career at the University of Pennsylvania was fragile. She migrated from lab to lab, relying on one senior scientist after another to take her in. She never made more than $60,000 a year.

By all accounts intense and single-minded, Dr. Kariko lives for “the bench” — the spot in the lab where she works. She cares little for fame. “The bench is there, the science is good,” she shrugged in a recent interview. “Who cares?”

Dr. Anthony Fauci, director of the National Institutes of Allergy and infectious Diseases, knows Dr. Kariko’s work. “She was, in a positive sense, kind of obsessed with the concept of messenger RNA,” he said.

Dr. Kariko’s struggles to stay afloat in academia have a familiar ring to scientists. She needed grants to pursue ideas that seemed wild and fanciful. She did not get them, even as more mundane research was rewarded.

“When your idea is against the conventional wisdom that makes sense to the star chamber, it is very hard to break out,” said Dr. David Langer, a neurosurgeon who has worked with Dr. Kariko.

Dr. Kariko’s ideas about mRNA were definitely unorthodox. Increasingly, they also seem to have been prescient.

“It’s going to be transforming,” Dr. Fauci said of mRNA research. “It is already transforming for Covid-19, but also for other vaccines. H.I.V. — people in the field are already excited. Influenza, malaria.”

7. Amazon 2020 Shareholder Letter – Jeff Bezos

If you want to be successful in business (in life, actually), you have to create more than you consume. Your goal should be to create value for everyone you interact with. Any business that doesn’t create value for those it touches, even if it appears successful on the surface, isn’t long for this world. It’s on the way out.

Remember that stock prices are not about the past. They are a prediction of future cash flows discounted back to the present. The stock market anticipates…

…The fact is, the large team of thousands of people who lead operations at Amazon have always cared deeply for our hourly employees, and we’re proud of the work environment we’ve created. We’re also proud of the fact that Amazon is a company that does more than just create jobs for computer scientists and people with advanced degrees. We create jobs for people who never got that advantage.

Despite what we’ve accomplished, it’s clear to me that we need a better vision for our employees’ success. We have always wanted to be Earth’s Most Customer-Centric Company. We won’t change that. It’s what got us here. But I am committing us to an addition. We are going to be Earth’s Best Employer and Earth’s Safest Place to Work.

In my upcoming role as Executive Chair, I’m going to focus on new initiatives. I’m an inventor. It’s what I enjoy the most and what I do best. It’s where I create the most value. I’m excited to work alongside the large team of passionate people we have in Ops and help invent in this arena of Earth’s Best Employer and Earth’s Safest Place to Work. On the details, we at Amazon are always flexible, but on matters of vision we are stubborn and relentless. We have never failed when we set our minds to something, and we’re not going to fail at this either…

…This is my last annual shareholder letter as the CEO of Amazon, and I have one last thing of utmost importance I feel compelled to teach. I hope all Amazonians take it to heart.

Here is a passage from Richard Dawkins’ (extraordinary) book The Blind Watchmaker. It’s about a basic fact of biology.

“Staving off death is a thing that you have to work at. Left to itself – and that is what it is when it dies – the body tends to revert to a state of equilibrium with its environment. If you measure some quantity such as the temperature, the acidity, the water content or the electrical potential in a living body, you will typically find that it is markedly different from the corresponding measure in the surroundings. Our bodies, for instance, are usually hotter than our surroundings, and in cold climates they have to work hard to maintain the differential.

When we die the work stops, the temperature differential starts to disappear, and we end up the same temperature as our surroundings. Not all animals work so hard to avoid coming into equilibrium with their surrounding temperature, but all animals do some comparable work. For instance, in a dry country, animals and plants work to maintain the fluid content of their cells, work against a natural tendency for water to flow from them into the dry outside world. If they fail they die. More generally, if living things didn’t work actively to prevent it, they would eventually merge into their surroundings, and cease to exist as autonomous beings. That is what happens when they die.”

While the passage is not intended as a metaphor, it’s nevertheless a fantastic one, and very relevant to Amazon. I would argue that it’s relevant to all companies and all institutions and to each of our individual lives too. In what ways does the world pull at you in an attempt to make you normal? How much work does it take to maintain your distinctiveness? To keep alive the thing or things that make you special?

I know a happily married couple who have a running joke in their relationship. Not infrequently, the husband looks at the wife with faux distress and says to her, “Can’t you just be normal?” They both smile and laugh, and of course the deep truth is that her distinctiveness is something he loves about her. But, at the same time, it’s also true that things would often be easier – take less energy – if we were a little more normal.

This phenomenon happens at all scale levels. Democracies are not normal. Tyranny is the historical norm. If we stopped doing all of the continuous hard work that is needed to maintain our distinctiveness in that regard, we would quickly come into equilibrium with tyranny.

We all know that distinctiveness – originality – is valuable. We are all taught to “be yourself.” What I’m really asking you to do is to embrace and be realistic about how much energy it takes to maintain that distinctiveness. The world wants you to be typical – in a thousand ways, it pulls at you. Don’t let it happen.

You have to pay a price for your distinctiveness, and it’s worth it. The fairy tale version of “be yourself ” is that all the pain stops as soon as you allow your distinctiveness to shine. That version is misleading. Being yourself is worth it, but don’t expect it to be easy or free. You’ll have to put energy into it continuously.

The world will always try to make Amazon more typical – to bring us into equilibrium with our environment. It will take continuous effort, but we can and must be better than that.

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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. Of all the companies mentioned, we currently have a vested interest in Amazon, Facebook, Microsoft, and Shopify. Holdings are subject to change at any time.

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

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

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

Here are the articles for the week ending 11 April 2021:

1. Twitter thread on the importance of learning how to sell your product – Yuri Sagalov

It’s been almost 10 years since one of my most embarrassing fundraising moments as a founder. A moment so embarrassing that I couldn’t talk about it for years. It taught me the difference between raising a Seed round and a Series A, as well as some well needed humility.

In 2010, our seed raise was a breeze. We were young, arrogant, and deeply technical — a recipe for an oversubscribed round in 2010. We confidently handwaved away questions like “how will you get customers?” and spent most of our time building product.

In 2011 we started getting approached by Sand Hill funds to talk about a potential Series A, in the way that Sand Hill funds approach startups: They’re excited, they’re ready to fund, but actually they just want to learn more. Suddenly, we found ourselves fundraising again.

We were building an enterprise product but still didn’t really have any paying customers (we had some free users). This time around my handwaving didn’t work as well. Some investors politely nodded and then passed, but one AAA Sand Hill partner meeting went particularly poorly…

…We had users, and we even had some users who loved the product. But, ultimately, we were building a B2B/Enterprise product, and in 2010/2011 I knew nothing about sales and go to market. I made the naive mistake of believing that if we build it, they will come.

The partner and I sparred back and forth for a few minutes, until he suddenly interrupted me and said:  “Yuri, hope isn’t a strategy.” He then got up and left the room, leaving me to awkwardly finish the final 20 min of the meeting with his other partners…

…I spent a lot of time being offended and angry at how that partner behaved in that meeting. And while I continue to think he could have acted nicer — he was also right. We *didn’t* have a plan on how to get customers at that point, and we weren’t ready to raise our next round.

2. When Jeff Bezos’s 2-Pizza Teams Fell Short, He Turned to the Brilliant Model Amazon Uses Today – Jeff Haden

You’ve probably heard of Amazon’s two-pizza-team rule: No team should be larger than the number of people that can be adequately fed by two large pizzas.

What you likely don’t know is that despite the approach’s initial success, few people inside Amazon actually talk about two-pizza teams.

Instead, the model was gradually refined and ultimately replaced by a far more capable type of team model, one still in use today…

…Amazon found that the biggest predictor of a team’s success wasn’t whether it was small but whether it had a leader with “the appropriate skills, authority, and experience to staff and manage a team whose sole [my italics] focus was to get the job done.”

Or as Amazon’s SVP of devices, Dave Limp, said, “The best way to fail at inventing something is by making it somebody’s part-time job.”

That’s why, in time, two-pizza teams evolved into single-threaded leader (STL) teams, a term borrowed from computer science that means to only work on one thing at a time.

Single-threaded is term borrowed from computer science that means to only work on one thing at a time.

One example of how a single-threaded leader team succeeded where two-pizza teams failed? The idea that became Fulfillment by Amazon (FBA).

The idea behind FBA was simple: give third-party sellers access to Amazon’s warehouse and shipping services.

The benefits for third-party sellers were clear: Merchants would send products to Amazon for Amazon to store, pick, pack, and ship on their behalf, not only eliminating a third-party seller’s logistics headaches, but making warehousing costs variable rather than fixed.

Executives in retail and operations teams thought FBA was a great idea, but for well over a year nothing happened. They were all “exceptionally capable people, but they didn’t have the bandwidth to manage the myriad details FBA entailed,” the authors write.

Then Tom Taylor, a VP at the time, was asked to drop all his other responsibilities and was given full authority to hire and staff a team. Crucially, that team was also given sufficient autonomy to build and roll out their assigned task–without coordinating with or seeking approval from other teams.

In short, one highly skilled person was put in charge — and not only had the authority to see the project through, but was allowed to focus solely on seeing the project through.

3. The company that modern capitalism couldn’t survive long without – Samanth Subramanian

Which makes it all the more remarkable that a single Dutch company sits at the very heart of this $439 billion industry. At its headquarters in Veldhoven, in the Netherlands, ASML assembles photolithography machines, which etch circuit patterns onto chip wafers using low-wavelength light. Other companies make such machines too, but ASML controls more than 60% of the market; in 2019, its revenue was 11.8 billion euros ($13.2 billion). It is also the only manufacturer of the latest, most precise generation of chip-making machines, which uses extreme ultraviolet light (EUV), with a wavelength of 13.5 nanometers—a ten-thousandth the width of a human hair.

It’s difficult to think of another company anywhere that is simultaneously this important and yet this unknown to the public at large. If Veldhoven vanished tomorrow, our version of capitalism—our cellphone-toting, remote-working, Netflix-binging, online-buying, cloud-storing, smart car-driving, Internet-of-Things-ing capitalism—would judder to a halt. ASML isn’t a monopoly, but its market depends upon its technology to a degree that can almost be discomfiting…

…The world’s largest consumer of semiconductor chips is China; in 2020, the country imported 543 billion chips, worth around $350 billion. Its state-owned chipmaker, SMIC, was founded in 2000. “Back then, the manufacturing didn’t have to be as precise, so it didn’t matter if you didn’t have clean rooms or if a truck rolling down the road outside shook the building minutely,” Sinha said.

But over the past decade or so, the processes have become much more exacting. At the same time, Sinha said, the US government grew worried about what China might use cutting-edge chips for, and what surveillance technology it might install on any chips it sells to the world. “The concern was, if you allow China to go and make chips at scale using an EUV, those chips would be impossible to scrutinize with all their billions of transistors on them,” Sinha said. Under US pressure, chipmakers were restricted from selling their products to Huawei. Along similar lines, ASML’s EUV was placed on the Wassenaar list, a multilateral regime that controls the export of several critical technologies to non-member states such as China.

It doesn’t take any great insight into the human psyche to discover what Wennink, ASML’s CEO, thinks of not being able to sell to the world’s biggest market. He knows that behind the ban on selling EUVs to China is not just a worry about national security but also an act of economic one-upmanship—a desire to keep China dependent on non-Chinese vendors. Most military applications don’t even need cutting-edge chips from EUVs, he argued. They can work just fine with older chips. “And the argument we make to governments is that…our equipment is part of a production system for products that are so multifunctional and general purpose,” Wennink said. “They help process medical data. Or traffic data… You try to educate governments that a sanction will slow innovation, and costs will go up.”

4. Google Director Of Engineering: This is how fast the world will change in ten years – Michael Simmons

Ray Kurzweil, the director of engineering at Google and arguably the world #1 futurist, breaks down what the second half of the exponential curve better than anyone else in his book, The Singularity Is Near.

Kurzweil’s basic premise is this: “The future will be far more surprising than most people realize.”

The reason it’ll be more surprising, he argues, is, “because few observers have truly internalized the implications of the fact that the rate of change itself is accelerating.” In other words, “an exponential curve looks like a straight line when examined for only a brief duration. As a result, even sophisticated commentators, when considering the future, typically extrapolate the current pace of change over the next ten years or one hundred years to determine their expectations.”…

…“My models show that we are doubling the paradigm-shift rate every decade.” — Ray Kurzweil…

…To summarize the profundity of this 10-year doubling rate, Kurzweil says:

“We won’t experience one hundred years of technological advance in the twenty-first century; we will witness on the order of twenty thousand years of progress (again, when measured by today’s rate of progress), or about one thousand times greater than what was achieved in the twentieth century.”

Let that sink in for a second…

…“In order to keep up with the world of 2050, you will need not merely to invent new ideas and products but above all to reinvent yourself again and again.” — Yuval Noah Harari

To recap, we are on the precipice of an era of extreme competition — which means that the amount and pace of competition will accelerate 4x in the next 20 years. If you don’t prepare now, you will be progressively outcompeted and overwhelmed. So the question becomes, how do you want to run the race?

A few options emerge:

1. Follow the pace of the crowd: In other words, do what most people are doing (i.e. get a 9–5 job and do what’s expected of you). This is the least stressful option in the short-term, but you risk falling behind in the long-term.
2. Work harder than others: This helps you progress in your career faster, but you sacrifice time with family & friends along with personal health… not to mention that you risk losing out to people who are learning more than you.
3. Outlearn others and let your knowledge compound: Learning is the ultimate productivity hack. In other words, it provides the greatest leverage. It’s the tool that the greatest innovators and business thinkers of our time (Elon Musk, Jeff Bezos, Bill Gates, Warren Buffett, and others) use to get ahead.

5. Bill Hwang Had $20 Billion, Then Lost It All in Two Days –  Erik Schatzker, Sridhar Natarajan, and Katherine Burton

Before he lost it all—all $20 billion—Bill Hwang was the greatest trader you’d never heard of.

Starting in 2013, he parlayed more than $200 million left over from his shuttered hedge fund into a mind-boggling fortune by betting on stocks. Had he folded his hand in early March and cashed in, Hwang, 57, would have stood out among the world’s billionaires. There are richer men and women, of course, but their money is mostly tied up in businesses, real estate, complex investments, sports teams, and artwork. Hwang’s $20 billion net worth was almost as liquid as a government stimulus check. And then, in two short days, it was gone.

The sudden implosion of Hwang’s Archegos Capital Management in late March is one of the most spectacular failures in modern financial history: No individual has lost so much money so quickly. At its peak, Hwang’s wealth briefly eclipsed $30 billion. It’s also a peculiar one…

…He became the biggest of whales—financial slang for someone with a dominant presence in the market—without ever breaking the surface. By design or by accident, Archegos never showed up in the regulatory filings that disclose major shareholders of public stocks. Hwang used swaps, a type of derivative that gives an investor exposure to the gains or losses in an underlying asset without owning it directly. This concealed both his identity and the size of his positions. Even the firms that financed his investments couldn’t see the big picture.

That’s why on Friday, March 26, when investors around the world learned that a company called Archegos had defaulted on loans used to build a staggering $100 billion portfolio, the first question was, “Who on earth is Bill Hwang?” Because he was using borrowed money and levering up his bets fivefold, Hwang’s collapse left a trail of destruction. Banks dumped his holdings, savaging stock prices. Credit Suisse Group AG, one of Hwang’s lenders, lost $4.7 billion; several top executives, including the head of investment banking, have been forced out. Nomura Holdings Inc. faces a loss of about $2 billion…

…On March 25, when Hwang’s financiers were finally able to compare notes, it became clear that his trading strategy was strikingly simple. Archegos appears to have plowed most of the money it borrowed into a handful of stocks—ViacomCBS, GSX Techedu, and Shopify among them. This was no arbitrage on collateralized bundles of obscure financial contracts. Hwang invested the Tiger way, using deep fundamental analysis to find promising stocks, and he built a highly concentrated portfolio. The denizens of Reddit’s WallStreetBets day trading on Robinhood can do almost the same thing, riding such popular themes as cord cutting, virtual education, and online shopping. Only no brokerage will extend them anywhere near the amount of leverage billionaires get…

…U.S. rules prevent individual investors from buying securities with more than 50% of the money borrowed on margin. No such limits apply to hedge funds and family offices. People familiar with Archegos say the firm steadily ramped up its leverage. Initially that meant about “2x,” or $1 million borrowed for every $1 million of capital. By late March the leverage was 5x or more.

Hwang also kept his banks in the dark by trading via swap agreements. In a typical swap, a bank gives its client exposure to an underlying asset, such as a stock. While the client gains—or loses—from any changes in price, the bank shows up in filings as the registered holder of the shares.

That’s how Hwang was able to amass huge positions so quietly. And because lenders had details only of their own dealings with him, they, too, couldn’t know he was piling on leverage in the same stocks via swaps with other banks. ViacomCBS Inc. is one example. By late March, Archegos had exposure to tens of millions of shares of the media conglomerate through Morgan Stanley, Goldman Sachs Group Inc., Credit Suisse, and Wells Fargo & Co. The largest holder of record, indexing giant Vanguard Group Inc., had 59 million shares…

…The fourth quarter of 2020 was a fruitful one for Hwang. While the S&P 500 rose almost 12%, seven of the 10 stocks Archegos was known to hold gained more than 30%, with Baidu, Vipshop, and Farfetch jumping at least 70%.

All that activity made Archegos one of Wall Street’s most coveted clients. People familiar with the situation say it was paying prime brokers tens of millions of dollars a year in fees, possibly more than $100 million in total. As his swap accounts churned out cash, Hwang kept accumulating extra capital to invest—and to lever up. Goldman finally relented and signed on Archegos as a client in late 2020. Weeks later it all would end in a flash.

The first in a cascade of events during the week of March 22 came shortly after the 4 p.m. close of trading that Monday in New York. ViacomCBS, struggling to keep up with Apple TV, Disney+, Home Box Office, and Netflix, announced a $3 billion sale of stock and convertible debt. The company’s shares, propelled by Hwang’s buying, had tripled in four months. Raising money to invest in streaming made sense. Or so it seemed in the ViacomCBS C-suite.

Instead, the stock tanked 9% on Tuesday and 23% on Wednesday. Hwang’s bets suddenly went haywire, jeopardizing his swap agreements. A few bankers pleaded with him to sell shares; he would take losses and survive, they reasoned, avoiding a default. Hwang refused, according to people with knowledge of those discussions, the long-ago lesson from Robertson evidently forgotten.

That Thursday his prime brokers held a series of emergency meetings. Hwang, say people with swaps experience, likely had borrowed roughly $85 million for every $20 million, investing $100 and setting aside $5 to post margin as needed. But the massive portfolio had cratered so quickly that its losses blew through that small buffer as well as his capital.

The dilemma for Hwang’s lenders was obvious. If the stocks in his swap accounts rebounded, everyone would be fine. But if even one bank flinched and started selling, they’d all be exposed to plummeting prices. Credit Suisse wanted to wait.

Late that afternoon, without a word to its fellow lenders, Morgan Stanley made a preemptive move. The firm quietly unloaded $5 billion of its Archegos holdings at a discount, mainly to a group of hedge funds. On Friday morning, well before the 9:30 a.m. New York open, Goldman started liquidating $6.6 billion in blocks of Baidu, Tencent Music Entertainment Group, and Vipshop. It soon followed with $3.9 billion of ViacomCBS, Discovery, Farfetch, Iqiyi, and GSX Techedu.

When the smoke finally cleared, Goldman, Deutsche Bank AG, Morgan Stanley, and Wells Fargo had escaped the Archegos fire sale unscathed. There’s no question they moved faster to sell. It’s also possible they had extended less leverage or demanded more margin. As of now, Credit Suisse and Nomura appear to have sustained the greatest damage. Mitsubishi UFJ Financial Group Inc., another prime broker, has disclosed $300 million in likely losses.

6. Here’s how Lazada lost its lead to Shopee in Southeast Asia (Part 1 of 2) – Late Post

Southeast Asia’s homegrown e-commerce platform, Shopee, is a pioneer in more ways than one. Formed in 2015, it is an offshoot of gaming company Garena, helmed by founders who studied abroad and worked overseas for multinational companies. Its fourth quarter and full year 2020 financial reports indicate that Shopee’s turnover for the year was USD 35.4 billion, double that of 2019 and accounting for 57% of the entire Southeast Asian e-commerce market’s transaction volume.

Yet Shopee’s position is far from secure, as a seasoned online retailer from China wants a piece of the market too. Alibaba (NYSE: BABA; HKG: 9988), China’s largest e-commerce company, has been sparing no effort to extend its reach in the region. Southeast Asia was the largest and first overseas market where Alibaba landed. Alibaba CEO Daniel Zhang Yong and co-founder Peng Lei flew into the region for meetings on a monthly basis. In 2016, when Shopee was still a fledgling firm, Alibaba acquired Lazada, which was at the time the largest e-commerce company in the region.

Now, Shopee seems to have captured the lion’s share of the market. Its parent company, Sea Limited (NYSE: SE), is the largest tech company in the region, with a market value of nearly USD 130 billion…

…A good number of former Alibaba employees believed that selecting a suitable region for expansion was a simple matter. “Amazon’s home turf is in the Americas and Europe, and there is almost no chance of succeeding there. Russia and the Middle East are close to China, but their slower speed of economic development is not ideal. India is a potential area for investment, but it is impossible to do it without the assistance of local partners. Africa and Southeast Asia are the only two regions left. Compared to Southeast Asia, Africa’s distance from China and limited human resources pool is a problem,” they said to LatePost…

…Alibaba entered the regional market through Lazada, which was established in Singapore in 2012. Lazada contains the DNA of German incubator Rocket Internet, which itself is notorious for being a “copycat factory” that duplicates business models lifted from Silicon Valley and transplants them in new locations abroad.

By 2015, Lazada’s GMV had exceeded USD 1.3 billion, surpassing Indonesian counterpart Tokopedia to become the region’s leading e-commerce platform. Not long after, in April 2016, Alibaba bought a 51% stake in Lazada, then followed up with an investment of USD 1 billion in June 2017 to raise its stake to 83%…

…Following the acquisition, Alibaba promised Lazada that it would be able to maintain independent operations, but disagreements and conflict quickly broke out.

“For example, in 2017, Cainiao [Alibaba’s delivery provider] wanted to build a 10,000 sqm warehouse, but Lazada wanted to try one that was 5,000 sqm first,” said a Lazada insider. “That year, Alibaba also wanted to bring some major international brands to Lazada, but Lazada’s employees felt that these brands were too expensive and would not be received well by locals.”

In order to ensure that its directives would be implemented, Alibaba decided to transform Lazada’s internal structure, announcing in March 2018 that Peng Lei, Ant Financial’s former CEO, would take over as CEO of Lazada, as part of the terms of a USD 2 billion investment.

After this mammoth financing, Lazada did not immediately move to counteract its competitors, but instead began the process of cleaning up its internal organization. A Lazada advertising supplier told LatePost that because Lazada was almost a wholly owned subsidiary, account management across multiple countries was now more complicated, and until this could be sorted out, budgeting and spending nearly ground to a halt…

…At the end of 2017, Shopee’s parent company, Garena, changed its name to Sea Limited and listed on the New York Stock Exchange at a value of USD 6.3 billion.

“After it went public, many Shopee people sold their stock,” said an investor of Shopee. “They didn’t believe that it was possible for it to grow bigger.”

In 2018, however, Shopee seized the opportunity to launch an offensive in light of Lazada’s stagnation in Southeast Asia, led by CEO Chris Feng. Today, Shopee’s market capitalization has exceeded USD 120 billion. It is said by Shopee’s employees that 80% of Sea Limited’s stock price is supported by Shopee’s growth potential, while 80% of Shopee is supported by Feng.

Chris Feng is a native of Huai’an, Jiangsu, and received a scholarship from the Singaporean government in 2000 when he was a sophomore in high school. Later, he attended the National University of Singapore to study computer science, and pursued further studies at Stanford University. He joined McKinsey and then moved to Rocket Internet, where he became responsible for Lazada’s cross-border business.

Insiders close to Feng say he led a team’s defection from Lazada to join Garena in 2014 due to dissatisfaction with the situation at Lazada. He founded the mobile games division of Garena and started Shopee a year later. According to people familiar with the matter, he is well respected by his subordinates and characterized as a “very, very smart and very, very confident” person who “reacts quickly and has excellent abilities of recall.” Reportedly, he holds large-scale meetings involving dozens of individuals every two weeks, and can casually invoke data and information mentioned during previous meetings with ease.

On weekdays, Feng is known to wear Shopee’s team shirts, only donning formal suits on formal occasions. He still lives in affordable public housing (HDB) flats set up by the Singaporean government. A longtime friend of his has commented that Feng does not value money, but is “really a person who wants to do big things.”

Feng’s experience and contacts in Lazada are said to have been crucial to Shopee’s growth. For example, he was keenly aware of Lazada’s chaotic situation in 2018 and seized the chance to launch an offensive.

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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. Of all the companies mentioned, we currently have a vested interest in Alphabet (parent of Google), Amazon, Apple, ASML, Netflix, Sea, and Shopify. Holdings are subject to change at any time.

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

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

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

Here are the articles for the week ending 4 April 2021:

1. How mRNA Technology Could Change the World – Derek Thompson

But mRNA’s story likely will not end with COVID-19: Its potential stretches far beyond this pandemic. This year, a team at Yale patented a similar RNA-based technology to vaccinate against malaria, perhaps the world’s most devastating disease. Because mRNA is so easy to edit, Pfizer says that it is planning to use it against seasonal flu, which mutates constantly and kills hundreds of thousands of people around the world every year. The company that partnered with Pfizer last year, BioNTech, is developing individualized therapies that would create on-demand proteins associated with specific tumors to teach the body to fight off advanced cancer. In mouse trials, synthetic-mRNA therapies have been shown to slow and reverse the effects of multiple sclerosis. “I’m fully convinced now even more than before that mRNA can be broadly transformational,” Özlem Türeci, BioNTech’s chief medical officer, told me. “In principle, everything you can do with protein can be substituted by mRNA.”

In principle is the billion-dollar asterisk. mRNA’s promise ranges from the expensive-yet-experimental to the glorious-yet-speculative. But the past year was a reminder that scientific progress may happen suddenly, after long periods of gestation. “This has been a coming-out party for mRNA, for sure,” says John Mascola, the director of the Vaccine Research Center at the National Institute of Allergy and Infectious Diseases. “In the world of science, RNA technology could be the biggest story of the year. We didn’t know if it worked. And now we do.”…

…“There was a lot of skepticism in the industry when we started, because this was a new technology with no approved products,” Türeci told me. “Drug development is highly regulated, so people don’t like to deviate from paths with which they have experience.” BioNTech and Moderna pressed on for years without approved products, thanks to the support of philanthropists, investors, and other companies. Moderna partnered with the NIH and received tens of millions of dollars from DARPA, the Defense Advanced Research Projects Agency, to develop vaccines against viruses, including Zika. In 2018, Pfizer signed a deal with BioNTech to develop mRNA vaccines for the flu.

“The technology initially appealed to us for the flu because of its great speed and flexibility,” Philip Dormitzer, who leads Pfizer’s viral-vaccines research and development programs, told me. “You can edit mRNA very quickly. That is quite useful for a virus like the flu, which requires two updated vaccines each year, for the Northern and Southern Hemisphere.”

By the time the coronavirus outbreak shut down the city of Wuhan, China, Moderna and BioNTech had spent years fine-tuning their technology. When the outbreak spread throughout the world, Pfizer and BioNTech were prepared to shift immediately and redirect their flu research toward SARS-CoV-2. “It was really a case of our researchers swapping the flu protein for the coronavirus spike protein,” Dormitzer said. “It turned out that it wasn’t that big a leap.”

Armed with years of mRNA clinical work that built on decades of basic research, scientists solved the mystery of SARS-CoV-2 with astonishing speed. On January 11, 2020, Chinese researchers published the genetic sequence of the virus. Moderna’s mRNA vaccine recipe was finalized in about 48 hours. By late February, batches of the vaccine had been shipped to Bethesda, Maryland, for clinical trials. Its development was accelerated by the Trump administration’s Operation Warp Speed, which invested billions of dollars in several vaccine candidates, including Moderna’s. With the perfect timing of a Hollywood epic, mRNA entered the promised land after about 40 wandering years of research. Scientific progress had proceeded at its typical two-speed pace—slowly, slowly, then all at once.

2. More accuracy – Robert Vinall

As I look back on the letter, it struck me that the importance I place on striving for an accurate picture of the future might seem so obvious as to be hardly worth mentioning. After all, if a company’s intrinsic value is the sum of discounted future cash flow, why on earth would you not want to form as accurate a view of the future as possible? I can imagine my insistence on this point is particularly puzzling to younger investors whose formative years have been dominated by the boom in Internet stocks. “Doh!” they might exhort, “Of course you have to skate to where the puck is going, not where it was.” 

The reason it is not obvious to older generations of value investors is that in our formative years, investing based on the assumption that historical patterns of cashflow generation would reassert themselves – better known as “reversion to the mean” – seemed the better strategy. Many of the great investing track records were built by investing in stable, unchanging businesses when they went through a period of underperformance on the assumption that they would eventually recover. It was an approach to investing that was based on a good understanding of a company’s history and the assumption that the future would not look too different to the past. It worked far better than betting on companies with short histories and big plans for the future, and it seemed obvious that it would continue to.

These two contrasting approaches to investing – one placing more weight on the future; the other on the past – are a reminder that the optimal strategy is a function of the era you invest in. If you are in a market characterised by rapid and widespread change, it pays to be forward-looking despite the inherent difficulty of judging the future. If, on the other hand, you are in a market where the pace of change is slower and more localised, then it may simply be better to bet on reversion to the mean as the future is too uncertain and genuine change too infrequent.

The contrasting outcomes of different brands of value investing in different eras pose an intriguing question. If each era selects for the type of investor who is best adapted to it, does the younger investor have an edge over the older one? My strong sense is “yes”. I am fortunate to know several successful younger investors, and they seem perfectly adapted to the market they invest in. I, by contrast, have had to adapt, which in practice does not so much mean learning new tricks as unlearning old ones. The former is certainly easier than the latter as learning is fun, but parting ways with cherished ideas is painful. Reluctant though I am to acknowledge it, as grey hairs begin to colonise my scalp, experience is a disadvantage.

In one important respect though, there is an advantage to experience. When the nature of the market does change, it should, at least in theory, be easier for the investor that has lived through different types of market to adapt than for the investor who has only experienced one type. The younger investor suddenly finds themselves in the position of the older investor without the benefit of having experienced a change in the market before.

In practice, however, few investors have sustained multidecade success. This may not solely be down to how difficult it is. It could also be that the rewards to the stellar performer are so great in one era that they lose interest in competing in the next one when they realise that their skills are no longer as finely attuned to the market. For sure though, it is a monumental challenge.

To increase the chances of adapting to different markets, I see one big thing an investor should do and one big thing they should not. The single biggest thing they should do is commit to adapt. The single biggest thing an investor should not do is tie themselves to a particular investment style or geography or industry or any other categorisation.  These two points may sound obvious but generally, fund managers do the complete opposite. Investors in funds tend to look for a specific niche expertise in fund managers, and fund managers respond to this by developing a personal brand for a particular style of investing or segment of the market. Their brand promise is that they will not adapt.

3. Moore’s Law for Everything – Sam Altman

In the next five years, computer programs that can think will read legal documents and give medical advice. In the next decade, they will do assembly-line work and maybe even become companions. And in the decades after that, they will do almost everything, including making new scientific discoveries that will expand our concept of “everything.”

This technological revolution is unstoppable. And a recursive loop of innovation, as these smart machines themselves help us make smarter machines, will accelerate the revolution’s pace. Three crucial consequences follow:

1. This revolution will create phenomenal wealth. The price of many kinds of labor (which drives the costs of goods and services) will fall toward zero once sufficiently powerful AI “joins the workforce.”
2. The world will change so rapidly and drastically that an equally drastic change in policy will be needed to distribute this wealth and enable more people to pursue the life they want.
3. If we get both of these right, we can improve the standard of living for people more than we ever have before.

Because we are at the beginning of this tectonic shift, we have a rare opportunity to pivot toward the future. That pivot can’t simply address current social and political problems; it must be designed for the radically different society of the near future. Policy plans that don’t account for this imminent transformation will fail for the same reason that the organizing principles of pre-agrarian or feudal societies would fail today…

…AI will lower the cost of goods and services, because labor is the driving cost at many levels of the supply chain. If robots can build a house on land you already own from natural resources mined and refined onsite, using solar power, the cost of building that house is close to the cost to rent the robots. And if those robots are made by other robots, the cost to rent them will be much less than it was when humans made them.

Similarly, we can imagine AI doctors that can diagnose health problems better than any human, and AI teachers that can diagnose and explain exactly what a student doesn’t understand…

…The traditional way to address inequality has been by progressively taxing income. For a variety of reasons, that hasn’t worked very well. It will work much, much worse in the future. While people will still have jobs, many of those jobs won’t be ones that create a lot of economic value in the way we think of value today. As AI produces most of the world’s basic goods and services, people will be freed up to spend more time with people they care about, care for people, appreciate art and nature, or work toward social good.

We should therefore focus on taxing capital rather than labor, and we should use these taxes as an opportunity to directly distribute ownership and wealth to citizens. In other words, the best way to improve capitalism is to enable everyone to benefit from it directly as an equity owner

This is not a new idea, but it will be newly feasible as AI grows more powerful, because there will be dramatically more wealth to go around. The two dominant sources of wealth will be 1) companies, particularly ones that make use of AI, and 2) land, which has a fixed supply…

…We could do something called the American Equity Fund. The American Equity Fund would be capitalized by taxing companies above a certain valuation 2.5% of their market value each year, payable in shares transferred to the fund, and by taxing 2.5% of the value of all privately-held land, payable in dollars.

All citizens over 18 would get an annual distribution, in dollars and company shares, into their accounts. People would be entrusted to use the money however they needed or wanted—for better education, healthcare, housing, starting a company, whatever. Rising costs in government-funded industries would face real pressure as more people chose their own services in a competitive marketplace.

As long as the country keeps doing better, every citizen would get more money from the Fund every year (on average; there will still be economic cycles). Every citizen would therefore increasingly partake of the freedoms, powers, autonomies, and opportunities that come with economic self-determination. Poverty would be greatly reduced and many more people would have a shot at the life they want.

4. The Robots Are Coming For Your Office – Nilay Patel and Kevin Roose

[Patel] You just said, “We’re journalists, it’s an industry that employs automation to do parts of our job.” I think that gets kinda right to the heart of the matter, which is the definition of automation, right?

I think when most people think of automation, they think of robots building cars and replacing factory workers in Detroit. You are talking about something much broader than that.

[Roose] Yeah. I mean, that’s sort of the classic model of automation. And still, every time there’s a story about automation — and I hate this, and it’s like my personal vendetta against newspaper and magazine editors — every time you see a story about automation, there’s always a picture of a physical robot. And I get it. Most robots that we think of from sci-fi are physical robots. But most robots that exist in the world today, by a vast majority, are software.

And so, what you’re seeing today in corporate environments, in journalism, in lots of places, is that automation is showing up as software, that does parts of the job that, frankly, I used to do. My first job in journalism was writing corporate earnings stories. And that’s a job that has been largely automated by these software products now…

…[Patel] How big is the total RPA market right now?

[Roose] It’s in the billions of dollars. I don’t know the exact figure, but the biggest companies in this are called UiPath and Automation Anywhere and there are other companies in this space, like Blue Prism. But just UiPath alone is valued at something like $35 billion and is expected to IPO later this year. So, these are large companies that are doing many billions of dollars in revenue a year, and they’re working with most of the Fortune 500 at this point.

[Patel] And the actual product they sell, is it basically software that uses other software?

[Roose] A lot of it is that. A lot of it is, this bot will convert between these two file formats or it’ll do sort of basic-level optical character recognition so that you can scan expense reports and import that data into Excel, or something like that. So, a lot of it is pretty simple. You know, a lot of AI researchers don’t even consider RPA AI, because so much of it is just like static, rule-based algorithms. But a lot of them are starting to layer on more AI and predictive capability and things like that…

…[Patel] That feels like I could map it to a pretty familiar consumer story. You’ve got a factory, it’s got some output. It’s almost like a video game, right? You’ve got a factory, it’s got some output, you need to make X, Y, and Z parts in various quantities and you need to deliver on a certain time. And to some extent, your job is to play tower defense and just fill all the bins at the right time. Or you could just play against the computer and the computer will beat you every time. That’s what that seems like. It seems very obvious that you should just let the computer do it.

[Roose] Totally. And that’s the logic that a lot of executives have. And I don’t even know that that’s the wrong logic. Like I don’t think we should be preserving jobs that can be automated just to preserve jobs. The concern, I think I, and some other folks who watch this industry have, is that this type of automation is purely substitutive.

So in the past we’ve had automation that carried positive consequences and negative consequences. So the factory machines put some people out of their jobs, but they created many more jobs and they lowered the cost of the factories’ goods and they made it more accessible to people and so people bought more of them. And it had this kind of offsetting effect where you had some workers losing their jobs, but more jobs being created elsewhere in the economy that those people could then go do.

And the concern that the economists that I’ve talked to had, was that this kind of RPA, like replacing people in the back office, like it’s not actually that good.

It’s not the good kind of automation that actually does move the economy forward. It’s kind of this crappy, patchwork automation that purely takes out people and doesn’t give them anything else to do. And so I think on a macroeconomic level, the problem with this kind of automation is not actually how advanced it is, it’s how simple it is. And if we are worried about the sort of future of the economy and jobs, we should actually want more sophisticated AI, more sophisticated automation that could actually create sort of dynamic, new jobs for these people who are displaced, to go into…

…[Patel] So you’ve called them boring bots. You say the technology is not so sophisticated. The industry calls it RPA. Like, there’s a lot of pressure on making this seem not the most technologically sophisticated or exciting thing. It comes with a lot of change, but I’m wondering, are there any stories of RPA going horribly wrong?

[Roose] I’m just imagining like, I think the most consumer-facing automation is, you call the customer support line and you go through the phone tree. It makes all the sense in the world on paper: if all I need is the balance of my credit card, I should just press 5 and a robot will read it to me, but like I just want to talk to a person every time. Because that phone tree never has the options I want or it’s always confused or something is wrong. There has to be a similar story in the back office where the accounting software went completely sideways and no one caught it, right?

Yeah, I mean, there’s several stories like that in the book. There’s a trading firm called Knight Capital that had an algorithm go haywire and it lost millions of dollars in milliseconds. There was actually just a story in the financial markets — I forget who it was, it was one of the big banks — accidentally wired hundreds of millions of dollars to someone else and couldn’t get it back. And so it was just like, they just lost that. I’m sure that automation had some role in that, but that might have been a human error.

But there are also lower-level instances of this going haywire. One of the examples I talk about in the book is this guy Mike Fowler, who is an Australian entrepreneur who came up with a way to automate T-shirt design. So, I don’t know if you remember like five or six years ago, but there were all these auto-generated T-shirts on Facebook that were advertised. So, you know, it’d be like, “Kiss me, I’m a tech blogger who loves punk rock.” You know, and those would just be like Mad Libs, you know?…

…And so he made a lot of money doing this, and then one day it went totally wrong because he hadn’t cleaned up the word bank that this algorithm drew from. So there were people noticing shirts for sale on Amazon that were saying things like “Keep calm and hit her,” or, “Keep calm and rape a lot.” Like just words that he had forgotten to clean out of the database, and so as a result, his store got taken down. He lost all his business. He had to change jobs, like it was a traumatic event for him. And that’s a colorful example but there are, I’m sure, lots of more mundane examples of this happening at places that have implemented RPA.

5. The Big Lessons of the Last Year – Morgan Housel

Jason Zweig explained years ago that part of the reason the same mistakes repeat isn’t because people don’t learn their lesson; it’s because people “are too good at learning lessons, and they learn overprecise lessons.”

A good lesson from the dot-com bust was the perils of overconfidence. But the lesson most people took away was “the stock market becomes overvalued when it trades at a P/E ratio over 30.” It was hyperspecific, so many of the same investors who lost their shirts in 2002 got up and walked straight into the housing bubble, where they lost again.

The most important lessons from a big event are usually the broad, 30,000-foot takeaways. They’re more likely to apply to the next iteration of crisis.

Covid-19 is far from over, but we’re now more than a year into this tragic mess. Enough has happened that we can start to ask “what lessons have we learned?” If you’re a doctor or a health regulator, some of those lessons are hyperspecific. But for most of us the biggest lessons are broad…

…A virus shutting down the global economy and killing millions of people seemed remote enough for most people to never contemplate. Before a year ago it sounded like the one-in-billions freak accident only seen in movies.

But break the last year into smaller pieces.

A virus transferred from animal to human (has happened forever) and those humans interacted with other people (of course). It was a mystery for a while (understandable) and bad news was likely suppressed (political incentives, don’t yell fire in a theater). Other countries thought it would be contained (exceptionalism, standard denial) and didn’t act fast enough (bureaucracy, lack of leadership). We weren’t prepared (common over-optimism) and the reaction to masks and lockdowns became heated (of course) so as to become sporadic (diversity, same as ever). Feelings turned tribal (standard during an election year) and a rush to move on led to premature reopenings (standard denial, the inevitability of different people experiencing different realities).

Each of those events on their own seems obvious, even common. But when you multiply them together you get something surprising, even unprecedented.

Big risks are always like that, which makes them too easy to underestimate. How starkly we have been reminded over the last year.

6. What Is Archegos and How Did It Rattle the Stock Market –  Juliet Chung and Margot Patrick

Archegos is the family investment vehicle owned by Mr. Hwang, a former protégé of hedge-fund titan Julian Robertson. Mr. Hwang was a so-called Tiger cub, an offshoot of Mr. Robertson’s Tiger Management. Mr. Hwang founded Tiger Asia in 2001. Based in New York, it went on to become one of the biggest Asia-focused hedge funds, running more than $5 billion at its peak. In 2008, it was one of a swath of funds that suffered losses related to the soaring share price of Volkswagen AG of Germany

In 2012, Tiger Asia said it planned to hand money back to investors. Later that year, the firm pleaded guilty to a criminal fraud charge for using inside information from investment banks to profit on securities trades. Mr. Hwang and Tiger Asia paid $44 million to settle a related civil lawsuit, The Wall Street Journal reported at the time.

Mr. Hwang turned Tiger Asia into his family office and renamed it Archegos, according to its website…

…Archegos took big, concentrated positions in companies and held some positions via something called “total return swaps.” Those are contracts brokered by Wall Street banks that allow a user to take on the profits and losses of a portfolio of stocks or other assets in exchange for a fee.

Swaps allow investors to take huge positions while posting limited funds up front, in essence borrowing from the bank. The use of swaps allowed Mr. Hwang to maintain his anonymity, even as Archegos was estimated to have had exposure to the economics of more than 10% of multiple companies’ shares. Investors holding more than 10% of a company’s securities are deemed to be company insiders and are subject to additional regulations around disclosures and profits.

Swaps are common and have been around for a long time. They are also controversial. Long Term Capital Management, a hedge fund advised by two Nobel laureates that nearly brought down Wall Street in the late 1990s, used swaps. Warren Buffett wrote about the risks of swaps in his 2003 letter to investors.

7. Twitter thread on how a software entrepreneur burned US$10 million – Andrew Wilkinson

This is a story about how I lost $10,000,000 by doing something stupid. Ten. Million. Dollars. Literally up in smoke. Money bonfire. That’s enough to retire with $250,000+ in annual income. Here’s what happened…

In 2009, @metalab was a small but profitable agency. The business was making a couple hundred thousand dollars a year in annual profit and I was trying to figure out how to invest the profits. Agencies can be great businesses, but they are HARD.

You lose clients at random, your pipeline dries up on a dime. It’s feast or famine and unpredictable. I kept reading about what  @dhh and @jasonfried were doing with Basecamp, building software for themselves then selling monthly access to it.

This was a relatively new concept back in those days, and it seemed like they were living the dream. I had a business crush. The model they used for Basecamp was:

1. Build great software that scratched their own itch (project management)
2. Assume others have this problem
3. Charge a monthly recurring amount to give them access (SaaS)
4. Focus on organic growth via product improvement and public writing
5. Spend less than they make
6. Profit…

…I loved Jason and David’s focus on building a business on your own terms, in a way that made you happy. I hated the idea of having some annoying VC involved, pressuring me to grow or move to San Francisco (believe it or not, that was almost 100% required at the time)…

…I was a huge to-do list junkie, but back then all of the task apps were either single-player or weird desktop apps with syncing issues. I decided to build a shared to-do list app for teams.

I grabbed a couple of devs from the agency and we started working on it. About 9 months later we were in beta. We called it Flow, and it was actually really cool. From day one, it was a huge hit. A lot of people had the same problem and there was nothing else like it…

…When we turned on billing for our beta users, we jumped to $20k MRR in the first month. We started growing at 10% per month and were the new hotness. I got reach outs from all the top VCs and tons of tech luminaries started using the product. We’d made it…or so I thought.

There was just one problem: I was consistently spending 2-3x our monthly revenue and losing money. And not venture capital. Out of my personal bank account.

Then I heard a name start popping up. Quietly at first, then a lot. Asana.

It turned out that Dustin Moskovitz (@moskov), the billionaire co-founder of Facebook, was a fellow to-do list junkie, and he was quietly working on his own product. A few months later it went live. And I breathed a big sigh of relief.

It was ugly! It was designed by engineers. Complicated and hard to use. Not a threat in the slightest. I felt validated: With a team a quarter of the size, and a fraction of the money, we had built what I felt was a superior product.

Around this time, Dustin invited me for a coffee in San Francisco. He implied—in the nicest possible terms—that they were going to crush us. (Emphasis on nice, he is a very nice, humble dude. Both Dustin and @christianreber, my two key competitors, turned out to be mensches)

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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. Of all the companies mentioned, we currently have a vested interest in Amazon and Facebook. Holdings are subject to change at any time.

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

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

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

Here are the articles for the week ending 28 March 2021:

1. Elevate Our Minds – Kazuo Inamori

I can’t observe nature, the formation of matter in the universe, the birth of life or the process of evolution and not see a destiny that is more than coincidental.

The world seems to have a “flow” that evolves and develops everything. I call this “the will of the universe.” This will is filled with love, sincerity and harmony. Our personal destiny depends on whether or not the energy emitted by our mind is in harmony with the universal will.

Fortune smiles upon us when we make a wish with a pure mind that is in harmony with this universal will.

Our attitude and heart play a decisive role in achieving wonderful results in our life and work.

A loving, sincere and harmonious heart leads to success. Such a heart is a natural part of our spiritual selves. “Love” rejoices in other people’s happiness as if it were our own. “Sincerity” is a mindset that seeks good for the sake of society and others. “Harmony” compels us to always wish for happiness, not just for ourselves, but for everyone around us.

A loving, affectionate, sincere and harmonious heart is the foundation that leads a person to success.

Wonderful success can come only from the designs of a pure mind. No matter how strong our desires may be, if they are generated from our selfishness, success cannot be sustained.

The stronger an irrational desire is, the more it will conflict with society and the more catastrophic its results will be.

To sustain success, our desire and enthusiasm must be pure. In other words, you must make sure that your desire is pure before you make it permeate your subconscious mind. And, only continuous efforts stemming from pure hearts will enable us to realize our goals.

2. Unlocking the Covid Code – Jon Gertner

In the sphere of public health, one of the first big breakthroughs enabled by faster genomic sequencing came in 2014, when a team at the Broad Institute of M.I.T. and Harvard began sequencing samples of the Ebola virus from infected victims during an outbreak in Africa. The work showed that, by contrasting genetic codes, hidden pathways of transmission could be identified and interrupted, with the potential for slowing (or even stopping) the spread of infection. It was one of the first real-world uses of what has come to be called genetic surveillance. A few years later, doctors toting portable genomic sequencers began tracking the Zika virus around Central and South America. Sequencers were getting better, faster and easier to use.

To many, the most familiar faces of this technology are clinical testing companies, which use sequencing machines to read portions of our genetic code (known as “panels” or “exomes”) to investigate a few crucial genes, like those linked to a higher risk of breast cancer. But more profound promises of genome sequencing have been accumulating stealthily in recent years, in fields from personal health to cultural anthropology to environmental monitoring. Crispr, a technology reliant on sequencing, gives scientists the potential to repair disease-causing mutations in our genomes. “Liquid biopsies,” in which a small amount of blood is analyzed for DNA markers, offer the prospect of cancer diagnoses long before symptoms appear. The Harvard geneticist George Church told me that one day sensors might “sip the air” so that a genomic app on our phones can tell us if there’s a pathogen lurking in a room. Sequencing might even make it possible to store any kind of data we might want in DNA — such an archival system would, in theory, be so efficient and dense as to be able to hold the entire contents of the internet in a pillowcase…

…As machines improved, the impact was felt mainly in university labs, which had relied on a process called Sanger sequencing, developed in the mid-1970s by the Nobel laureate Frederick Sanger. This laborious technique, which involved running DNA samples through baths of electrically charged gels, was what the scientists at Oxford had depended upon in the mid-1990s; it was also what Dave O’Connor, a virologist at the University of Wisconsin, Madison, was using in the early 2000s, as he and his lab partner, Tom Friedrich, tracked virus mutations. “The H.I.V. genome has about 10,000 letters,” O’Connor told me, which makes it simpler than the human genome (at three billion letters) or the SARS-CoV-2 genome (at about 30,000). “In an H.I.V. genome, when we first started doing it, we would be able to look at a couple hundred letters at a time.” But O’Connor says his work changed with the advent of new sequencing machines. By around 2010, he and Friedrich could decode 500,000 letters in a day. A few years later, it was five million.

By 2015, the pace of improvement was breathtaking. “When I was a postdoctoral fellow, I actually worked in Fred Sanger’s lab,” Tom Maniatis, the head of the New York Genome Center, told me. “I had to sequence a piece of DNA that was about 35 base pairs, and it took me a year to do that. And now, you can do a genome, with three billion base pairs, overnight.” Also astounding was the decrease in cost. Illumina achieved the $1,000 genome in 2014. Last summer, the company announced that its NovaSeq 6000 could sequence a whole human genome for $600; at the time, deSouza, Illumina’s chief executive, told me that his company’s path to a $100 genome would not entail a breakthrough, just incremental technical improvements. “At this point, there’s no miracle that’s required,” he said. Several of Illumina’s competitors — including BGI, a Chinese genomics company — have indicated that they will also soon achieve a $100 genome. Those in the industry whom I spoke with predicted that it may be only a year or two away.

These numbers don’t fully explain what faster speeds and affordability might portend. But in health care, the prospect of a cheap whole-genome test, perhaps from birth, suggests a significant step closer to the realization of personalized medicines and lifestyle plans, tailored to our genetic strengths and vulnerabilities. “When that happens, that’s probably going to be the most powerful and valuable clinical test you could have, because it’s a lifetime record,” Maniatis told me. Your complete genome doesn’t change over the course of your life, so it needs to be sequenced only once. And Maniatis imagines that as new information is accumulated through clinical studies, your physician, armed with new research results, could revisit your genome and discover, say, when you’re 35 that you have a mutation that’s going be a problem when you’re 50. “Really, that is not science fiction,” he says. “That is, I’m personally certain, going to happen.”

3. Outgrowing Software – Ben Evans

Walmart was built on trucking and freeways (and computers), but Walmart is a retailer, not a trucking company: it used trucks to change retail. Now people do the same with software.

But it’s also interesting to look at the specific industries that have already been destabilised by software, and at what happened next. The first one, pretty obviously, was recorded music. Tech had a huge effect on the music business, but no-one in tech today spends much time thinking about it. 15 and 20 years ago music was a way to sell devices and to keep people in an ecosystem, but streaming subscription services mean music no longer has much strategic leverage – you don’t lose a music library if you switch from iPhone to Android, or even from Spotify to Apple Music. Meanwhile, the absolute size of the market is tiny relative to what tech has become – total recorded music industry revenues were less than $20bn last year (half the peak in 2000), where Apple’s were $215bn. No-one cares about music anymore.

Something similar happened in books. Amazon has half the market, ebooks became a real business (though they remain a niche), and self-publishing has become a new vertical, but I suspect Apple wouldn’t bother to do ebooks again if it had the choice. Just as for music, there’s no strategic leverage, and total US book market revenues last year were perhaps $25bn, where Amazon’s US revenue was $260bn. No-one in tech cares about online book sales or ebooks.

More fundamentally, though, for both music and books, most of the arguments and questions are music industry questions and book industry questions, not tech or software questions. Spotify is suing Apple over the App Store commission rules, but otherwise, all the Spotify questions are music questions. Why don’t artists make more from streaming? Ask the labels. Why didn’t the internet kill labels or publishers? Ask music people and book people.

4. Inside Facebook Reality Labs: Wrist-based interaction for the next computing platform – Facebook

The future of HCI [human-computer interaction] demands an exceptionally easy-to-use, reliable, and private interface that lets us remain completely present in the real world at all times. That interface will require many innovations in order to become the primary way we interact with the digital world. Two of the most critical elements are contextually-aware AI that understands your commands and actions as well as the context and environment around you, and technology to let you communicate with the system effortlessly — an approach we call ultra-low-friction input. The AI will make deep inferences about what information you might need or things you might want to do in various contexts, based on an understanding of you and your surroundings, and will present you with a tailored set of choices. The input will make selecting a choice effortless — using it will be as easy  as clicking a virtual, always-available button through a slight movement of your finger.

But this system is many years off. So today, we’re taking a closer look at a version that may be possible much sooner: wrist-based input combined with usable but limited contextualized AI, which dynamically adapts to you and your environment.

We started imagining the ideal input device for AR glasses six years ago when FRL Research (then Oculus Research) was founded. Our north star was to develop ubiquitous input technology — something that anybody could use in all kinds of situations encountered throughout the course of the day. First and foremost, the system needed to be built responsibly with privacy, security, and safety in mind from the ground up, giving people meaningful ways to personalize and control their AR experience. The interface would also need to be intuitive, always available, unobtrusive, and easy to use. Ideally, it would also support rich, high-bandwidth control that works well for everything from manipulating a virtual object to editing an electronic document. On top of all of this, it would need a form factor comfortable enough to wear all day and energy-efficient enough to keep going just as long.

That’s a long list of requirements. As we examined the possibilities, two things became clear: The first was that nothing that existed at the time came close to meeting all those criteria. The other was that any solution that eventually emerged would have to be worn on the wrist.

Why the wrist? There are many other input sources available, all of them useful. Voice is intuitive, but not private enough for the public sphere or reliable enough due to background noise. A separate device you could store in your pocket like a phone or a game controller adds a layer of friction between you and your environment. As we explored the possibilities, placing an input device at the wrist became the clear answer: The wrist is a traditional place to wear a watch, meaning it could reasonably fit into everyday life and social contexts. It’s a comfortable location for all-day wear. It’s located right next to the primary instruments you use to interact with the world — your hands. This proximity would allow us to bring the rich control capabilities of your hands into AR, enabling intuitive, powerful, and satisfying interaction.

A wrist-based wearable has the additional benefit of easily serving as a platform for compute, battery, and antennas while supporting a broad array of sensors. The missing piece was finding a clear path to rich input, and a potentially ideal solution was EMG.

EMG — electromyography — uses sensors to translate electrical motor nerve signals that travel through the wrist to the hand into digital commands that you can use to control the functions of a device. These signals let you communicate crisp one-bit commands to your device, a degree of control that’s highly personalizable and adaptable to many situations.

The signals through the wrist are so clear that EMG can understand finger motion of just a millimeter. That means input can be effortless. Ultimately, it may even be possible to sense just the intention to move a finger. 

“What we’re trying to do with neural interfaces is to let you control the machine directly, using the output of the peripheral nervous system — specifically the nerves outside the brain that animate your hand and finger muscles,” says FRL Director of Neuromotor Interfaces Thomas Reardon, who joined the FRL team when Facebook acquired CTRL-labs in 2019.

This is not akin to mind reading. Think of it like this: You take many photos and choose to share only some of them. Similarly, you have many thoughts and you choose to act on only some of them. When that happens, your brain sends signals to your hands and fingers telling them to move in specific ways in order to perform actions like typing and swiping. This is about decoding those signals at the wrist — the actions you’ve already decided to perform — and translating them into digital commands for your device. It’s a much faster way to act on the instructions that you already send to your device when you tap to select a song on your phone, click a mouse, or type on a keyboard today.

5. Completing The God Protocols: A Comprehensive Overview of Chainlink in 2021 – SmartContent

In 1997, computer scientist Nick Szabo described what he termed the “God Protocols.” In short, the God Protocols refer to the general idea of a set of computer protocols that could arbitrate and facilitate processes involving an exchange of value between two or more independent parties without any bias, error, or privacy concerns. This perfect third party would be equally accessible to all participants, fairly and flawlessly execute actions according to mutually pre-agreed upon rules and commands, and wouldn’t leak sensitive information to unintended entities.

When extrapolated out to multi-party contracts, the God Protocols are designed to eliminate inefficiencies and counterparty risk by replacing human-based arbitrators/executors with math-based arbitrators/executors, resulting in the correct party consistently getting what they are owed, when they are owed, and from whom they are owed, based entirely on a provably objective interpretation of the events in which the contract is written about. Additionally, the Gods Protocols would extract as little value as possible from the process, only receiving what is needed to cover the costs of performing it…

…The third component to the God protocols is for smart contracts to become aware of events and interact with systems existing outside the native blockchain they run on. External connectivity entails two functions: 1) consuming data originating outside the blockchain and 2) passing instructional commands to external systems for them to perform (e.g., execute a payment on PayPal).

Blockchains are inherently closed and deterministic systems, meaning they have no built-in capabilities to talk to and exchange data between external systems (as doing so could break network consensus). While this generates the valuable security and reliability properties that users seek when using a blockchain, it also severely limits the types of data inputs that smart contracts can ingest and the types of output actions they can trigger on external systems. Most valuable datasets like financial asset prices, weather conditions, sports scores, and IoT sensors, as well as the currently preferred fiat settlement methods like credit cards and bank wires, exist outside the blockchain (off-chain). Given the importance of these resources to real-world business processes, blockchains need a secure bridge to the outside world in order to support a vast majority of smart contract application use cases.

Providing smart contracts connection to the outside world requires an additional piece of infrastructure known as an oracle. An oracle is an external entity that operates on behalf of a smart contract by performing actions not possible or practical by the blockchain itself. This usually involves retrieving and delivering off-chain data to the smart contract to trigger its execution or passing data from the smart contract to an external system to trigger an off-chain event. It can also involve various types of off-chain computations in advanced oracle networks (discussed more below), such as aggregating data from multiple sources or generating a provably fair source of randomness.

Similar to blockchains, the oracle mechanism cannot be operated by a single entity, as that would give the centralized oracle sole control over the inputs the contract consumes, thus control over the outputs it produces. Even if the blockchain is highly secure and the smart contract logic is perfectly written, the oracle will put at risk the entire value proposition of the smart contract if it is not built to the same security and reliability standards as the underlying blockchain network, often referred to as the oracle problem. Why have a blockchain network of thousands of nodes when it’s triggered by a single entity?

6. What If Interest Rates Don’t Matter as Much as We Think? – Ben Carlson

It’s obvious the Fed is propping up risk assets, right?

Well investors in the 1960s, 1970s and 1990s were more than happy to take speculation to another level with rates much much higher than they’ve been since 2008.

The same is true of the housing market…

…Interest rates do matter. They provide a hurdle rate, discount rate, benchmark, alternative to risk assets, however you want to look at it.

But they aren’t the be-all, end-all to the markets some would have you believe.

There are so many other factors at play that determine why investors do what they do with their money — demographics, demand, risk appetite, past experiences and a whole host of psychological and market-related dynamics.

Interest rates don’t turn people into gamblers.

They don’t force investors into lottery-ticket traders looking to get rich overnight.

Humans are just fine doing that on their own, regardless of interest rate levels.

Could there be a psychological impact if rates rise from here or fall from here or go nowhere for years on end?

Of course!

7. Five Investing Powers – Morgan Housel

Low susceptibility to FOMO. But for a different reason than you might think. The urge to buy an investment because its price went up means you probably don’t know why the price has gone up. And if you don’t know why the price has gone up you’re more likely to bail when it goes down. Most good investing is just sticking around for the longest time possible, through thick and thin. Quash the need to own whatever is going up the most and you reduce the urge to abandon whatever eventually goes down. Someone will always be getting richer than you. It’s OK.

Knowing what game you’re playing. An idea that’s obvious but overlooked is that investors on the same field play different games. We buy the same companies, read the same news, talk to the same people, are quoted the same market prices – but we’re everything from day traders to endowments with century-long time horizons. Even investors who think they’re playing the same game – say, stock pickers – have wildly different goals and risk tolerances. My view is that most investing debates do not reflect genuine disagreement; they reflect investors playing different games talking over each other, upset that people who don’t want what you want can’t see what you see. Understanding your game, without being swayed by people playing different games, is a rare investing power.

Recognizing the difference between patience and stubbornness. Two things are true: 1) every asset goes through temporary out-of-favor periods, and 2) the world changes, and some things fall permanently out of favor. Industries go through normal cycles, then they die. Investing strategies work for decades, then they stop. Realizing that patience plays the most important role in investing, but it shouldn’t be used blindly in every situation, is so hard. Dealing with it requires a combination of conviction and flexibility that can feel like a contradiction. The trick – and that’s the right word – is realizing that some behaviors never change but the composition of the economy always does. Having a few immutable beliefs but even more that you’re willing to abandon is a rare investing power.

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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. Of all the companies mentioned, we currently have a vested interest in Amazon, Apple, Facebook, Illumina, and PayPal. Holdings are subject to change at any time.

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

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

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

Here are the articles for the week ending 21 March 2021:

1. Reverse Wealth Transfer on Steroids – Josh Brown

Do not buy SPACs, digital currencies or non fungible tokens sold to you by millionaires and billionaires with your stimulus check.

This is the exact opposite of what’s intended for young people like yourself receiving stimulus checks from the government. These checks are meant to improve your current situation by giving you a chance to purchase things that you need today or pay your bills or pay down debt. Speculating in digital assets is not part of the intent. Buying an online baseball card is not helping you, even if it goes up in price immediately after your having bought it…

…Trillionaires have the right to create any kind of nonsense they want and offer it up for sale. You have the right to come to your senses and say, “You know what, I don’t actually need that shit, I need a job. I need a nice new suit to go on interviews with. I need to fix my car. I need to upgrade my apartment so I can bring a date home and not be embarrassed about my situation.”…

…Take the $1400 and do one of these things:

Buy a business suit, some nice shirts and a pair of shoes. Laugh all you want, but these will be tools you can use to get into the right rooms and meet the right people. I promise you this is true: When you’re well dressed, people treat you differently. With respect. With honor. They hold doors for you and make eye contact with you. They can tell you hold yourself in high esteem and this subconsciously encourages them to hold you in high esteem as well. You can scoff at this and call it materialistic or bourgeois or anachronistic or whatever other big bad words you learned in college, but what I am telling you is the truth. If you had invented Facebook, you would have invented Facebook. But you didn’t. So the hoodie isn’t going to work. Watch how people deal with you when your shirt is tucked in and your shoes are shined.

Buy a bicycle. Set a routine. Breathe fresh air. See the sun. Feel the breeze. Smell the roses. You can listen to your podcasts while getting some exercise and being a human being. Every hour you spend with your eyes off the screens is an hour better spent. You will know I am right because you will feel it in your soul.

Buy a cookbook and some high quality pots and pans. Maintaining a grown-up kitchen with nice implements and utensils, as well as obtaining the ability to make quality meals for yourself or others will bring you the kind of psychic income that speculating in someone else’s shitty art projects can never replace.

2. Ray Dalio & The Power of Setting Defaults For Optimism – Ben Carlson

Optimism pays when it comes to investing because, most of the time, markets go up. The stock market is up roughly 3 out of every 4 years, on average. Over the long-term, optimism as a strategy is nearly impossible to beat. This is why buy and hold is perhaps the greatest strategy ever invented.

Unfortunately, there are always good reasons to be worried. The future is always uncertain. There is always bad news and we hear about that bad news more than any generation in history in the information age.

And there is something about finance people that makes them worry more about the downside than the upside. It’s like the exact opposite of people in Silicon Valley who are almost unanimously optimistic about the future.

Ray Dalio may be right to worry about the future. But he has a long track record of worrying about the future that hasn’t really panned out that well.

Dalio penned a piece for Institutional Investor about the importance of knowing when you’re wrong and changing your mind. He used his own prediction of a depression in the early-1980s as an example:

The biggest of these mistakes occurred in 1981–’82, when I became convinced that the U.S. economy was about to fall into a depression. My research had led me to believe that, with the Federal Reserve’s tight money policy and lots of debt outstanding, there would be a global wave of debt defaults, and if the Fed tried to handle it by printing money, inflation would accelerate. I was so certain that a depression was coming that I proclaimed it in newspaper columns, on TV, even in testimony to Congress. When Mexico defaulted on its debt in August 1982, I was sure I was right. Boy, was I wrong. What I’d considered improbable was exactly what happened: Fed chairman Paul Volcker’s move to lower interest rates and make money and credit available helped jump-start a bull market in stocks and the U.S. economy’s greatest ever noninflationary growth period.

Of course, there was no depression. Instead, the early-1980s kicked off one of the longest expansions in market and economic history.

That history bled into the 1990s as well. It may not seem like it when you look back at high double-digit returns from 1980-1999 but the nirvana-like economic and market environment in the 1990s was not a foregone conclusion at the outset of the decade.

In a piece from the New York Magazine in 1992, Dalio was quoted saying bonds were a better bet than stocks over the course of the 1990s:

Over the long term, both Dalio and Jones agree, as a result of these circumstances bonds in the nineties will almost certainly outperform stocks. In the fifties, says Dalio, wary investors were still looking in the rearview mirror at the Depression of the thirties, when stocks took the shellacking of all time. Thus, bonds remained the preferred investment when the environment of accelerating growth and inflation actually favored stocks. As a result, those who took what appeared to be a risk and bought stocks in the fifties wound up making fortunes, while those who bought bonds wound up eventually losing their shirts.

Now, says Dalio, the situation is precisely reversed. Investors in the nineties remain traumatized over the carnage that inflation and sky-high interest rates wreaked in the bond market in the seventies, so they’re investing in stocks instead. Unfortunately, says Dalio, the current economic climate of low inflation and historically slow growth means that bonds will actually prove to be the better long-term performers.

To be fair, bonds did perform well in the 1990s. The 10 year treasury returned nearly 67% in total from 1992-1999 or 6.6% per year. That’s pretty good for bonds. But the S&P 500 was up more than 316% or nearly 20% per year from 1992-1999.

Dalio was wrong again.

Then in 2015, Dalio began warning we could see a repeat of the 1937 downturn. This nasty recession and 50% market crash is highly underrated by historical standards because it was sandwiched between the Great Depression and WWII. Dalio made a similar prediction for a 1937 situation in 2017.

Alas, there was no double-dip recession following the Great Financial Crisis. The stock market and the economy were doing just fine until the pandemic hit and now are back on trend.

Now, I’m not pointing out Dalio’s mistakes here to rub it in his face. We all get stuff wrong when it comes to the markets. This stuff is hard…

…Whatever the case may be, it appears Dalio doesn’t allow his macro predictions to influence Bridgewater’s investment strategy. Or if he does, it certainly doesn’t show up in their long-term track record.

I’m a huge advocate for default settings as an investor.

You should default your savings rate. Default increases to that savings rate over time. Default your investment choices. Default your bill payments. Automating good decisions ahead of time is one of the most important steps you can take to meaningfully improve your finances.

And when it comes to investing, the most important default by far is optimism.

Yes, there are always going to be risks but pessimism does not pay as a strategy over the long-run.

If you’re not optimistic about the future, what’s the point of investing in the first place?

3. Too Much, Too Soon, Too Fast – Morgan Housel

Let me tell you about Robert Wadlow. He was enormous, the largest human ever known.

A pituitary gland abnormality bombarded Wadlow’s body with growth hormone, leading to staggering size. He was six feet tall at age seven, seven feet tall by age 11, and when he died at age 22 stood an inch shy of nine feet tall, weighed 500 pounds, and wore size 37 shoes. His hand was a foot wide.

He was what fictional stories would portray as a superhuman athlete, capable of running faster, jumping higher, lifting more weight and crushing more bad guys than any normal person. Like a real-life Paul Bunyan.

But that was not Wadlow’s life at all.

He required steel leg braces to stand and a cane to walk. His walk wasn’t much more than a limp, requiring tremendous effort. What few videos of Wadlow exist show a man whose movements are strained and awkward. He was rarely seen standing on his own, and is usually leaning on a wall for support. So much pressure was put on his legs that near the end of his life he had little feeling below his knees. Had Wadlow lived longer and kept growing, casual walking would have caused leg bones to break. What actually killed him was nearly as grim: Wadlow had high blood pressure in his legs due to his heart’s strain to pump throughout his enormous body, which caused an ulcer, which led to a deadly infection.

You can’t triple the size of a human and expect triple the performance – the mechanics don’t work like that. Huge animals tend to have short, squatty legs (rhinos) or extremely long legs relative to their torso (giraffes). Wadlow grew too large given the structure of the human body. There are limits to scaling.

Writing before Wadlow’s time, biologist J.B.S. Haldane once showed how many things this scaling issue applies to.

A flea can jump two feet in the air, an athletic human about five. But if a flea were as large as a man, it would not be able to jump thousands of feet – it doesn’t scale like that. Air resistance would be far greater for the giant flea, and the amount of energy needed to jump a given height is proportional to weight. If a flea were 1,000 times its normal size, its hop might increase from two feet to perhaps six, Haldane assumed.

Look around and this concept is everywhere, in every direction…

…“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 into a different size or speed.

Which, of course, also applies to business and investing.

4. Apple, CAID, and China: rock, meet hard place – Eric Seufert

Early this week, it was revealed that the China Advertising Association (CAA), a state-backed advertising trade group in China, has rolled out its China Advertising ID (CAID) to a consortium of large Chinese advertisers for use as an alternative to the IDFA, which is set to be deprecated imminently in iOS 14.5.

The CAID is effectively a crowd-sourced persistent ID derived from device fingerprints: the CAA has created something of a data co-op, where members — which pay a participation fee — pool IP-indexed fingerprints to allow for devices to be identified as they engage with apps. The general idea is that if enough parameters are captured for a given device in a fingerprint, and the device is fingerprinted in enough apps in a short amount of time, the device can be identified even when its IP address changes because the other parameters (like memory utilization) stay relatively constant.

Building this type of probabilistic identity mechanism is fairly straightforward, but in order for it to be viable, participation and coordination are required from publishers that have large and overlapping user bases. This is the reason I was skeptical of such a solution being broadly adopted, as I articulated in this Twitter thread from a few months ago: in order for a fingerprinting solution based on IP addresses to provide utility, frequent touchpoints with users must be maintained to capture fingerprint snapshots that change subtlely enough for an identity to be probabilistically valid. It seemed unlikely that Western companies would be willing to cooperate to the degree necessary to deliver that. But the ability to coordinate nearly unimaginable, mass-scale projects, of the flavor seen during COVID, is the Chinese government’s distinctive advantage. Whereas a data co-op comprised of large US-based app publishers and ad networks is nearly unimaginable, apparently, ByteDance, Tencent, and Baidu are all participating in the CAID program that is organized by the state-sponsored CAA.

The development and adoption of the CAID puts Apple in a difficult position. Rock, meet hard place: China is Apple’s second-largest market after the US, and the specter of a WeChat ban on the iPhone during the Trump administration was estimated to potentially reduce Apple’s iPhone sales revenue by up to 30%. Apple already applies a separate standard with its App Store guidelines for certain Chinese developers, allowing eg. Tencent to run what is essentially an app store inside of WeChat. Would Apple simply extend this notion of a separate Chinese principle to privacy and allow CAID to be used for persistent identity by Chinese companies while subjecting companies domiciled elsewhere (read: Facebook) to the restrictions of ATT, which explicitly prohibits fingerprinting?

5. Twitter thread on the laws that govern the banking business – Maxfield on Banks

The longer you study a subject, the closer you get to the core laws that govern it. Here are 10 laws that govern banking, deduced from a decade of studying the industry… [thread]

1. Success in banking is foremost about winning a war of attrition. More than 17,300 banks have failed since the birth of the modern American banking industry in the Civil War. That’s over three times the number of banks in business today…

…3. The darlings in one era are often pariahs in the next. In 1978, Continental Illinois Bank & Trust was selected by Dun’s Review as one of America’s five best-managed companies. Six years later, it was seized by the FDIC due to mismanagement.

4. The crux of banking is watching what others are doing and then not doing it yourself. Warren Buffett calls this the institutional imperative: “the tendency of executives to mindlessly imitate the behavior of their peers, no matter how foolish it may be to do so.”

5. Credit quality is a myth until it’s a reality. Washington Mutual’s nonperforming assets as a % of all assets:

1998: 0.73%
1999: 0.55%
2000: 0.53%
2001: 0.93%
2002: 0.97%
2003: 0.70%
2004: 0.58%
2005: 0.57%
2006: 0.80%
2007: 2.17%
2Q08: 6.62%
4Q08: Failed…

…8. All roads lead to skin in the game. One reason M&T Bank has been so successful, its CEO Rene Jones once explained, “is that we could get 60% of our shareholders seated around the coffee table in my predecessor’s office.”

6. 2020 in Review – Howard Marks

Finally, much of the worry about whether we’re in a bubble relates to valuations. For the S&P 500, for example, the current ratio of price to projected 2021 earnings is roughly 22 (depending on which earnings estimates you use). This seems expensive compared to the historic average in the range of 15-16. But knee-jerk judgments based on the relationship between current valuations and historic averages are too simplistic to be dispositive. Before making a judgment about today’s valuation of the S&P 500, one must consider (a) the context in terms of interest rates, (b) the shift in its composition in favor of rapidly growing technology companies, with their higher valuations, (c) the valuations of the index’s individual components, including those tech companies, and (d) the outlook for the economy. With these factors in mind, I don’t think most of today’s asset valuations are crazy. Of course, a big correction in speculative stocks could have a negative impact on today’s bullish investor psychology.

In particular, as to item (a) above, we can look at the relationship between today’s 4.5% earnings yield* on the S&P 500 and the yield on the 10-year Treasury note of 1.4%. The implied “equity risk premium” of 310 basis points is very much in line with the average of 300 bp over the last 20 years. Valuations can also be viewed relative to short-term interest rates. The current p/e ratio on the S&P 500 of 22 is slightly below the reading of 24 in March 2000 (the height of the tech bubble), and the fed funds rate is around zero today versus 6.5% back then. Thus, in 2000, the earning yield on the S&P 500 was 4.2%, or 230 basis points below the fed funds rate, while today it’s 450 bp above. In other words, the S&P 500 is much cheaper today relative to short-term rates than it was 21 years ago.

The story is similar in the credit market. For example, the yield spread on high yield bonds versus Treasurys is below the historic range, although probably still more than adequate to offset likely credit losses. Thus, as with most other assets today, the price of high yield bonds is high in the absolute, fair-ish in relative terms, and highly reliant on interest rates staying low.

So where does that leave us? In many ways, we’re back to the investment environment we faced in the years immediately prior to 2020: an uncertain world, offering the lowest prospective returns we’ve ever seen, with asset prices that are at least full to high, and with people engaging in pro-risk behavior in search of better returns. This suggests we should return to Oaktree’s pre-Covid-19 mantra: move forward, but with caution. But a year or two ago, we were in an economic recovery that was a decade old – the longest in history. Instead, it now appears we’re at the beginning of an economic up-cycle that’s likely to run for years.

Over the course of my career, there have been a handful of times when I felt the logic for calling a top (or bottom) was compelling and the probability of success was high. This isn’t one of them. There’s increasing mention of a possible bubble based on concerns about valuations, federal government spending, inflation and interest rates, but I see too many positives for the answer to be black-or-white.

7. Twitter thread on lessons learned from working for Sheryl Sandberg, currently Facebook’s COO – Dan Rose

I learned about leadership & scaling from Sheryl Sandberg. My direct manager for 10+ yrs, we spent countless hours together in weekly 1x1s (she attended religiously), meetings, offsites, dinners, travel, etc. Here are some of the most important lessons I took away from Sheryl:

In one of our early M-team offsites, everyone shared their mission in life. Sheryl described her passion for scaling organizations. She was single-mindedly focused on this purpose and loved everything about scaling. It’s a huge strength to know what you were put on earth to do.

Sheryl implemented critical systems to help us scale – eg 360 perf reviews, calibrations, promotions, refresh grants, PIPs. She brought structure to our management team and board meetings, hired senior people across the company, and streamlined communications up and down the org.

Sheryl told Mark the things he didn’t want to hear. As companies grow, people don’t want to give the CEO bad news. Mark knew Sheryl would never worry about losing her job or falling out of favor. And over time Sheryl taught me and others how to be truth-tellers for her and Mark.

Sheryl refused to participate in late night meetings. She had the confidence to admit she went to bed at 10pm and told Mark she’d be happy to meet when she woke up at 5am if he still hadn’t gone to bed yet. Her vulnerability was inspiring and signaled strength not weakness…

…Sheryl & I disagreed early on about a decision. I thought Mark would agree with me so I went around her to make my case. She sat me down and explained that if we were going to work together she needed to be able to trust me. She invited escalation but insisted on transparency.

We faced a tough situation with a partner and one of their board members asked Sheryl to meet. She invited me to join but I demurred, I knew this would be a contentious mtg. She told me about one of her colleagues in DC who testified when nobody else wanted to – “step up, own it”

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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. Of all the companies mentioned, we currently have a vested interest in Apple, Facebook, and Tencent. Holdings are subject to change at any time.