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 November 2022:
1. What to Watch in AI – Mario Gabriele and guests
Is there any profession as quintessentially right-brained as an “artist?” Or one as left-brained as a “programmer?”
What’s been so remarkable to us about the rapid evolution that has characterized the last year, especially in the large language models, is how they’re now powering assistive tools that radically increase productivity, impact, and value across a wide range of professions.
For artists, we’ve got AI image-generation tools like OpenAI’s DALL-E, Midjourney, and many others. For programmers, we’ve got Microsoft’s GitHub Copilot, which helps software developers write, test, and refine code in many of the most currently popular computer languages.
While some AI skeptics characterize large language models as brute-force prediction machines that won’t ever imbue computers with anything like human intelligence or consciousness, what we see, in mind-blowing practice, is how profoundly these kinds of AI tools are already beginning to enhance human flourishing.
What Copilot does for developers and DALL-E does for visual creatives of all kinds is reduce or eliminate rote, time-consuming, but still crucial aspects of their jobs. Of course, this dynamic is hardly unique to software developers and artists. Large language models are trained on massive quantities of text data, then incorporate what they “learn” to generate statistically probable (contextually sensible) output to user-supplied prompts. So while Github Copilot was trained by ingesting massive quantities of computer code, different versions of Copilot are equally possible for virtually any profession.
A Copilot for attorneys, for example, could help them draft contracts, motions, briefs, and other legal documents based on natural language queries, previous cases, and best practices. It could also suggest relevant precedents, statutes, and citations, or flag potential errors, inconsistencies, or risks in existing documents.
A Copilot for architects could help them design, model, and optimize their buildings and structures based on their specifications, constraints, and objectives. It could also generate interactive visualizations and help scope out the environmental, social, and economic impacts of projects.
Imagine a world where millions of professionals across thousands of industries use domain-specific versions of Copilot to soar faster and higher to new levels of productivity, accuracy, and creativity. A world where professionals across all industries can use general-purpose tools like our portfolio company Adept’s Action Transformer to harness the power of every app, API, or software program ever written via interfaces that allow them to describe the tasks they want to accomplish in plain language.
In dystopian visions of the future, technology in general and AI in particular are often characterized as forces that will lead to an even more polarized world of haves and have-nots, with the bulk of humanity being disenfranchised, marginalized, and immiserated by machines.
In the world we actually see evolving today, new AI tools effectively democratize facility and efficiency in unprecedented ways. In doing so, they’re empowering individual professionals to achieve new productivity levels and society to achieve gains that may exceed those unleashed by the Industrial Revolution. Not only that, but people will also find their jobs more engaging and fulfilling because they’ll have more time to focus on the most creative, strategic, and novel aspects of them.
This future is here. There will be an AI amplifying tool for every major profession within five years. These tools can catalyze human excellence across occupations – right brain, left brain, and any brain.
– Reid Hoffman, cofounder at Greylock, and Saam Motamedi, partner at Greylock…
…It’s been another hot summer in AI. We’ve seen the rise of new research collectives that open-sourced breakthrough AI models developed by large centralized labs at a never before seen pace. While these text-to-image/video models offer viral consumer-grade products that capture our imagination, the most impactful applications of these models are unlikely to be their first-order effect. I believe the place to build is at the intersection of AI and science, specifically in the life sciences.
Today’s scientific method is firmly rooted in data-driven experimentation. The resolution and scale of the data we can generate to explain biological systems are continually improving while develop AI model architectures capable of modeling human language, natural images, or social network graphs. These architectures can be directly transferred into modeling proteins’ language, cells’ images, or chemical molecule graphs. This uncanny generalization ability is now unlocking breakthroughs in protein structure prediction and drug molecule design. AI is driving a new generation of technology-driven biotech companies (“TechBio”) attacking the trillion-dollar pharmaceutical industry to deliver improved medicines faster and at a lower cost.
With Air Street Capital, I have invested heavily in companies driving this industry forward. One of the companies I’ve backed is Valence Discovery, which develops generative design methods to create new classes of potent drug molecules previously out of reach due to the requisite design complexity. Valence is pursuing ultra-large generative chemistry initiatives with leading research institutions to push the boundaries of today’s generative AI methods for drug design.
One founder in this space is Ali Madani, who led an AI for protein engineering moonshot called ProGen at Salesforce Research. There he developed large language models specifically applied to designing brand-new artificial proteins that recapitulated or even outperformed the function of their naturally occurring peers. The group produced the first 3D crystal structure of an AI-generated protein. Proteins are the functional actuators of all life, and the possibilities a technology like this might unlock are vast.
– Nathan Benaich, General Partner at Air Street Capital…
…Artificial intelligence will transform how we use pharmaceuticals to treat human illness.
When people think of AI and pharma, the application that most often jumps to mind is AI for drug discovery. (For good reason: AI-driven drug discovery holds tremendous potential.)
But there is another compelling machine learning use case that, while less widely covered (and less zealously funded), promises to bring life-changing therapeutics to market faster and more effectively for millions of patients. This is the use of digital twins in clinical trials.
It is well-documented how inefficient and expensive clinical trials are today, with the average new drug requiring over a decade and $2 billion to bring to market. Recruiting trial participants is one major stumbling block in shepherding a drug through clinical trials. A single trial requires recruiting hundreds or thousands of volunteers to populate its experimental and control arms. This has become a significant bottleneck. Eighty percent of clinical trials experience enrollment-related delays, with trial sponsors losing up to $8 million in potential revenue per day that a trial is delayed. Hundreds of clinical trials are terminated each year due to insufficient patient enrollment; indeed, this is the number one reason that clinical trials get terminated.
“Digital twins” offer a transformative solution to this challenge. The basic concept is simple: generative machine learning models can simulate placebo outcomes for patients in clinical trials. This can be done at the individual patient level: a digital twin can be created for each human trial participant in the experimental arm of a trial, simulating how that individual would have performed had they instead been in the control arm.
Crucially, this means that pharmaceutical companies need to recruit significantly fewer human participants because much of the control arm patient population can be replaced by digital twins. This makes clinical trials significantly faster and cheaper, enabling life-changing therapeutics to more quickly come to market and reach millions of patients in need.
San Francisco-based Unlearn is one AI startup at the forefront of this transformative technology. Unlearn is currently working with some of the world’s largest pharma companies, including Merck KGaA, which is deploying the startup’s digital twin technology to accelerate its clinical trials. Earlier this year, the European Medical Agency (Europe’s version of the FDA) officially signed off on Unlearn’s technology for use in clinical trials, major regulatory validation that the technology is ready to be deployed at broad scale.
A few years from now, expect it to be standard practice for pharmaceutical and biotechnology companies to incorporate digital twins as part of their clinical trial protocols to streamline a therapeutic’s path to market.
It’s worth noting that digital twins for clinical trials represent a compelling example of generative AI, though it has nothing to do with buzzy text-to-image models. Producing simulated placebo outcomes for individual patients is an excellent example of how generative machine learning models can have a massive real-world impact – and create billions of dollars of value.
* Disclaimer: The author is a Partner at Radical Ventures, an investor in Unlearn.
– Rob Toews, partner at Radical Ventures
2. RWH016: The Best Of The Best w/ François Rochon – William Green and François Rochon
[[00:11:52] William Green: So you quit engineering after maybe three years of discovering the joy of real serious investing and went to work for a, an investment firm in Montreal. I have the sense that it was a disillusioning experience and showed you a lot about the disadvantages of institutional money management.
[00:12:12] William Green: Can you talk about what happened, what you saw there that made you think, Yeah, I want to be in this business but I want to work for myself so I can follow the rules that I want to follow instead of doing it in this misguided way?
[00:12:24] François Rochon: Well, I don’t know if it’s misguided. I think most money managers are sincere doing their best. I really do. And so when I worked at that big firm that manage institutional clients, they did the best they could. And they add pressure from the clients to do well on a quarterly basis, or at least on a yearly basis.
[00:12:48] François Rochon: So I just realized in real life, I wouldn’t say I was, lost illusions. I just realized, and in real life, it’s hard to have a long term horizon. Your clients. In those cases, the institutional clients have to share your time horizon for the relationship to work. Because if your clients don’t give you the time horizon, you need to get the rewards from equity investing. It’s a wasted time, to invest that way. So I realized that, most people in the business, you, I have the luxury of having a long term horizon.
[00:13:27] François Rochon: So, when I realized that, I said, Well, if I really want to invest the way, I believe is the best way to invest, I have to start my own firm. And, when I started to gather clients in the early two thousands, I really took the time to explain to all those clients that we needed to have, both of.
[00:13:47] François Rochon: I have a long term horizon and not to focus too much on the short term results and I don’t know exactly when I started to talk about my rule of tree, but pretty early on I thought the importance of that rule and which is basically one year out the stock market will go down. One stock out of three that you’ll purchase will be a disappointment and at least one year outta three you’ll underperform the index.
[00:14:14] François Rochon: And I think when you accept that from the start, you deal better with market fluctuations. The mistakes. You’ll make securities and, you have to accept from the start that have here you are on perform the market. Even if you do a good job and you study the company very well and you made some intelligent long term choices, you can have two or three years in a row that you under perform in. You have to be able to accept that.
[00:14:43] William Green: It seems also that rule of three is a fundamental reminder that you need to be humble as an investor. That a third of the stocks you purchase are likely to do poorly. A third of the time you’re going to underperform the index. And a third of the, a third of the years, the stock market’s going to fall by 10 cent or more.
[00:15:01] William Green: It’s kind of wiring yourself in a way from the start conditioning yourself from the start, have fairly realistic and humble expectations about the roughness of the terrain you’re going to have to navigate.
[00:15:13] François Rochon: Oh, yes. And I think as the years go by, I think, it’s very hard not to be, to stay humble and get even, a little more humble because, it’s a very tough industry. It’s a very tough, when you want to beat the stock market over many years, not just three or four years, but over decades. I think you, you have to be armed with a lot of, and you always, I think is kind of the, catalyst.
[00:15:38] François Rochon: To help you become a better investor because you always want to learn more and understand more. And I think, it turns out that, it’s kind of, a good tool to help in the learning process…
…[00:18:47] François Rochon: And so far, my experience has been since 96 that, there’s been a very strong correlations between the increase of the owners and the companies we own. And, the quotation of the stock market.
[00:19:00] William Green: The correlation is so striking when I look at your shareholder letters that it’s worth actually kind of dwelling on the numbers.
[00:19:06] William Green: Like there was one point in one of the letters where you said, Over 20 years from 1996 to the end of 2015, your company’s intrinsic value increased by 1102%, and the value of their stocks increased by 1141%. So incredibly close, 1102% for the increase in intrinsic value, 1141% for the increase in the value of the stock.
[00:19:33] William Green: So as you point out again and again in the shareholder letters, this is not a coincidence. The correlation is kind of amazing.
[00:19:41] François Rochon: It is amazing. I think the fundamental process that lies behind the, I think the approach of investing, if the value increases, let’s say market, increase the value stocks, but over a year or two or three, anything can happen.
[00:20:02] François Rochon: So that’s why I say it’s kinda a paradox. But if you keep focusing on what’s happening to the companies you own, eventually the stock market will.
[00:20:13] William Green: So one of the things that seems, if I understand this correctly, to be fundamental to your approach is that you are looking for outstanding companies that basically are increasing their intrinsic value faster than the average.
[00:20:27] William Green: So if you expect, you often talk about how stocks historically maybe go up six or 7% a year in the US and maybe there’s a 2% dividend, something like that. So let’s say historically you’d expect an eight or 9% return, what you are looking for is outstanding companies that can grow maybe five percentage points faster than that. is that a fair summary of what seems like a pretty simple approach, but obviously it’s incredibly difficult to pull off?
[00:20:53] François Rochon: It is. What I’m aiming for, I don’t remember exactly, but I think since 96, the increase in the owner’s earning portfolio on average, and if you include a dividend, it’s close to 13% annual.
[00:21:08] François Rochon: So it’s probably a little more than 12% in terms of earnings per share growth, and perhaps less than 1% of dividend because many companies in the portfolio don’t pay dividend. So that treating per percent is probably, like you say, four or 5% better than the, the average of the sub market. Let’s say the s and p fell, which probably have has grown exactly as you say, probably 9% over the last five years.
[00:21:33] François Rochon: That’s why I’m trying to do when I purchase a stock for the portfolio is find a company that I believe if you combine the earnings growth going forward and the dividend yield, you come closer.
[00:21:47] William Green: How do you deal with the pressure not to overpay you for these outstanding companies? Because there’s a section of your annual letter where you talk about your mistakes.
[00:21:57] William Green: In the past, you much to your credit, every report you go through various mistakes and they almost always are errors of omission rather than commission. There are things where you fail to buy them, and it seems to me repeatedly, year after year, the reason why you failed to buy them and missed out on huge returns is cause they were slightly more expensive than you wanted them to be.
[00:22:16] William Green: So how do you get these outstanding companies of prices that you can bear?
[00:22:23] François Rochon: It’s not easy because if I want to be logical here, if I’m going to own a company, let’s say for 10 years, that’s going to grow its earnings by 12, 13, 14% annually to get that reward in of the stock, there can be a slight decrease in the P ratio, but not too much.
[00:22:44] François Rochon: Because let’s say if you quadruple your earnings over 10 years, but the P ratio goes out from, I don’t know, 30 to 20 times, you don’t earn 15% annually on your investment because there was some P contraction at some point in the future. So ideally, you want the P ratio in the future to be similar to what you’re paying.
[00:23:07] François Rochon: So I’m not necessarily looking for a, let’s say a bargain company that trades that way below its intrinsic value. Of course, I like it when I do, but to me, if I can find a great companies and in the future, the peer ratio is similar to when I purchase it, if I’m right on the growth rate, of course it can be a investment.
[00:23:29] François Rochon: The danger is that if you overpay a little bit, you kinda discounted in. Also it go back to to have this margin of safety when you purchase the stock. But like you say, I made the mistake of not purchasing great companies because I wanted that ratio to be lower. The stock. I missed great investment because of that.
[00:23:59] François Rochon: So it’s to find the right balance of, keeping the margin of safety, principle in line and always at the same time always trying to see that perhaps if you pay higher than you’d like to, the growth rate of the company will be high enough that even if there is a little shrinkage of the key ratio at the end of your investment, you’ll still do ok.
[00:24:23] François Rochon: So if you can find a company that can grow by 20% a. and you lose a little bit on the ratio after 10 years, you’ll probably do. So I think many mistakes I did can be, intuit or at research or Starbucks. I fail probably to see that the growth rate would be much higher than 12 or 18%. I don’t remember exactly, but I think in terms of that research, it was probably 17, 18% annually the growth rate since I’ve been watching it for more than two decades now.
[00:24:58] François Rochon: So it’s warranted a much higher ratio than I was ready to pay. So I think that’s one big lesson. When you do find an outstanding company, you have to be able to pay higher PE ratio…
… [01:18:40] William Green: And so yeah, it’s, you can’t really fake the interest, but if you have the interest, if you harness some weird interest like that, it ends up yielding in incredible benefits I think. One thing, François, before I let you go, the, I wanted to ask you about that. I feel like you’ve figured something out that’s really important that a lot of people haven’t figured out, which is, you write a lot in your letters over the years about the importance of unwavering optimism.
[01:19:07] William Green: And I think it’s really, it’s a really interesting insight. here we are in this very difficult period where we’re getting hit with inflation and there’s, the market has been kind of melting down and, there are fears of recession and there’s war in Ukraine and the like. And it seems to me that one of your secret weapons is one that, so John Templeton also had, which is that you’re an unwavering optimist.
[01:19:28] William Green: And I wonder if you could talk about why you are and why you have this kind of confidence in what you call the world of free enterprise.
[01:19:35] François Rochon: Yes, you’re right. I think nothing was ever built on pessimism. I think you never make wise decision with fears. I think optimism is an important ingredient to success. Not the only ingredient, but one important ingredient. I would say if you study human history and you go back many years in the past, I think the only conclusion is that you cannot be not amazed of how much we’ve improved over the last centuries. I mean, just in terms of technology, it’s incredible the changes that we’ve made, and you have to understand what is the fountainhead of those improvements, and it’s the human mind is just inventing things, creating things, finding ways of doing things better, always very slowly and not in a linear fashion.
[01:20:34] François Rochon: Of course, there’s some tough periods and some better periods, but over a long period of time, the improvement has been quite steady and quite impressive. I mean, the standard le of living has probably doubled every 25 years in the last century, which is incredible. And, so people worry about, climate change and they’re right to, to be worried and they worry that, we won’t have any, more oil and, we’ll have to find alternate energy.
[01:21:06] François Rochon: And I think they’re right too. Not necessarily that, we’ll, we won’t have any, oil left, but I think we do have to find better sources of energy. But what will bring those changes, those improvements, either for energy or fixing climate change? Will come from ideas and the human mind. And if you think about it, the all the great progresses of the last century came from idea. Nothing really has changed in our environment, that nature and the human nature. But we find ways to always improve things because we have this drive as human beings of never being satisfied. We will always want to improve our situation.
[01:21:54] François Rochon: And I think this drive is very powerful and gives me the feeling that, things will always. There’ll be, there’ll be tough periods, There’ll be, crisis and catastrophes. I accept that and I’ve been accepting that for 30 years. And, I’ve seen the recessions, I’ve seen, terrorist attacks. I’ve seen, a lot of crisis in many countries. But in the end, I think, the human race always advances forward.
[01:22:24] François Rochon: And, the right approach is to be optimistic and we’ll find solutions to all of our problems. Just, we have to put our minds to it. But I’m confident that the survival gene, this is probably the most, the strongest gene we have. We want to survive, We want to move forward, is a very, great fuel for human investment.
[01:22:46] François Rochon: And, pretty optimistic is going to continue. I would say that in the next, I don’t know if it’s going to be around 50 years, but I’m pretty sure if I’m around our standard of living will increased by percent, then live even better than we’re today. And I’m pretty c that we’ll find solutions to all our big problems, climate changes and inflation.
[01:23:10] William Green: I think part of what I like François, is that your optimism isn’t a naive temperamental impulse, that just infuses everything. It’s built very much on a kind of data driven knowledge of the past. And so remember, for example, reading in one of your letters, you talked about a Tale of two sitters by Charles Dickens, and you said that since its publication in the 1850s, the percentage of people living in extreme poverty in the world has fallen from 87% to less than 10% today.
[01:23:39] William Green: And you mentioned that the average standard of living has increased by a factor of more than 25 times since the book was published in 1859. So you look at that and you think, this isn’t naive. This has happened, this is our history, and think of all the terrible things that we’ve been through in that last 160 years since that book came out.
[01:23:56] William Green: And likewise, there’s an extraordinary table that I think you originally drew up during the 2008, 2009 financial crisis and then published again or updated in March, 2020 at the initial height of the Covid Pandemic where you listed 14, I think, major corrections over the last, I think 60 or so years, followed by these massive rebounds.
[01:24:19] William Green: And it was very striking to me. Again, it’s a data driven reason for optimism. you listed, for example, in I think 1973 to 74, the market fell something like 48% and then was followed by 106% gain over the next five years or so. And this process seems to have happened again and again. Can you talk about that sense of just that the sun also rises, right?
[01:24:43] William Green: That, here we are going through a difficult period and yet when you look back historically again and again, the sun also rises.
[01:24:52] François Rochon: Yes. It’s the lesson that the, if you study a human ministry, that’s the lesson that, remember Im Lincoln said 150 years ago, so this two shall pass away. And then Grants said that, this phrases summarize the whole human history things pass, crisis passed. And in the end, the human race continues to always improve things and move forward. And I would say same thing with companies like we talked at the beginning of the interview, companies grow their earning six, 7% yearly and give a 2% dividend on average. So that’s a eight or 9% return for stock. So of course when they go down 30, 40, 50%, there’s every reason to believe that within five or six or seven years, they’ll make new records. Just because earnings continue to increase increasing earnings at
[01:25:48] François Rochon: 7% annually, double that whole earning in the US every 10 years. So it makes sense that every 10 years, the s and p 500 or the industrial average doubles in value because earnings have double over the last 10 years. And there’ll be a recession of course, and earnings will go without recession, but they’ll rebound and, eventually they’ll make new records.
[01:26:13] François Rochon: So I think that’s very reassuring to understand that because you know that they’ll be tough times, but if you patient, you’ll be reward.
[01:26:22] William Green: It’s beautiful cause it means you have to understand these fundamental forces that are at play here, Like the power of intrinsic value, growing the power of productivity, increasing the power of human ingenuity to solve problems.
[01:26:35] William Green: But once you kind of understand that you don’t really need to be that naive to be optimistic. I suspect.
[01:26:42] François Rochon: No, I don’t think I’m naive, but just realistic. That’s just the nature of our human society. And there’s some very bad things I couldn’t agree with more. I mean, everything you read about tragedies and terrible things that happen all over the world.
[01:26:58] François Rochon: But there’s also great things, great accomplishment, great things that civilization have built over the years. And you have to look at that either also. Both are important. And, in the end, I think the overall balance is that, more good have come out of the human ministry than that.
3. Proof of Work – Nick Maggiulli
When you see a lot of people making a lot of money that wouldn’t normally be making a lot of money, that’s a sign that something’s off. When you have 29 year-olds worth $26 billion naming sports stadiums, look out. When individuals are going from unemployment to retirement in a few months, proceed with caution. Ultimately, when too many people are getting too lucky too often, that’s your wakeup call. That’s your hint that the good times won’t last forever. Why?
Because the world trends towards equilibrium. The world trends towards proof of work. It’s rare for fortunes to be created so effortlessly. Therefore, if you see easy money being made, it’s one of the strongest signals that something’s not right. Of course, some people will hit the lottery or be born into wealth. They are the lucky ones. But, most of us aren’t. Most of us have to work for it. We have to show the proof.
This explains why 70% of wealthy families lose their fortunes by the second generation and 90% lose it by the third generation. They didn’t have the proof. These future generations didn’t know how to build or preserve wealth like their ancestors did, so they squandered it.
The same thing happens during moments of financial excess. Those who got rich overnight don’t understand how their wealth was actually generated (i.e. a bubble). So they keep doing the same things that got them rich in the first place, in an effort to further increase their fortunes. But, once the bubble pops, the behavior that got them rich leads to their ruin. As they create, so they destroy. It’s a double-edged sword all the way down.
But the bigger problem underlying every get-rich-quick scheme is the belief that there’s an easier way to get rich. That there’s some sort of shortcut. But, there isn’t. There are no secrets when it comes to building wealth. If there were, then we would all be rich already. Think about it. If it takes 32 years for the typical self-made millionaire to gain their wealth, why would you expect to do it in just one? It makes no sense.
4. A Few Good Stories – Morgan Housel
Virtually everything was in short supply during World War II. The U.S. Army produced over 100 million uniforms to supply the Allies, which left little fabric left over for civilian clothes. It got worse in 1943 when the Army mandated that the synthetic material typically used in bathing suits had to be reserved for making military parachutes.
Clothing companies got creative by designing bathing suits with less and less fabric. One French designer named Louis Réard took it to the extreme, designing a bathing suit with as little fabric as he could get away with.
Réard introduced the new bathing suit in 1946. When deciding what to call it, he read in a newspaper about nuclear bomb tests that were taking place on a thin strip of rocks in the Pacific and were catching the public’s attention.
A thin strip catching people’s attention? That’s exactly what Réard was trying to do, too. So he named his swimsuit after the atoll where the nuclear tests were taking place – Bikini…
…Martin Luther King’s famous speech at the Lincoln Memorial on August 28th, 1963, did not go down as planned. King’s advisor and speechwriter, Clarence Jones, drafted a full speech for King to deliver, based on, he recalled, a “summary of ideas we had talked about.”
The first few minutes of King’s speech follow the script. Video shows him constantly looking down at his notes, reading verbatim. “Go back to Georgia, go back to Louisiana, go back to the slums and ghettos of our northern cities, knowing that somehow this situation can and will be changed.” Just then, around halfway through the speech, gospel singer Mahalia Jackson – who was standing to King’s left, maybe 10 feet away – shouts out, “Tell ‘em about the dream Martin! Tell ‘em about the dream!”
Jones recalls: “[King] looks over at her in real time, then he takes the text of the written speech and he slides it to the left side of the lectern. He grabs the lectern and looks out on more than 250,000 people.”
There’s then a six-second pause before King looks up at the sky and says:
I have a dream. It is a dream deeply rooted in the American dream.
I have a dream that one day this nation will rise up and live out the true meaning of its creed: “We hold these truths to be self-evident, that all men are created equal.”
I have a dream that my four little children will one day live in a nation where they will not be judged by the color of their skin but by the content of their character.
I have a dream today!
The rest was history.
Jones says: “That portion of the speech, which is most celebrated in this country and around the world, is not the speech that he planned to give.” The best story – not the most prepared, or the most thought out, or the most analytical – wins.
5. FTX’s Balance Sheet Was Bad – Matt Levine
What. And yet bad as all of this is, it can’t prepare you for the balance sheet itself, published by FT Alphaville, which is less a balance sheet and more a list of some tickers interspersed with hasty apologies. If you blithely add up the “liquid,” “less liquid” and “illiquid” assets, at their “deliverable” value as of Thursday, and subtract the liabilities, you do get a positive net equity of about $700 million. (Roughly $9.6 billion of assets versus $8.9 billion of liabilities.) But then there is the “Hidden, poorly internally labeled ‘fiat@’ account,” with a balance of negative $8 billion. I don’t actually think that you’re supposed to subtract that number from net equity — though I do not know how this balance sheet is supposed to work! — but it doesn’t matter. If you try to calculate the equity of a balance sheet with an entry for HIDDEN POORLY INTERNALLY LABELED ACCOUNT, Microsoft Clippy will appear before you in the flesh, bloodshot and staggering, with a knife in his little paper-clip hand, saying “just what do you think you’re doing Dave?” You cannot apply ordinary arithmetic to numbers in a cell labeled “HIDDEN POORLY INTERNALLY LABELED ACCOUNT.” The result of adding or subtracting those numbers with ordinary numbers is not a number; it is prison…
…For a minute, ignore this nightmare balance sheet, and think about what FTX’s balance sheet should be. Conceptually, customers give you money — apparently about $16 billion in dollars, crypto, etc. — and then you hang on to the money and owe it back to them. In the simplest world, you keep the customers’ money in exactly the form they give it to you: Someone deposits $100, you keep $100 for him; someone deposits one Bitcoin, you keep one Bitcoin for her. For reasons we have discussed — some legitimate! — FTX doesn’t quite work that way, and you could imagine some more complicated balance sheet where a lot of the money and crypto that came in from some customers was loaned to others. But broadly speaking your balance sheet is still going to look roughly like:
Liabilities: Money customers gave you, which you owe to them;
Assets: Stuff you bought with that money.
And then the basic question is, how bad is the mismatch. Like, $16 billion of dollar liabilities and $16 billion of liquid dollar-denominated assets? Sure, great. $16 billion of dollar liabilities and $16 billion worth of Bitcoin assets? Not ideal, incredibly risky, but in some broad sense understandable. $16 billion of dollar liabilities and assets consisting entirely of some magic beans that you bought in the market for $16 billion? Very bad. $16 billion of dollar liabilities and assets consisting mostly of some magic beans that you invented yourself and acquired for zero dollars? WHAT? Never mind the valuation of the beans; where did the money go? What happened to the $16 billion? Spending $5 billion of customer money on Serum would have been horrible, but FTX didn’t do that, and couldn’t have, because there wasn’t $5 billion of Serum available to buy. FTX shot its customer money into some still-unexplained reaches of the astral plane and was like “well we do have $5 billion of this Serum token we made up, that’s something?” No it isn’t!
One simple point here is that FTX’s Serum holdings — $2.2 billion last week, $5.4 billion before that — could not have been sold for anything like $2.2 billion. FTX’s Serum holdings were vastly larger than the entire circulating supply of Serum. If FTX had attempted to sell them into the market over the course of a week or month or year, it would have swamped the market and crashed the price. Perhaps it could have gotten a few hundred million dollars for them. But I think a realistic valuation of that huge stash of Serum would be closer to zero. That is not a comment on Serum; it’s a comment on the size of the stash.
But I do want to comment on Serum, because Serum is not some weird token that FTX cornered for some reason; Serum is a token that FTX made up. To use a loose but reasonable analogy, Serum (the protocol) is sort of FTX’s decentralized exchange subsidiary, and SRM (the token) is sort of the stock in that subsidiary. A little of the stock trades publicly, but it is mostly held by FTX, its corporate parent, as it were. The public market price of the small free float might give a reasonable estimate of the value of the subsidiary. But in the real world, the value of the subsidiary is incredibly tightly linked to the value of FTX’s overall business. If everyone is like “ah yes FTX is a good exchange operator and a leader in safe crypto trading,” then its decentralized exchange protocol has a good chance of being popular and profitable. If everyone is like “ah yes FTX is a careless fraud,” then Serum is going to have a hard time. 3 At the point that FTX is shopping its Serum stake to seek a rescue financing due to HIDDEN POORLY INTERNALLY LABELED ACCOUNT, its huge stash of Serum is toast! Just toast!…
…I am not saying that all of FTX’s assets were made up. That desperation balance sheet lists dollar and yen accounts, stablecoins, unaffiliated cryptocurrencies, equities, venture investments, etc., all things that were not created or controlled by FTX. 5 And that desperation balance sheet reflects FTX’s position after $5 billion of customer outflows last weekend; presumably FTX burned through its more liquid normal stuff (Bitcoin, dollars, etc.) to meet those withdrawals, so what was left was the weirdo cats and dogs. 6 Still it is striking that the balance sheet that FTX circulated to potential rescuers consisted mostly of stuff it made up. Its balance sheet consisted mostly of stuff it made up! Stuff it made up! You can’t do that! That’s not how balance sheets work! That’s not how anything works!
Oh, fine: It is how crypto works. This might all sound familiar not just because we talked about FTT last week, but because we talked about the collapse of TerraUSD and Luna earlier this year. Terra was a blockchain system run by Do Kwon, and it raised billions of dollars by selling dollar-denominated tokens — TerraUSD — that were supposed to keep their value because they were backed by a variable amount of another token — Luna — that Kwon had also invented. For a while people thought the Terra ecosystem was promising, so the Luna token was worth a lot, so Terra could go around saying its TerraUSD tokens were extremely safe, because the billions of dollars of TerraUSD “debt” were backed by more billions of dollars’ worth of Luna. And then one day people changed their minds, and the price of Luna — which was just a bet on Terra’s future — collapsed, so TerraUSD was unbacked, and the whole thing collapsed. The FTX situation is not the same, but it rhymes. The role of TerraUSD — the “debt” — is played here by FTX’s customer balances; the role of Luna — the backing token — is played by FTT and SRM. In both cases, confidence in the business collapsed, and it turned out that the debt was actually backed by nothing.
6. How fear robs investors of opportunities and returns – Chin Hui Leong
When it comes to investing, many picture themselves making rational, well thought-out decisions. However, in reality, this same group is prone to reacting poorly to stock market moves. This disconnect is down to the way we process information, says Daniel Kahneman, who is considered to be one of the fathers of behavioural finance.
In his book “Thinking, Fast and Slow”, Kahneman describes two general modes of thinking: System 1 (reflexive) and System 2 (reflective). Where System 1 is built for intuitive, snap decisions, System 2 is primed for untangling complex problems which require time. Under this framework, most investors consider themselves as System 2 thinkers, tapping on the analytical side of their brain to process data, deliberate over the pros and cons, and come up with a rational investment decision. Yet, in practice, System 1 often overwhelms System 2 before the latter has a chance to act.
It’s not a matter of choice. According to Kahneman, most of the time, we function based on System 1. Our reflexive mode is useful for daily routines and recognising familiar situations, and it does a good job in prompting the appropriate reaction. In addition, because System 1 is adept at processing similarities, it will alert us when there is a deviation from the norm. For instance, if you step onto the road and there’s a car speeding towards you, you will sense danger and move out of the way. Here, System 1 kicks in automatically without deliberation, saving your skin.
Therein lies a wrinkle. What’s good for avoiding danger is not always helpful when it comes to investing. In particular, watching the stock market fall day by day, month after month, is enough to send investors’ System 1 into overdrive, overwhelm their System 2 mode, and cause them to panic sell. The result is what we see today: few takers despite the lower stock valuations…
…In his book “Your Money and Your Brain”, Zweig says that predictions of the future often fall prey to relying too heavily on the short-term past to forecast the long-term future. If we apply this behaviour to the current context, it would be akin to taking all of today’s worst problems and projecting these worries indefinitely into the future.
Faced with nothing but gloom, it’s no wonder fearful investors are sitting out. Under the circumstances, it is helpful to remember that the stock market has undergone worse situations before. Tellingly, not all predictions of doom turned out to be true…
…In 2014, a former Harvard economist withdrew almost US$1 million of his own money, speculating that cash will lose almost all its value due to the US Federal Reserve’s zero-interest rate policy. Yet, in today’s rising interest rate environment, the US dollar has gained ground over almost every major currency. That’s not the only prediction that didn’t pan out. Two years earlier, around 2012, a high-profile investment advisor suggested that investors should dump most of their US stocks in favour of gold. With the benefit of hindsight, we can now say that it was a terrible idea.
Over the past decade, the value of the S&P 500 index, which represents 500 of the largest US companies, has almost tripled, during the time when the value of gold fell by 3%.
7. The Fingerprints of History – Michael Batnick
There are a handful of times in my life where the first encounter with somebody stayed with me forever. One of those moments was in 2014 (15?) when I met Scott Krisiloff.
At the time, Scott was running an asset management company, but the thing that hit me had nothing to do with his day job. He told Josh and I that he was in the process of reading every issue that Time Magazine had ever published, starting in 1923. I couldn’t believe it…
…Scott read ~4,000 issues covering 77 years, ultimately stopping in 2000 once his first child was born… Not only did Scott take years of his life to go through all of this, but he documented it for us to enjoy…
…I’m fired up to stand on Scott’s shoulders and read every single one of these monthly recaps. I’ll leave you with 10 things he learned from this incredible experience.
1) Compared to the scale of history, a human lifespan is relatively brief. In the early days of TIME, the editors of the magazine began obituaries with the phrase “As it must to all men, Death came, last week to…” It was a reminder that eventually we all return to the same place no matter how rich, famous or powerful. We all know that life is short, but watching the cycle of birth and death for entire generations drives home just how short life really is. Over 77 years I watched multiple generations live life’s cycle. I also got to watch the major events that shaped society during those life spans. I noticed that major events happen relatively infrequently, are set in motion over very long periods of time and are driven by forces larger than any individual. A human lifespan is incredibly brief when measured against that scale.
2) Focus on the things that matter. We are all here for a short amount of time, so it’s critical to use that time wisely. Wealth, fame and power won’t lead to immortality. Societal memory is short and even those who make it to “the top” are eventually forgotten. This happens even faster than you might think. If you seek validation, personal achievement isn’t the place to find it. Invest in family, friends and self understanding. These are the things that will be most valuable on your journey through life…
…5) Just when you think you understand everything, everything will change. When I was reading TIME I often imagined myself as someone who was born around 1900 and began a career in 1923. By the 1970s I reached a point where it felt as if I had seen it all. I had 50 years of career “experience” and cycles were repeating. Then the 1980s happened. Economic dynamics changed and turned everything I thought I knew on its head. I learned from this experience that there are structural breaks in the way that the world works and more forces in play than anyone has the capacity to understand…
…10) We all share a small world. In TIME’s Person of the Century issue it also noted that “Einstein taught the greatest humility of all: that we are but a speck in an unfathomably large universe. The more we gain insight into its mysterious forces, cosmic and atomic, the more reason we have to be humble. And the more we harness the huge power of these forces, the more such humility becomes an imperative.” This was the most important takeaway from observing the passage of time over the course of three quarters of a century. We don’t fully understand why or how we are here but we share our short time on this planet with billions of other souls who are each trying to make sense of the same world in their own way. The need for compassion, empathy and humility is so much greater than the need for competition and conquest.
I first set out to read every issue of TIME with this spirit of conquest, but the experience changed me. I learned that these goals can be personally and societally destructive and that victory won’t give you the wealth you seek. As a result I will spend the rest of my life treasuring every moment that I have here with the people that I love. And I will spend my working hours building and supporting strong institutions that promote human understanding.
I imagine that anyone who lives a long life might draw similar conclusions about what is and isn’t important, and I feel that it is a gift to have been given this perspective at a relatively young age. Ultimately, by reading every issue of TIME I learned the value of time, which is, by far, our most precious commodity.
Disclaimer: The Good Investors is the personal investing blog of two simple guys who are passionate about educating Singaporeans about stock market investing. By using this Site, you specifically agree that none of the information provided constitutes financial, investment, or other professional advice. It is only intended to provide education. Speak with a professional before making important decisions about your money, your professional life, or even your personal life. We currently have a vested interest in Microsoft. Holdings are subject to change at any time.