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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 27 February 2022:

1. Share prices are tanking. Please read this – Scott Phillips

Right now, I’m sitting at my desk, a little numb.

My Twitter feed is full of real-time reports of the Russian invasion of Ukraine.

True, it’s half a world away, but I can’t help but think “There but for the grace of whatever god there may be, go I”.

The invasion is, of course, unconscionable. Despicable.

Ukrainians are pondering a scary and uncertain future, not sure what happens next. Hoping, I’m sure, for the best, but perhaps expecting the worst.

For a world used to relative peace (with exceptions) in modern times, this is a sobering slice of ugly reality.

I’m a finance guy, of course. The Motley Fool is an investment advisory business.

Markets are down today. By a decent margin.

I’ll get to that, but it’s hard to prioritise a relatively small percentage point loss, against what the people of Ukraine have awoken to this morning, their time.

I just did a finance segment on Radio 2GB in Sydney. Yes, the market is ugly, I said. But it’s hard to make that the first thing we talk about, given the impact on lives in Europe.

And yet, as I said, I’m a finance guy, working for an investment company. So, knowing that people would be worried, and in keeping with my area of expertise, I did what I thought was important: I explained what’s going on, finance-wise, and I put it in the context of the long term journey of wealth creation and preservation.

And, of course, it’s possible to walk and chew gum at the same time: to fully acknowledge the horror of an invasion of Ukraine and at the same time consider the investment response…

…I want you to know that no-one knows what the short-term will bring. Just as geopolitics is unpredictable, so is the share market.

Why? For the same reasons: the fundamentals are one thing… but in the short term it’s people who influence things most. Sentiment. Mood. Emotion. Panic. Fear. Greed. They’ll all govern how share prices move in the next few days and weeks.

And the problem is that we can’t know how that’ll change. Maybe investors and traders go into a long, drawn-out funk. Or maybe bargain hunters start buying first thing in the morning, and the ASX closes higher tomorrow.

I don’t know, and you don’t know. And we need to make our peace with that short-term uncertainty.

I want you to know that, with a few exceptions, ASX-listed companies won’t be doing anything different tomorrow, next week, next month or next year, no matter what happens in Ukraine.

Which means that any share price falls are completely disconnected from business fundamentals in many, frankly most, cases. Woolworths Group Ltd (ASX: WOW) keeps selling groceries. Cochlear Limited (ASX: COH) keeps restoring hearing. Commonwealth Bank of Australia (ASX: CBA) keeps processing transactions…

…I’m (almost) always fully invested.

Why? Because, over time, the market has always set new highs.

Not in the absence of tough days like today.

But despite these sorts of days.

2. What Is Swift and Could It Be Used in Sanctions Against Russia? –  Patricia Kowsmann and Ian Talley

What is Swift?

The Society for Worldwide Interbank Financial Telecommunication, or Swift, is the financial-messaging infrastructure that links the world’s banks. The Belgium-based system is run by its member banks and handles millions of daily payment instructions across more than 200 countries and territories and 11,000 financial institutions. Iran and North Korea are cut off from it. 

Why is Swift important for countries, including Russia?

Cross-border financing is critical to every part of the economy, including trade, foreign investment, remittances and the central bank’s management of the economy. Disconnecting a country, in this case Russia, from Swift would hit all of that.

Why are other countries resisting it?

Critics say there could be economic blowback, not just in Europe, which has deep trade ties and relies heavily on Russia’s natural gas exports, but also the rest of the world. Some former U.S. officials say the move could severely hurt Russia’s economy, but also harm Western business interests such as the major oil companies. President Biden, while ruling it out for now, said the option isn’t off the table completely…

…Additionally, using Swift as a weapon could erode the dollar-dominated global financial system, including by fostering alternatives to Swift being developed by Russia and the world’s second largest economy, China. That could undermine Western power, especially the diplomatic leverage that sanctions offer.

3. Teaching AI to translate 100s of spoken and written languages in real time – Sergey Edunov, Paco Guzman, Juan Pino, and Angela Fan

For people who understand languages like English, Mandarin, or Spanish, it may seem like today’s apps and web tools already provide the translation technology we need. But billions of people are being left out — unable to easily access most of the information on the internet or connect with most of the online world in their native language. Today’s machine translation (MT) systems are improving rapidly, but they still rely heavily on learning from large amounts of textual data, so they do not generally work well for low-resource languages, i.e., languages that lack training data, and for languages that don’t have a standardized writing system.

Eliminating language barriers would be profound, making it possible for billions of people to access information online in their native or preferred languages. Advances in MT won’t just help those people who don’t speak one of the languages that dominates the internet today; they’ll also fundamentally change the way people in the world connect and share ideas…

…The AI translation systems of today are not designed to serve the thousands of languages used around the world, or to provide real-time speech-to-speech translation. To truly serve everyone, the MT research community will need to overcome three important challenges. We will need to overcome data scarcity by acquiring more training data in more languages as well as finding new ways to leverage the data already available today. We’ll also need to overcome the modeling challenges that arise as models grow to serve many more languages. And we will need to find new ways to evaluate and improve on their results.

Data scarcity remains one of the biggest hurdles to expanding translation tools across more languages. MT systems for text translations typically rely on learning from millions of sentences of annotated data. Because of this, MT systems capable of high-quality translations have been developed for only the handful of languages that dominate the web. Expanding to other languages means finding ways to acquire and use training examples from languages with sparse web presences.

For direct speech-to-speech translation, the challenge of acquiring data is even more severe. Most speech MT systems use text as an intermediary step, meaning speech in one language is first converted to text, then translated to text in the target language, and then finally input into a text-to-speech system to generate audio. This makes speech-to-speech translations dependent on text in ways that limit their efficiency and make them difficult to scale to languages that are primarily oral.

Direct speech-to-speech translation models can enable translations for languages that don’t have standardized writing systems. This speech-based approach could also lead to much faster, more efficient translation systems, since they won’t require the additional steps of converting speech to text, translating it, and then generating speech in the target language.

In addition to their needing suitable training data in thousands of languages, MT systems today are simply not designed to scale to meet the needs of everyone around the globe. Many MT systems are bilingual, meaning there is a separate model for each language pair, such as English-Russian or Japanese-Spanish. This approach is extraordinarily difficult to scale to dozens of language pairs, let alone to all the languages in use around the world. Imagine needing to create and maintain many thousands of different models for every combination from Thai-Lao to Nepali-Assamese. Many experts have suggested that multilingual systems might be helpful here. But it has been tremendously difficult to incorporate many languages into a single efficient, high-performance multilingual model that has the capacity to represent all languages.

Real-time speech-to-speech MT models face many of the same challenges as text-based models but also need to overcome latency — the lag that occurs when one language is being translated to another — before they can be effectively used to enable real-time translations. The main challenge comes from the fact that a sentence can be spoken in different word orders in different languages. Even professional simultaneous interpreters lag behind the original speech by around three seconds. Consider a sentence in German, “Ich möchte alle Sprachen übersetzen,” and its equivalent in Spanish, “Quisiera traducir todos los idiomas.” Both mean “I would like to translate all languages.” But translating from German to English in real time would be more challenging because the verb “translate” appears at the end of the sentence, while the word order in Spanish and English is similar.

4. What’s at stake in Ukraine is the direction of human history – Yuval Noah Harari

At the heart of the Ukraine crisis lies a fundamental question about the nature of history and the nature of humanity: is change possible? Can humans change the way they behave, or does history repeat itself endlessly, with humans forever condemned to reenact past tragedies without changing anything except the decor?

One school of thought firmly denies the possibility of change. It argues that the world is a jungle, that the strong prey upon the weak and that the only thing preventing one country from wolfing down another is military force.

This is how it always was, and this is how it always will be. Those who don’t believe in the law of the jungle are not just deluding themselves, but are putting their very existence at risk. They will not survive long.

Another school of thought argues that the so-called law of the jungle isn’t a natural law at all. Humans made it, and humans can change it. Contrary to popular misconceptions, the first clear evidence for organised warfare appears in the archaeological record only 13,000 years ago.

Even after that date there have been many periods devoid of archaeological evidence for war. Unlike gravity, war isn’t a fundamental force of nature. Its intensity and existence depend on underlying technological, economic and cultural factors. As these factors change, so does war…

…During the same period, the global economy has been transformed from one based on materials to one based on knowledge. Where once the main sources of wealth were material assets such as gold mines, wheat fields and oil wells, today the main source of wealth is knowledge. And whereas you can seize oil fields by force, you cannot acquire knowledge that way. The profitability of conquest has declined as a result.

Finally, a tectonic shift has taken place in global culture. Many elites in history – Hun chieftains, Viking jarls and Roman patricians, for example – viewed war positively. Rulers from Sargon the Great to Benito Mussolini sought to immortalise themselves by conquest (and artists such as Homer and Shakespeare happily obliged such fancies). Other elites, such as the Christian church, viewed war as evil but inevitable.

In the past few generations, however, for the first time in history the world became dominated by elites who see war as both evil and avoidable. Even the likes of George W Bush and Donald Trump, not to mention the Merkels and Arderns of the world, are very different types of politicians than Atilla the Hun or Alaric the Goth…

…The decline of war is evident in numerous statistics. Since 1945, it has become relatively rare for international borders to be redrawn by foreign invasion, and not a single internationally recognised country has been completely wiped off the map by external conquest. There has been no shortage of other types of conflicts, such as civil wars and insurgencies.

But even when taking all types of conflict into account, in the first two decades of the 21st century human violence has killed fewer people than suicide, car accidents or obesity-related diseases. Gunpowder has become less lethal than sugar…

…The decline of war didn’t result from a divine miracle or from a change in the laws of nature. It resulted from humans making better choices. It is arguably the greatest political and moral achievement of modern civilisation. Unfortunately, the fact that it stems from human choice also means that it is reversible.

Technology, economics and culture continue to change. The rise of cyber weapons, AI-driven economies and newly militaristic cultures could result in a new era of war, worse than anything we have seen before. To enjoy peace, we need almost everyone to make good choices. By contrast, a poor choice by just one side can lead to war.

This is why the Russian threat to invade Ukraine should concern every person on Earth. If it again becomes normative for powerful countries to wolf down their weaker neighbours, it would affect the way people all over the world feel and behave.

The first and most obvious result of a return to the law of the jungle would be a sharp increase in military spending at the expense of everything else. The money that should go to teachers, nurses and social workers would instead go to tanks, missiles and cyber weapons.

A return to the jungle would also undermine global co-operation on problems such as preventing catastrophic climate change or regulating disruptive technologies such as artificial intelligence and genetic engineering. It isn’t easy to work alongside countries that are preparing to eliminate you.

And as both climate change and an AI arms race accelerate, the threat of armed conflict will only increase further, closing a vicious circle that may well doom our species.

5. The Infinite Optimism of Physicist David Deutsch – John Horgan and David Deutsch

Horgan: Are you as optimistic now as when you wrote The Beginning of Infinity?

Deutsch: What I call optimism is the proposition that all evils are due to a lack of knowledge, and that knowledge is attainable by the methods of reason and science. I think the arguments against that proposition are as untenable as ever.

I’m also “optimistic” in the sense that I expect progress to continue in the future. I’m even a little more so now than I was, because I see that the idea of it is catching on.

Horgan: Do you really, truly, believe in existence of other universes, as implied by the many-worlds hypothesis?

Deutsch: It’s my opinion that the state of the arguments, and evidence, about other universes closely parallels that about dinosaurs. Namely: they’re real – get over it.

But I think that belief is an irrational state of mind and I try to avoid it. As Popper said: “I am opposed to the thesis that the scientist must believe in his theory. As far as I am concerned ‘I do not believe in belief,’ as E. M. Forster says; and I especially do not believe in belief in science.” (Actually Forster’s view was much more equivocal than Popper’s on this.)…

…Horgan: Do you believe in what Steven Weinberg has called a “final theory” in physics?

Deutsch: No. I guess that deeper theories will always reveal still deeper problems. (“Deeper” doesn’t necessarily mean “in terms of ever smaller constituents,” by the way.)

Horgan: Edward Witten has said that consciousness “will always remain a mystery.” What do you think?

Deutsch: I think nothing worth understanding will always remain a mystery. And consciousness (qualia, creativity, free will etc.) seems eminently worth understanding.

6. Sebastian Kanovich – Powering Emerging Markets Payments – Patrick O’Shaughnessy and Sebastian Kanovich

[00:16:18] Patrick: What have you learned given how many times you’ve done it about working with new regulators and regulatory environments? What is excellent to you on your team at dealing with this unique aspect of it, if that’s such a key part of success?

[00:16:32] Sebastian: To me, the biggest lesson has been the importance of treating regulators as grownups that are trying to do the best they can in the markets under the conditions they operate. Sometimes us from a payment standpoint or from a technology standpoint, we want to move fast. We want everything to be obvious in 30 seconds. We forget that people in the regulatory bodies have a very different set of incentives. They want to understand exactly what is it that’s going to be processed, and making sure that you raise their comfort level and you continue to invest in that education process, it’s something that we’ve learned.

In many countries where we operate, we are working with the regulator to build a regulatory framework. This is how a regulatory framework should look for a company like Google. These are the things you should take care of. This is how you should think of taxes. And I think over time, they get to see us more and more as an enabler. The thing that has happened in the last few years is that some of the merchants for which we process have become ubiquitous in the markets where we operate. Users won’t live without Facebook or without Google, or they’ll do WhatsApp messaging and commerce, and they’ll drive an Uber and they’ll get a Rappi . All of that complexity exists and regulators understand. So they are more and more open to say, how do we cover for this? How do we make sure there’s a regulatory framework? There’s a way for these companies to be able to thrive and us as a regulator to be comfortable. Understanding those two things has been extremely important…

…[00:29:18] Patrick: There’s a nice thesis that I like to think about, which is that for every repetitive digital function, there will be an API first company that standardizes that function and provides a sort of Lego piece so that developers can build as many apps as they want. And they basically hire out the discreet repeatable functions. Since you’re doing that, providing one of those very big function in this case, abstracted away from payments, what have you learned just about great API building? What advice would you give to the founders out there not in payments, but just in the API space that are trying to build an excellent single function that becomes widely adopted for developers?

[00:29:55] Sebastian: I think the biggest temptation when you are building an API business is what your API should do and what it shouldn’t do and what are the limits of what you are trying to build. APIs are powerful where they’re standardized. So if for any given use case, you need to integrate into five different places, even if the value proposition is great, to me, that’s dead before starting. We always try to find an initial pain point that can be covered and be ruthless about saying no to the other stuff, because we think that’s a way that you generally differentiate. It’s tough to be solving hundreds of things because you are aiming to standardize. By definition if you standardizes, you need to say no to some stuff. If you have too many use cases, you are not covering anything. That’s something we’ve learned and we’ve learned the hard way.

The other thing is API businesses are sometimes tempted to compete with their customers. When you’re providing infrastructure, you are sitting in the middle of that transaction where value is being created, and it’s very tempting for companies to say, “I understand the user. I understand the merchants. Why do I sit in the middle?” Part of what I think has made dLocal successful as of now, it’s making sure that our merchants and our counterparts understand that we are not here to compete with them. We are here to power them and for infrastructure place like us and typically API based companies are infrastructure place, I see many of them being tempted to be in front of the end user, and that’s something I would strongly discourage.

[00:31:11] Patrick: Maybe we could give an example of each of those two things. Those are awesome lessons. So starting with the first one, in dLocal, what was an example of the feature that was tempting to build or that you did build that turned out to too much of a distraction for whatever reason?

[00:31:25] Sebastian: We’ve been asked 100 times to go to Germany or to the U.K. Is it easy to do from an API standpoint? Very easy. Do we have the regulatory framework? Absolutely. Are we going to do it? No way. Part of that is saying, what are the use cases that are really complex that we’re going to be able to solve? I’m sure that we could get some traction in that business. Is it going to be a differentiator? No, it’s not. So we’d rather double down or invest in places where it might take longer, but if we get it right, we are differentiating. That’s why we get much more excited over Bangladesh than we get about Germany, because there’s other APIs that are solving the German problem really well or the U.K. or the U.S. problem really well. That’s one lesson.

On the second side on not going after your users, when we were starting, we got many of our merchants to ask us to send emails to our database saying, promote our product. Today it’s very easy to say no. Back in 2016, when we were starting, we said it might be tempting. And we understood really fast that was not a smart decision. Many payments companies do that. We were always against it, because the moment you do it once, you start, the next situation is to this is the product you should be buying. This is how you should be thinking about which ride sharing company to use. And we want to be able to provide infrastructure. We shouldn’t be choosing winners. It’s very tempting and it’s something we haven’t done. And we are strongly committed not to do.

7. Makes You Think – Morgan Housel

A few lines I came across recently that got me thinking:

“It is far easier to figure out if something is fragile than to predict the occurrence of an event that may harm it.” – Nassim Taleb…

…“Everything feels unprecedented when you haven’t engaged with history.” – Kelly Hayes

“My definition of wisdom is knowing the long-term consequences of your actions.” – Naval Ravikant…

…“It is difficult to remove by logic an idea not placed there by logic in the first place.” – Gordon Livingston

“The best arguments in the world won’t change a single person’s mind. The only thing that can do that is a good story.” – Richard Powers…

…“Technology finds most of its uses after it has been invented, rather than being invented to meet a foreseen need.” – Jared Diamond…

…“Science gathers knowledge faster than society gathers wisdom.” – Isaac Asimov

“Humans don’t mind hardship, in fact they thrive on it; what they mind is not feeling necessary. Modern society has perfected the art of making people not feel necessary.” – Sebastian Junger

“Psychology is a theory of human behavior. Philosophy is an ideal of human behavior. History is a record of human behavior.” – Will Durant

“No amount of sophistication is going to allay the fact that all your knowledge is about the past and all your decisions are about the future.” – Kolossus

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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 dLocal. 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 20 February 2022:

1. Classic 05: A History of 5 Stock Market Crashes w/ Scott Nations – Sitg Brodersen, Preston Pysh, Scott Nations

Preston Pysh  01:18

So Scott, in this episode we’re going to be talking about the crashes of 1907, 1929, 1987, 2008, and the Flash Crash of 2010. I’m sure some, if not all of those years are very familiar for a lot of people in our audience. But let’s start all the way back to 1907. And for people not familiar with this crash, JP Morgan was a key character in this crash. So talk to us a little bit about him and talk to us about the characteristics of the 1907 Crash.

Scott Nations  01:46

JP Morgan was a fascinating man. He was a fascinating man. He was a man of privilege. He was born into privilege. His father was Judas Morgan, who was, well, essentially made the family even more wealthy by selling civil war bonds in London during the American Civil War. JP Morgan was educated as you would expect somebody of his wealth. He had a peripatetic education. He was obviously educated in the United States, but also in Switzerland and in Germany. As a young man in Germany, he developed an appreciation for art; actually a love for art, which informed his private life. But JP Morgan was really raised to be a banker in the early part of the 20th century. He was by far the wealthiest man on Wall Street. Well, maybe not the wealthiest, but certainly the most powerful. He was absolutely the most powerful man on Wall Street. He was called, “the Zeus of Wall Street.” And he really was involved in every aspect of finance in the United States in the first part of the 20th century.

Stig Brodersen  02:54

Now, if we go back to October 1907, the market crashed almost 50 percent from previous ESP. The panic might have been even worse if it hadn’t been for JP Morgan, and he pledged a huge sum of his money and convinced others to do the same. Perhaps you could tell us some of the factors about what caused the crash, but also the story about Morgan’s intervention in the market. It’s a very fascinating story.

Scott Nations  03:22

Before 1907, the United States was really beginning to understand that it was going to be the American Century. It was powerful. It was probably at that point, the most powerful country on the globe. And so, frankly, the United States got carried away with itself. And we’ll talk about some of the specifics of some of these crashes and how these shared some similarities in a bit. But you asked specifically about Morgan’s intervention in the market. This was before the US Federal Reserve existed. In fact, the Panic of 1907 was the cause the Federal Reserve was created. But if you were worried about the market; you were worried about the Panic of 1907, the person you went to see was JP Morgan because, again, he was so powerful. And one example occurred in the midst of the panic. On Thursday, the 24th of October of 1907, when the Press of the New York Stock Exchange went to JP Morgan. At the time, his office was directly across the street from the New York Stock Exchange. Very simply, “Mr. Morgan, we will have to close the exchange early. There’s simply too much selling.” And JP Morgan understood what that meant.

Scott Nations  04:37

His question was: How in the world do you ever reopen a stock market that you’ve been forced to close because there’s too much selling? And so, JP Morgan asked, “When do you normally close?” “Well, sir, we normally close at three o’clock, but we can’t get there. It’s too much sign.” He said, “Then, you will not close one minute early.” And his confidence was…it was not naked. He rounded up bankers in the Wall Street area. Got them all into his office. It was a time when if JP Morgan called, you came running. And he told the assembled bankers, “You have 15 minutes to raise $25 million to save the stock market.” $25 million back then was a colossal amount of money, but JP Morgan essentially said, “You have 15 minutes to raise this money or the stock market is going to close. And who knows when it will ever reopen?” And that’s just one specific story of his involvement. That’s not the first time he did something like that. Probably the most immediate, but within 15 minutes, they had raised actually more than $25 million. The officials were able to go on the floor and say, “We have $25 million to lend to investors, who are in trouble.” People were so desperate to get this money that the clerk, who was responsible for recording borrowers and amounts had his suit coat ripped off of him in the turmoil. So JP Morgan was really the man; the single man, who managed to save the stock market in 1907.

Preston Pysh  06:11

So Scott, you briefly mentioned that the Panic in 1907 was the reason for the creation of the Federal Reserve. Talk to us a little bit more about that idea.

Scott Nations  06:19

It became obvious to everybody after things had settled down after the Panic of 1907, the United States government needed a way to inject liquidity into the system and didn’t have it. And that there needed to be a lender of last resort, if you will, for the financial market. And that didn’t exist before 1907. And so, the Federal Reserve was created in 1913 because everybody realized, if nothing else, JP Morgan is not going to live forever. And we can’t rely on one man, one person to essentially bailout the stock market in times of stress.

Stig Brodersen  06:57

Let’s turn to the next crash, the crash of 1929. And to really understand what happened, we also have to understand how crazy the market behaved in 1927 and 1928. And I think you do a fantastic job of that in your book explaining everything leading up to the crash. In 1928, the Dow closed in 300, which probably to the listeners out there seems outrageously cheap, but that was definitely not the case. And this was at the end of the second biggest two-year run ever. It was actually more than 90%. So Scott, what drove the all-time highs leading up to the crash in 1929?

Scott Nations  07:38

In the late 1920s, actually much of the entire decade, but particularly in the last half of the 1920s, there were simply a euphoria at work in the United States. It was not just financial. It was…it had to do with the United States’ place in the world. And from a military point of view, also from an industrial point of view. So as you pointed out, in 1927 and 1928, the stock market gained more than 90%. We had come out of World War I. We felt great about our place in the world, but there were also some other things that were…for example, in a situation like that; with an economy roaring like that; a stock market booming like that, you would expect the Federal Reserve, which was new at the time, you would expect them to raise rates. One Federal Reserve officer at one time described it as “taking away the punch bowl, when the party really got going.” And the Federal Reserve did not do that. In fact, they kept rates low. They kept rates too low, largely because they wanted to help England return to the gold standard after World War I. That was a tragic mistake–keeping rates that low. There was also a roster of new technologies that were unleashed following World War I. Radio would probably be the biggest, but also the automobile industry really got going; really came into its own. And then, America just felt good about itself. And so, all of those things spawn this euphoria that eventually made its way into the stock market. And the stock market got carried away with itself.

Stig Brodersen  09:13

It’s very interesting. And you mentioned that before here with the Federal Reserve. Now, could you talk more about which actions did it take? You already, again, briefly touched upon that. But if you should outline and put some years on like before, during and then, especially after the crash. It was very interesting, the type of monetary policy that the Federal Reserve decided to carry out.

Scott Nations  09:34

The Federal Reserve really started making errors in policy in 1924, when they were essentially begged by the British government to help them get back on a gold standard by lowering interest rates here in the United States. And they did that. And they continued that sort of policy, and eventually the Federal Reserve simply lost control of the monetary situation in the United States. There was so much money being made by industry and individuals that they were happy to loan that money, the stock market speculators, and that’s sometimes called, “the call money market.” Call money is money that’s available to investors to speculate with, and for a long time that money had been provided by banks. And now, outside investors were providing it, and they did it in droves because interest rates were so low, otherwise. And the bubble was undeniable. In the late 1920s, American brokerage firms paid a $100,000 to put a brokerage office on a single transatlantic liner, the Barren Garea. A $100,000 just to open up; the opportunity to open a brokerage office. Another brokerage firm opened a tent at the US Amateur Golf Open in Pebble Beach. The stock market was such a phenomenon, and the rally was such a phenomenon that people didn’t want to get away from it. 

2. Latest success from Google’s AI group: Controlling a fusion reactor – John Timmer

As the world waits for construction of the largest fusion reactor yet, called ITER, smaller reactors with similar designs are still running. These reactors, called tokamaks, help us test both hardware and software. The hardware testing helps us refine things like the materials used for container walls or the shape and location of control magnets.

But arguably, the software is the most important. To enable fusion, the control software of a tokamak has to monitor the state of the plasma it contains and respond to any changes by making real-time adjustments to the system’s magnets. Failure to do so can result in anything from a drop in energy (which leads to the failure of any fusion) to seeing the plasma spill out of containment (and scorch the walls of the container).

Getting that control software right requires a detailed understanding of both the control magnets and the plasma the magnets manipulate, or, it would be more accurate to say, getting that control software right has required. Because today, Google’s DeepMind AI team is announcing that its software has been successfully trained to control a tokamak…

3. EE380 Talk [on cryptocurrencies and their externalities] – David Rosenthal

“Blockchain” is unfortunately a term used to describe two completely different technologies, which have in common only that they both use a Merkle Tree data structure. Permissioned blockchains have a central authority controlling which network nodes can add blocks to the chain, and are thus not decentralized, whereas permissionless blockchains such as Bitcoin’s do not; this difference is fundamental:

• Permissioned blockchains can use well-established and relatively efficient techniques such as Byzantine Fault Tolerance, and thus don’t have significant carbon footprints. These techniques ensure that each node in the network has performed the same computation on the same data to arrive at the same state for the next block in the chain. This is a consensus mechanism.
• In principle each node in a permissionless blockchain’s network can perform a different computation on different data to arrive at a different state for the next block in the chain. Which of these blocks ends up in the chain is determined by a randomized, biased election mechanism. For example, in Proof-of-Work blockchains such as Bitcoin’s a node wins election by being the first to solve a puzzle. The length of time it takes to solve the puzzle is random, but the probability of being first is biased, it is proportional to the compute power the node uses. Initially, because of network latencies, nodes may disagree as to the next block in the chain, but eventually it will become clear which block gained the most acceptance among the nodes. This is why a Bitcoin transaction should not be regarded as final until it is six blocks from the head.

Discussing “blockchains” and their externalities without specifying permissionless or permissioned is meaningless, they are completely different technologies. One is 30 years old, the other is 13 years old.

Because there is no central authority controlling who can participate, decentralized consensus systems must defend against Sybil attacks, in which the attacker creates a majority of seemingly independent participants which are secretly under his control. The defense is to ensure that the reward for a successful Sybil attack is less than the cost of mounting it. Thus participation in a permissionless blockchain must be expensive, so miners must be reimbursed for their costly efforts. There is no central authority capable of collecting funds from users and distributing them to the miners in proportion to these efforts. Thus miners’ reimbursement must be generated organically by the blockchain itself; a permissionless blockchain needs a cryptocurrency to be secure.

Because miners’ opex and capex costs cannot be paid in the blockchain’s cryptocurrency, exchanges are required to enable the rewards for mining to be converted into fiat currency to pay these costs. Someone needs to be on the other side of these sell orders. The only reason to be on the buy side of these orders is the belief that “number go up”. Thus the exchanges need to attract speculators in order to perform their function.

Thus a permissionless blockchain requires a cryptocurrency to function, and this cryptocurrency requires speculation to function.

Why are economies of scale a fundamental problem for decentralized systems? Participation must be expensive, and so will be subject to economies of scale. They will drive the system to centralize. So the expenditure in attempting to ensure that the system is decentralized is a futile waste…

…The costs that Proof-of-Stake imposes to make participation expensive are the risk of loss and the foregone liquidity of the “stake”, an escrowed amount of the cryptocurrency itself. This has two philosophical problems:

• It isn’t just that the Gini coefficients of cryptocurrencies are extremely high[4], but that Proof-of-Stake makes this a self-reinforcing problem. Because the rewards for mining new blocks, and the fees for including transactions in blocks, flow to the HODL-ers in proportion to their HODL-ings, whatever Gini coefficient the systems starts out with will always increase. Proof-of-Stake isn’t effective at decentralization.
• Cryptocurrency whales are believers in “number go up”. The eventual progress of their coin “to the moon!” means that the temporary costs of staking are irrelevant.

There are also a host of severe technical problems. The accomplished Ethereum team have been making a praiseworthy effort to overcome them for more than 7 years and are still more than a year away from being able to migrate off Proof-of-Work.

4. Geoffrey Moore – Building Gorilla Businesses – Patrick O’Shaughnessy and Geoffrey Moore 

[00:03:07] Patrick: Geoffrey, your books were some of my earliest education in the world of the competitive landscape of technology. I’d actually start at the end in terms of how I think about your work, which is with the concept of a gorilla as a business. Everyone’s going to know, Crossing the Chasm. We’re going to talk a lot about all the insight from that book and that thinking. But I think the gorilla as a concept is for me a great unifying theme of your work, aspirationally we all are going to want to be gorillas or invest in gorillas, or start gorillas at some point. Maybe just begin there. What do you mean by a gorilla company? Define that for us to begin.

[00:03:43] Geoffrey: The simplest definition is a market share leader in a powerful category. In order to sort of take that model apart, we created something called the hierarchy of powers. The idea behind the hierarchy of powers was, go back to investing. If you want to invest in a successful company, you want to invest in one that has more competitive advantage than the alternative investments. How would you actually analyze competitive advantage? That led us to something called the hierarchy of powers. This is the core investment model by on the Gorilla Game and a book called Living on the Fault Line and Going Forward. The hierarchy of power says the most powerful power is what we call category power. It has to do with the technology adoption life cycle, and where is the category that this company specializes in monetizing, where is it in its adoption life cycle? For most businesses most of the time it’s on what we call main stream. In other words, the category’s been established for a decade or more, there’s budget for it. It’s settled out. There’s a pecking order of vendors in the category and the category probably grows close to GDP growth rates. Value investors spend most of their life with categories in that world.

Tech investors, and my whole world is tech. We invest at the beginning of these life cycles. Sometimes before this, there’s not even a category, it doesn’t even exist yet, it’s called category creation. But the key moment in that category development life cycle or what they call the technology adoption life cycle, is when all of a sudden the world goes all in on the new paradigm. The way we went all in on cloud computing, the way we went all in on mobile apps, the way we’ve gone all in on streaming video. When it goes all in what happens is, all of a sudden the world which in a prior year did not have budget for this category, now everybody has budget for this category. And so it creates this huge secular uplift and spend, we called it the tornado. We had a book called Inside the Tornado, huge secular. That’s category power. If you are in that category, that rising tide floats all boats, that is the number one predictor of your future success for the next several years. That’s why you see these incredible valuations in companies that are losing money because the investing community said, yeah, but they’re in the hot category. Having said that, the next thing we said is, well, that category is going to sort out with a pecking order. The power law of returns from that pecking order is, the gorilla is going to get the lion share or the gorilla’s share if you will.

Number two will probably get half of what the gorilla gets. And number three will get half of what the chimp gets. And so that led to gorilla to chimp monkey sort of returns. And so the idea behind the Gorilla Game was, you would see a category going into tornado. You would buy a portfolio of companies that could win. As you saw who was winning, you would gradually exit the ones that are monkeys and chimps and put more and more money into your gorilla. And then you would hold the gorilla because the gorilla’s power position, what happens is the ecosystem forms around the gorilla, which instantiates the gorilla permanently in that category. Now you can screw it up, but in general, it’s not just that the gorillas powerful during the tornado, even on main street, the world is now organized permanently around the gorillas de facto standards and whatever. There was just a clear sense of the sooner you could identify the gorilla and then concentrate in the gorilla, the better it would go…

…[00:09:43] Patrick: I want to come back to category creation and how you think about the idea of a category itself, but this is a great excuse to talk about your notion of architecture. If we were to think about a two by two matrix or something with open and closed architecture on one access and proprietary and non proprietary on the other, this is for me, a critical unlocking idea. Salesforce is a great example. Most power full version of a gorilla. I love the litmus test that you never get fired for blank. The blanks are the gorillas. But talk us through this concept of architecture. Why is this so important within a category? What does it mean? And what does that two by two matrix mean?

[00:10:19] Geoffrey: The difference between open architecture and closed architecture was, Apple has a very closed architecture. You don’t participate in Apples architecture. Whereas Android has a very open architecture. Okay. The idea is, do you want other people to complete your solution? The cable box was contained, but the Roku is an open architecture. In general, I think originally it was all closed. The IBM architecture was just IBM. DEC was just DEC. The Sun just Sun. No, actually it was Sun, they began to do open architecture. They would buy their storage from a different vendor or you’d get your operating system from the Berkeley operating system. That was the beginning of open architecture. I think what we learned during the last 20 years is in general open architecture beats closed architecture, because closed architectures always have a single point of failure. Meaning if any part of the closed architecture doesn’t work, you can’t ship. In an open architecture if you have a failure of one component, you can get it from another vendor and get back in the game.

Now open architecture is harder to manage for quality, and so that was always the challenge, but that was closed versus open. Proprietary versus non-proprietary, has to do with who gets to control the next release of this thing. Open source is not proprietary. Open source, there’s no locking. But proprietary there is locking. And so the most powerful idea was proprietary open architectures, where you had proprietary control of an ecosystem that involved other companies, but they had to eventually play to your standard. That’s what gave the gorilla the most power. Because now what the gorilla can do is, you have to stay with me, I’m a market mover. I don’t just move my own products. I move everybody’s products. By the way, by staying with me, you leave my competitor behind. Every time I differentiate from my competitor, then you conform to my standards, you just made yourself incompatible with their standards…

…[00:16:40] Patrick: What’s that been like watching more recently, if we think about the most pure play enabling technologies today? It might be the API companies, the Stripe, the Twilio, the Okta’s of the world. Well, how did those companies solve this problem of you need the actual use case, the actual application? Amazon AWS is enabling technology, but it was its own best first customer on the retail side. So that application problem was solved by them. How do you approach these pure play, hire this API for this one function in your application type company?

[00:17:09] Geoffrey: It’s typically around the use case. Like Okta, I think started with single sign on. People were just saying, this is such a pain in the neck, that I have to sign into this, have sign. Okta said, okay, we’ll do single sign on. And then once you did single sign on, you thought, well, wait a minute, we’re sitting in a very interesting piece of real state here. There’s a bunch of highways coming together. Maybe we should have some service stations and a restaurant, we should build some hotels. That’s what Okta did. But enabling infrastructure always starts with a problematic application use case that you can’t solve with existing infrastructure.

And so initially, first of all it looks like, well, your market is so small, there’s only this one use case and there’s only this one application and you’re building all this technology to make that better. Are you sure you want to do that? And if that was the only return, the answer would be, well, no, it doesn’t make any sense at all. But if you’re say, no, that’s my point of entry. And then expand, we called it the bowling alley phase of the technology adoption life cycle, where you’d say I, okay, I’ve got my first use case in my first industry. Can I get a second use case in that industry? Or can I find that use case in the second industry? Either way you were going to expand outward. And then at some point, if you can get enough expansion, the world goes well, hang on, this is the new infrastructure. That’s when the tornado starts.

5. Twitter thread on the importance of alignment within a company – Jean-Michel Lemieux

Another common question I’m answering working with scaling tech companies is…

Q. What’s the worst leadership advice you’ve heard?

A. By far the worst is “Hire great people and get out of their way”. 

Let me explain… 🧵 (1/32)

2/ After a year leading engineering at Atlassian @scottfarkas told me in my perf review that I was doing ok but wondered why I didn’t talk and involve him more regularly.

3/ My answer was “I thought that was my job — to take away all this crap from you and let you do your CEO thing. I thought you wanted me to be autonomous. I need autonomy.” He said sure, but you should cheat “and use my brain to help you”

4/ At that point I changed some habits, involved him more in different ways, got over the autonomy complex, and we got a lot more done together. I learned a lot and we made better decisions.

5/ Since then I’ve hired many leaders and had to repeat the same conversation that @scottfarkas had with me over and over and over. Most people default to expect the wrong version of autonomy.

6/ These experiences sent me down a multi-year reflection. Why did I feel like success was maximizing autonomy and showing that I could take care of things without bugging my boss?

7/ I prioritized autonomy over alignment. It’s a million times easier to measure and feel high autonomy than it is to measure high alignment.

8/ What I’ve learned since, way too slowly, is that companies are performing a monumental balancing act trying to decide what 98% of their problem space to focus, what to ignore, and how to ship. That’s your strategy. And it’s complex, ambiguous, and changing.

9/ The hardest part of building a company is alignment on strategy and clearly communicating it. Think about it this way, a 1 degree deviation in course of a rocket heading to the sun means it will miss the sun by 1.2 million miles. A lack of alignment compounds quickly…

…14/ There’s mass confusion on what to align on? Most people just want to know the very high level goals. And this causes most companies that I work with to align superficially. Their strategy is a superficial incomplete map, they don’t remove scope, communicate clearly, etc…

…17/ The biggest alignment problem is the gap between how much people think they have to align versus what they should align on. There are many strategic decisions in the “how”. eg, what technologies to use, new system vs integration, build in core or in an app.

18/ Alignment forces you to talk with your boss and peers to: – define a strategy, narrow focus – communicate it clearly together – and ensure you’re hired enough people who “get it” and can fill in the implementation details with their teams.

19/ So…when you hire someone or you have a new leader, your number one job is alignment. And you do this continuously. It’s definitely never going to be “hire them and get out of their way”.

6. Owning the funnel – Lillian Li

Since I started writing Chinese Characteristics, I’ve been puzzled by a few observations: why is there a fanatic fixation on internet traffic? Why do firms distinguish between private and public traffic? Why did every consumer app become a super-app? And why are B2B offerings are going the same way? Why is every player worth their salt is moving into payments now? Finally, why do Alibaba’s acquisitions tend to languish while Tencent’s investments tend to thrive?

My current framing for Chinese tech’s underlying logic is that every player is always working on owning the awareness-to-fulfilment funnel (or customer journey). This is a descriptive product strategy that builds on a foundational ethos of owning the user. It outlines the offerings that a tech platform needs to provide to achieve that goal. It looks like Western players are converging in the same direction, Shopify and Google’s move into payments and Facebook’s store fronts are all part of the trend.

This behaviour pattern is stark in Chinese tech is for two reasons. The first is that a defined geographical market constrains Chinese tech. It’s no secret that Chinese companies tend to struggle with internationalisation. Unlike their western counterparts, who can build sizable companies being the best-of-breed for different geographies, Chinese tech companies have to focus on owning the user (and funnel) to grow. As I mentioned in my Bilibili piece:

Relative to western consumer tech companies, who tend to focus on “serving a function” as their core mission, Chinese companies tend to focus on “owning the user” as their core mission (though the initial wedge into the consumer is always through a function – Meituan through food delivery, Ofo through bike-sharing, etc.). Owning the end-user and their attention is what led to the rise of the super apps and Bilibili is no different….Put another way; they want to own the Chinese Gen Z population’s attention through providing a comprehensive entertainment service rather than be the platform that caters for all Chinese UGC video needs. 

In an ecosystem where hundreds of competitors spring up overnight, functions and features get commoditised as soon as they are made. Owning the user by providing the whole monetisation funnel is the closest thing to a moat.

The second reason is Tencent. Tencent is the default operating system for the Chinese population, and it has a particular trait. It doesn’t rely on advertising to monetise. What started as a shrewd product decision to prioritise the user experience has had a lasting impact on the nature of internet traffic in China. Inventory on WeChat is scarce, and it commands a premium from advertisers. In chat, links are earned, Tencent’s anointed portfolio can share links, while the associates of arch-nemesis Alibaba and Bytedance get blocked for spam. Baidu has been stagnating in their ad revenue strategy from lacklustre search (owning the funnel means a walled garden approach). When traffic hegemons are capricious, everyone suffers.

Regardless of the origins, once some tech players have started the game of owning their proprietary funnel (or user), everyone has to move in the same direction just to keep up.

7. Six Questions For Derek Thompson – Morgan Housel and Derek Thompson

What aren’t people talking about enough?

For the world, carbon removal technology. It’s the most obviously important nascent technology on the planet, given the fact that even if we shift immediately to 100% renewable energy, that still leaves all the carbon dioxide we’ve already spewed into the atmosphere, which will stay there for decades. We have to find a way to vacuum the skies to avoid the worst effects of global warming…

…What do you want to know about the economy that we can’t know?

What is the right level and distribution of income to maximize total national happiness, both now and in the future? The time element of the question is important. If you waved a magic wand and made it so that everybody had equalish income today, that would clearly eliminate a lot of misery. But if you enforced equal incomes permanently, you’d create a lot of new problems. Where are the rewards for effort? Where are the incentives for hard work, or invention, or problem-solving? How do you fix the issue of free-loading, or resentment between workers and loafers in the utopia of pure and permanent equality? Mandating perfect and permanent equality doesn’t work. But it’s really, really hard to determine what level of inequality is “right.”

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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), Apple, Meta Platforms (parent of Facebook), Okta, Shopify, Tencent, and Twilio. 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 13 February 2022:

1. The Reason Putin Would Risk War – Anne Applebaum

But of all the questions that repeatedly arise about a possible Russian invasion of Ukraine, the one that gets the least satisfactory answers is this one: Why?

Why would Russia’s president, Vladimir Putin, attack a neighboring country that has not provoked him? Why would he risk the blood of his own soldiers? Why would he risk sanctions, and perhaps an economic crisis, as a result? And if he is not really willing to risk these things, then why is he playing this elaborate game?…

…But although Putin missed the euphoria of the ’80s, he certainly took full part in the orgy of greed that gripped Russia in the ’90s. Having weathered the trauma of the Berlin Wall, Putin returned to the Soviet Union and joined his former colleagues in a massive looting of the Soviet state. With the assistance of Russian organized crime as well as the amoral international offshore-money-laundering industry, some of the former Soviet nomenklatura stole assets, took the money out of the country, hid it abroad, and then brought the cash back and used it to buy more assets. Wealth accumulated; a power struggle followed. Some of the original oligarchs landed in prison or exile. Eventually Putin wound up as the top billionaire among all the other billionaires—or at least the one who controls the secret police.

This position makes Putin simultaneously very strong and very weak, a paradox that many Americans and Europeans find hard to understand. He is strong, of course, because he controls so many levers of Russia’s society and economy. Try to imagine an American president who controlled not only the executive branch—including the FBI, CIA, and NSA—but also Congress and the judiciary; The New York Times, The Wall Street Journal, The Dallas Morning News, and all of the other newspapers; and all major businesses, including Exxon, Apple, Google, and General Motors.

Putin’s control comes without legal limits. He and the people around him operate without checks and balances, without ethics rules, without transparency of any kind. They determine who can be a candidate in elections, and who is allowed to speak in public. They can make decisions from one day to the next—sending troops to the Ukrainian border, for example—after consulting no one and taking no advice. When Putin contemplates an invasion, he does not have to consider the interest of Russian businesses or consumers who might suffer from economic sanctions. He doesn’t have to take into account the families of Russian soldiers who might die in a conflict that they don’t want. They have no choice, and no voice.

And yet at the same time, Putin’s position is extremely precarious. Despite all of that power and all of that money, despite total control over the information space and total domination of the political space, Putin must know, at some level, that he is an illegitimate leader. He has never won a fair election, and he has never campaigned in a contest that he could lose. He knows that the political system he helped create is profoundly unfair, that his regime not only runs the country but owns it, making economic and foreign-policy decisions that are designed to benefit the companies from which he and his inner circle personally profit. He knows that the institutions of the state exist not to serve the Russian people, but to steal from them. He knows that this system works very well for a few rich people, but very badly for everyone else. He knows, in other words, that one day, prodemocracy activists of the kind he saw in Dresden might come for him too. 

2. Classic 06: Elon Musk – Stig Brodersen and Preston Pysh

Preston Pysh  14:41

One of the key points that I felt was really important to highlight his childhood was his desire to read. They talked about in the book how he had pretty much gone to the local public library and almost had read every single book inside of that library. They described hs characteristic, “If you saw Elon Musk at any given point in time, he probably had a book in his hand, and he was reading it.” And I think that that’s really important for people to understand and to know that a guy like Elon Musk doesn’t become as intelligent as he is. And we’ll get into some of this stuff later on in the discussion here.

15:15

But the one takeaway that I had is this guy is brilliant. He is absolutely a wicked smart dude. And I attribute most of that to the fact that he is a total learning machine. And that’s such a common thread that we’ve found with all these billionaires that we study. They are total learning machines. They are learning something every single day. They’re learning something new. They’re studying things that might not even seem like they’re correlated. And we definitely got that at a very extreme level with Elon Musk, and I find that to be extremely important for people to understand…

...Preston Pysh  24:58

It was around 200 million, I want to say. From the sale of PayPal off to eBay, based on the equity that he owned, he had a very large chunk of money at this point. He moves to Los Angeles, and he really wants to get into the space industry. And he has this idea to start his own space company. There’s some time in between here where he’s living in LA and really trying to figure out what is it that he really wants to do in space. And he’s in these different Mars societies. And he’s donating money to these research stations and things like that.

But in the end, he decides that he wants to start his own space rocket company and really go into the private space industry. Now, where I think the story was really awesome in the book. He talks about how he wants to go over to Russia and buy some of their rockets to start his own space company. So he goes over to Russia and he just has a really bad visit with them. And they really didn’t take him seriously because he’s like 29 years old. He’s still in his 20s at this point. He goes over to Russia and he’s like, “Yeah, I want to buy some of your rockets.” And they look at him like he’s absolutely crazy and weren’t really playing ball really with him.

26:15

So on the flight back, he went over there with some of his close friends that he was wanting to start this space business with… And on the way back, he pulls out his laptop computer and has like all the components listed for basically building his own rocket. And he looks at his friends and he says, “We don’t need to buy this rocket from Russia. Let’s just do our own. Let’s just make our own.” And I think his buddies were looking at him like, “This guy’s going off the deep end.” He’s in these Mars society wanting to the initial thought was let’s put a plant on Mars. So we can say that we put life on Mars. And just this discussion in the book was absolutely fascinating. I think anybody who would read this part would really get a kick out of it.

But anyway, Elon was not in the least bit deterred by how crazy it might be to start his own rocket company and create his own space company from the ground up. I mean, literally, from the ground up and not be buying any of the components from anybody. He’s just like, “We’ll make it all and we’ll just do it.”

Stig Brodersen  27:20

I think it was just so much fun because what people don’t realize that if they listen to the book is that he has a very detailed plan of how to colonize Mars, like, “This year, there should be so many inhabitants. And this year, we should fly this out to Mars.” And if this came from anyone else than Elon Musk, I don’t know… The FBI will probably arrest that guy because he thought he was crazy. He is one that would harm other people. I don’t know. He just sounds so crazy.

But the interesting thing is that all of these things and we were talking about Tesla, and later on, but all these things that he said that would happen, actually happened. I mean, I can see why people would think he would be crazy with his plans about building a rocket because no one does that. Usually, you have countries doing this and it would take decades for countries to do it. But he just flies out to Russia with a friend of his to buy rockets. And when they said no, he just built his own. And he just seems so unrealistic that’s even possible.

Preston Pysh  28:23

You know, the thing I didn’t know before reading this book is I just thought the mission of SpaceX was really to pump all these private satellites into space and be profitable and bid on government work and stuff like that. But that wasn’t it. The mission of SpaceX is to colonize Mars. And I mean, they say that in a very straight face manner. Like that’s the thing that I think is so crazy. When I read that in the book, and I heard that for the first time, I was pretty much flabbergasted like, “Oh, that that was probably not right.” And then it keeps coming back up and keeps coming up. And I’m telling you, folks, the mission of SpaceX is to colonize Mars and to put human beings in colonies on Mars. That’s what Elon is wanting to do.

In fact, that mission statement is so strong for him, that he will not take the company public until that mission is pretty much assured. He will not take the company public. So that’s just totally… I find that to be total insanity. Okay, I really do I find that to be totally nuts because I just don’t think that you would find too many people in this world that would want to do that. Maybe I’m wrong. Maybe I’m out in the left field, but I don’t think you’d find too many people that would want to do that. Let alone would have the money to pay to go do that and live in those conditions. I just think that’d be really dismal. But what are your thoughts on that? Is he out to launch?

3. NZS Capital Part II: What’s Going on in Today’s Markets? (Plus more Semiconductors!) – Ben Gilbert, David Rosenthal, Brad Slingerland, and Jon Bathgate

David: Speaking of, we were talking before the episode, the reason we wanted to do this with you guys is from the first episode we did with NZS, your whole way of using complexity theory to think about investing in companies and markets is fascinating. I love it. So many of our listeners loved it and we thought because it’s so different from everything else we’ve heard. Let’s talk to you guys about what is going on right now here in late January 2022 as markets are different than they were a month ago.

Ben: Let me tee up with what David means by right now. We’re recording this at 9:00 AM Pacific on January 27. Right now, the S&P year to date is down about 9.5%, probably rebounded a little bit this morning, and the NASDAQ, which everyone knows is more tech-focused, down about 15%. Quite a start to 2022 after a hell of a run in 2020 and 2021.

By the time you hear this, who knows because it seems like every cycle in every part of the business has gotten shorter and shorter, but that is where we are today. Brad, maybe let’s start with you. This is an enormous question so you can choose to answer however you’d like, but what is going on and how did we get here?

Brad: I want to go all the way back a million years in time, but we probably couldn’t.

David: This is Acquired.

Brad: Around the evolution of human psychology. Just to not go quite back that far. I mean, obviously, we had the pandemic started, we’re coming up on two years on that. There was this initial fear that Jon references, I think everybody probably remembers, it does feel like a lifetime ago. Then this just unleashing of incredible coordinated global economic stimulus, both fiscal and monetary in form of low rates here in the US, literally checks being sent to people.

There is this period of uncertainty in 2020 that just exploded into this period of spending in 2021. You look at consumer spending 2021 over 2019 and it’s like probably 18% more I think is the recent Commerce Department data for the US. That’s […] 2020 but versus pre-pandemic levels, there’s just all this money. The way we’re spending it, where we’ve spent it as consumers has been in different places. Instead of going on vacation, we’ve been fixing up our houses, so it’s caused all this sort of acute demand for a lot of things and then not demand for these other things.

The economy just can’t turn. We are so global. We’ve been on the sort of 30-year globalization trend where the supply chain is getting more spread out, and in a lot of ways more fragile and you just can’t get your hands on things. This huge burst in demand last year caused this big pickup in inflation. I think one of the latest numbers is 6% or 7%, and some of it is transitory, some of it is maybe a little bit structural and we can come back to that.

Now the governments are saying, okay, well, we gave everybody way too much money. We gave way too much stimulus out there in the economy, and we’re going to reel it back in. The main tool they have to do that is to raise interest rates. They’ve signaled raising interest rates—depending on how you want to read the tea leaves—maybe four times.

Ben: When they’re raising interest rates, I think I haven’t seen, obviously they’ve been taking on more and more on their balance sheet every month. They’ve been buying hundreds of billions of dollars in assets and I think that’s tapering. Have they ever announced any plan to start shrinking the balance sheet of the Fed along with these interest rate raises?

Brad: I think that ultimately, the Fed would like to stop the experiment of running a massive balance sheet. Suddenly, there are a lot of questions on certainty around how that plays out. You end up with this scenario where no rates are going up and then there’s this tension in the stock market between people who think this is appropriate, inflation is the root of all evil, it’s structural, and it’s here to last and we’ve got to just kill it.

The people who think well, actually, the economy’s quite fragile. We’re still in a pandemic, people are still sick. There’s a lot of things going on. If we all of a sudden just hoover all of the money back out as quickly as possible, then that’s probably as bad as what the situation was, to begin with. The market always wants to find some level of homeostasis.

One of the things we learned from complex adaptive systems is to really think biologically rather than computationally, which is the way a lot of market participants think. If we think about homeostasis, here in our body, we’re trying to constantly maintain our temperature right around 98.6 degrees, we’re trying to make sure we’re not hungry, and then we get enough sleep at night. All these things that our bodies regulate often without us knowing.

The market’s also trying to do this. It’s trying to come to a consensus on what do we think interest rates are going to be a year from now, 5 years from now, or 10 years from now? What do we think inflation is going to be? What do we think profit margins are going to be? What do we think is going to happen in emerging market growth versus developed market growth?

Most of the time, you can never reach equilibrium or homeostasis in a complex adaptive system. You can in a biological closed system like a human body, but most of the time, it’s constantly being perturbed. This idea of disequilibrium is the equilibrium is a concept from Brian Arthur, who sort of wrote a lot of the great texts, complexity economics, and wrote the original paper on compounding and network effects.

David: Increasing returns, right?

Brad: Sorry, increasing returns not network effects. The market, in particular right now, is struggling to find this homeostasis point, these extreme bouts of volatility up and down. The one thing the market needs to come to some sort of agreement on is what is the discount rate? What are interest rates? What should people use as their hurdle rate for the next 1, 3, 5, 10 years? Right now, there are two camps that are disagreeing on it. I think this creates tension, this sort of bouncing back and forth between these two equilibriums in the market.

That started in March of 2021, actually. It was the first time rates started to go up, growth stock started to come down. You can just see this sort of anti-correlation over the last 10 months now of rates going up, growth stocks coming down, and then we’re in this extreme phase right now.

It’s interesting if you look back, I’ve been through a few rate hike cycles in the market over the last 24 years now, I guess. There does tend to be this initial difficulty in finding an equilibrium fear over high growth, high multiple stocks, stocks that may not have current earnings, but people are banking on earnings in the future.

Then what happens is people tend to gravitate back towards the growth assets because they are the assets that are going to create the most value long term. We’re in this initial period of finding equilibrium or something as close to equilibrium as we can get, and then I would expect this to be no different from prior cycles where unless there’s something structural that we’re not aware of yet, people would be gravitating back towards growth assets.

Ben: As another way to put that—just to make sure I’m understanding it—for these companies without earnings but have high growth that got tremendous multiple expansion by public market investors over the last several years, that was the first place where investors got scared and were selling and created all this downward compression on the multiples so these prices dropped like crazy if this high growth, currently unprofitable, or currently not cash generating tech companies.

Those get sort of whacked the hardest first, but you’re saying ultimately if that’s where the growth is in terms of the companies that will become large and profitable in the future, then that’s a place also where there’s flight back there after the exhale of, okay, we’re safe.

Brad: Yeah, that tends to be what happens. One of the things we learned from complex adaptive systems is we can’t predict the future. I’m always sort of on thin ice when I say this happened in the past and so it might happen in the future. I don’t see any particular reason why at the right equilibrium point, these growth assets aren’t, again, more attractive.

Everybody should have their own sort of way of managing a portfolio of investments, whether it’s in public markets, real estate, or whatever you do. What we do is we balance two types of investments we call resilience and optionality and we’re able to shift back and forth. In times of volatility like today, we like to say, and I’m quoting Brinton here but we don’t see volatility as risk, we view it as an opportunity.

Come back to whatever the basics of your own investment strategy are, it’s a very personal thing for everybody and say, what are the two different types of businesses that I own and where should I be shifting the portfolio today? For us that would be, as the market is volatile, moving out are more resilient growth businesses into our more optional growth businesses.

4. Joy & Competitiveness & Culture – Ravi Gupta

Talking about culture is easy. Living it is hard. But I think at least part of the reason it’s so hard to live is because people often don’t take the time to rigorously define it.

Before we get to some thoughts about how you might go about defining your culture, we should talk about why culture is important.3

Earlier in my career, I thought young people talked about strategy and execution being important and old people talked about culture being important. I actually think they are both true. It’s just a timing difference. The thing that matters right now is the strategy and the execution. The thing that matters in the long term is the people who are setting that strategy and driving that execution. In my mind, the culture determines who self-selects to be those people over the long-term. So if you care about the people who will make the strategy and execution decisions in the moment beyond right now, you should care about culture.

I think of culture as the unwritten contract with your team. Here’s what matters to us. Here’s what will endure even if everything else changes. You should only put things in it that you will honor no matter what. With that in mind, I think it makes sense to only have one or two of these things.

5. How Do You Solve A Problem Like Inflation? – Stephanie Kelton

The second chapter of my book, The Deficit Myth, is titled ‘Think of Inflation.’ From the very beginning, MMT has rejected the conventional approach to fiscal sustainability. While mainstream economists were warning of a looming debt crisis here in America, MMT economists were explaining that the relevant constraint facing currency-issuing governments (like the US, the UK, or Japan) is inflation, not bond vigilantes or insolvency.1

It’s been a long time since the world’s major economies had to wrestle with the problem of high inflation. For most of the last decade—and longer in Japan’s case—central banks have been struggling to push inflation higher not lower.

Now that inflation is here—and running well above target in the US, the UK, Canada, across the Euro Area, and beyond—a fiery debate has erupted over what sent prices soaring and what should be done to rein them back in.

Some blame monetary policy—i.e. the Federal Reserve—for stoking the fire by holding interest rates too low for too long and for ‘pumping too much liquidity’ into the system via the Fed’s massive bond-buying program. Others mainly fault Congress and the White House—i.e. fiscal policy—for sending out too many checks to too many people for too many months, sparking an “excess aggregate demand” problem. Occasionally, someone will even assert that the run-up in inflation is the natural consequence of having embarked on an “MMT experiment,” by which they usually mean the combination of quantitative easing (QE) and massive deficit spending.

On one level, I think it’s fair to say that policymakers did experiment with MMT. But I’m not talking about about QE, which was never championed by MMT economists. What I mean is that the fiscal response to the pandemic differed in important ways from what was done in the wake of the Great Recession, when people like Larry Summers and Jason Furman were helping to shape the Obama administration’s (inadequate) economic policy. Back then, both men pushed hard for deficit reduction, with Furman touting a White House budget that would “show that we can live within our means” by bringing “spending down to the lowest share of the economy since Eisenhower was president.” He delivered those remarks in February 2011, when the unemployment rate (U3) stood at 9 percent and headline inflation (CPI-U) was running at just 2.1 percent.

But this time around, it looked like Congress—Democrats and Republicans—had grown more comfortable with the idea of allowing fiscal deficits to cushion the downturn and sustain the economic recovery. And it was the robust fiscal response that came out of the late-Trump/early-Biden administrations that reflected a shift toward a more enlightened understanding of our monetary system and the spending capacities of the federal government—i.e. MMT. Instead of cowering in fear of debt and deficits, as it did during the Obama years, Congress went big. Not once, not twice, but repeatedly, committing some $5 trillion in fiscal support in the first year of the pandemic alone…

…Alongside the debate over what caused the current bout of high inflation is a debate about how to resolve the problem. A number of people have asked me for the MMT solution. There isn’t one. Let me explain.

Before the pandemic, when inflation was consistently running below 2 percent, I was often asked what MMT would tell us to do if inflation ever became a problem. I have probably answered that question a hundred times, and I always try to separate my response into two parts.

The first part of the answer reminds people that the goal is to fend off inflation before it becomes a problem—i.e. the MMT framework aims to promote price stability. The second part of the answer addresses the question of how to deal with inflation after prices begin to accelerate.

Here are my favorite pre-emptive measures. First, instead of relying on a pool of unemployed workers (NAIRU) to keep inflation in check, MMT relies on a buffer stock of employed workers—and a wage anchor—to promote price stability. This has always been the first line of defense against inflation in the MMT framework. The idea is to create a new automatic stabilizer that triggers a powerful counter-cyclical response to changing economic conditions.4 Instead of allowing millions of people to fall into unemployment each time the economy falters, workers could transition into a public service job that replaces some or all of their lost income. The program enhances price stability by maintaining a supply of employable labor from which employers can hire (at a small premium) as conditions improve. The program facilitates bigger deficits (or smaller surpluses) when the economy softens and smaller deficits (or larger surpluses) as demand strengthens.5

The other way to fend off inflationary pressures before they emerge is to change the way Congress currently evaluates proposed legislation. Instead of asking the Congressional Budget Office (CBO) to assess the budgetary impacts of a proposed legislation, lawmakers should seek to identify—and mitigate— any inflationary pressures before voting to authorize the spending (or tax cuts). As MMT economist Scott Fullwiler put it, this is about replacing the budget constraint with an inflation constraint.

6. Twitter thread on counter-intuitive investing truths – Max Koh

I’ve received a ton of crappy investing advice over the years. And I see even more here on Twitter. What I’m about to say will piss off some people. Don’t read if you’re easily agitated. Still here? Then grab a whiskey and here’s 25 investing “truths” that just ain’t so:

1. Picking individual stocks isn’t for everyone. 90% of people lack the temperament to be good investors. If seeing your net worth get eroded by 30% or more scares you… Then this is not the game you’re built for. It’ll cause you more pain than joy.  And you won’t last long

2. Diversification isn’t for idiots. People who diversify are those who acknowledge that they don’t know what the future holds. It’s healthy to have self doubt. The real idiot is the one who goes all in purely because you spent months deep diving the business.

3. Concentration isn’t an action. It’s an outcome. Concentration is mostly a result of letting your winners run. It’s an outcome that comes from great performance. It’s NOT something you do from day 1 based purely on your own blind faith (or ignorance)…

…9. A company can be a better buy at $200 instead of $20. When companies are much smaller, they’re less proven. But as they execute and their revenues grow, their market cap grows too. So a company can be a safer bet when it’s bigger. It’s all about the execution…

…12. Management is the most important moat of all. In the end, almost everything can and will be copied. What endures will be the culture and quality of people running the ship. That is much harder to replicate. Speaking of management… Find great leaders and teams who impress you with their character and values. You often find positive surprises when you invest in good quality managers. They also help you sleep better at night when your stock drops 50%.

13. Management is important, but execution is king. The quality of the people matters. But make sure the numbers align with the narrative. For great companies with great leaders, you should see a consistent trend in their key metrics. (continued…) Other than some hiccups along the way… The overall direction of the business and metrics should be moving up. Otherwise, something is amiss. I get suspicious if the management says a lot but numbers are taking a long time to show. Execution is everything…

…17. Everyone talks about product-market fit. Nobody talks about investor-portfolio fit. Even if you own the best companies, you could still lose $$. Because your portfolio may not be constructed in a way that suits your unique personality. (continued…) To endure drawdowns and hold through… Your portfolio must fit your specific risk profile and time horizon. And you only learn whether your portfolio is suitable for you during  corrections. The market is an expensive place to find out who you really are.

7. The Attention Span. “Racehorses and Psychopaths.” – Tom Morgan

Cognitive biases are not a particularly interesting topic to me. Just learning about biases doesn’t seem to change people’s behavior much. But I was fascinated by an excellent recent review of Julia Galef’s new book The Scout Mindset (below). Scott Siskind writes:

“Of the fifty-odd biases discovered by Kahneman, Tversky, and their successors, forty-nine are cute quirks, and one is destroying civilization. This last one is confirmation bias – our tendency to interpret evidence as confirming our pre-existing beliefs instead of changing our minds.”

Why is confirmation bias “destroying civilization?” I think it’s super helpful to step back for a second and examine this idea through the universal framework of map and territory. Consciousness exists on a spectrum from pure abstraction (map) to pure engagement (territory).

Galef’s Scout Mindset sets out to remove information to provide a clearer view of the territory. Soldier Mindset just adds more confirmations to make the map more elaborate, regardless of its accuracy.

The really, really dark side here is that the stronger an abstraction, often an outright lie, the more motivating it can be for tribal behavior. The soldier metaphor is doubly-appropriate. Taken to its most horrifying extreme, war and genocide is facilitated by abstraction. Beyond direct kinship bonds, we have developed common coordinating fictions like nationalities. We went from being able to mobilize a tribe of hundreds, to nations of millions. How many people do you personally think you’d be able to convince to risk their life for you? As the author of Sapiens, Yuval Noah Harari, puts it: “you could never convince a monkey to give you a banana by promising him limitless bananas after death in monkey heaven.” A motivating abstraction has to take over at the cognitive limits of empathy, beyond who you can really know and love personally. And yet we can compete and kill more easily by stripping universal humanity from our enemies by turning them into an out-group.

The single passage I have thought of most as I ponder the cultural events of the last two years, and last two thousand years, is from Karen Stenner:

“All the available evidence indicates that exposure to difference, talking about difference, and applauding difference – the hallmarks of liberal democracy – are the surest ways to aggravate those who are innately intolerant, and to guarantee the increased expression of their predispositions in manifestly intolerant attitudes and behaviours. Paradoxically, then, it would seem that we can best limit intolerance of difference by parading, talking about, and applauding our sameness.”

Social movements that create more in-groups are less likely to succeed than ones that emphasize our universal humanity. There’s a remarkable study where participants were shown a video of a hand being stabbed, while their empathic response was measured by fMRI. They found that the empathic response was larger when participants viewed a painful event occurring to a hand labeled with their own in-group, rather than a hand labeled with a different out-group. All it took was a single word emphasizing difference to change how people felt about others experiencing pain.

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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 PayPal and Tesla. 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 06 February 2022:

1. Oral History Interview: Morris Chang – SEMI, The Computer History Museum and Morris Chang

Q: The idea really wasn’t very well received in the industry at that time.

MC: No. It was very poorly received. Well, people just dismissed it, you know, “What the hell is Taiwan doing? What the hell is Morris Chang doing?” They really didn’t think that it was going to go anywhere. There was no market because there was very little fabless industry, almost none. No fabless industry. So who are you going to sell these wafers to? Who are you going to manufacture the wafers for? Of course, the obvious answer was the companies that already existed at that time, the Intels, and TIs, Motorolas, and so on. Now, those companies knew that they would let you manufacture their wafers only when they didn’t have the capacity, or when they didn’t want to manufacture the stuff themselves anymore. Now, when they didn’t have the capacity, and asked you to do the manufacturing, then as soon as they got the capacity, they would stop orders to you, so it couldn’t be a stable market. And when they didn’t want to make the wafers anymore, well, the chance was that it was losing money for them. The product was losing money for them. And so what do you want to do? Do you want to take over the loss, you know? And so that wouldn’t be a very good market either.

So the conclusion at that time, the conventional conclusion was that there was no market. Maybe this idea, this pure-play foundry idea, exploited the only strength you have, which is manufacturing, but there’s no market for it. That’s why it was so poorly thought of. What very few people saw, and I can’t tell you that I saw the rise of the fabless industry, I only hoped for it. But I probably had better reasons to hope for it than people at Intel, and TI, and Motorola, etc because I was now standing outside. When I was at TI and General Instrument, I saw a lot of IC designers wanting to leave and set up their own business, but the only thing, or the biggest thing that stopped them from leaving those companies was that they couldn’t raise enough money to form their own company. Because at that time, it was thought that every company needed manufacturing, needed wafer manufacturing, and that was the most capital intensive part of a semiconductor company, of an IC company. And I saw all those people wanting to leave, but being stopped by the lack of ability to raise a lot of money to build a wafer fab. So I thought that maybe TSMC, a pure-play foundry, could remedy that. And as a result of us being able to remedy that then those designers would successfully form their own companies, and they will become our customers, and they will constitute a stable and growing market for us…

…Q: Was there ever a time when it looked like TSMC, or the dedicated foundry idea would not work?

MC: Oh, yeah, I mean the first few years were not easy, but look, the investors had already put in so much money, and we never had any thought of failing. And in fact, we only had two loss years in all our history. We had a loss year in 1987, the first year that we started, and we again had a loss year in 1990. I mean the first few years were pretty tough, but from ’91 on, we just grew without looking back. The year 2000, that was a tough year for a lot of people. Yes, it was a tough year for us too, but we were profitable, 2000, 2001. We have not lost any money, and we don’t intend to lose any money from 1991 on.

Q: In your view, why has the Taiwan foundry industry been successful?

MC: Well, when you say, “Why has our foundry industry been so successful?,” I have to change that. Actually as of two years ago, some analyst made a calculation…TSMC, up to that point, accumulatory, had made 110 percent of the total pure-play foundry industries’ profit. That means our profit exceeded all other people’s losses by 10 percent. Yes, I guess that’s what it meant. So when you say, “Why is the foundry industry so successful…,” maybe you should change your question to, “Why has TSMC been so successful?”  

2. Bored Ape Yacht Club Artist Says Compensation ‘Definitely Not Ideal’ – Matthew Gault

The people behind the BAYC collection, Yuga Labs, have made millions. But someone had to design the now-iconic apes. Every grin and hat and disinterested eye was lovingly crafted by artists before it was fed into an algorithm. In a new interview at Rolling Stone, BAYC lead artist Seneca shared a conflicted experience working in the NFT space.

Seneca is an artist specializing in disturbing and dreamlike imagery. She was the lead designer of the BAYC collection and did many of the initial sketches. She didn’t draw every hat, shirt, and ape herself, but she’s responsible for much of the overall design. “Not a ton of people know that I did these drawings, which is terrible for an artist,” she told Rolling Stone.

Yuga Labs did pay Seneca for her work, and though she wouldn’t disclose the details of the transaction, she said it “was definitely not ideal.”

She’s still hyped on crypto, web3, and NFTs, but she said she learned some valuable lessons working on BAYC. She told Rolling Stone that artists should ask for royalties and understand NFTs and smart contracts before taking on a project like BAYC.

3. Gavin Baker – The Cyclone Under the Surface – Patrick O’Shaughnessy and Gavin Baker

[00:09:15] Patrick: If we had talked, I don’t know, 9, 10, 11 months ago, the setup arguably would not have been nearly as good. Who knows what we would have said then. Maybe we would have thought multiples would have just continued to expand. But today, undoubtedly, like you said, they’re at or below their 2018 levels. The businesses are better. So it stands to reason sort of that there’s more interesting opportunity set in those set in those three major sub-sectors of semis, software and internet. I want to come back to those in a minute. Before we do that, I’d love to level set with the things in the market or the economy or the world that you’re most carefully interested in and watching relative to the last time we talked, when obviously it was sort of all COVID. But the world has changed a lot since then. We’re sort of settled into COVID, inflation has become a dominant theme. What are the themes that, outside of just individual companies, have your interest most, that you think most matter for general market returns from this point forward?

[00:10:05] Gavin: I think for me, inflation is the only thing that matters. And I think there’s a lot of focus on the fed. To me, the fed is a little bit of a side show. I’ve lived through a lot of fed tightening cycles. There’s a lot of great work that’s been done on how equities do. Generally stocks are up, actually I think in every tightening cycle dating back something like 25 years, stocks are up 12 months after the first rate hike. By the way, the reason they’re up is they generally sell off into the first rate hike because the market is anticipatory. And everybody sees these studies, things happen faster, the market is becoming even more anticipatory over time. So I think the Fed is a little bit of a sideshow, from my perspective, and what’s different about this Fed tightening cycle is you just had the highest CPI print in 40 years. And I do think in terms of mistakes I made, I really under-reacted to Powell’s appointment. I’m not somebody who’s mindlessly bullish on growth. I’d say I was very cautious of high multiple growth stocks for probably the summer of 2020 to April, May of 2021. Wrote this big piece on Medium explaining why I was getting more positive. That was way too early. But a lot of those stocks, even back in May, their multiples that already corrected 50, 60%-plus. We digested a pretty big move in the 10 year. Powell was reappointed, clearly with a mandate to crush inflation. The market got that right. I mean, it was right away. The data Powell was appointed, that was a sea change in the market that has persisted through today. And I think just what’s different is that 7% CPI number. And if you think about what drives the market, just like stocks, it just comes down to earnings and multiples. And liquidity drives the multiples and GDP growth drives earnings growth.

The fed, because inflation is at 7%, I think that’s why this selloff has been so severe. Just because this is different than anything any professional, I mean, maybe there’s some people. I guess Warren Buffett was investing in 1982, okay. Maybe there are a couple of people who were professional investors in active investors in 1982, but not many. So as a bottoms-up investor, you do kind of have to be macro-aware. And I think there’s two parts to inflation. The first one is supply chain driven, the shortage of goods everybody’s read about. Ships stacked up the port, we can’t get enough semiconductors to make cars. I am so relaxed about that. It is very rare for me to have a view on something like that. I just think we now have hundreds of years of history and capitalism is amazing at solving problems. It is so good. And we have seen a massive supply response. This is a statistic, I actually just ran this this morning. Amazon has spent more money on capex, and this is just illustrative, it’s not a comment on Amazon. It’s a comment on the supply response. They have spent more money on capex in the last two years than they did in the preceding 20 years.

[00:13:06] Patrick: Insane.

[00:13:07] Gavin: Think about that. From 1999 to they spent 62 billion on capex. They’re going to spend 87 billion in 2020 and 2021.

[00:13:16] Patrick: That is crazy.

[00:13:18] Gavin: That’s unimaginable. And no, I did not go through and nerdily adjust every year for capitalized leases. And maybe it makes it more striking, maybe it makes it less striking, but either way it’s crazy. Taiwan City, their 2022 capex is going to be many multiples of 2018. 2021 and 2022, they’ll spend more than they did in the preceding five years. So there is a massive supply response coming. We know that the economy is slow. We know it from credit card data, retail sales, which a couple of reports here have 16% for the year. They’re flat in November, down two in December. And then the Atlanta Fed does this thing they called the GDP now. And that was ten in November, five in December. So the economy is slowing rapidly. So you’ve got this massive supply response, an economy rapidly slowing before the fed begins to take away the punch bowl. I think you’re about to have a truly massive shift in consumer spending away from goods towards services. If you trend out and look at real personal expenditures, goods spending is roughly 500 billion above the pre-COVID trend line. Services spending is 500 billion below the trend line. And that shift, Omicron is probably the end of COVID, to me as a factor for investing for daily life. So I do think the economy will finally normalize. So when you have this supply response, meaning a slowing economy and a shift away from goods towards services, then I just think all of that inflation goes away.

Goldman did this analysis. Auto is accounted for half of the overshoot in core inflation, used auto prices. They were kind of flat for forever and then they went up 50% in 18 months. All that goes away. Maybe it doesn’t, want to be appropriately humble, but I think highly likely that all that is going to go away. If it doesn’t go away, wow, okay, I’m going to be horribly, horribly wrong. And I do think this post-World War II period is an interesting analog for this. You had a 20% CPI basically, because there was huge boom, factories, really good at making takes and fighter jets and not good at making anything else. There was a supply response and CPI went right back down. And so I think for that component, that is for sure going to normalize. And I think the other thing is wage inflation. And this is something where there are things happening in the economy that have literally never happened before. Like the ratio, there’s more unemployed people looking for work than there are job openings. Now there’s more job openings than there are people looking for work. The ratio of job openings to unemployed hit an all time high. Something happened that’s never happened before. I think it’s important to think about it with an open mind and it’s like, okay, why has this happened?

Well point number one, we had massive stimulus since the New Deal. And on top of that, we had a debt jubilee. And I don’t think we really fully understand how powerful that debt jubilee was. We basically said, “You don’t have to pay rent.” Student loan forgiveness, eviction moratoriums, all this stuff. You had all of that. You had people, lot of people over the age of 62 left the workforce. And I think part of that is people probably took these voluntary buyouts that companies, I’m sure they wish they had not given in the spring of 2020, that I do think you have give people credit for being rational. I think the idea of getting COVID is much scarier if you’re over 60 than if you’re under 40. Sad to say I’m over 40. So you had a lot of people retire. And then I also think you had a lot of people who, because of remote learning, a lot of two income households went to one income households. All of that is normalizing. The debt jubilee is over, stimulus is fading, consumer savings are beginning to draw down. I do think after Omicron, kids are going to be able to sustainably go back to school. So a lot of that stuff is fading, but really, really who knows. And if wage inflation is here to stay, I think it means very bad things for the market. It’s just that simple. I think on balance, it’s probably not here to stay. These forces of globalization, they’re too powerful. I’m not sure that the idler movement is here to stay. It’s one thing to be an idler while you have a debt jubilee and, and a lot of savings. It’s another thing when you burn all of that down.

But I just think it’s important to be humble. Anytime you’re talking about forecasting the future, you want to be humble. People have been trying to do it for thousands of years unsuccessfully. And at the end of the day, that is what fundamentally investing is. You are forecasting the future. You have a differential opinion on the future, full stop. People don’t like to admit that, but that is what it is. As hard as that is to do for individual companies, it’s way harder to do for entire economy, which is the world’s most complex chaotic system, high sensitivity to initial conditions, unpredictable interactions. Everything I’m saying, I want to caveat with that. I don’t know if I’ve given you my two examples before, Patrick, and feel free to stop me if I have, but I always think about the Federal Reserve, they employ more PhD economists than anyone. They have more information on the economy than anyone, like way more information than anyone. They have vast amounts of computing power, and they have no ability to forecast the economy out more than six months. And so A, I’m way less smart. B, I have way less information, certainly have less computing power. So there was a letter written, an op-ed written in the Wall Street Journal somewhere in between 2010 and 12. And I think a majority of the world’s PhD economists signed it. Every famous macro-investor you can think of signed it, but it basically said, “Hey Ben Bernanke, you have no idea what you’re doing. This quantitative easing is going to cause massive inflation. It’s going to ruin America. You’re going to bring about hyperinflation. It’s going to be the ruin of America.” They were dead wrong, horribly wrong…

…[00:25:39] Patrick: I’d love to dive in a little bit, just underneath that big trend, you mentioned the three sub-sectors of semis, software, internet. Maybe we could also talk about a fourth category, which is the big five or the big 10 technology companies that are conglomerates at this point. Maybe we’ll start with semis. I’ve talked to you about this in the past, I’m just totally fascinated by the semiconductor industry. I know this is where you cut your teeth a lot, followed it since its beginning and since the start of your career. A lot of people had never heard of Taiwan Semiconductor two years ago. And I think a lot more people have now, for a variety of reasons, not just the shortages and the importance of supply chain, but also the geopolitical stuff. Walk us through your take on semis today and what’s evolved and what matters in that subsector in tech, since it’s such a key one?

[00:26:21] Gavin: Let’s step back and look at the last 15 years of semis. The industry has completely consolidated to where you almost have these monopolies – monopolies or duopolies in every subsector of semis. You either have a monopoly, duopoly, or in the worst case, an oligopoly of three. And in even their suppliers to capital equipment companies, they’re all either monopolies to duopolies. So the industry has massively consolidated over the last 15 to 20 years in a way that maybe should have never been allowed to happen. Although the fact is that a lot of these markets, for a lot of reasons, mostly because the network effects around software code and then economies of scale, they do tend toward being a monopoly, a monopoly or duopoly. So in basebands, there’s a duopoly. CPUs, there’s a duopoly. GPUs, there’s a duopoly, now it’s an oligopoly because intel is entering that industry. Memory, it’s oligopoly for for both NAND and DRAM, analog almost part by part, it’s generally a duopoly, same thing for FPGAs. So it’s a very consolidated, concentrated industry. And you have had demand, I think structurally shift up. And this has always been a secular growth industry, it’s always grown, I call between 1.5 to low twos, multiple of GDP, global GDP. So it’s always been a secular growth industry, but that multiplier’s shifted up. And the reason it’s shifted up is broadly speaking because of artificial intelligence. Human beings, when they write software code, they make a big effort to minimize their, at least good programmers do, use of resources like compute and memory. You used to have to have a budget you had to work with before the dates of cloud computing, only so much memory and only so much storage. The way of cloud computing has thrown that all out the window. And AI is just the inverse. The way you make AI better is you train it on more data. That’s it.

It’s really just that simple. And there’s just a really good rule of thumb, and Microsoft wrote about this in a research paper 10 years ago, or maybe not, 12 years ago, the quality of a given AI algorithm doubles with every 10X increase in the amount of data you used to train that algorithm. And Mark Edrison wrote this op-ed, whatever it was, 10 years ago about how software is eating the world, now AI is eating software. And that just means that the world is getting much, much more compute and semiconductor intensive. And then on top of that, you have all these, at the end of the day, cars are a massive, massive consumer market. And as those become EVs the next AVS, the semiconductor content for car is really exploding. And you put those two things together, the world is just becoming a lot more semiconductor intensive. The bummer, and I would say I’m probably as cautious as I’ve been on semiconductors in a long time right now, it’s still a cyclical industry. If you look at the history in the industry in the eighties and nineties, you have these capacity cycles and they’re driven by the fact that, God I can’t remember his last name, but he was hilarious, TJ, he ran Cypress Semiconductor, he famously said real men own fabs, because there was this trend of going fab-less. But it used to be, in the eighties and nineties, if you ran out of capacity, well, the only thing you could do was build a new fab. And everybody would tend to run out of capacity at the same time, so all these fabs would come them on at the same time. And so you could think of demand as being the smooth, underlying, true demand, the relatively smooth line, and then capacity comes on in the stair step path.

So you would have these vicious cycles, and companies were always going out of business, but then the world moved to fab-less with few exceptions. Today, Intel, Samsung, Taiwan Semi, they’re the are only companies in the world that can make leading edge logic. There’s only three companies that can make leading edge DRAM, maybe four for NAND. And so they got much better about aggregating capacity smoothly. And as a result of that, the cycles you’ve seen last 20 years are just inventory cycles. And the reason for that is the fundamental equation that covers semis is customer inventories must equal lead times. Because if they don’t, and you’re purchasing manager, you get fired. Okay? And so whatever lead times are, that is what customer inventories are. And that leads to this crazy positive feedback loop where if lead times are going up, inventories are building, which causes lead times to go up, which causes inventories to build further. And then as soon as something changes, all that unwinds. And then lead times are going down, you’re burning inventories. So if you’re a semiconductor company, you’re never seeing true in demand. You’re either seeing above market demand because lead times are going out and inventories are building, or below market demand, or below true in demand. And so you’ve had these inventory cycles really consistently for the last 20 years.

What you have right now is, I think a massive inventory cycle. And everything we talked about, the economy slowing even before the fed hikes hit, PCEs shifting away from goods towards experiences. I think demand for semis is almost inevitably going to decelerate a little and that’s going to lead to an unwind of this inventory cycle. And then all the capacity that’s being brought on probably makes it worse. But then I think, you get to the other side of that, and you’re left with that industry that used to grow at 2X nominal GDP to one that probably now is a 3X nominal GDP grower. And you still have that super consolidated supply structure. You’re now having people saying semiconductor companies should be valuing software companies. And no, they shouldn’t. You have a bunch of people. Every fund I know that’s under 50 billion is frantically looking for a semiconductor analyst, where somebody’s really good at semis, have a lot of tourist to the sector. And it’s just when these companies miss, they miss big. Just going back to the fourth quarter of 2018, you can see some really, really, really big misses. So I would say relatively cautious on semis.

4. 14th Five-Year Digital Economy Development Plan – Lillian Li

“It’s the Chinese government’s wishful blueprint. It’s a guidance document that’s put together through rounds of discussions and buy-ins from provincial, municipal and state levels. Still, if any startup or large corporations release the OKRs, there’s no guarantee they will all happen. The history of Chinese Five Year Plans (FYP) is littered with their failures as much as their successes…

…Key takeaways

• The anti-monopoly and other regulations ensuring fair competition will continue throughout 2021 to 2025 –  it seems like there’s significant intent to bring in rules of law to this domain in order to remove systemic risk. More rules around data safety and fair competition seem inevitable given the tone of this document. 

Implications:

• More comprehensive laws and regulations are coming that will specify the limits of platforms and promote consumer and worker welfare.
• The exact methodology for how consumer welfare and fair competition will be guided is still being defined, leaving a certain margin of error for interpretation.
• Fintech will be seen as finance by another name and will be regulated as such.
• Given the indicators around transaction growth and e-commerce, I also do not think the government wants to see platforms completely destroyed. Who’s going to deliver the growth if everyone’s stagnating? 
• Timing will be the tricky part and I have no insight here.  

Key takeaways

• Platform players specifically are asked to step up and become de facto institutions – Tech giants are being asked not what their country can do for them but what they can do for their country. In the guidance plan, the tech players are asked to help with sharing data for future data exchanges and to open their technology stack to help SMEs and other industries digitalise.

Implications: 

• I don’t think platforms will be nationalised, though their functions could become somewhat grey. They are faced with a carrot and stick situation. For instance, they could be asked to help Chinese industries digitalise through DingTalk, Tencent middleware, PDD agricultural investment fund and Meituan’s new retail functions, and not to double down on their current consumer platforms, as there are implications for consumer welfare encroachment.
• I’m sanguine about this, as I think all Chinese consumer tech platforms are being offered a chance to have a second leg as a B2B company. They have the government’s support if they go forward with it. Put another way; they also have a cornered resource since China will not be asking AWS, Google or Salesforce to help with China’s digital transformation anytime soon.

Key takeaways 

• Software and manufacturing cloud is front and centre of policy. It receives strong tailwinds and platforms have a role to play – What gets measured gets done, and in the indicators for the Digital Economy Five-Year Plan, the size of the software and IT service industry is being asked to grow by at least 72% 2025.

Implications:

• The focus for manufacturing industries seems to be the digitalisation of the supply chain I expect many startup players in this space to accelerate through funding and government support in the coming years. More on this in the State of Chinese Cloud part I
• Agricultural tech is also seen as a top priority given the frequency it gets mentioned (seven times in the document), it is still a 13.8 trillion RMB ($2.1 trillion) that employs 25% of the Chinese workforce.
• Open-source software gets several shoutouts as a way to harness decentralised software manpower. This has also followed what I’ve observed in the VC community, opensource in China has been having a hot year in 2021. Now with government backing, expect Chinese open-source to go mainstream in the coming years. I’ll be posting more frequently on this topic too.

5. Fluke – Morgan Housel

Forecasting is hard. And not because people aren’t smart, but because trivial accidents can be influential in ways that are impossible to foresee…

…One night in college – I remember it was late, maybe midnight – I was reading a blog post about hedge fund manager Eddie Lampert. It was written by a guy named Sham Gad, who I had never heard of. I can’t remember where I found his blog; maybe I was searching for information on Lampert, who I admired.

Sham wrote that Lampert went to Harvard. I knew that was wrong – he actually went to Yale. Obviously it doesn’t matter, who cares? But using my student email address (which I rarely used but turned out to be important) I emailed Sham to let him know he was wrong. I never do stuff like that, then or now. The common denominator of the internet is misinformation. I have no idea why I thought it was necessary.

Sham’s a nice guy. He responded and said thanks, he’ll fix it.

A few minutes later he sent another email: “Hey I see from your email address that you go to USC. I’ll be in Los Angeles tomorrow. I’ve never been before, what’s the best way to get from LAX to downtown?”

It was a weird thing to ask a stranger who just trolled your blog. But it’s a reasonable question. If you’re familiar with LA you know there is no good answer. It’s the least transportation-friendly city in the world.

I don’t know why, but without thinking I responded: “It’s hard. I can pick you up. Let me know when you get in.”

He said great. I’ll see you tomorrow.

I’m a private guy. I’ve never done anything like this. At this point my relationship with Sham consisted of 10 cumulative sentences. I didn’t know if he was 17 or 87 years old. But the next day I was driving to LAX to get him.

We stopped at Chipotle on the way back. While eating he said, “I haven’t booked a hotel yet. Is there one nearby you can drop me off at?”

Adding to the list of things you shouldn’t say to a stranger, I said, “You can crash on my couch.”

“Wow, thanks,” he said.

I texted my girlfriend and said, “I met a guy named Sham online. I just picked him up at the airport and he’s sleeping on our couch tonight.”

“Excuse me?” she said.

I know, I’m sorry. I don’t know why I agreed to this…

…The next summer I was interning at a private equity firm. One day – and I remember this occurring within the same hour – two life-changing things happened.

Global credit markets started exploding in 2007, the preamble to the financial crisis. The firm I was at wasn’t in great shape. They told me there wouldn’t be a full-time spot for me after I graduated. I’d have to leave the next month.

That hurt. I needed to find a job as the economy was melting down.

I also needed to finish a project I was working on, researching logistics companies for the private equity firm. That included gathering information on a tiny public company called FreightCar America.

I went to Yahoo Finance. I didn’t find much, but just before clicking away I saw one lonely article in the FreightCar America news feed.

It was a Motley Fool article written by … Sham Gad. (It’s here).

Hey, I know that guy!

I emailed Sham for the first time in a year and told him how cool it was that he was writing for a publication.

We chatted for a bit. I told him I was looking for a new job. Anything. I was desperate.

“The Motley Fool is hiring writers,” he said. “I can put in a good word.” He owed me a favor, after all.

And that was that. I became a Motley Fool writer and stayed for ten years.

I’ve been a writer my whole career. It was never planned, never dreamed, never foreseen. It only happened because Sham got Eddie Lampert’s alma mater wrong and I needed a job at the very moment he wrote a blog post about a company I was researching at a job I was about to be laid off at.

6. Our Take on the Data Deluge, and What’s Next – Dharmesh Thakker, Chiraag Deora and Jason Mendel

Today, our company Collibra*, which focuses on data intelligence—particularly around areas like compliance—also hit a corporate milestone when it announced its latest $250 million financing. It all underscores just how detailed and granular the data market has become, and how much market value is up for grabs as companies both 1) increasingly seek out better data to make more-informed decisions, and 2) use data to improve customers’ experiences.

So what’s driving this data deluge? And how long can it continue? Our research and discussions with hundreds of companies over the last five or more years have highlighted six key factors driving the creation and growth of data and business-intelligence (BI) companies. They’ve also given us insights around how the market may shift in the coming years, so we’re sharing some predictions here too.

Literally, zettabytes of data

The first factor driving the growth of new, data-focused technology is simply the unbelievable volume of data being produced today—data that needs to go somewhere to be useful. Data is being produced from all around us whenever we interact with mobile applications, shop online or even through customer support interactions. If technology is being used, data is being created. Research firm IDC predicts that the global datasphere will grow to 143 zettabytes (for context, each zettabyte is 1 trillion gigabytes) by 2024—a 26% increase from the 45 zettabytes of data that were around in 2019.

It’s obvious, but important we say it anyway. The shift to the cloud is real!

We are still very early in the public-cloud adoption journey, as the majority of data still resides in legacy, on-premise data centers. By 2025, IDC estimates that approximately 46% of the world’s stored data will reside in public-cloud environments. This is a direct driver of the massive increase in data, and new data technologies, as the cost of compute and storage in the public cloud is much lower–there are no upfront capital-expenditure requirements, and access to data is often governed by reasonable, pay-as-you-go or consumption-based pricing. In addition, the automation that comes with the cloud allows companies to free up system engineers from worrying about customizing on-premise systems, and instead focus on other data-management priorities. The migration to cloud promotes flexibility, scalability, and cost efficiency in a way not previously possible with on-premise deployments.

Consumers need information, and they need it now.

Old-style, batch data sets historically have been used for many analytics needs; in this method, data is gathered over time prior to being analyzed. There are and will continue to be great use-cases for batch analytics, including managing payroll or customer billing. But with the advent of mobile computing and the Internet of Things, among other trends, there has been a pressing, new need for analyzing data in real time. Use cases here include fraud detection, tracking real-time ETAs on ridesharing applications, managing the temperature of your home as the day progresses, and many more. Per IDC, the market for real- time or continuous analytics is expected to grow to $4.4 billion by 2024. Aside from enabling a different set of applications, real-time analytics contributes heavily to the growth of data given the constant need for up-to-date data.

7. Why 7% Inflation Today Is Far Different Than in 1982 – Greg Ip

Consumer price inflation in December, at 7%, was last this high in the summer of 1982. That’s about all the two periods have in common.

Today, the inflation rate is on the rise. Back then, it was falling. It had peaked at 14.8% in 1980, while Jimmy Carter was still president and the Iranian revolution had pushed up oil prices. Core inflation that year reached 13.6%.

Upon becoming Federal Reserve chairman in 1979, Paul Volcker set out to crush inflation with tight monetary policy. In combination with credit controls, that effort pushed the U.S. into a brief recession in 1980. Then, as the Fed’s benchmark interest rate reached 19% in 1981, a much deeper recession began. By the summer of 1982, inflation and interest rates were both falling sharply. Four decades of generally low-single-digit inflation would follow.

“We have had dramatic success in getting the inflation rate down,” one Fed official observed that August. But Mr. Volcker had other problems to contend with: His high interest rates had pushed Mexico into default, touching off the Latin American debt crisis, and unemployment would climb to a post-World War II high of 10.8% that fall.

Unemployment took out that record in the early months of the Covid-19 pandemic in 2020. Since then, it has been falling rapidly as the economy roars back thanks to vaccines, fewer restrictions on mobility and ample fiscal and monetary stimulus. In December, unemployment sank to 3.9%, closing in on the 50-year low of 3.5% set just before the pandemic.

Monetary policy then and now couldn’t be more different. Back in 1982, the Fed was still targeting the money supply, causing interest rates to fluctuate unpredictably. Today, it largely ignores the money supply, which expanded dramatically as the Fed bought bonds to hold down long-term interest rates. Its main policy target, the federal-funds rate, is close to zero.

Rather than 1982, two previous episodes when inflation reached 7% might hold more useful lessons for today. The first was in 1946. The end of the war had unleashed pent-up demand for consumer goods, and price controls had lapsed. Inflation reached nearly 20% in 1947 before falling all the way back. Today, consumption patterns have similarly been distorted and supply chains disrupted by the pandemic.

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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, Meituan, and Tencent. 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 30 January 2022:

1. How Inflation Swindles The Equity Investor – Warren Buffett

There is no mystery at all about the problems of bondholders in an era of inflation. When the value of the dollar deteriorates month after month, a security with income and principal payments denominated in those dollars isn’t going to be a big winner. You hardly need a Ph.D. in economics to figure that one out.

It was long assumed that stocks were something else. For many years, the conventional wisdom insisted that stocks were a hedge against inflation. The proposition was rooted in the fact that stocks are not claims against dollars, as bonds are, but represent ownership of companies with productive facilities. These, investors believed, would retain their value in real terms, let the politicians print money as they might.

And why didn’t it turn out that way? The main reason, I believe, is that stocks, in economic substance, are really very similar to bonds.

I know that this belief will seem eccentric to many investors. They will immediately observe that the return on a bond (the coupon) is fixed, while the return on an equity investment (the company’s earnings) can vary substantially from one year to another. True enough. But anyone who examines the aggregate returns that have been earned by companies during the postwar years will discover something extraordinary: the returns on equity have in fact not varied much at all.

2. Complexity Investing & Semiconductors (with NZS Capital) – Ben Gilbert, David Rosenthal, Brinton Johns and Jon Bathgate

David: I’d heard a little bit about complexity theory and the Santa Fe Institute, which I want to get into. I think Bill Gurley talks about this fairly frequently and Michael Madison, and that’s how I kind of originally got turned onto it. Tell us a little bit more about what is it? Because it’s not at all about investing. It’s about the world.

Brinton: That’s right. In fact, I think it was Bill Gurley that recommended Complexity to Brad. Complex adaptive systems are all around us. That’s what governs the world. That’s how the world works. We don’t know how the future is going to unfold because the system is interacting together and it creates what’s called emergent behavior.

Emergent behavior makes predicting useless in most cases, and we can have guidelines, and heuristics and those are all helpful. As far as exact outcomes and what’s going to happen in the future, those are a lot more difficult.

Santa Fe Institute started with a group of scientists from the Los Alamos National Labs. They came together—they were mostly physicists—and they started talking to economists. It was sort of hard sciences and soft sciences, and the physicists were like, hey, economists, guys. You guys seem really smart, but your theories don’t work. All your math doesn’t work. So what’s up with that? With our math, it’s extremely precise. In fact, when the math is off just a little bit, Einstein’s like oh, your math is off. Pluto should really be here and come up with a Theory of Relativity.

David: It’s like we literally made the atomic bomb, it works.

Brinton: Yeah, it works. So they started coming together around this idea of complexity. What is complexity? How do we define complexity? Where does it sit? Because we are living in this complex, adaptive system, how do we think about the future? How do we think about life? How do we think about going forward?

For us, this sparked an interest in biological systems and we found this sort of biology vein much more interesting than the traditional economics vein, and much more applicable to investing than the traditional economics vein…

…We just learned so much. I remember sitting outside of this cafe in Palo Alto with Brad and we have just sort of been at this course with Deborah Gordon, this lady that teaches at Stanford, here to study ants. I thought, man, this concept of resilience is really fascinating. It’s really more about resilience than it is about predicting the future and it’s about adaptability.

Biology doesn’t really care that much about the future. They care about adapting to this wide range of futures. Bees don’t really care if it’s going to snow tomorrow, they can adapt to snow. They’ve learned how to do that over millions of years. What if we looked at companies like that?

Of course, we kept reading, we kept writing. This is probably 2011–2012, and in 2013 we published this long paper that you reference, which is super geeky, but it’s got a lot of pictures because that’s the way we think.

David: You’ve got the Back to the Future DeLorean in there.

Brinton: It’s got the DeLorean. What more could you want? We were really hoping for a DeLorean for the office. That’s our dream office furniture.

Ben: On the note of ants, this is probably the first and best example of an extreme version of resilience in an organization. Can you share the insight you had there?

Brinton: Yeah. We attended this class by Deborah Gordon and she has been studying this group of ants for 30 years in New Mexico. They obsess over this group of ants. They know what every ant is doing at all times. What they found was really fascinating.

They found that about half of the ants of the colony weren’t doing anything. They were just sort of sitting around and then they had half the hands doing these defined jobs. That’s very counterintuitive. We think of ants as sort of the ultimate productivity machines. Then it turns out ants aren’t optimized around productivity. They’re optimized around longevity. They’re optimized around resilience, around living as long as possible, let’s say it that way.

That was really insightful for us. We thought, man, all these companies are optimized around productivity and Wall Street only makes it worse because we’re obsessed over quarterly earnings. What if companies were really optimized around this long-term thinking? Of course, we see that with lots of companies, most of them tend to be run by founders, because founders have a lot of skin in the game, they think long-term, but there are CEOs that think that way also.

We know that the average tenure of a CEO in a SP 500 is less than five years. They’re not optimized like ants are. They’re trying to get a lot of returns really quickly. But companies that take this long-term view are so much more interesting.

David: When I read that, in your paper, the thing that hit me over the head, I was like, oh, this is Warren and Charlie’s laziness bordering on sloth.

Brinton: That’s exactly it.

David: The goal is not productivity. The goal is long-term steady returns and resilience.

Brinton: I think Warren and Charlie got this very early and there’s a lot of science behind that math, but they don’t need that. They’re so good with folksy wisdom.

3. Zoom CEO Eric Yuan on trusting your gut, learning from failure, and leaving behind an enduring legacy – Byron Deeter

When Eric joined Webex as a founding engineer, he witnessed the transformation of this first generation video and collaboration product into a major player that was acquired by Cisco in 2007. He’d also worked his way up to VP of Engineering. But by 2011, Eric was no longer happy.

“Every time I talked to a Webex customer, I was embarrassed,” he says. “I did not see a single happy customer.” Eric realized there was no way to fix all the modern problems plaguing customers by tweaking legacy Webex software. He was convinced that the only way to win back disenchanted customers was to build a new solution from the ground up.

But when he presented his ideas to his coworkers, they were not sold on cannibalizing their existing product. They also doubted whether Eric’s proposal was even possible. In the face of this tremendous pressure from naysayers to abandon his ideas, Eric trusted his gut. He decided to tender his resignation and start his own company.

Buoyed by a strong instinct that he could build something superior, Eric began creating the product we now know as Zoom. The first iteration took him only one year. “I like Nike’s mantra,” says Eric. “Just do it. A lot of my friends told me, ‘Eric, please don’t do it.’ But if it’s your dream, you need to ignore them.”…

…Eric stresses the value of building trusting relationships with customers. He prizes this above all else, even if it means leaving money on the table. “Quite often our sales team would tell me, ‘Eric, we’ve got to increase the price. Customers told us we can,’” he says.

But Eric would repeatedly refuse. He remained steadfast in his conviction that some things are worth more than money. “Our philosophy is to always keep adding more value, while keeping the same price,” he says. “Because down the road, the customer will realize ‘Wow, I paid $14.99, but the product just keeps getting better and better.’”

“If you’re a founder, don’t always think about always increasing the price,” Eric advises. He believes it’s myopic to think that short-term cash in the bank is worth more than deep usage engagement, which creates momentum that will build over time.

4. The Tech Monopolies Go Vertical – Fabricated Knowledge (Doug)

The phrase “Owe the bank 500 dollars, that is your problem. Owe the bank 500 million – that is the bank’s problem.” is something that comes to mind for some of the tech monopolies right now. There is a shifting relationship between the largest software companies in the world and their suppliers, and as the leading software companies have become ever-larger portions of the compute pie, it’s kind of become the problem of the tech companies, and not the semiconductor companies that service them to push forward the natural limits of hardware. Software ate the world so completely that now the large tech companies have to deal with the actual hardware that underlies their stack. Especially as some companies like Intel have fallen behind…

…I believe that in a few years, most of the large tech companies will have a much tighter level of integration and we will likely see much less “commoditized” platforms. Yes, they might run on partially open stacks (think open networking roadmap and Facebook) but their differentiation is going to be not only software but also hardware. We are going back to the old patterns of integration of both Software and Hardware.

The unit economics of this is profound, partially because if a company doesn’t pursue this, they will have to pay the exponential cost of AI compute at face value, but also potential competitors will have to face a new barrier to entry. The profit deserts around their moats, as mentioned in the first @modestproposal1 Invest like the Best podcast, will climb even higher. They will be able to sell products below their competitors while making a profit..

…This is a barrier to entry that few companies can really climb over anymore, with 500 million in R&D only possible by a few companies (270 according to a screener I used) and many of the companies with R&D budgets larger than 500m is large tech companies themselves. It is no surprise they are going custom, as now this is a very capital intense way to create a gulf between them and the rest. For example, something I wanted to note is that every single company mentioned so far spends more on absolute R&D than Intel! Samsung, a company that is out of the scope of this discussion rounds out the list of the companies that spend more than Intel on R&D worldwide. This is likely not a coincidence! Semiconductors are becoming more capital intense as we hit the wall of physics, and by being at that leading edge the new technology monopolies will get to operate in that world alone.

Just imagine now that you are an entrant, trying to sell IaaS, maybe like Digital Ocean (huge fan). If Intel and AMD chips are all that you can use, you better pray and hope their roadmaps are strong, because now that your competitors are able to create and expand their own roadmaps faster than the large semiconductor platforms, you may be forced to eventually buy from them or just be at a structural gross margin disadvantage. You could offer identical services but make worse profits, just on the basis that you don’t make your own chips. If they lower prices, you could even lose money! You cannot compete…

…Software ate the world and hardware has been struggling to keep up recently. Now the largest software companies are slowly becoming hardware companies and pursuing an integrated strategy that only can be achieved at the largest scale possible and with barriers of entry that are quickly expanding in addition to their well-known network or aggregation effects. The walls are slowly rising, the moats slowly widening, and as we are on the cusp of a new hardware renaissance, the decisions the hyperscalers make now are going to have a long-lasting competitive shadow. Stay tuned.

5. It’s Never a Market Crash Problem – Safal Niveshak

It’s almost always an –

• I don’t know who I am problem
• I don’t know how much pain
• I am willing to take problem
• I don’t have the patience to give my stocks time to grow problem
• I bought on the tip of that popular social media influencer and did not do my homework problem
• I did not diversify well problem
• I bought the stock just because it dipped problem

6. Tyler Cowen is the best curator of talent in the world – Tony Kulesa

I am a biotech investor. I know a lot of top biotech investors. I’ve also spent close to a decade at two of the best life science academic institutions in the world.

Tyler’s understanding of biotech is that of a very broad economist. Yet, he is often beating me and many of the people and institutions that I know.

Tyler has identified talent either earlier than or missed by top undergraduate programs, the best biotech startups, and the best biotech investors, all without any insider knowledge of biotech. In comparison, Forbes 30U30, MIT Tech Review TR35, or Stat Wunderkind, and other industry awards that highlight talent are lagging indicators of success. It’s hard to find an awardee of these programs that was not already widely recognized for their achievements among insiders in their field. The winners of Emergent Ventures are truly emergent.

I have now met >5 Emergent Venture winners that work in life sciences. The average age of this group is ~20 years old.

One has attracted international recognition for his new non-profit founded this year. Tyler funded him ~2.5 years ago when his most notable public accomplishment was amassing 300 twitter followers.

Another winner has now started a company backed by top tier investors – professional talent hunters – but he received his first funding from Tyler a year prior, when he was still experimenting with what to build.

Others had been rejected by undergrad programs at Harvard, MIT, and Stanford, but their research talents have become recognized by the best academic life scientists and top biotech startups…

…It isn’t just a matter of more elite selection. In fact, Emergent Ventures has a higher acceptance rate than elite colleges. In May 2020, Tyler reported in an interview with Tim Ferriss that the award rate is ~10%. For comparison, the 2021 acceptance rates of Harvard, Princeton, and Yale were 5%, 6%, and 7%. It also isn’t a wider pool. At that time, he had only ~800 total applications since 2018.

Tyler’s success at discovering and enabling the most talented people before anyone else notices them boils down to four components:

1. Distribution: Tyler promotes the opportunity in such a way that the talent level of the application pool is extraordinarily high and the people who apply are uniquely earnest.
2. Application: Emergent Ventures’ application is laser focused on the quality of the applicant’s ideas, and boils out the noise of credentials, references, and test scores.
3. Selection: Tyler has relentlessly trained his taste for decades, the way a world class athlete trains for the olympics.
4. Inspiration: Tyler personally encourages winners to be bolder, creating an ambition flywheel as they in turn inspire future applicants.

7. Some Things I Remind Myself During Market Corrections – Ben Carlson

Time horizon is all that matters during a correction. This may sound like a humblebrag of sorts but market corrections don’t really bother me all that much anymore. The sight of my holdings falling in price day after day doesn’t bother me for the simple fact that I’ve already resigned myself to this fate.

You see I don’t put money into risk assets that I’m going to need for spending purposes in the next 5 years or so. It’s all long-term capital.

And given this money is going to be invested for the long-term, I already know in advance I’m going to have to endure corrections, bear markets and crashes from time to time.

I know my balance will get vaporized on occasion, I just don’t know when those occasions will be.

The money that I know will be spent in the short-term doesn’t go into risk assets.

An understanding of your time horizon saves you from becoming a forced seller.

It’s best to sell when you want to not when you have to. I’m guessing a lot of the selling in recent days has come from margin calls from investors who bought stocks using leverage. You don’t see massive moves of 10-15% in individual names like we’ve seen without some forced selling.

Buy and hold can be painful when stocks are falling but ‘buy on leverage and get a margin call when your stocks just got killed’ is a far worse fate.

Buy and hold requires you to do both when stocks are falling. It’s much easier to both buy and hold when stuff is going up.

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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 Zoom. Holdings are subject to change at any time.