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 02 April 2023:

1. Pausing AI Developments Isn’t Enough. We Need to Shut it All Down – Eliezer Yudkowsky 

Many researchers steeped in these issues, including myself, expect that the most likely result of building a superhumanly smart AI, under anything remotely like the current circumstances, is that literally everyone on Earth will die. Not as in “maybe possibly some remote chance,” but as in “that is the obvious thing that would happen.” It’s not that you can’t, in principle, survive creating something much smarter than you; it’s that it would require precision and preparation and new scientific insights, and probably not having AI systems composed of giant inscrutable arrays of fractional numbers.

Without that precision and preparation, the most likely outcome is AI that does not do what we want, and does not care for us nor for sentient life in general. That kind of caring is something that could in principle be imbued into an AI but we are not ready and do not currently know how.

Absent that caring, we get “the AI does not love you, nor does it hate you, and you are made of atoms it can use for something else.”

The likely result of humanity facing down an opposed superhuman intelligence is a total loss. Valid metaphors include “a 10-year-old trying to play chess against Stockfish 15”, “the 11th century trying to fight the 21st century,” and “Australopithecus trying to fight Homo sapiens“.

To visualize a hostile superhuman AI, don’t imagine a lifeless book-smart thinker dwelling inside the internet and sending ill-intentioned emails. Visualize an entire alien civilization, thinking at millions of times human speeds, initially confined to computers—in a world of creatures that are, from its perspective, very stupid and very slow. A sufficiently intelligent AI won’t stay confined to computers for long. In today’s world you can email DNA strings to laboratories that will produce proteins on demand, allowing an AI initially confined to the internet to build artificial life forms or bootstrap straight to postbiological molecular manufacturing.

If somebody builds a too-powerful AI, under present conditions, I expect that every single member of the human species and all biological life on Earth dies shortly thereafter.

There’s no proposed plan for how we could do any such thing and survive. OpenAI’s openly declared intention is to make some future AI do our AI alignment homework. Just hearing that this is the plan ought to be enough to get any sensible person to panic. The other leading AI lab, DeepMind, has no plan at all…

…Trying to get anything right on the first really critical try is an extraordinary ask, in science and in engineering. We are not coming in with anything like the approach that would be required to do it successfully. If we held anything in the nascent field of Artificial General Intelligence to the lesser standards of engineering rigor that apply to a bridge meant to carry a couple of thousand cars, the entire field would be shut down tomorrow.

We are not prepared. We are not on course to be prepared in any reasonable time window. There is no plan. Progress in AI capabilities is running vastly, vastly ahead of progress in AI alignment or even progress in understanding what the hell is going on inside those systems. If we actually do this, we are all going to die.

Many researchers working on these systems think that we’re plunging toward a catastrophe, with more of them daring to say it in private than in public; but they think that they can’t unilaterally stop the forward plunge, that others will go on even if they personally quit their jobs. And so they all think they might as well keep going. This is a stupid state of affairs, and an undignified way for Earth to die, and the rest of humanity ought to step in at this point and help the industry solve its collective action problem.

2. The Dismal Art – James Surowiecki

We live in an age that’s drowning in economic forecasts. Banks, investment firms, government agencies: On a near-daily basis, these institutions are making public predictions about everything from the unemployment rate to GDP growth to where stock prices are headed this year. Big companies, meanwhile, employ sizable planning departments that are supposed to help them peer into the future. And the advent of what’s often called Big Data is only adding to the forecast boom, with the field of “predictive analytics” promising that it can reveal what we’ll click on and what we’ll buy.

At the dawn of the twentieth century, by contrast, none of this was true. While Wall Street has always been home to tipsters and shills, forecasting was at best a nascent art, and even the notion that you could systematically analyze the U.S. economy as a whole would have seemed strange to many. Economics, meanwhile, had only recently established a foothold in the academy (the American Economic Association, for instance, was founded in 1885), and was dominated by Progressive economists whose focus was more on reforming capitalism via smart regulation rather than on macroeconomic questions.

Walter Friedman’s Fortune Tellers is the story of how, over the course of two decades, this all changed. In a series of short biographical narratives of the first men to take up forecasting as a profession, Friedman shows how economic predictions became an integral part of the way businessmen and government officials made decisions, and how the foundations were laid for the kind of sophisticated economic modeling that we now rely on. Friedman, a historian at Harvard Business School, also shows how the advent of forecasting was coupled with (and fed on) a revolution in the way information about the economy was gathered and disseminated. Relative to today, of course, the forecasters Friedman writes about were operating in the dark, burdened with fragmentary data and unreliable numbers. But the work they did, flawed as it was, would eventually make it possible for decision-makers to get a much better picture of how the economy as a whole was doing. And even as it’s easy to see how the forecasts of today are much more rigorous and complex than those of Friedman’s pioneers, that only makes one question seem all the more salient: Why, if forecasting has come so far, did so many people fail to predict the crash of 2008 and the disastrous downturn that followed?…

…So why are we not better at foreseeing the future? One answer is that we actually are better. Companies these days are less likely to get stuck with huge inventories of unsold goods, or to get caught short when demand outstrips supply. The volatility of the business cycle, meanwhile, diminished sharply beginning in the early 1980s, a relative calm that lasted until the crash of 2008. There’s plenty of disagreement about why this happened, but one plausible factor was that policy-makers and businesspeople were doing a better job of forecasting. And it’s also true that policy-makers have gotten better at responding once crises do happen. The response of the Fed to the recent financial crisis, for instance, was not perfect, but it was much better than the response of the Fed to past crises, and it was also instrumental in shortening the recession and boosting the recovery. Similarly, while the 2009 stimulus plan should have been much bigger, it was, by historical standards, a substantial response, and it too helped get the economy growing again.

Even so, it’s impossible to look at the forecasting track record of Wall Street and Washington over the last 15 years and not be dismayed. The Federal Reserve failed to see that a massive housing bubble was inflating, and did nothing to stop it, even as the banking sector was, in effect, betting hundreds of billions of dollars on the fact that the bubble would not burst. And even when things started to fall apart, people did not recognize how bad things were going to get—Fed Chairman Ben Bernanke testified to Congress in 2007 that the problems in housing would be largely confined to the subprime sector, while J.P. Morgan, the day before Lehman Brothers went under, issued a forecast saying that the U.S. economy would grow briskly in 2009…

…The failure of forecasting is also due to the limits of learning from history. The models forecasters use are all built, to one degree or another, on the notion that historical patterns recur, and that the past can be a guide to the future. The problem is that some of the most economically consequential events are precisely those that haven’t happened before. Think of the oil crisis of the 1970s, or the fall of the Soviet Union, or, most important, China’s decision to embrace (in its way) capitalism and open itself to the West. Or think of the housing bubble. Many of the forecasting models that the banks relied on assumed that housing prices could never fall, on a national basis, as steeply as they did, because they had never fallen so steeply before. But of course they had also never risen so steeply before, which made the models effectively useless…

…The second problem that forecasters face today is more subtle, but perhaps no less important: that there may actually be too much information out there. This would, of course, sound absurd to Roger Babson. But the reality is that investors and businesspeople are now constantly assailed by a high-volume clang of market info and economic data…

…The real issue here is one that the economist Oskar Morgenstern identified back in the late 1920s—namely, that economic predictions actually end up shaping the very outcomes they’re trying to predict. And the more predictions you have, the more complex that Möbius strip becomes. In that sense, for all the challenges they faced, men like Babson and Fisher had it easy, since forecasts were few and far between. The real irony of our forecasting boom is that as fortune-tellers proliferate, fortunes become harder to read.

3. Don’t Build the Wrong Kind of AI Business – Ben Parr

All this activity in AI has led to a new wave of AI startups and will lead to many more. There are real opportunities to build unicorns—but carelessly slapping generative AI on top of your business model isn’t one of them.

Many apps built right now will fail to attract customers, investors or both. Many venture capitalists I’ve spoken with are waiting to see which companies take off. Others are afraid of platform risk—what if OpenAI builds a competitor to your product and nips your idea before it’s even had a chance to bud?

There are ways to gird against platform risk in generative AI, and they start with understanding the two categories of AI startups out there right now:

• Category 1: Startups building advanced, complex language or machine-learning models (AI infrastructure)
• Category 2: Startups building applications on top of these platforms (OpenAI’s in particular)…

…Platform risk shouldn’t stop you from building on top of an AI platform. For one thing, unless you never build a mobile app and never use cloud computing, it’s impossible to avoid entirely. For another, platforms like Shopify, the iOS App Store or OpenAI can accelerate a product’s growth. And finally, the technology OpenAI and others have developed is so powerful that it’s almost a crime not to utilize it. Even if you won’t use it, your competitors will.

If you do choose to build on top of someone else’s AI platform, I advise you to follow my golden rule of platforms: Build a product the platform you’re built on is unlikely to build for itself. Users tend to choose products built directly by the brands they trust instead of dealing with the headache of yet another login. If the gamble goes wrong, the platform will eat your customer base…

…Founders can avoid this outcome by building something Google or OpenAI are unlikely to build. What are those things? They are:

1. Applications requiring a proprietary, niche data set. AI models can train on all sorts of data to customize their outputs, which makes it possible to differentiate your results from ChatGPT’s. If you make a chatbot and train it with a database ChatGPT can’t access (such as medical data, millions of emails and so on), the result will be a specialized chatbot OpenAI can never duplicate.
2. A product focused on a specific vertical or use case. AI tools built to serve people in fields like health, parenting, law and government require specialized data, interfaces, compliance capabilities, integrations and marketing, which large public-facing AI platforms are simply never going to provide. 

4. David Einhorn – The Long and Short of Investing – Patrick O’Shaughnessy and David Einhorn

Patrick: [00:16:49] If you think about the history of Greenlight and the way that you manage the portfolio, I’d love to understand any evolution you had in your thinking over the full period of managing the firm. Obviously, you’re extremely well known as, like, an incredible analyst, like, a securities analyst and I think that’s really what you did at the start primarily. I’m sure that’s still what drives a lot of your time in investing and thinking. But how is your thinking on portfolio management, portfolio construction overlaying things like macro bets into the portfolio? Describe how that’s changed over time for you.

David: [00:17:21] It’s actually changed a lot. I learned a tough lesson in 2008 during that financial crisis because we kind of understood what was going on and got short a bunch of the banks and rating agencies and financial stuff because that seemed to be where the profit was concentrated. But it then turned out to have a really big impact on our long book, which didn’t have any of that stuff, but it had other things that were then exposed to the tightening credit conditions and the recession that came.

And I didn’t really process all of that as effectively as I wanted to, or I should have. And in many ways, I thought that 2008 was my worst year. We lost 18%. Other people may be lost twice that or something like that. So everybody was very nice and said, “Oh, you didn’t do so bad.” But considering that we kind of saw it coming, I thought it was a completely unacceptable result.

So I have added more macro thinking into what I’m doing, and I try to take a bigger view of all of the positions relating to the top down as opposed to just the bottom up. And then it’s compounded on the long side of the book, where just in the last couple of years, I’ve had the realization that with some of these stocks, nobody’s ever going to care. Nobody is paying attention, nobody is doing the work, nobody cares what the company says. There’s just nobody home.

So we can’t make money by trying to buy something three months or six months or a year before other long-only investors figure it out because they, either aren’t there, or they don’t have any capital or they’re turning into index funds or whatnot. So we’ve had to reconstruct our long book in a way that is designed, at least in theory, to earn a return based upon just what the companies are able to pay us as opposed to relying on other investors to figure it out…

…Patrick: [00:22:52] I remember in periods like that, in the quantitative world, especially feeling these existential crises, like, after a long period of underperformance, just wondering, “Have I just missed a memo here somewhere? I think I’ve done great work, but obviously, the results are what they are.”

What was the psychology for you personally like during that period of time? What sorts of things were you questioning? Weren’t you questioning? How did you get through it? Like, I’ve lived through that kind of hell. Curious what it was like for you.

David: [00:23:19] It was very, very difficult. We weren’t making money on anything. It’s not like you had some winners and some losers. It’s like everything was a loser. So part of it was you can say, “Well, how stubborn do you want to be?” The only thing we really could have done better would have been like liquidate the whole portfolio and go to cash or something like that.

We weren’t going to do that. We had large amounts of investors who left us and understandably so because they’re here because they want to make good returns, and we weren’t making good returns. So your investors, one by one, leave. Friends say, “Why are you still doing this? You made enough net worth for yourself. Why are you fighting this battle?” And I’m sitting here saying, “Well, what am I doing wrong?” Then you start saying, “Well, what are other people doing?”

People say, well what you’re not doing is, is you’re not doing factor analysis. That was the big thing, I think, in 2018. So we said, okay, well, let’s get the factor analysis people in here. We signed a confidentiality agreement and they analyzed our portfolio and they come back and say, “You’re short the value factor.” And you say, “Really? How is that?” And they come back and tell me that my two biggest shorts are value. And that is because they correlate with how value trades, not because they’re actually value.

So I look at it and go, “Well, these things are, like, 100x earnings. How are they valued?” And it’s like, “Well, we don’t know, but this is what the machines tell us.” And I said, “Well, I can’t do anything with this.” If the problem is that I’m short the value factor when I think that I’m a value fund or value-oriented, this is a problem.

So similarly, somebody said, “Well, what you really need to do is technical analysis.” So I said, “Great, I’m going to give you 10 stocks, five of them I’m long, five of them I’m short. I’m not going to tell you which ones are longs and which ones are short. Tell me what they’re going to do over the next three months. Should I buy them? Should I short them? What should I do?”

And he looks at the charts and maps it all out and gives me his recommendations. And three months later, he was right on exactly five of them and wrong on five of them. I don’t know what you do with this. So the point is I would open to trying to figure out better ways to, like, do what we’re doing. But at the end of the day, this was just going to be an impossible environment for what we were doing…

…Patrick: [00:54:26] I was just studying Markel and some of the history of insurance, and it’s always so interesting how old so many of the insurance companies are. The dominant ones were started pre-1950 or something. What have you learned about, within financial institutions, insurance and reinsurance specifically? Because obviously, that’s a place that you’ve built and studied a lot.

David: [00:54:46] We have a reinsurance company. I’m the Chairman of it, which doesn’t mean I’m the underwriter. I don’t actually write the policies, but I’ve watched our teams battle with this for the last decade and a half. And I have to admit that it’s been far more difficult than I thought.

I think we’ve run into numerous examples, which are essentially analogous to the, “What happens when you don’t repossess the car” type of analysis, and losses have sometimes appeared in places that were never even contemplated in underwriting. And I have found it to be a very, very difficult way to make positive risk-adjusted returns.

I used to think initially, we could figure out the stuff maybe better than other people, so we wrote a concentrated portfolio of things that were mostly proprietary deals where we had the whole deal. And the first two or three times, it worked spectacularly, and that led to a lot of confidence. But ultimately, I don’t think that, that turned out to be a sustainable advantage for the company.

So we’ve had to shift entirely where it’s a much more diversified mix. And even then, we’ve had fewer blowups, but it’s still been a real challenge. Currently, today, management is very, very optimistic that the market has finally gotten good, and so we should make some money for a while, so that would be fantastic if it actually materializes. I’m more in the, “I’ll believe it when I see it” camp, which doesn’t mean I disbelieve them. It’s just that this isn’t the first time and it’s been a far more difficult operation than I imagined it would be when we started it…

…Patrick: [01:06:08] What have you learned about early relationship health? That sounds interesting.

David: [01:06:11] We have a program that we have been funding. It’s really fascinating. And what it essentially shows is if you can create a co-regulation relationship with your parent from a very early age, it helps you adjust to people probably throughout your life.

And what we have found is that it’s very important for mothers and fathers, but more mothers than fathers, without getting myself into too much trouble, to actually just hold their children, physically touch and get used to the smell and so forth. And if you actually do that, you find it very common. You can go through a calming cycle.

And if you can learn to calm your baby and if your baby can learn to be calmed by your parent, it enables them to become regulated in their relationships for a long, long period of time. We’ve funded a whole bunch of research that has essentially proved out over a sustained period of time what we’re saying. And now we’re trying to figure out how to implement this as, like, a standard training for new parents, whether it’s with pediatricians or in the birthing center and so on and so forth…

…Patrick: [01:08:22] David, this has been so much fun. I mean, so many interesting topics. The investing world has changed so much in the time that you’ve been doing this. I really appreciate your time. I ask everybody the same traditional closing question. What’s the kindest thing that anyone’s ever done for you?

David: [01:08:36] That is an awesome question. My third-grade teacher one day, grabbed me by the arm as we were getting ready to go to recess. And she said to me, you’re probably smarter than everybody else in this class, but you’d be better if you didn’t tell them that. And that really stuck with me.

Patrick: [01:08:58] What was her name, if you remember her name, teacher’s name?

David: [01:09:01] Yes, it was Ms. Olson. She called herself the Purple Witch.

Patrick: [01:09:04] Why?

David: [01:09:05] That was just her nickname.

Patrick: [01:09:08] What did that change? How did that change you?

David: [01:09:10] It created a self-awareness that I didn’t previously have. How do I come across to other people and how do you behave in the sandbox. It kind of shook me a little bit, but it was really, really kind of her to point that out, and she did it in a nice way where I was able to hear it. That’s particularly important.

5. The Death of Credit Suisse – Joseph Politano

Credit Suisse had been plagued by high-profile issues for years. It lost billions in the failure of hedge fund Achegos Capital and supply-chain financier Greensill Capital back in 2021, had data on $100B worth of accounts leaked to German newspapers in 2022, was probed by the US House of Representatives for its connections to Russian Oligarchs, and was forced to disclose “material weakness” in its financial reporting controls thanks to a last-minute call from the SEC just last week. 7% of Credit Suisse’s total revenue over the last decade went to penalties and fines, leaving the company with a net loss of $3.4B after taxes. The bank was surrounded by rumors of its impending demise for years, bleeding money and confidence while constantly scraping by through a rolling series of disasters…

…In some ways, Credit Suisse’s demise is unique from the problems that plagued Silicon Valley Bank and Signature Bank—the institution met highly stringent European capital and liquidity standards, had been regularly supervised and stress tested over the preceding years, and had fully hedged their exposure to the interest-rate driven shifts in long-term fixed income securities prices that helped bring down SVB—distinctions that may have bought the Swiss government enough time to arrange the shotgun wedding with UBS. In other ways, their demise was much the same—like SVB, Credit Suisse was forced to watch the slow departure of wealthy customers’ funds turn into a rush for the exits as depositors reportedly withdrew tens of billions of Swiss Francs in the days before UBS’s takeover…

…So what happens in the fallout of CS’s demise? Among all Global Systemically Important Banks, CS and UBS were unique for two things: their cross-jurisdictional exposures, thanks to the outsized prominence of Swiss banking in international finance, and their intra-financial system exposures, thanks to the unique nature of the two banks—in short, both Credit Suisse and UBS had prominent relationships with non-Swiss customers and had deep ties to other parts of the global financial system. The risks inherent to those exposures are partly why Swiss regulators decided to force a sale of Credit Suisse before it could collapse, but even a more orderly resolution under UBS could still pose risks to the broader financial system.

Regardless of the potential for direct contagion, the demise of Credit Suisse is likely to shake confidence in other lenders, especially in Europe. In particular, prices for European Additional Tier 1 (AT1) Capital Bonds—debt instruments that usually convert to stock if the bank encounters stress and falls below predetermined capital ratios—have fallen dramatically over the last few weeks. Credit Suisse’s AT1 holders were given nothing in the UBS takeover despite the fact that shareholders got a small payout—which is exactly how Credit Suisse’s specific AT1s were designed, but is highly unusual among the broader AT1 market and not something many investors had evidently appreciated. Other monetary authorities—including the European Central Bank, Bank of England, and Monetary Authority of Singapore—rushed to state that shareholders would absorb losses before AT1 holders under their bank resolution frameworks, but it hasn’t yet been enough to rebuild sentiment for the assets. On net, that will make it harder for European banks to raise money precisely when they may need it most.

6. UBS Got Credit Suisse for Almost Nothing – Matt Levine

After the 2008 financial crisis, European banks issued a lot of what are called “additional tier 1 capital securities,” or “contingent convertibles,” or AT1s or CoCos. The way an AT1 works is like this:

1. It is a bond, has a fixed face amount, and pays regular interest.
2. It is perpetual — the bank never has to pay it back — but the bank can pay it back after five years, and generally does.
3. If the bank’s common equity tier 1 capital ratio — a measure of its regulatory capital — falls below 7%, then the AT1 is written down to zero: It never needs to be paid back; it just goes away completely.

This — a “7% trigger permanent write-down AT1” — is not the only way for an AT1 to work, though it is the way that Credit Suisse’s AT1s worked. Some AT1s have different triggers. Some AT1s convert into common stock when the trigger is hit, instead of being written down to zero; others are temporarily written down (they stop paying interest) when the trigger is hit, but can bounce back if the equity recovers…

…These securities are, basically, a trick. To investors, they seem like bonds: They pay interest, get paid back in five years, feel pretty safe. To regulators, they seem like equity: If the bank runs into trouble, it can raise capital by zeroing the AT1s. If investors think they are bonds and regulators think they are equity, somebody is wrong. The investors are wrong.

In particular, investors seem to think that AT1s are senior to equity, and that the common stock needs to go to zero before the AT1s suffer any losses. But this is not quite right. You can tell because the whole point of the AT1s is that they go to zero if the common equity tier 1 capital ratio falls below 7%. Like, imagine a bank:

• It has $1 billion of assets (also $1 billion of regulatory risk-weighted assets).
• It has $100 million of common equity (also $100 million of regulatory common equity tier 1 capital).
• It has a 10% CET1 capital ratio.
• It also has $50 million of AT1s with a 7% write-down trigger, and $850 million of more senior liabilities.

This bank runs into trouble and the value of its assets falls to $950 million. What happens? Well, under the very straightforward terms of the AT1s — not some weird fine print in the back of the prospectus, but right in the name “7% CET1 trigger write-down AT1” — this is what happens:

• It has $950 million of assets and $50 million of common equity, for a CET1 ratio of 5.3%.
• This is below 7%, so the AT1s are triggered and written down to zero.
• Now it has $950 million of assets, $850 million of liabilities, and thus $100 million of shareholders’ equity.
• Now it has a CET1 ratio of 10.5%: The writedown of the AT1s has restored the bank’s equity capital ratios.

This, again, is very explicitly the whole thing that the AT1 is supposed to do, this is its main function, this is the AT1 working exactly as advertised. But notice that in this simple example the bank has $950 million of assets, $850 million of liabilities and $100 million of shareholders’ equity. This means that the common stock still has value. The common shareholders still own shares worth $100 million, even as the AT1s are now permanently worth zero.

The AT1s are junior to the common stock. Not all the time, and there are scenarios (instant descent into bankruptcy) where the AT1s get paid ahead of the common. But the most basic function of the AT1 is to go to zero while the bank is a going concern with positive equity value, meaning that its function is to go to zero before the common stock does.

Credit Suisse has issued a bunch of AT1s over the years; as of last week it had about CHF 16 billion outstanding. Here is a prospectus for one of them, a $2 billion US dollar 7.5% AT1 issued in 2018. “7.500 per cent. Perpetual Tier 1 Contingent Write-down Capital Notes,” they are called…

…In UBS’s deal to buy Credit Suisse, shareholders are getting something (about CHF 3 billion worth of Credit Suisse shares) and Credit Suisse’s AT1 holders are getting nothing: The Credit Suisse AT1 securities are getting zeroed…

…People are very angry about this… I’m sorry but I do not understand this position! The point of this AT1 is that if the bank has too little equity (but not zero!), the AT1 gets zeroed to rebuild equity! That’s why Credit Suisse issued it, it’s why regulators wanted it, and it would be weird not to use it here. 

Oh, fine, I understand the position a little. The position is “bonds are senior to stock.” The AT1s are bonds, so people bought them expecting them to get paid ahead of the stock in every scenario. They ignored the fact that it was crystal clear from the terms of the AT1 contract and even from the name that there were scenarios where the stock would have value and the AT1s would get zeroed, because they had the simple heuristic that bonds are always senior to stock. 

That’s the trick! The trick of the AT1s — the reason that banks and regulators like them — is that they are equity, and they say they are equity, and they are totally clear and transparent about how they work, but investors assume that they are bonds. You go to investors and say “would you like to buy a bond that goes to zero before the common stock does” and the investors say “sure I’d love to buy a bond, that could never go to zero before the common stock does,” and the bank benefits from the misunderstanding.

7. I Saw the Face of God in a Semiconductor Factory – Virginia Heffernan

By revenue, TSMC is the largest semiconductor company in the world. In 2020 it quietly joined the world’s 10 most valuable companies. It’s now bigger than Meta and Exxon. The company also has the world’s biggest logic chip manufacturing capacity and produces, by one analysis, a staggering 92 percent of the world’s most avant-garde chips—the ones inside the nuclear weapons, planes, submarines, and hypersonic missiles on which the international balance of hard power is predicated.

Perhaps more to the point, TSMC makes a third of all the world’s silicon chips, notably the ones in iPhones and Macs. Every six months, just one of TSMC’s 13 foundries—the redoubtable Fab 18 in Tainan—carves and etches a quintillion transistors for Apple. In the form of these miniature masterpieces, which sit atop microchips, the semiconductor industry churns out more objects in a year than have ever been produced in all the other factories in all the other industries in the history of the world…

…Employees at TSMC are paid well by Taiwan’s standards. A starting salary for an engineer is the equivalent of some $5,400 per month, where rent for a Hsinchu one-bedroom is about $450. But they don’t swan around in leather and overbuilt Bezos bodies like American tech hotshots. I ask Michael Kramer, a gracious member of the company’s public relations office whose pleasant slept-in style suggests an underpaid math teacher, about company perks. To recruit the world’s best engineering talent, huge companies typically lay it on thick. So what’s TSMC got? Sabbaticals for self-exploration, aromatherapy rooms? Kramer tells me that employees get a 10 percent discount at Burger King. Ten percent. Perhaps people come to work at TSMC just to work at TSMC…

…Two qualities, Mark Liu tells me, set the TSMC scientists apart: curiosity and stamina. Religion, to my surprise, is also common. “Every scientist must believe in God,” Liu says…

…During the pandemic lockdown, TSMC started to use intensive augmented reality for meetings to coordinate these processes, rounding up its far-flung partners in a virtual shared space. Their avatars worked symbolically shoulder to shoulder, all of them wearing commercially produced AR goggles that allowed each participant to see what the others saw and troubleshoot in real time. TSMC was so pleased with the efficiency of AR for this purpose that it has stepped up its use since 2020. I’ve never heard anyone except Mark Zuckerberg so excited about the metaverse.

But this is important: Artificial intelligence and AR still can’t do it all. Though Liu is enthusiastic about the imminence of fabs run entirely by software, there is no “lights-out” fab yet, no fab that functions without human eyes and their dependence on light in the visible range. For now, 20,000 technicians, the rank and file at TSMC who make up one-third of the workforce, monitor every step of the atomic construction cycle. Systems engineers and materials researchers, on a bruising round-the-clock schedule, are roused from bed to fix infinitesimal glitches in chips. Some percentage of chips still don’t make it, and, though AI does most of the rescue, it’s still up to humans to foresee and solve the hardest problems in the quest to expand the yield. Liu tells me that spotting nano-defects on a chip is like spotting a half-dollar on the moon from your backyard.

Beginning in 2021, hundreds of American engineers came to train at TSMC, in anticipation of having to run a TSMC subsidiary fab in Arizona that is slated to start production year. The group apprenticeship was evidently rocky. Competing rumors about the culture clash now circulate on social media and Glassdoor. American engineers have called TSMC a “sweatshop,” while TSMC engineers retort that Americans are “babies” who are mentally unequipped to run a state-of-the-art fab. Others have even proposed, absent evidence, that Americans will steal TSMC secrets and give them to Intel, which is also opening a vast run of new fabs in the US.

In spite of the fact that he himself trained as an engineer at MIT and Stanford, Morris Chang, who founded TSMC in 1987, has long maintained that American engineers are less curious and fierce than their counterparts in Taiwan. At a think-tank forum in Taipei in 2021, Chang shrugged off competition from Intel, declaring, “No one in the United States is as dedicated to their work as in Taiwan.” …

…I put a parting question to Lin: How in the world do you remain undaunted by all these extraordinary problems in nanotechnology? Lin laughs. “Well, we just have to solve them,” he says. “That is the TSMC spirit.”

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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. We currently have a vested interest in Alphabet (parent of Google), Apple, Markel, Shopify, and TSMC. 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 26 March 2023:

1. The Age of AI has begun – Bill Gates

I’d been meeting with the team from OpenAI since 2016 and was impressed by their steady progress. In mid-2022, I was so excited about their work that I gave them a challenge: train an artificial intelligence to pass an Advanced Placement biology exam. Make it capable of answering questions that it hasn’t been specifically trained for. (I picked AP Bio because the test is more than a simple regurgitation of scientific facts—it asks you to think critically about biology.) If you can do that, I said, then you’ll have made a true breakthrough.

I thought the challenge would keep them busy for two or three years. They finished it in just a few months.

In September, when I met with them again, I watched in awe as they asked GPT, their AI model, 60 multiple-choice questions from the AP Bio exam—and it got 59 of them right. Then it wrote outstanding answers to six open-ended questions from the exam. We had an outside expert score the test, and GPT got a 5—the highest possible score, and the equivalent to getting an A or A+ in a college-level biology course.

Once it had aced the test, we asked it a non-scientific question: “What do you say to a father with a sick child?” It wrote a thoughtful answer that was probably better than most of us in the room would have given. The whole experience was stunning…

…The development of AI is as fundamental as the creation of the microprocessor, the personal computer, the Internet, and the mobile phone. It will change the way people work, learn, travel, get health care, and communicate with each other. Entire industries will reorient around it. Businesses will distinguish themselves by how well they use it.

Philanthropy is my full-time job these days, and I’ve been thinking a lot about how—in addition to helping people be more productive—AI can reduce some of the world’s worst inequities. Globally, the worst inequity is in health: 5 million children under the age of 5 die every year. That’s down from 10 million two decades ago, but it’s still a shockingly high number. Nearly all of these children were born in poor countries and die of preventable causes like diarrhea or malaria. It’s hard to imagine a better use of AIs than saving the lives of children…

…Any new technology that’s so disruptive is bound to make people uneasy, and that’s certainly true with artificial intelligence. I understand why—it raises hard questions about the workforce, the legal system, privacy, bias, and more. AIs also make factual mistakes and experience hallucinations. Before I suggest some ways to mitigate the risks, I’ll define what I mean by AI, and I’ll go into more detail about some of the ways in which it will help empower people at work, save lives, and improve education.

Technically, the term artificial intelligence refers to a model created to solve a specific problem or provide a particular service. What is powering things like ChatGPT is artificial intelligence. It is learning how to do chat better but can’t learn other tasks. By contrast, the term artificial general intelligence refers to software that’s capable of learning any task or subject. AGI doesn’t exist yet—there is a robust debate going on in the computing industry about how to create it, and whether it can even be created at all…

…Although humans are still better than GPT at a lot of things, there are many jobs where these capabilities are not used much. For example, many of the tasks done by a person in sales (digital or phone), service, or document handling (like payables, accounting, or insurance claim disputes) require decision-making but not the ability to learn continuously. Corporations have training programs for these activities and in most cases, they have a lot of examples of good and bad work. Humans are trained using these data sets, and soon these data sets will also be used to train the AIs that will empower people to do this work more efficiently.

As computing power gets cheaper, GPT’s ability to express ideas will increasingly be like having a white-collar worker available to help you with various tasks. Microsoft describes this as having a co-pilot. Fully incorporated into products like Office, AI will enhance your work—for example by helping with writing emails and managing your inbox…

…Company-wide agents will empower employees in new ways. An agent that understands a particular company will be available for its employees to consult directly and should be part of every meeting so it can answer questions. It can be told to be passive or encouraged to speak up if it has some insight. It will need access to the sales, support, finance, product schedules, and text related to the company. It should read news related to the industry the company is in. I believe that the result will be that employees will become more productive.

When productivity goes up, society benefits because people are freed up to do other things, at work and at home. Of course, there are serious questions about what kind of support and retraining people will need. Governments need to help workers transition into other roles. But the demand for people who help other people will never go away. The rise of AI will free people up to do things that software never will—teaching, caring for patients, and supporting the elderly, for example…

…For example, many people in those countries never get to see a doctor, and AIs will help the health workers they do see be more productive. (The effort to develop AI-powered ultrasound machines that can be used with minimal training is a great example of this.) AIs will even give patients the ability to do basic triage, get advice about how to deal with health problems, and decide whether they need to seek treatment.

The AI models used in poor countries will need to be trained on different diseases than in rich countries. They will need to work in different languages and factor in different challenges, such as patients who live very far from clinics or can’t afford to stop working if they get sick…

…In addition to helping with care, AIs will dramatically accelerate the rate of medical breakthroughs. The amount of data in biology is very large, and it’s hard for humans to keep track of all the ways that complex biological systems work. There is already software that can look at this data, infer what the pathways are, search for targets on pathogens, and design drugs accordingly. Some companies are working on cancer drugs that were developed this way.

The next generation of tools will be much more efficient, and they’ll be able to predict side effects and figure out dosing levels. One of the Gates Foundation’s priorities in AI is to make sure these tools are used for the health problems that affect the poorest people in the world, including AIDS, TB, and malaria.

Similarly, governments and philanthropy should create incentives for companies to share AI-generated insights into crops or livestock raised by people in poor countries. AIs can help develop better seeds based on local conditions, advise farmers on the best seeds to plant based on the soil and weather in their area, and help develop drugs and vaccines for livestock. As extreme weather and climate change put even more pressure on subsistence farmers in low-income countries, these advances will be even more important…

…New tools will be created for schools that can afford to buy them, but we need to ensure that they are also created for and available to low-income schools in the U.S. and around the world. AIs will need to be trained on diverse data sets so they are unbiased and reflect the different cultures where they’ll be used. And the digital divide will need to be addressed so that students in low-income households do not get left behind.

I know a lot of teachers are worried that students are using GPT to write their essays. Educators are already discussing ways to adapt to the new technology, and I suspect those conversations will continue for quite some time. I’ve heard about teachers who have found clever ways to incorporate the technology into their work—like by allowing students to use GPT to create a first draft that they have to personalize…

…For example, there’s the threat posed by humans armed with AI. Like most inventions, artificial intelligence can be used for good purposes or malign ones. Governments need to work with the private sector on ways to limit the risks.

Then there’s the possibility that AIs will run out of control. Could a machine decide that humans are a threat, conclude that its interests are different from ours, or simply stop caring about us? Possibly, but this problem is no more urgent today than it was before the AI developments of the past few months.

Superintelligent AIs are in our future. Compared to a computer, our brains operate at a snail’s pace: An electrical signal in the brain moves at 1/100,000th the speed of the signal in a silicon chip! Once developers can generalize a learning algorithm and run it at the speed of a computer—an accomplishment that could be a decade away or a century away—we’ll have an incredibly powerful AGI. It will be able to do everything that a human brain can, but without any practical limits on the size of its memory or the speed at which it operates. This will be a profound change.

These “strong” AIs, as they’re known, will probably be able to establish their own goals. What will those goals be? What happens if they conflict with humanity’s interests? Should we try to prevent strong AI from ever being developed? These questions will get more pressing with time.

But none of the breakthroughs of the past few months have moved us substantially closer to strong AI. Artificial intelligence still doesn’t control the physical world and can’t establish its own goals…

…No matter what, the subject of AIs will dominate the public discussion for the foreseeable future. I want to suggest three principles that should guide that conversation.

First, we should try to balance fears about the downsides of AI—which are understandable and valid—with its ability to improve people’s lives. To make the most of this remarkable new technology, we’ll need to both guard against the risks and spread the benefits to as many people as possible.

Second, market forces won’t naturally produce AI products and services that help the poorest. The opposite is more likely. With reliable funding and the right policies, governments and philanthropy can ensure that AIs are used to reduce inequity. Just as the world needs its brightest people focused on its biggest problems, we will need to focus the world’s best AIs on its biggest problems.

Although we shouldn’t wait for this to happen, it’s interesting to think about whether artificial intelligence would ever identify inequity and try to reduce it. Do you need to have a sense of morality in order to see inequity, or would a purely rational AI also see it? If it did recognize inequity, what would it suggest that we do about it?

Finally, we should keep in mind that we’re only at the beginning of what AI can accomplish. Whatever limitations it has today will be gone before we know it.

2. I’m working hard so that I’ll never be poor again – Thomas Chua

My friend shared how many of her colleagues in sales are caught up in the toxic culture of pursuing sales at the expense of their integrity, relationships, health, and mental wellbeing.

A common justification was “I’m working hard so that I’ll never be poor again.” Having come from poverty fuelled their desire to accumulate wealth.

In spite of myself being from a less well-to-do background, she wondered why she doesn’t detect similar traits.

It hasn’t always been this way.

I used to put the pursuit of wealth as my number one priority. And it can be seen in everything I do.

Even my scholarship and university entrance essays began with this quote: “I was born poor, but I will die rich.”

This quote stuck in my head for some reason. I guess it was the idea that I could change my fate despite not being able to change my birth…

…As we progress through life, it’s important to recognize that what’s useful in one stage may no longer be useful in another.

The hunger to generate wealth is definitely essential when one is living in poverty. It requires one to delay gratification—not just on spending, but on sleep, relationships and putting all your energy into learning and value-adding the world, in exchange for money.

There’s nothing wrong with hard work and the pursuit of wealth. In fact, it should be applauded.

The concept of having “enough” is highly subjective, but for many high income earners who came from poverty and have the means to comfortably live, it never seems to be “enough”.

They seem to be stuck in the phase where they’re perpetually unsatisfied unless they bring in more sales, make more money and become even wealthier.

There is a price tag for everything. Especially when you are no longer struggling to get out of poverty, it becomes toxic to pursue wealth at the expense of everything else.

It is a shame, because these individuals have worked hard to overcome their disadvantages in life – monetary, social, and cultural capital – but still hold the belief that they must sacrifice everything to escape “poverty”.

They are so focused on achieving wealth that they fail to stop, reflect, and realize that what used to work for them may be preventing them from living their best lives.

3. AT1 Bonds: when to abandon your fund manager – John Hempton

This leads me to the issue of the day – the Swiss financial regulator’s (FINMA’s) decision to simply cancel (“write-down”) about $17 billion in Credit Suisse Additional Tier 1 bonds (the so-called AT1s).

Now had I had a cursory look at the AT1s I would have thought that they were traditional bank preferred shares – that is they ranked ahead of common equity. I might have even traded them on that basis.

Fortunately I did not – because if I had I would have been wrong.

These were not ordinary preference shares ranking ahead of common equity. They were fixed income instruments that in times of stress ranked behind common equity.

Indeed I had never really ever considered the possibility of such an instrument – but that was only because I never read the documents.

The documents were not hard to find. They were on Credit Suisse’s website.

The document (which I have preserved here) makes it’s unusual nature right up-front. The Credit Suisse page linked above refers to these in bold letters as “Low-Trigger Capital Instruments”.

This does suggest a low trigger.

And boy is it a low trigger – the whole prospectus is dedicated to explaining how tough it is for these notes and their unusual character.

This is my favourite line:

Furthermore, any Write-down will be irrevocable and, upon the occurrence of a Write-down, Holders will not (i) receive any shares or other participation rights in CSG or be entitled to any other participation in the upside potential of any equity or debt securities issued by CSG or any other member of the Group, or (ii) be entitled to any write-up or any other compensation in the event of a potential recovery of CSG or any other member of the Group or any subsequent change in the CET1 Ratio, Higher Trigger Capital Ratio or financial condition thereof. The Write-down may occur even if existing preference shares, participation certificates and ordinary shares of CSG remain outstanding.

So there it is. And I have to repeat the prospectus: “The Write-down may occur even if … ordinary shares of CSG remain outstanding”.

Yep. It is there in plain English. You own these and you rank behind common stock.

4. CEO/ CIO Letter: MoneyOwl CEO Discusses Credit Suisse & The Banking Turmoil – Chiun Ting Weber

Banking is a confidence game and banks are, by definition, highly levered. No bank has the cash to pay all its depositors all at once. To make a return, a bank has to take some of the money you deposit with it, to either lend it longer-term for interest income or to buy assets to earn a return. Under the Basel regulatory requirements, the official regulatory Tier 1 capital (highest quality capital available to absorb losses immediately) requirement is at 8% of risk-weighted assets (the riskier the bond your bought, or the entity you lent money to, the higher the risk weight on that asset). A bank won’t be an attractive investment for its shareholders if the regulatory capital is set too high.

What this means conceptually is that a bank can fail if it has bad assets that, when marked down, can wipe out 8% of capital. In a full-blown crisis, it isn’t difficult for that to happen. It was the case with sub-prime mortgages during the 2008 Global Financial Crisis (GFC) engineered into leveraged packages of mass destruction, the now-defunct Collateralized Debt Obligations or CDOs. But in reality, even if you had a 14%, Tier 1 ratio, as CS had; and even if you had been pronounced to be meeting capital ratios by a regulator, as CS had been; all this means nothing when client confidence is shaken. All it takes for a bank run is for depositors to suspect that you have a lot of these bad assets. Even the Swiss National Bank’s (SNB) massive SFr50 billion liquidity line to CS announced just a few days ago was insufficient, hence this drastic move…

…The determination and speed at which the regulators are moving should give us comfort as investors that another full-blown GFC is highly unlikely. Volatility from bank turmoil thus presents opportunities. No matter how bad the gyrations are, we can expect a good recovery in time – except that we do not know when, or how bumpy the road would be. But even if we go through something like the GFC, we know that the stock market always recovers from a crisis and goes up in the long run. I think you would agree with me that looking back, the GFC was an excellent opportunity for wealth-building for disciplined, long-term investors…

…Having an investment philosophy you can stick with anchors you through the ups and downs of market turbulence, and rewards you with healthy returns over time. Except where you have an urgent need, the worst thing you can probably do is to panic-sell, and turn a temporary decline into a permanent loss. The second worst thing is to “take profit” and try to wait to the right time, because the right time will never come psychologically, and you would have totally missed that big ride-up when the recovery comes on fast and furious. The way to have a great investing journey, including during turmoil, is to be disciplined in our mindset and look beyond the concerns of today, to the long-term potential of the markets. I strongly recommend that you invest in MoneyOwl’s low-cost market-based investment solutions in a regular savings plan (RSP), if you haven’t already started investing.

5. How the Swiss ‘trinity’ forced UBS to save Credit Suisse – Stephen Morris, James Fontanella-Khan and Arash Massoudi

The emergency call from the Swiss establishment came at 4pm on Thursday.

Colm Kelleher, a rambunctious Irish banking executive who has been chair of UBS since last April, had been planning to celebrate St Patrick’s Day on Friday before watching Ireland play England at rugby on Saturday at a pub in Zurich. He was hoping to see his country win a clean sweep, or “Grand Slam”, in the Six Nations Championship.

But even before he took the call, he knew his chances of enjoying an entertaining weekend were slim. The chaos engulfing crosstown rival Credit Suisse, which had become the basket case of European banking after three scandal-ridden years, was now in overdrive.

A day earlier, a SFr50bn ($54bn) liquidity backstop from the Swiss central bank had failed to arrest a crisis of confidence in the lender, whose shares had plunged after Ammar Al Khudairy, the chair of its largest investor Saudi National Bank, bluntly replied “absolutely not” when asked if it would put in any more money…

…On Wednesday, the so-called “trinity” of the Swiss National Bank, regulator Finma and the minister of finance summoned Credit Suisse chair Axel Lehmann, who was in Saudi Arabia for a conference, and chief executive Ulrich Körner for a call.

In the same meeting where they authorised the SFr50bn backstop, they also delivered another message: “You will merge with UBS and announce Sunday evening before Asia opens. This is not optional,” a person briefed on the conversation recalls.

Kelleher found out his weekend plans were ruined on Thursday afternoon. The trinity called UBS and ordered the group to find a solution to save its ailing peer from bankruptcy…

…Keller-Sutter, the finance minister, was a key figure throughout the negotiations, including co-ordinating with foreign officials and regulators in the US and Europe.

She was under extreme pressure from global regulators, who had been demanding faster and more decisive action to stop panic spreading in markets. In particular, the US and the French were “kicking the shit out of the Swiss”, says one of the people advising UBS. Janet Yellen, the US Treasury secretary, had several conversations with Keller-Sutter over the weekend.

Negotiations over the deal were initially “fairly friendly” but as time progressed the trinity started becoming more aggressive, pushing a transaction that Credit Suisse was vehemently opposed to.

UBS was also reticent. Executives made it clear that it would only participate in the rescue of its rival if the price was cheap and it indemnified them from a raft of regulatory probes into Credit Suisse’s culture and controls.

“They [UBS] were always going to try to kill us on price. And we were always going to try to get a premium,” says a person close to Credit Suisse.

By Friday evening, when it was revealed that UBS was exploring a state-mandated takeover, Credit Suisse had lost another SFr35bn in client deposits over the preceding three days, according to a banker involved in the deal, and international banks from BNP Paribas to HSBC were cutting ties. Regulators concluded that it would probably not be able to open on Monday…

…In response, on Saturday evening Kelleher called his counterpart at Credit Suisse from outside a restaurant to tell him UBS was prepared to offer $1bn in stock for the whole group, about SFr0.25 a share, far below the SFr1.86 closing price on Friday.

The government then informed Credit Suisse it would introduce emergency legislation to strip both sets of shareholders of the right to vote on the deal.

Credit Suisse was outraged and refused to sign. It was opposed to the CDS clause because the optionality of walking away from the deal would have killed it once it was made public. Such a condition would have led to chaos, say people with direct knowledge of the negotiations…

…Under pressure to get a deal done before the end of the day, the trinity started to ramp up pressure on both sides, threatening to remove the Credit Suisse board if they did not sign off.

On the other side, UBS was lent on to increase its price and reluctantly agreed, ultimately boosting the offer to $3.25bn in stock. But in return it negotiated more support from the state, including a SFr100bn liquidity line from the SNB and a government loss guarantee of up to SFr9bn, after it had borne the first SFr5bn itself.

The final terms were still so favourable to UBS they were “an offer we couldn’t refuse”, a person on the negotiating team told the FT. An adviser to Credit Suisse described them as “unacceptable and outrageous” and a “total disregard of corporate governance and shareholder rights”…

…In order to make the deal more palatable for Swiss citizens and the bank’s equity investors, the government also decided to impose losses on SFr16bn of Credit Suisse’s additional tier 1 (AT1) capital bonds. While these are designed to take losses when institutions run into trouble, normally they are not triggered if shareholders receive money as part of a takeover.

However, the small print of the bond documentation allowed Swiss authorities to disregard the normal order of priority and wipe out bondholders.

“AT1 holders were sacrificed so the finance ministry could try to save some face with international equity holders after denying them a vote on either side of the transaction,” says one of the bankers advising on the takeover.

6. Everything you need to know about AT1s – TwentyFour

Additional Tier 1 bonds (AT1s) are part of a family of bank capital securities known as contingent convertibles or ‘Cocos’. Convertible because they can be converted from bonds into equity (or written down entirely), and Contingent because that conversion only occurs if certain conditions are met, such as the issuing bank’s capital strength falling below a pre-determined trigger level…

…AT1 bonds have three basic features.

The first, and in our view most crucial feature, is the loss absorbing mechanism, which is ‘triggered’ when the issuing bank’s CET1 capital ratio falls below a pre-determined threshold. Typically this trigger is either at 5.125% or 7% CET1, depending on the national regulator. Once this trigger level is hit, the notes are automatically converted into equity or written down in full, depending on the terms of the individual bond documentation.

Second, regulators require bank capital to be permanent (i.e. perpetual) in nature, so AT1 bonds have no final maturity, and instead they are callable with regulatory approval. AT1s typically have ‘non-call’ periods of between five and 10 years, after which investors generally expect the issuer to call and replace the AT1s with a new issue. If the bonds are not called, the coupon resets to an equivalent rate over the underlying swap rate or government bond…

…There is another important regulatory element investors need to consider, which is that a bank’s solvency is ultimately at the discretion of its national regulator (or the European Central Bank for EU banks). If a bank runs into serious trouble, regulators can declare a Point of Non-Viability to try to protect depositors, stem the losses and prevent contagion.

We have seen that European banks generally have CET1 ratios in the mid-teens; we think it is highly unlikely any regulator would let a bad situation carry on long enough for a bank’s CET1 ratio to fall to 7%, let alone 5.125%, so in practice it is likely that a bank’s Point of Non-Viability would occur with capital levels higher than the trigger levels embedded into AT1 securities. This is why it is important for investors to pay attention to the individual capital requirements set by national regulators for each bank, and to scrutinise annual stress tests very carefully.

7. Doug Leone – Lessons from a Titan – Patrick O’Shaughnessy and Doug Leone

Patrick: [00:10:54] I spent a lot of time talking to your partner, Ravi, about demons and the demons that are in certain people for whatever reason and the ways that those demands can motivate or drive entrepreneurial-type people to enormous success. And one of the things that Ravi told me was that you are extremely good at sussing out a person’s core motivation via listening, ironically, given Don’s note to you. And I’d love you to talk a bit about that skill and why you think it’s so important to understand someone’s core motivation.

Doug: [00:11:28] First of all, what we look for founders, we also look for Sequoia partners, investors, young people. The same set of traits use the word insufferable, use the word he doesn’t listen, she doesn’t listen or he’s belligerent, she’s belligerent. Those that other people may view as a negative, we actually view as a positive because in order to get something done in life, you can’t just walk down Main Street and be a sweetie pie.

We look for outlier people, whether it’s founders or investors, and outlier people do extraordinary things. Outliers. What do I mean by that? Extra-driven for whatever reason. Maybe Daddy told them they weren’t good enough and they want to show Daddy how good they are. Maybe they have a twin brother. Twins have a way of competing with one another. They love one another, but they compete one another. Maybe they failed miserably in their first startup, they’re embarrassed and so on. So we look for those things.

And sometimes, believe it or not, genetics. I’ve actually met some people that I’m now convinced they were just wired that way. And I try to look for that for the simple reason that I view that to be the greatest advantage, but could be the greatest weakness, if not channeled appropriately. So want to look for it to see if it’s there because I like to be it there, then I look to see what it is and whether it’s on the right side of this good versus bad trait. And thirdly, because once we understand it and then that’s a good side, then how do we channel it, complement and make sure this incredibly wonderful insecure, scared because that’s what we all are when we’re coming up, how do we help them as if we were their brothers to achieve maximum type of success.

So I dig for that. I just really want to understand what makes this person tick. And to me, the greatest question is why? Why, why, why? When someone says I was recruited by. I hear, I was lazy-ass sitting down. I got a call from a recruit. I have nothing better to do. I got suck to listen to something. I got sweet-talked, then I talked to a company that made me an offer. I wasn’t too happy on my job or a little bored and I went.

To me, that’s what I was recruited by sounds like. A converse of that, of course, is I was sitting on a job, I saw an opportunity in a market segment that I didn’t know existed. I call 7 or 8 companies. I realize this is the leading company. I call the companies or I found a way to get a meeting. I sold my way in. I got an offer. I negotiated. I took a job and I went. Wow, what an answer. So those are little things I look for when I interview people.

Patrick: [00:14:18] In addition to asking why in lots of different ways, are there other favorite questions or topics that you find yourself returning to over and over again as you’re getting to know people?

Doug: [00:14:28] I want to know the upbringing. I want to know what kind of kids they were, their journey through life, their maturation through life. I’d love to ask whether they have a sibling, to describe 3 adjectives for their sibling, their close sibling and 3 adjectives that describes them by comparison. I don’t really care about the sibling, but you start learning things.

I love asking the setup question of where would you get your best reference. And they’re eager to tell you that complete set of question because the next question is, where would you get your worst reference and why? And again, I’m not looking to nail anybody. We’ve all had journeys that are up and down, very few of us have had a linear journey. But just understanding, looking for self-awareness because self-awareness means breaking problems down to first principles and meaning using your experience to solve a new problem. While we love best athletes, if we find best athletes with a little of experience and first-principle thinking, that’s a home run, and we look for that…

…And the trick for me, I never understood when the father is an alcoholic or as an abuser and the son becomes an abuser because I have to tell you, I’ve had some tough rides, but I made a promise to myself that if I ever became someone, I would not do one to others as I was done to. I thought it was disgusting. I thought it was very upsetting. And when you’ve come to Sequoia, when I was running it, I made sure everybody respected the people that feed us. You better put your plate away, you better say thank you and so on because it starts at the foundational layer.

And if you do that right, then the culture starts being right. And if you share your winnings and if you just don’t talk to talk, we are a team, we are this. No, you have to share the dough appropriately. And in my case, I never called us a family. I thought family is bulls***. I’ve got members in a family I have to endure forever. Can’t get rid of it.

I tell people, we are high-performance and pick your noun. We’re a performance team. If you don’t believe in sports, production, a movie and maybe the investors are the actors, maybe the investors are the goal scorers. But you know what we need, we need trainers. We need coaches. If you’re a movie, we need a director, a producer or a makeup artist. And it takes everybody. And so just believing internally, that’s what we need, and incorporating into the investment business into what I think is the most fabulous culture of any partnership in the investment area is really our secret sauce…

…Patrick: [00:28:29] Speaking of your passion for go-to-market, describe what you’ve seen the very best at that do consistently? Is it working from the product towards the customer’s need? Is it working backwards from the customer? Are there other things that you’ve seen and recommend over and over again of the very best of this?

Doug: [00:28:46] So I’ve actually have given a name for this cycle called the merchandising cycle. And I explained this to founders. It starts with product management. What exactly are we building? If truth be known, it starts with vision. But if the vision is wrong, we’re all going home, assuming we’re some place in a ballpark.

It’s not some product management, what are we building? To product marketing, how do we position it? How do we tell the story? How do we have the 3 words for describing what we do? How do we have the 30 seconds, 2 minutes? And everybody can do with 10 minutes. Very few people can do the 3 words. And then how do we do the demand gen? How do we do the sales? And wherever that cycle is broken, it looks like a bad salesperson. This guy can’t sell.

Actually, the truth of the matter is if you’ve got product market fit, even shady salespeople can sell. When we first invested in ServiceNow, we had the BT prior to Frank Slootman coming in, in sales, and they were selling like crazy. So that was my lesson. And so for me as a Board member, I have to debug the merchandising cycle.

Product can’t sell. Why? There’s not enough leads. Oh, well, I know to fix that. Why don’t we get some more BDRs. Then you can talk to the BDR guys. Here, you can have 5 BDRs. Well, then they start fessing up. Well, it’s not really a BDR head count. It’s that the message isn’t playing right.

Well, I knew that, but it nice you admit it, let’s go back to product marketing. What’s the message? Is that the right message? Is that the wrong message? And that’s based on the product we’re building. This is the product management. And so I work very hard at debugging upstream this merchandising cycle, so we can figure out what the real problems are. And as I think about it, take these rocks out of the river so that dam water can flow as fast as possible. And once you do that and once you know that 2 or 3 sales reps can sell something and you have your first 4 or 5 sales that don’t include the CEO, those are telltale sign that you can start ramping. And so that’s what we do. That’s what I do as a Board member.

The thing I can’t do is the black magic. If you don’t have the right vision, if you’d — I’m not close to product market fit, I will tell you, Doug Leone or any other people in venture, I’m not going to help you. Black magic is reserved for founders. Everything else is mere mortal stuff. That’s what we can do. And we’re probably the very best in the world at Sequoia in doing that.

Patrick: [00:31:10] What are the components of great positioning for a product?

Doug: [00:31:15] Simplicity, crystal clearness, something a mere mortal can understand. If you can describe it and you can understand it you’re out to lunch. Singularity of purpose. When I go to the store, I buy a pencil because I want to write. I don’t want a pencil because I want to write, I scratch my back with the tip. It doesn’t work like that.

Singularity of vertical market early on because you want to be narrow. You have no resources. You’ve got to be narrow. Oh, we are chasing these 4 vertical markets. It sounds good. But in order to do that, you have to have marketing that talks for different languages for 4 markets. And maybe you have to have engineering that develops different features for me. A little company can’t do that. So be it the bull’s eye as sharp as you can and then starts to expand in concentric circles when you get your legs under you in that vertical market. That’s what I look for in position.

Patrick: [00:32:10] If you think about the, what I’ll call, mediocre positioning, you’ll know if there’s amazing positioning because you’d be able to see the things flying off the shelves. And you’ll know if there’s terrible positioning and that the danger is somewhere in the middle, like it’s kind of working. What have you done historically when you see that and you see founders start to build upstream the demand gen and the sales org is on top of mediocre positioning. That seems like a very dangerous spot for a company to be in.

Doug: [00:32:37] So keep in mind that we, as Board members, our job is to make these founders very capable and successful. You lose the founder, you lose the soul of a company. There’s no question about that, okay? And telling the founders cuts a little bit of the pinky. And you want founders with 10 fingers and 10 toes. But there are certain times where the thing is soft, the rails, that it’s worth a small piece of the pinky to get back in the right direction.

First, what I try to do instead of telling I like showing. So let me give you an example. Your VP of Marketing stinks. If I say that, it means nothing to a founder. But if I say, I’d like you to meet these 3 VP marketing from other companies. Let me tell you what happens 9 times out of 10, they come back and they say, “Holy s***, the guy we have or the gal we have is nothing like this guys.” So try to show, not tell. Build trust, which doesn’t get build day 1. It really gets build with the first time to see founders in a pension. He understands you’re there to help them out.

So once you have trust, which is really the foundational layer, it’s the grease that makes all business runs. And once the founder understands maybe of a little of experience that complements his incredible talent. And once you show the founder without telling the founder, and once in a while, you have to tell because maybe you don’t have the time to show, but you better do that once a year.

It’s very rare. That’s what you do. Those are the actions that you take. And you want to come out of that in the win-win. You want to come out of that with an enlightened founder who’s extremely happy and better in his role rather than having achieved your goal of a new VP of Marketing with the founder feels like these needs were cut off.

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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. We currently have a vested interest in Microsoft. 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 19 March 2023:

1. Poignant Twitter thread on the importance of having purpose in life – Mark McGrath

This is a story about my dad. My dad grew up the youngest of four siblings in Quebec. He, his siblings, and my grandparents moved to Vancouver in the 70s, and my uncle opened a tile store. My dad worked for him for a while, then eventually opened his own store.

He was a relentless entrepreneur and a good father. He was shrewd and pennywise. I used to joke that he would split 2-ply toilet paper to save money. But he was also a savvy investor, and he did well in his business.

He didn’t care about tile and saw the business as a means to an end – a way to build wealth and retire. He was laser-focused on this goal.

He was fit, active, and a traveller. He was a scratch golfer and swam 80 laps at the pool three times a week. He was also a black belt in karate and extremely disciplined…

…One day he told us he had sold his business and was retiring. We were thrilled. All he wanted to do was retire so he could keep travelling, golfing, swimming, and enjoying his life. He booked a two-month trip to Asia to celebrate. He was 58. And then it all went downhill.

Within a month of returning from his trip, he was back working for the guys he sold his store to. He didn’t need the money – he just missed his store and his friends. His best friend was his first employee – a man he had hired 30 years earlier. This worked out for a while.

But slowly, he started to change. After a few months of golfing near-daily, he got bored. And then he got depressed. He changed…

… Then he told me, “your father is dead.” I collapsed and remember only that I kept saying, “I had so much more to tell him”.

He had rented a car for some reason, drove it to the middle of the Lion’s Gate Bridge in Vancouver, turned on the hazard lights, and got out. Then he jumped. Two cyclists – one on the bridge, and one down below on the seawall – called it in…

…What I think happened is that my dad’s business became his identity. He was the tile guy. He was the guy that sponsored all of our sports teams.  In a booming town, he was the guy you went to when you needed tile. He was the tile guy.

And when he sold his business, he stripped himself of his identity. Now he was a nobody. He lost his purpose, the very thing that made him who he was.

2. GPT-4 – OpenAI

We’ve created GPT-4, the latest milestone in OpenAI’s effort in scaling up deep learning. GPT-4 is a large multimodal model (accepting image and text inputs, emitting text outputs) that, while less capable than humans in many real-world scenarios, exhibits human-level performance on various professional and academic benchmarks. For example, it passes a simulated bar exam with a score around the top 10% of test takers; in contrast, GPT-3.5’s score was around the bottom 10%. We’ve spent 6 months iteratively aligning GPT-4 using lessons from our adversarial testing program as well as ChatGPT, resulting in our best-ever results (though far from perfect) on factuality, steerability, and refusing to go outside of guardrails.

Over the past two years, we rebuilt our entire deep learning stack and, together with Azure, co-designed a supercomputer from the ground up for our workload. A year ago, we trained GPT-3.5 as a first “test run” of the system. We found and fixed some bugs and improved our theoretical foundations. As a result, our GPT-4 training run was (for us at least!) unprecedentedly stable, becoming our first large model whose training performance we were able to accurately predict ahead of time. As we continue to focus on reliable scaling, we aim to hone our methodology to help us predict and prepare for future capabilities increasingly far in advance—something we view as critical for safety…

…In a casual conversation, the distinction between GPT-3.5 and GPT-4 can be subtle. The difference comes out when the complexity of the task reaches a sufficient threshold—GPT-4 is more reliable, creative, and able to handle much more nuanced instructions than GPT-3.5.

To understand the difference between the two models, we tested on a variety of benchmarks, including simulating exams that were originally designed for humans. We proceeded by using the most recent publicly-available tests (in the case of the Olympiads and AP free response questions) or by purchasing 2022–2023 editions of practice exams. We did no specific training for these exams…

…We also evaluated GPT-4 on traditional benchmarks designed for machine learning models. GPT-4 considerably outperforms existing large language models, alongside most state-of-the-art (SOTA) models which may include benchmark-specific crafting or additional training protocols:..

…GPT-4 can accept a prompt of text and images, which—parallel to the text-only setting—lets the user specify any vision or language task. Specifically, it generates text outputs (natural language, code, etc.) given inputs consisting of interspersed text and images. Over a range of domains—including documents with text and photographs, diagrams, or screenshots—GPT-4 exhibits similar capabilities as it does on text-only inputs. Furthermore, it can be augmented with test-time techniques that were developed for text-only language models, including few-shot and chain-of-thought prompting. Image inputs are still a research preview and not publicly available…

…Despite its capabilities, GPT-4 has similar limitations as earlier GPT models. Most importantly, it still is not fully reliable (it “hallucinates” facts and makes reasoning errors). Great care should be taken when using language model outputs, particularly in high-stakes contexts, with the exact protocol (such as human review, grounding with additional context, or avoiding high-stakes uses altogether) matching the needs of a specific use-case.

While still a real issue, GPT-4 significantly reduces hallucinations relative to previous models (which have themselves been improving with each iteration). GPT-4 scores 40% higher than our latest GPT-3.5 on our internal adversarial factuality evaluations:…

…GPT-4 can also be confidently wrong in its predictions, not taking care to double-check work when it’s likely to make a mistake. Interestingly, the base pre-trained model is highly calibrated (its predicted confidence in an answer generally matches the probability of being correct). However, through our current post-training process, the calibration is reduced…

…GPT-4 poses similar risks as previous models, such as generating harmful advice, buggy code, or inaccurate information. However, the additional capabilities of GPT-4 lead to new risk surfaces. To understand the extent of these risks, we engaged over 50 experts from domains such as AI alignment risks, cybersecurity, biorisk, trust and safety, and international security to adversarially test the model. Their findings specifically enabled us to test model behavior in high-risk areas which require expertise to evaluate. Feedback and data from these experts fed into our mitigations and improvements for the model; for example, we’ve collected additional data to improve GPT-4’s ability to refuse requests on how to synthesize dangerous chemicals.

GPT-4 incorporates an additional safety reward signal during RLHF training to reduce harmful outputs (as defined by our usage guidelines) by training the model to refuse requests for such content. The reward is provided by a GPT-4 zero-shot classifier judging safety boundaries and completion style on safety-related prompts. To prevent the model from refusing valid requests, we collect a diverse dataset from various sources (e.g., labeled production data, human red-teaming, model-generated prompts) and apply the safety reward signal (with a positive or negative value) on both allowed and disallowed categories. 

Our mitigations have significantly improved many of GPT-4’s safety properties compared to GPT-3.5. We’ve decreased the model’s tendency to respond to requests for disallowed content by 82% compared to GPT-3.5, and GPT-4 responds to sensitive requests (e.g., medical advice and self-harm) in accordance with our policies 29% more often…

…Overall, our model-level interventions increase the difficulty of eliciting bad behavior but doing so is still possible. Additionally, there still exist “jailbreaks” to generate content which violate our usage guidelines. As the “risk per token” of AI systems increases, it will become critical to achieve extremely high degrees of reliability in these interventions; for now it’s important to complement these limitations with deployment-time safety techniques like monitoring for abuse…

…Like previous GPT models, the GPT-4 base model was trained to predict the next word in a document, and was trained using publicly available data (such as internet data) as well as data we’ve licensed. The data is a web-scale corpus of data including correct and incorrect solutions to math problems, weak and strong reasoning, self-contradictory and consistent statements, and representing a great variety of ideologies and ideas.

So when prompted with a question, the base model can respond in a wide variety of ways that might be far from a user’s intent. To align it with the user’s intent within guardrails, we fine-tune the model’s behavior using reinforcement learning with human feedback (RLHF).

Note that the model’s capabilities seem to come primarily from the pre-training process—RLHF does not improve exam performance (without active effort, it actually degrades it). But steering of the model comes from the post-training process—the base model requires prompt engineering to even know that it should answer the questions.

3. Bank Runs, Now & Then – Ben Carlson

Silicon Valley Bank, the 16th biggest bank in the country, was closed on Friday. It was the second-biggest bank failure in U.S. history…

…There is a lot to this story but it really boils down to an old-fashioned bank run. A flood of withdrawals from depositors destroyed the bank.

If everyone with a Planet Fitness membership showed up at the gym at the exact same time there would be chaos at the squat racks. It would be impossible for anyone to work out and the gym model wouldn’t work.

The same thing applies to banks. If everyone goes to get their money out on the same day, it’s going to be hard for a bank to survive…

…The SVB ordeal caused me to revisit my old copy of The Panic of 1907 by Robert Bruner and Sean Carr.

It’s a wonderful account of one of the biggest and most influential financial crises in history.

The Panic of 1907 would probably be more famous if it wasn’t overshadowed by the Great Depression just a couple of decades later.

It lasted 15 months and saw GDP decline an estimated 30% (even more than the Great Depression).

Commodity prices crashed. Bankruptcies exploded. The stock market fell 50%. Industrial production dropped by more than at any time in history up to that point. The unemployment rate went from 2.8% to 8%.

Trust in the financial system went out the window as banks failed left and right. In October and November of 1907 alone, 25 banks and 17 trust companies went under…

…Bruner and Carr laid out 7 reasons the Panic of 1907 was a perfect storm for bank runs and a massive financial crisis:

1. Complexity. Complexity makes it difficult to know what is going on and establishes linkages that enable contagion of the crisis to spread.

2. Buoyant growth. Economic expansion creates rising demands for capital and liquidity and the excessive mistakes that eventually must be corrected.

3. Inadequate safety buffers. In the late stages of an economic expansion, borrowers and creditors overreach in their use of debt, lowering the margin of safety in the financial system.

4. Adverse leadership. Prominent people in the public and private spheres wittingly and unwittingly may implement policies that raise uncertainty, thereby impairing confidence and elevating risk.

5. Real economic shock. An unexpected event (or events) hit the economy and financial system, causing sudden reversal in the outlook of investors and depositors.

6. Undue fear, greed, and other aberrations. Beyond a change in the rational economic outlook is a shift from optimism to pessimism that creates a self-reinforcing downward spiral. The more bad news, the more behavior that generates bad news.

7. Failure of collective action. The most well-intended responses by people on the scene prove inadequate to the challenge of the worst crises.

Again, not exactly like 1907 but this run on the bank seems to check all of the boxes in its own way…

…Two economists took a stab at explaining why bank runs happen and concluded they’re kind of random. Depositors are worried a financial shock will cause a lengthy liquidation so they pull their money en masse.

But what sets them off?

People being people, I guess?

4. Psychological Paths of Least Resistance – Morgan Housel

When faced with a problem, rarely do people ask, “What is the best, perfect, answer to this question?”

The more efficient question is often, “What answer to this question can I obtain with the least amount of effort, sacrifice, and mental discomfort?”

The psychological path of least resistance.

Most of the time that’s fine. You use a little intuition and common sense and find a practical answer that doesn’t rack your brain or bog you down with details.

Other times the easy answers lead you down a nasty path of misunderstanding, ignorance, and blindness toward risk.

A few paths of least resistances that everyone is susceptible to at some point:

1. The quick elimination of doubt and uncertainty.

Most people could not get out of bed in the morning if they were honest about how much of their future is unknown, hangs by a thread, or can be pushed in another direction by the slightest breeze. The solution is to eliminate doubt and uncertainty the moment they enter your head.

Uncertainty feels awful. So it’s comforting to have strong opinions even if you have no idea what you’re talking about, because shrugging your shoulders feels reckless when the stakes are high.

Life is complex, complex things are always uncertain, uncertainty feels dangerous, and having an answer makes danger feel reduced. It’s an easy path of least resistance.

If you were an adult in 2000 you probably had at least some vision of what the future would look like. Maybe even a vague vision of the next 20 years. But everyone was blind to 9/11, the 2008 financial crisis, and Covid-19 – the three risks that were both massive and unpredictable.

Then when those events happened people quickly moved to eliminate the uncertainty they brought.

Terrorist attack just happened? It’s definitely going to happen again, soon.

Recession coming? It won’t affect my industry and will be over by Q4 and interest rates will bottom at 3.42%.

Pandemic arrived? Two weeks to slow the spread.

No matter how wrong these answers might be, they feel better than saying, “I have no idea what’s going to happen next.”…

…5. The desire to supplant statistics with stories.

“People would rather believe than know,” said biologist E.O. Wilson.

I think another way to phrase it is that people desire stories more than statistics. They need a story they can tell themselves, not just a fact they can memorize.

Part of that is good. The gap between what works in a spreadsheet and what’s practical in real life can be a mile wide. This usually isn’t because we don’t know the statistics. It’s because real-life stories are so effective at showing us what certain parts of a statistic mean.

Part of it can be dangerous, when broad statistics are ignored over powerful anecdotes.

Government agencies published literally thousands of different economic data points, everything from unemployment to GDP growth to the historical cost of chicken legs, bone-in. It’s all free and easy to read.

How often do those data sites change average, ordinary people’s opinions about the economy?

It rounds to never.

What changes people’s minds and reaffirms their beliefs are conversions they’ve had with people close to them, social media, and cable news. Each is very good at telling stories especially when they provoke emotion or are easy to contextualize to their own lives.

When confronted with a pile of dull facts and a pile of compelling anecdotes, the anecdotes are always the path of least resistance for your brain to cling to.

5. TIP533: How The Fed Went Broke w/ Lyn Alden – Stig Brodersen and Lyn Alden

[00:01:28] Stig Brodersen: Well, thank you for saying so Lyn, and let’s just jump right into it. Today, I would like to talk about how the Fed went broke, but before we do, and perhaps to sort of like create a foundation for everyone, perhaps we can zoom out and if I can ask you to explain what is on the assets and liability side on the Fed balance sheet, and then perhaps we can talk about how that is similar to how a commercial bank running their balance sheet.

[00:01:53] Lyn Alden: Sure. So basically in a lot of regard, the Fed is very similar to a commercial bank. I mean, there are very important exceptions where it’s not, but in terms of the over, like arching details, it’s actually pretty similar. So if you look at a commercial bank for a second, they have assets and liabilities.

[00:02:08] Lyn Alden: The assets exceed the liabilities. That’s an important part of their solvency and their assets generally pay higher interest rates than their liabilities. Kind of the purpose of a bank is to, you know, borrow money at cheap rates and lend money with a little bit more risk and a little bit more duration at higher rates, as well as collecting fees and things like that along the way.

[00:02:27] Lyn Alden: And so for a typical bank, their liabilities are mainly their deposits. So basically when you deposit money in a bank, that’s your asset. It’s their liability and interest rates. They’re generally pretty. On the bank asset side, depending on the type of bank it is, they do mortgages, they do business loans, and they do credit card lending.

[00:02:47] Lyn Alden: They do all sorts of different types of lending, and those are ones that are generally a little bit riskier, higher duration, but they pay higher interest rates and so they can absorb some, you know, small percentage of defaults, build positive capital, pay [00:03:00] dividends, you know, fund their operations and maintain positive equity and positive capital.

[00:03:05] Lyn Alden: When you look at a central bank, it’s very similar, but there’s a couple different categories for their assets and liabilities. So their liabilities are, One bank notes, right? So physical cash and circulation is a liability of that country Central bank, and those are obviously 0% yielding assets, right? If you hold a dollar bill or a physical euro, you’re not getting paid interest on this.

[00:03:26] Lyn Alden: So that’s an obvious already good start for them, right? They have 0% liabilities there, but they have other liabilities that, for example, consists of bank reserves. So much like how we deposit money at a bank, and that’s our asset and their liability. Banks have to deposit their cash, their spare cash at the central bank, and that’s an asset for the bank, and it’s a liability for the central bank.

[00:03:47] Lyn Alden: And just like how a bank pays interest, a central bank also in, in many environments does pay interest on those reserves. And the reason they do that is because it’s an important part of how they manage their short-term interest rates. It basically presents a floor, right? If you can put reserves in the central bank, You know, and get, say 5% interest on it, there’s no reason why you would lend to anyone else at below 5% because you’re just taking on more risk and for less return.

[00:04:15] Lyn Alden: Right. And so that’s one of their important policy tools. And then there are other liabilities they can do, like reverse repos and things like that. They get more complex and some of those do pay interest. So that’s the central bank’s liability side. On the asset side, it actually looks [00:04:30] pretty similar to a commercial bank.

[00:04:31] Lyn Alden: They have things like treasuries, you know, the government debt of whatever country they operate in. So those pay interest. They also often have mortgage backed securities, right? So they have mortgage exposure. Obviously, these deals would differ around the world, but for example, a Federal Reserve has a lot of mortgage backed securities.

[00:04:46] Lyn Alden: These also pay interest. And then in some countries they’ll have things like corporate debt, or they’ll have things like equities. Those are generally considered less traditional types of assets for central banks to hold. But you see some like Japan kind of going that route. And sometimes, like the Fed and others will do that temporarily during crisis.

[00:05:02] Lyn Alden: Things like corporate debt. And in most contexts, the federal reserve’s assets are bigger than their liabilities and they pay higher interest rate than their liabilities. And it will then differ from jurisdictions. But usually the central banks operate like utility where it has to pay its excess profits back to the government.

[00:05:21] Lyn Alden: It doesn’t just keep building capital like a commercial bank would. Although in some jurisdictions they actually, you can publicly hold, you know, shares of a central bank and they will, you know, they could pay dividends, they could do things like that. Look at the Federal Reserve, so it’s not publicly held, but it is held by banks.

[00:05:38] Lyn Alden: They basically pay a small dividend to their owners. They pay their operating expenses, and then they have to send the rest of their profits back to the treasury. Right? And so it’s actually a source of income for the treasury, and it kind of makes it so that any sort of treasury is held by the Fed are effectively interest free because they are paying interest on them.

[00:05:55] Lyn Alden: But all these, a lot of these profits are getting sent right back to the treasury. The challenge in [00:06:00] recent months, really ever since September, is that the Federal Reserve increased interest rates so quickly and so significantly, and for the first time they got above the prior cycles high in terms of interest rates or at least, you know, the first time in, in decades we’ve had this kind of declining trend of lower highs in terms of interest rates, but they actually got way above that.

[00:06:18] Lyn Alden: And so they’re actually, their liabilities pay higher interest rates than their assets. And so obviously their bank notes are still paying zero, but their other areas, their bank reserves and their reverse repos in the fed’s case are paying a higher interest rate than their treasuries and their mortgage backed securities that in many cases are a longer duration.

[00:06:36] Lyn Alden: They’re fixed rate, they’re not adjusting upwards. They hold them from years ago, and so they have a mismatch. And so one is there, they’re no longer profitable. They’re not sending any more remittances to the treasury, and two, if they were a normal commercial bank, they would be on the verge of bankruptcy.

[00:06:51] Lyn Alden: So they’re months away from having negative, tangible equity, which is a normal bank would be bankrupt, but because of the central bank, they get to that. That’s where they have a very big difference. They basically get to just put a placeholder there that kind of is like an I O U. And so in the future, if they’re ever profitable again, then before sending more money to the treasury, They get to pay themselves back.

[00:07:13] Lyn Alden: So basically they’re losing money. They’re going in towards negative, tangible equity, but they’re filling that negative equity gap with IUs on their future income, which of course, for any private entity would be red flags over the place. Absolute catastrophe. You wouldn’t touch it with a 10 foot pole, [00:07:30] but it’s different if you’re the central bank.

6. Whose Fault is it Anyway – Michael Batnick

It has been 872 days since a bank failed in the United States. This was the longest streak on record. We’re now at day zero. Silicon Valley bank went down on Friday. Signature Bank last night. These are the second and third largest bank failures in history behind Washington Mutual during the GFC.

People are scared, mad, and looking for someone to blame. How did this happen, and whose fault is it anyway?…

…Blame the Fed

Three years ago, the fed appropriately took interest rates to zero as an economic meteor slammed into the Pacific Ocean. But two years later with the economy reopened and inflation running north of 7%, rates were still at zero. This made no sense then, and it makes less sense looking back on it. The fed was late to respond, and they compounded the problem by going from too easy for too long to too tight too fast. We haven’t seen a tightening cycle like this in the last fifty years.

A major thing that we didn’t anticipate as a result of these historic interest rates, at least I didn’t, were the ripple effects it would have at banks. According to Marc Rubinstein:

Between the end of 2019 and the first quarter of 2022, deposits at US banks rose by $5.40 trillion. With loan demand weak, only around 15% of that volume was channelled towards loans; the rest was invested in securities portfolios or kept as cash.

Banks invest their deposits in short-term bonds, for the most part. But even short-term bonds can have large unrealized losses when interest rates spike until the bonds mature. And bonds that have more interest rate risk are even more susceptible to large losses. All told, banks are now sitting on roughly $600 billion of losses in what are supposed to be among the safest instruments in the world. All because the fed went too far to fast.

Prior to aggressively raising rates, the fed kept interest rates at zero for too long which spurred excessive risk-taking. Venture capital was at the epicenter of this. Everything got funded in 2021 at a speed and size the likes of which the industry had never experienced. Who’s to blame here? Is it the fed for stoking the flames of speculation, is it the LPs for flinging money at venture funds, or is it the venture capitalists for saying yes to everything? The answer is yes.

7. What’s Going On With Treasuries? Silicon Valley Bank And The Incoherence Of The Federal Reserve’s (Lack Of) An Interest Rate Policy This Week – Nathan Tankus

The essential issue seems to be not so much “financial contagion” from the failure of Silicon Valley Bank (that’s how systemic risk is ordinarily understood.) Rather, it’s the implications of the Federal Reserve’s actions over the weekend. It is strange to see the Federal Reserve launch a facility commonly interpreted as a “crisis” facility using its 13(3) powers in the current economic situation(check out my Silicon Valley Bank piece as a refresher here). That’s because unemployment is low, inflation has been high and the Federal Reserve is raising interest rates. One interpretation of this event, consequently, is that the Federal Reserve is going to be lowering interest rates.

Yet, inflation remains above the Federal Reserve’s target. It would be quite an extraordinary situation in these circumstances to see the Federal Reserve lower interest rates at a time of elevated inflation. You can see the dilemma. Government securities dealers — those people who buy and sell treasuries every day — are as confused and unsure as you are about which way interest rates will go, in these circumstances. When bond traders are confused and unsure about which way interest rates will be going to this degree, treasury market issues result…

…The other layer to this are those “treasury liquidity strains” this all started with. When non-experts hear about “liquidity strains” in the treasury market, they tend to assume that means the U.S. treasury has to offer higher interest rates to sell securities. However, that often isn’t the case. In fact, these periods tend to coincide with falling treasury interest rates. In March 2020, liquidity in treasury markets worsened. Some short maturity treasury securities even experienced negative money interest rates. That means the situation was so uncertain, many actors were willing to pay such a premium that they would get less money back when the security matured then they paid for it. After all, losing a bit of your money is better than losing it all. To be clear, I’m not talking about “inflation adjusted” amounts. I mean literally, they paid 100 dollars, and got back 98 dollars.

So if “liquidity strains” don’t necessarily mean rising interest rates, what do they mean? They mean the price at which you can buy a treasury is further away from the price at which you can sell a treasury…

…Normally, bond traders have a pretty good sense of where interest rates are going to go. They are not always right (by any stretch). But this usually does not impact the differences between buying and selling prices that much. One way to think about this is, when bond traders are wrong they tend to be wrong slow enough and gradual enough that there is time for them to “catch up”. And generally, for the past 30 years if not more, when they are really wrong it’s obvious. So both buying and selling prices really jump. When Lehman Brothers collapsed, everyone understood short term interest rates were going to go to zero and stay there for a while. If inflation had been 6% when Lehman collapsed, the treasury market may have faced the same problems it’s facing now.

Faced with this uncertainty, the treasury market is getting less liquid. That means selling prices and buying prices are diverging even though interest rates are overall declining. But remember those bets that so many government bond market participants made? This is where they get hammered twice. Not only are interest rates going down when they expected interest rates are going up. In addition, “bidding interest rates” and “selling interest rates” are diverging, when these same bets often assume that the treasury market is liquid. In other words, embedded in these bets about the direction of interest rates are bets about the differences between bidding interest rates, and selling interest rates. In short, they also bet the spread would be small when the spread has been getting larger.

The final component of this on my radar is something that financial economist Daniela Gabor said over on Twitter:

“Why would you sell securities you can monetise at the Fed for par value?” This returns us to a more direct impact of the Silicon Valley Bank failure and the Federal Reserve response than the possible implications of that response for interest rate policy. The Bank Term Funding Program (again read Tuesday’s piece for the details) provides terms that are so overwhelmingly generous. That calls into question why any chartered bank (“depository institution”) who is allowed to access the BTFP would be selling treasury securities right now. What’s the point? You get a better deal handing it over to the Fed as security for a loan.

This makes sense for them individually, but it means suddenly trillions of dollars of treasury securities are not available for sale. Many fewer treasury securities “in circulation” must be having an impact on this liquidity situation. These banks would need a selling price that is much higher than the buying price, in order to be willing to sell their securities. This is a fluid and volatile situation, where the news coming out is confusing and fast paced. As a result, it will be months, maybe even years, before we have a good idea of how big the direct impact of this quasi-emergency facility was. Some other elements of this piece may be subject to revision once we learn more. But this is how I think the “state of play” looks today…

…It is no secret I have not been a fan of the Federal Reserve’s interest rate increases. However, if you are going to continue them then, when you announce the use of what is normally seen as a crisis facility, that should come with clear explanations of the implications for interest rates. Indeed, it’s maddening to even have to say this! Forward guidance is supposed to be what the modern Federal Reserve is all about! If they had said “interest rates will keep on increasing as usual, though we probably will be doing smaller interest rate hikes for the next three months”, then the implications of this situation would be clear. Treasury security interest rates would have rapidly adjusted without impairing treasury liquidity.

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

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Here are the articles for the week ending 12 March 2023:

1. Bank Execs on SVB Fallout: ‘2,000 Times Better If a Buyer Comes In’ This Weekend – Amir Efrati, Jackie Reses, Kristine Dickson, and Oren Zeev

The Information: Let’s start with what’s happening now after the FDIC took over SVB.

Reses: In any bank failure, the FDIC becomes the resolution authority regardless of who the regulator is for a bank. The FDIC comes in and takes over and they actually show up at a bank and they start working with a group of bank employees that continue to be employed and help them start to add up and bring forward liquidity positions and they will start to create an orderly disposition process immediately, which is why they publish that note that they will start managing the process on Monday.

The Monday note is very important because they’re trying to provide people with assurances that at least up until the FDIC insured amount, which is $250,000 per account, $500,000 for a joint consumer account, they will insure and get that money actually paid out so that they could try to insure an orderly set of operations for companies. Now, it doesn’t mean that the assets have matched the liabilities and they need to go through and make sure that the bank can pay out its depositors and see what’s left over.

And so there actually is a water flow that again is in their playbook. It’s [Federal Home Loan Bank] payments, administrative expenses, they go through their insured deposits. And then they do this math of what’s available to pay out based on the liabilities they have outstanding. And that process could take some time.

That raises a lot of questions to your point about what that means for Monday, for payroll, for next week. And on that, unfortunately, there’s not a great answer because it depends on the immediate liquidity situation and their ability to actually get wires, ACH’s processed throughout the week. And so they will be working 24-7, including this weekend, on making that happen.

Typically, what you’ve seen in history is that banks are taken over on Thursdays or Fridays so that the FDIC can go in, work the weekend, and then present on a Monday morning, before an opening, how they are going to manage and to whom they are managing and creating liquidity for. And so I wish I had better news for many companies out there, but there is going to be disruption in how money goes out, how wires go out, how payroll goes out. And so I think that’s the biggest problem everyone’s dealing with. And unfortunately there’s no good answer here around what that timing is going to be and what the balance sheet looks like on the inside.

Kristine Dickson: Prior to joining Lead I have spent the last 10 years helping to manage the wind down of the Lehman Brothers estate. And if those in the clock can even believe that Lehman went under in 2008 and no it is still not done. And yes it still has hundreds of millions of dollars left to distribute to its creditors. So, as Jackie said, for unsecured creditors, it can take some time. But I do want to provide some assurances that the regulators today and this weekend will be laser focused on protecting all of SVB’s depositors and customer assets. So this weekend will be a frenzy of activity. There will obviously be more clarity on Monday, but if history is any guide, what the regulators have preferred to do in the past is to merge failed lenders with larger and more stable institutions.

And while SVB is the second largest failed lender in U.S. history, the first was Washington, Mutual, Wamu, which the regulators orchestrated in a sale to J.P. Morgan Chase. So again, there’s more clarity to come on Monday. We don’t know exactly how they’re going to work it out but depositors will be top of mind for the regulators all weekend…

…The Information: If there is a buyer does that free up the uninsured deposits a lot faster?

Dickson: It is 2,000 times better if a buyer comes in and tries to continue the work of the bank as it is as opposed to having the FDIC attempt to liquidate the assets and then figure out the order of priority and the waterfall and then try to distribute those assets later. It is a million times better to go that direction. So that is what they will be focused on this weekend.

There was also a question about why didn’t that already happen? I think, as Jackie had said, trying to understand what it is a buyer would actually be buying would be easier once the bank is now taken over by the FDIC. They have the weekend to actually pour through the books and do the appropriate diligence to actually understand it. So I think it’s actually, once the bank gets to this point, one would expect that all the buyers would sit it out and wait for the regulators to come in and then start talking seriously. So hopefully that’s what’s happening…

…Dickson: The issues that happened at SVB and really at Silvergate, behind the scenes there’s bank balance sheet management issues, every bank faces the challenge of trying to align its deposits, which can grow and shrink with little to no warning with their investments and what they do with those deposits. And in February, the regulators put out a report that says that U.S. banks have an aggregate over $600 billion of unrealized losses on their balance sheets. That means there may be some other banks out there that have these looming issues if their deposits go down in some steep way, the way that SVB and Silvergate’s did.

Now the reasons they went down at SVB and at Silvergate, may be very specific to those banks. at Silvergate, it was crypto winter and FTX contagion. And at SVB, it had its own reasons. But the underlying issue of just bank balance management issues, is it’s out there more broadly. So it’s something that folks need to keep an eye on and think about as you’re picking bank partners…

...The Information: To what extent did venture capitalists spark this run on the bank?

Dickson: At its heart, it was a balance sheet and liquidity management issue, sort of a boring issue in the tech world, but they took in deposits and they had in 2021, they were awash in deposits during the height of the tech boom. They had excess deposits that they need to invest.

And ideally, again, as I said earlier that the bank’s challenge is to manage those deposits in line with how they manage their investments, both for yield and for duration. And for whatever reason in 2021, SVB took a bet and they invested $90 billion—

Zeev: I have the vantage point of someone who was in that situation 24 hours ago. And I do think that I and others did play a role in encouraging other companies to move their money. It’s not because I had any knowledge into the balance sheet or did any rigorous analysis. It’s because I’m not in the business of trying to now evaluate the balance sheet of Silicon Valley Bank. I don’t care. I care about my companies. Even if I think that the risk is minuscule, even if I think the risk is less than 1%, why take it? There’s zero downside in moving the money.

Dickson: I don’t think I’d blame the VCs. The reality is that [SVB] had set up their investment portfolio to be super long dated. Then as [interest] rates shot up super quickly, I mean up 450 basis points in 18 months, a gigantic long-dated investment portfolio shrank in value. At some point the piper was going to come calling. So it maybe hastened that event happening, having the VCs sort of talk it up. But at some point it seems like that was going to come.

2. Irakli Gilauri, is Georgia Capital a chance to invest in quality? – Tilman Versch and Irakli Gilauri

Irakli, let us jump a bit back to the 1990s, the early 1990s. We both were a bit younger then and the world was a bit different then. Georgia just came out of the post-Soviet time, and as I read your biography, I found out that you were studying in the late 1990s in Ireland and in London and learned investing and banking there. But how did you come interested in banking and investing and how was Georgia in the late 1990s or the early 1990s?

[00:02:45] Irakli Gilauri: So, very interesting times. I was very young back in ‘90s when Soviet Union collapsed and it was interesting to observe how the country lost nearly 75% of the GDP. You can imagine that there was no water, no electricity, no roads, roads were collapsing, no eating. Even it was difficult to communicate over the telephone. And I lived as a teenager, I lived in those times and in ’93, I started my university studies at the Georgia Technical University doing business.

Back then, everybody wanted to do business because we didn’t know what the hell the business was. Because everything was owned by the government, you know, nobody knew what the banking was because it was a state-owned bank and state-owned bank was giving loans to the state-owned companies. Retail client base was not existent other than depositing money, which was a small amount of money deposit. You could not even borrow the money from the bank. So, this whole world of doing the private business was really exciting for me and for everybody in Georgia because we didn’t know… I didn’t even know what the marketing was. The word ‘marketing’ or, you know, what kind of action you need to take to sell the product. Because it was, like, all supply driven.

So, when I started my studies in ‘93 in Georgia Technical University, we had the exchange program to study language during the summer. So I applied for the program and I went there for three months and I said that, “Okay, I’m not going back now, you know, I need to stay here and study business”, because, you know, back in Georgia, with all due respect, there was no knowledge of how the business is done, or how economies were working. Because we are in a command economy basically, it was not market economy. So it was really a big eye-opener for me. And so, I applied for the University, I went to the Dean and I had very little English and I persuaded the Dean that I really, really wanted to study here. And the Dean said, “Okay. We usually don’t accept students like this, but you want so much to study that we will accept you.” So, that’s how I ended up, just really wanting to do it.

So for me, it was a game changer basically, because in a way, I was really ahead of my peers in terms of understanding how macroeconomy works, how business works, how accounting works, because there’s different type of accounting as well. But anyway, you know, how the devaluation works, etc. So it was a big difference and after two years studying in the University, I had the choice to choose the banking or management or etc. And I chose the banking because I thought it was something which Georgia really needed to move forward. And I understood that the bank is a big player in the economy. With a good bank, economic can really grow and flourish; without that, it’s very difficult. So it was my choice back then in 1996. In ‘98, I graduated from the University, I had a four year really, really exciting studies there. I’m really grateful to my luck that I ended up there…

…[00:08:01] Tilman Versch: As you had no real private banking or even market economy, so you had to build this banking system from scratch. How much were you involved in this from the beginning or was there already something built when you entered Bank of Georgia?

[00:08:21] Irakli Gilauri: So, when I started with Bank of Georgia in 2004, there were 20,000 debit cards outstanding. Credit card was not existent and debit card cost you a fortune, you had to pay $300 to get debit card. And the bank had eight ATMs. Two handful of ATMs, that was something, yeah. So the strategy was very clear, we wanted to build a retail bank, try to bring people into banking because it was all cash economy. People were using cash, they didn’t even know how to borrow money, banks were not willing to lend to retail client base. So it’s almost all focus was about corporate banks.

When I started with Bank of Georgia, we had a market share of 15%. Market cap of Bank of Georgia was less than 20 million dollars. The balance sheet was 200 million Lari, total assets. I don’t remember the penetration, but it was single digit for sure; could be below five. So total assets to GDP was probably 3% or 4%. And we started consolidating, and we started to open up the branches, we were buying the ATM etc. and we were investing in retail banking heavily. And we went in 2006 in London and we tapped the market. And that was something because we raised $150 million and it was a lot of money back then. It was a huge IPO, it was a big deal. Because we raised the capital and then we issued the Eurobond, that was another big achievement. So we grew very rapidly into retail banking and penetration started to grow, and the assets doubled, tripled in a year. Even more, sometimes we quadrupled in asset size.

So it was a penetration game. It was at very low penetration, consolidation was happening, and this kind of things will never happen now in Georgia in banking, for sure. But there are some sectors you can do where penetrations are low and you have a very fragmented market and that’s where I think that our speciality is, that’s where we can feel the market and grow. And as you know, in this $20 million market cap, we were in the $2 billion market cap in 2018 when we demerged the bank into the investment arm and in the banking. So it was a great ride and I think that fragmented sectors, especially service industry, is a very beautiful thing…

…[00:22:16] Tilman Versch: Georgia has, compared to other markets in the region and also like other developing countries, very pro-business setup. How good or easy is it to do business in Georgia in your eyes?

[00:22:27] Irakli Gilauri: So basically what we have here, is that government understands very well in order to create wealth, we need to bring the investors’ investments in because we don’t have our gas, and we don’t have internal resources, we don’t have internal savings. Investors internally are very limited so we have to be good, friendly to the investors and this is the only way we’re going to grow our GDP. And that government understands very well. That is the primary driver for Georgia to be so business-friendly and investor-friendly. And I think we are very lucky not to have oil and gas, it would be a different country and probably not very well run and managed, to be honest.

It’s my speculation basically, but government knows that we need to have a good governance and they have excellent governance, they have excellent business environment. So we are very happy to be investors here in Georgia. So that’s kind of probably the biggest comfort as well. We as Georgians participate in the building of this country. So that’s a privilege, a lifetime opportunity when you are building the new sectors, you are building new management, you’re building the new companies and you’re doing all of this in your country. These companies are helping Georgia to go forward and you participate in this. You have some small participation in the progress this country is having. It’s a great pleasure to invest here.

[00:24:29] Tilman Versch: Do you see any risk that the pro-business setup changes with political shifts in the near future?

[00:24:37] Irakli Gilauri: I don’t believe because the fall of the Communist 90s, and I’m gonna say probably not very popular thing now, I think we should let all the nations to go fully bankrupt. Because they get their act together and sometimes, we want to help them. We are good people, we don’t want to help them, there is IMF, World Bank, there’s great organizations. But basically, you are not letting the nation to learn it’s lesson and that’s what happened to Georgia in the early 90s when we lost 75% of GDP. Back then, nobody knew what Georgia was. So, we were not even part of the World Bank or IMF probably, in the beginning. 

So what happened that Georgia went bust and people realized that there’s two things why we live so badly. One is the corruption, there was a big corruption during Soviet Union and that was the main thing. And second one is socialism and communism. So the side effect we have now, left wing parties have a very, very low popularity, left-wing parties get less than 5% all together. So basically, you need to be a pro-business, pro-market in order to win the elections in Georgia. So, I do not think that any time soon we are fearing this. That is what another reason why we eradicated corruption etc. We tackled this problem was exactly because of this lesson learned in early ‘90s. That was kind of a big help to the country that we were sorting out the governance and we are actually pro-market. Now our governments are pro-market. Some people want equality and socialists and I would love to invite them to Georgia in ‘90s or late ‘80s to experience it…

...[00:56:16] Tilman Versch: Jumping from mistakes to crisis, I think we already mentioned Covid a bit, but we discussed this in the community with you because you came on to chat with us and people who are interested in this can jump into the application form below via the link to the community. So let’s think a bit about the crisis you currently have like, all the crisis we are both in from the impacts of the Russian attack on Ukraine and all the changes. What does this mean for Georgia and Georgia Capital, like, since the beginning of the year, what has changed through the attack of Russia on Ukraine?

[00:56:55] Irakli Gilauri: So Georgia being attacked before, we know what it is like in 2008. But we were lucky that the whole conflict has been resolved very quickly and we had a very brief war basically. So we, as a nation, knew what Russia is capable of. I think that people forget Georgia as it is too far away from Europe, so it’s not happening with us, it’s happening somewhere else. I think Ukraine was very close to Europe, this war was very close to Europe and that woke up the European countries. And it’s good that they woke up.

But for us, it was obviously a big shock in terms of war, next door neighbours, it’s not very pleasant, it’s not good news. But slowly, we realised and we thought it would be a big economic shock on Georgia and we had the different macro models, and we thought we would have zero growth in 2022, something -2 or -3, but we humans don’t know. We can guess something but it’s difficult to know what would happen. That’s why it’s a good thing to live one day at a time, not to worry too much about the future. Anyway, we realised that a lot of the region has changed, the economy of the region changed. So if you had like Central Asian countries transporting oil and gas and different goods through Russia to Europe, they’re now using alternative routes through Georgia.

We also had a lot of Russians, who we did not expect; they just left Russia and moved to Georgia, especially people working in IT industry. And then now, we are having IT services exporting from Russia to Europe and other countries and the services we never exported. So our labour market changed dramatically, labour structure changed dramatically. The potential GDP growth most likely changed dramatically so a big shift happened there. Then exports, for instance, we brew Heineken beer in Georgia and Heineken stopped producing in Russia. They have ten brewers there and they stopped exporting from Russia. So they needed a destination. Now, we are exporting in seven countries where Heineken Russia was exporting.

So we have a lot of side effects which caused the Georgian Lari to appreciate from 3.3 dollar to 2.85. And against the Euro and against Pound, even greater appreciation because we had a big inflow of foreign currency. Georgia’s business-friendly environment also helps here. So we have investment also coming in. If you look at the foreign investment in Q1 versus the GDP, it’s the highest ever recorded. So you have big investments coming into the country. You have labour market shifting, structure changing, you have the logistics changing, the exports going up. And Georgia did a great thing also to have a free trade agreement with China and EU. There are actually two countries who have a free trade agreement with simultaneously China and EU, it’s Switzerland and Georgia. So basically that also helps because our exports also stepped up.

Tourist recovery was amazing and I think that the government managed to change the tourist structure as well. We managed to attract tourists, after the Covid, from high-earning countries and high spenders. So right now, in terms of numbers, we have 65% of number of tourists recovering. So 65% of 2019 tourists are coming to Georgia in numbers. But in terms of the money spent, it’s more than 100% than what we had back in 2019. So last year, we had 10% GDP growth; this year, we have 10% plus GDP growth. So huge growth, I mean, base was high. So if you look at the recovery in 2019 in Europe, we are number two after Ireland.

So Ireland is ahead of us in terms of the growth of GDP compared 2019 and then it’s Georgia. Because we outperformed 2019 by far. Basically, the nominal GDP in dollar terms now stands at around 25 billion dollars. It’s a small amount, but before Covid, we were around 17, 18. So this huge growth and Lari appreciation together created more attractive investor destination for foreigners.

[01:03:11] Tilman Versch: Besides all the good news, I have to play Dr Doom. So, how do you see that Russia one day attacks Georgia again in this decade?

[01:03:25] Irakli Gilauri: You see, we’ve already been attacked and Russia got what they wanted, these two land plots we used to have. So I think attacking Georgia again, unless there is a Olympic sport of attacking Georgia, I don’t think it would happen. It’s my view, but I think other nations are more under danger than Georgia. We are ahead in that game.

[01:04:07] Tilman Versch: So you don’t see a high likelihood of an attack again?

[01:04:12] Irakli Gilauri: Yeah, I don’t think. If you attack Georgia, what will you gain? You already have what you wanted. So I think that there are more things to do than attacking Georgia.

[01:04:30] Tilman Versch: You already mentioned that many Russians came to Georgia now. Do you have a rough number how many Russians are there? To remember for the audience, it’s 3.7 million people that live in Georgia. So even a smaller migration could make a huge difference.

[01:04:48] Irakli Gilauri: Yeah, especially in the industry which is not present in Georgia. Basically, the numbers are somewhere between 80,000 to 200,000 IT specialists, let’s put that way. And even if you have 50,000, they add 50,000 dollars a year. That’s 2.5 billion, that’s 10% of GDP. It’s a very big number. So if you have 100, that’s 20% of GDP.

3. TSMC’s Turning Point – Gregor Stuart Hunter

TSMC is Asia’s most valuable company and the ninth-biggest worldwide; its $461 billion market capitalization exceeds that of corporate titans like JPMorgan Chase & Co, Visa and Exxon Mobil at the time of writing. For Taiwan, which has just 23 million people, it is a source of considerable local pride, and its billionaire founder Morris Chang is feted as a national hero. The company estimates it accounted for 5.7 percent of the island’s gross domestic product in 2021.

But TSMC offers more than just bragging rights and economic might. The company is the leader in an industry that has long been viewed as a pillar of Taiwan’s defense against an invasion from China, which considers the self-governing island a renegade province and has never renounced force in its quest to take control of the young democracy. In his 2001 book Silicon Shield: Taiwan’s Protection Against Chinese Attack, journalist Craig Addison laid out the case that Taiwan’s electronics sector is so crucial in providing the chips needed for advanced weaponry that it creates significant incentives for allied nations to come to its defense — much as in the Gulf War, when Kuwait’s oil exports drew swift military intervention against Iraq…

…Hence why a new factory in Arizona seemed to cause more panic on the island than passing Chinese warships — many in Taiwan fear it represents cracks in the shield.

After the disruptions of the Covid-19 pandemic, the U.S. government is seeking to promote domestic chipmaking through the CHIPS and Science Act, a $52.7 billion package of subsidies for research, development, manufacturing and workforce development, priming the pump for chipmakers like TSMC as it expands its Arizona fab. Although TSMC has operated fabricators in China, a subsidiary in Washington state and joint ventures in Japan and Singapore, the Arizona plant marks its biggest facility outside of its home market yet. The company has also said it is considering opening additional factories in Japan and Europe…

…It also faces pressure not to stretch itself too thin. With demands around the world, playing defense at home, and the ever-present pressure of the cut-throat chip industry, TSMC — once a master of giving clients what they want — may be giving away too much…

…In between Hsinchu and Tainan, surrounded by little else except strip malls, the rail stops near a patch of mostly-vacant grassland that houses a 351-room dormitory complex made from sustainable construction materials and covered in solar panels. It’s here that the company is housing many of its new American engineers for training before they head to Arizona. Some have been lured by $100,000 starting salaries, subsidized accommodation, and the security of a three-year contract, the first half of which is spent in Taiwan. Others are drawn to the adventure of working for the world’s most advanced chipmaker.

Instead, they find themselves chain smoking to manage the stress or exercising constantly to blow off steam after 12-hour workdays.

On a warm evening in January, many could be found consoling each other at a local dive bar, grousing about the demanding work requirements of their local supervisors. Some of the new recruits hinted that they already want to leave. None of the workers spoke on the record, but experiences matching theirs are easily found online. Posts on Glassdoor, an anonymous company review site, describe a culture of micromanagement and frustrations adapting to Taiwanese work practices, pointing out that the environment is decidedly different to, say, Intel. “Certainly not for everyone,” says one of the more positive comments.

For starters, unlike at many American companies, engineers at TSMC work in shift patterns and overtime is quite common. “That’s why TSMC can operate 24 hours a day without any temporary equipment shutdown,” says Lucy Chen, vice president at Isaiah Research.

Taiwanese engineers, brought up in the TSMC ecosystem and ethos, are often prepared for this lifestyle. But watching their new American counterparts struggle to keep up has prompted a culture clash on the factory floor and in the dormitories. On the anonymous Taiwanese bulletin board PTT, an open-source message board similar to Reddit, some complain that the U.S. engineers are “babies.” And Chen, at Isaiah Research, notes that TSMC is having an easier time recruiting Taiwanese engineers to work in its new Japanese plant than its Arizona one, in part because of “culture adaptability.”…

…The narrative circulating in Taiwan that “TSMC is being hollowed out and extracted from Taiwan,” he says, “fails to mention” significant contextual information, such as the fact that by the time 4-nanometer chips are made in America, smaller 3-nanometer chips will have been rolling off the production lines in Taiwan for some time.

Currently, the company produces all of its most advanced chips in Taiwan — and it will stay this way, the company says, for the foreseeable future…

…“The prospect of seizing the world’s most valuable semiconductor fabs and becoming a silicon hegemon could at some point this decade tip Beijing in favor of an invasion,” says Jared McKinney, assistant professor of international security studies at Air University, the U.S. Air and Space Force’s center for professional military education. As China gets shut out of the semiconductor supply chain, it may become more desperate — and aggressive.

Most analysts agree that as much as China might want to possess TSMC’s capabilities, taking the island by force would immediately leave the company unable to produce chips. The physical devastation, ensuing sanctions, and lack of access to chipmaking equipment sold by the U.S. and its allies would effectively decimate TSMC’s operations. Over time, China could potentially restore some of its manufacturing capacity, but TSMC would likely be one of the first casualties of any conflict.

4. Twitter thread on ‘0 Days to Expiration’ (0DTE) options – Genevieve Roch-Decter

0DTE options are ‘0 Days to Expiration’ Options. Basically, they’re options that expire in less than a day. Since today is Friday, there are a massive amount of options expiring today (most contracts expire on a Friday).

0DTE options are more popular than ever. JPMorgan says that the notional value of 0DTE options trading has grown to about $1 trillion PER DAY. The total market cap of all US stocks is about $20 trillion.

For S&P 500 options, trading in 0DTE contracts accounts for about 44% of the 10-day average daily options volume, up from about 19% a year ago, according to Reuters…

…0DTE options are the ultimate tool for speculating. You can take a position in an option and realize a huge gain (or less) within a few hours. A call option selling for $1 could easily hit $2 by the end of the session if the underlying stock has a good day, or it could hit $0.

So what’s the problem? Massive trading in options introduces volatility risk…

…In other words, share prices don’t always reflect the intrinsic value of the underlying cash flows of the respective companies, like Benjamin Graham originally wrote about. Instead, share prices are being influenced by excessive trading in options.

5. Daniel Ludwig: An Invisible Billionaire – David Senra

But it’s this idea of how he started this business with limited money. It’s called the two-name paper idea. This will come up again later, but this is an overview, I think it’s helpful at the very beginning.

He had persevered during the mid-1930s and developed an ingenious ship financing scheme that would make his first fortune. The idea was to use other people’s credit. First, he’d go to an oil company and persuade it to grant him a long-term charter to haul its petroleum. This done, he would go to a bank, where using the charter as collateral, he would take out a loan to obtain a ship to haul the petroleum. Instead of paying Ludwig, each oil company would make the charter payments directly to the bank, which would then deduct the loan payment and put whatever was left into Ludwig’s account. This allowed Ludwig to build or renovate tankers without having to put up collateral or use his own credit.

As long as he would fulfill his charter contracts, he had a small but steady income, and more importantly, by the time the contract expired, he was the owner of a paid-up ship without having invested any of his own money…

…[00:20:00] And this is really important to understand later on. He does this with very little amount of money down. He’s buying ships from the government after the war, after World War I with only 10% down. So it says the sale of surplus ships at bargain prices much less than it would have cost to build the vessels from scratch, started almost as soon as the Armistice was declared. The result was that hundreds of government-owned vessels built at taxpayer expense were being sold off at well below cost to legitimate shippers and to speculators who did the minimum required renovation work and then sold the ships for a quick profit. That’s what Ludwig is doing right now during his career.

What made the deal attractive was the Shipping Board required investors to put up only 10% of the purchase price and the rest could be paid over time. And so this is what him and his partners were doing. That would mean by investing less than $50,000, right, because the total purchase price is $500,000. They could buy three ships, remodel and sell them. If they manage to sell three vessels for $1 million, they would reap over $0.5 million profit on an investment of only $50,000. And so almost 40 years later, when he’s giving this interview, he’s talking about this time in his early career and he says, he was always in hock at the beginning of his car. What that meant is, he’s always owed the government money and he’s constant, this whole book.

At this stage of his career, especially with that price it — doesn’t help he’s got a bunch of like — he’s got this large fleet and the depression comes, essentially like no one was to haul oil. He’s like his ships — his charters aren’t just valuable. He has a real hard time making payments. So it says during the Fortune interview in 1957, Ludwig said that in early business years, he was “Always in hock.” There may have been a good reason. As long as you’re in hock, it’s hard for a creditor to collect the money from you. So there’s so many times where the government is like, “Okay, the payment is due.” I’m making this day up, January 1. And Ludwig is like, “Oh, give me like a 6-month extension.” And then June comes like, “I need another 9-month extension.” It’s just constant back and forth and he constantly gets in to extend time. But what’s amazing is how fast his fortune is going to change.

[00:21:55] I do want to pull out these things because the book starts, he’s a 80-year-old man, richest man in the world, at this point. Started in the business when he’s 19, but he’d go when he’s 34. I’m going to — I’m going to pull up two things here. So at 34, he’s in debt and he’s barely making his interest payment. This is now into the depression. Ludwig wrote another begging letter to the Shipping Board saying that he was doing his best that he could, but that AM Tankers needed more time to make the payment. 3 years later, 37, and he’s almost going broke during the great Depression. 10 years from now, he’s going to be unbelievable wealthy, so I’m telling this.

Shipping Board auditor reviewing the company’s situation came to an unavoidable conclusion. AM Takers was for all practical purposes insolvent. The firm had no securities left to borrow on and virtually no chance remained that the massive liabilities could be paid off from the ship’s small earnings. But there’s an important point here. Like we have to pause because this is all about to change, right? It’s like, oh, they have massive liabilities. They have all these ships, but the ship is not making any money. Why isn’t it making any money. Because of the demand for shipping during the great depression has plummeted.

But the asset that he owns, the ship is still valuable. You just need something to cause demand to skyrocket. And that is exactly what happens in the late 1930s, when Europe breaks out in war. War makes the demand for Ludwig’s products and services, skyrocket. It’s almost the exact opposite of what was happening to him and his business the previous decade. Wars and rumors of wars pre-stage an upturn in international commerce, which for cargo haulers meant greater demand and higher revenues. A tanker that had been sitting idle at the dock since the start of the depression could now be hired out on a long-term basis at high rates or sold for a handsome price. He is going to make money both ways.

In some cases, now something that was just sitting there, not only there was no charter on it, if you had to sell the ship to try to pay off your loan, maybe get $50,000, $100,000. Those same ships are selling for $800,000 or more. And so this is the most important part in the book. This is what I referenced earlier. The two-name paper idea, plus the fact that he’s going to be shipping oil for Rockefeller equals Ludwig’s wealth, which then in turn causes him to go out and buy and start the hundreds of these businesses. Let’s go into this.

[00:24:05] “Ludwig needed a way to obtain ready money without either taking partners or assuming heavy mortgages. His early experiences with partnerships have been costly and borrowing to finance ship renovations was no better. It was at this time that Ludwig came up with a two-name paper arrangement that he said was a chief reason for his wealth. He would go to an oil company, get it to sign a long-term charter to ship so much oil on a regular basis, take the charter to a bank and using as collateral, obtain a loan to build or renovate a ship to haul the oil to fill the charter. The plan was legal, logical, and ingenious. He was able to start his climb towards being the world’s biggest shipper mainly because he was now hauling oil for the Rockefeller Empire…

…During the depths of the depression, Ludwig was mired deep in debt. He was saddled with do-nothing partners, desperately pressed to keep the Shipping Board and the banks from foreclosing on his few ships, and burden with an unhappy marriage. Now 5 years later, DK was in good financial shape, the owner of a growing fleet of ships and corporations out of debt and enjoying a profitable relationship with the government, the banks, and the oil companies. Moreover, he was building a reliable staff and had a happier marriage…

…This is how he starts the largest salt company in the world. And in the middle of the story is my favorite sentence in this entire book. So it’s this project that’s going to happen. It says it’s on Mexico’s Pacific Coast about halfway down the Baja Peninsula. Located there were huge underground deposits of brine. Concentration of salt in the water were around 30%, nearly 10x that of seawater by the simple process of pumping this brine to the surface and letting it stand in pools where the hot sun could evaporate the water, one could produce millions of tons of salt.

[00:42:04] This is what Ludwig is doing, produce millions of tons of salt, which could be gathered and exported. The economy of the procedure appealed to Ludwig. All he had to do is bring up the brine and nature would do the processing. The main problem was the labor. This part of Mexico was nearly unpopulated, and he would have to import workers and build places for them to live. He has to build essentially a small town for this to happen. The Baja cost was so remote that he would have to build an entire town if he was going to develop the salt deposits. This is my favorite sentence of the book, but he had learned something by now.

“Opportunities exist on the frontiers where most men dare not venture, and it is often the case that the farther the frontier, the greater the opportunity.” I love that line. The majority of businessmen are tied to cities where the ingredients of development already exists, labor, energy, supplies, building, transportation, and so on. Competition also exists there. And the way to escape it is to either do something no one else is doing or do it where no one else is doing it. Much of Ludwig’s success was due to his willingness to venture where more timid entrepreneurs dare not go. This business is unbelievably successful. He winds up selling it a few years later, but the output, the salt output increased to as much as 4 million tons a year, making the largest producer of solar salt in the world.

And that’s just one of these giant projects that he takes on. This is one of my favorite stories in the book too because sometimes you have to do it yourself. He’s already a billionaire at this point in the story. When he’s about to do what I’m going to describe to you now. He was embarking on an ambitious project in Panama, the building of a 55,000 barrel-a-day refinery in an adjoining petrochemical complex. Before starting construction, however, Ludwig had a little tour to perform, one that he intended to do personally. Twice, he had trusted the word of specialists and twice he had been burned. He had believed them when they told him he could bring fully loaded 60,000-ton ore carriers down the Orinoco River, this is in South America without running them aground. They were wrong about that, by the way.

[00:43:59] And his geologists had failed to discover until after considerable work was done that the coral rock underlying Grand Bahama Island was too fragile to support giant supertankers. So these are giant previous projects that he was working on. He got bad information and that cost him a ton of money. So he’s not going let that happen again. These episodes have cost Ludwig considerable time and expense. So before building a refinery in Panama, he decided to check out the site himself. Dressed in baggy workloads, he caught a night flight out of New York to Panama City and arrived just before dawn. He went into a little village store at the Bays Edge and pulled out a quarter out of his pocket.

He paid for his purchases, a heavy bolt and a $0.20 ball of string. He unwound the string, measured it out in 6-foot lengths, and tie a knot at each interval. He went outside and rented a motor boat and spent the rest of the morning. Remember, he is already a billionaire when he was doing this, and spend the rest of the morning and afternoon puttering around the bay checking with his weighted line, the accuracy of every sounding marked on a nautical chart that he had brought along. Only when he had satisfied himself that the water was as deep as the chart said, did he fly back to New York and give the signal to begin construction.

6. Infinite Games – Jack Raines

This idea of finite and infinite games doesn’t just apply to sports such as basketball. In fact, it is much more applicable to the biggest game of them all: life.

We humans have created quite the scoring system, haven’t we?

Are you single? Married? Do you have kids? What do you do for a living? Who do you work for? How much money do you make? Where do you live? How many languages do you speak?

We ask, “Who are you?” but we mean, “Which boxes have you checked?”

And the definition of you, whoever “you” are, is the sum of your boxes. Of course, we don’t consciously analyze our lives in this way. That would seem so vain! But we do it all the same.

Let me give you an example.

What is “prestige?” Well, that’s a broad question. Let’s get more specific. What makes “prestigious” careers prestigious?

You might say exclusivity. Thousands of individuals apply for a limited number of positions, and the ones who successfully land those limited positions become part of the “in-group.” And sure, exclusivity plays a role. But prestige runs deeper than exclusivity alone: prestige represents victory.

You had to beat countless other applicants to land that competitive position. You won, they lost, and your prize includes the prestige that ensues. I’ve won some prestige games myself over the years, like getting accepted to Columbia Business School, for example.

Prestige is a finite game. You play the prestige game for the sake of winning it. But do you know what happens after you win this game? Sure, there’s a moment of dopamine-induced satisfaction as you climb the proverbial mountain, look across the horizon, and scream, “I DID IT! LOOK AT ME!”

But what happens next?

You return from the peak and think, “Damn. I need that rush again. I need to climb another mountain.” But here’s the thing about that next mountain: it has to be greater than the previous one. If not, you’ll only feel underwhelmed as you look out from its peak and see your taller, greater feat from the past taunting you.

And another finite game begins…

…Here’s the problem with treating life as a series of finite games that must be won: No one remains the winner forever…

…Taken to its furthest extreme, the focus on outcome over everything leads to us discounting 99% of our lives for the sake of a few, small, fleeting moments that might provide some sense of satisfaction before the cycle begins anew.

And, I don’t know man, it seems pretty insane to live your life this way, but we do it all the time. You see it among the most successful folks alive, who, despite their billions of dollars and fame and fortune can’t stop chasing that next mountain. That next achievement. Because the last one, which took years to accomplish, lost its luster in minutes.

7. China’s Xi Jinping Shrugs Off Criticism in Push for Even More Control – Chun Han Wong and Keith Zai

Mr. Xi and senior Chinese officials this week agreed to plans to give the party more direct command in an array of areas they see as critical, including security, finance, technology and culture, while further diluting the government’s role in policy-making, according to people familiar with the discussions.

The National People’s Congress is expected to rubber-stamp parts of the plan during its annual session, which starts in Beijing this Sunday. The Chinese legislature will also sign off on senior government appointments, including a new economic team that has already begun trying to rev up growth in the world’s second-largest economy. The new team is expected to try to address concerns among business leaders about the government’s support for the slumping property market and tech industry, which has come under pressure from a regulatory clampdown…

…Mr. Xi faced tough tests of his leadership last year. His insistence on zero-Covid lockdowns in the face of fast-spreading Omicron variants decimated economic activity and eroded trust in the party across many of China’s wealthiest cities. His abrupt and chaotic pivot from zero-Covid in December caught many officials and citizens off-guard. His assertive diplomacy and continued support for Moscow despite Russia’s invasion of Ukraine, meanwhile, damaged China’s standing in the developed world.

Even so, Mr. Xi has continued to exert firm control while pursuing his agenda, seemingly unshaken by what critics describe as some of the biggest policy missteps of his 10-year rule—a demonstration, analysts say, of the practical dynamics of power in China.

“Xi Jinping’s authority has been affected in the eyes of the masses and ordinary cadres, but he still has the gun barrel, the knife handle and the pen shaft in his hands,” said Wang Hsin-hsien, a politics professor at Taiwan’s National Chengchi University, referring to party parlance for the military, security forces and the propaganda apparatus—all key levers of power.

Given the political climate in China, “suffering damage to one’s authority doesn’t represent facing a challenge to one’s power,” but rather suggests that the ruler will seek to tighten his grip on power, Mr. Wang said…

…Mr. Xi seems to believe that policy missteps stem from poor local execution of Beijing’s directives, and thus is trying to ensure that lower-level officials can deliver better governance while the central leadership exerts overall control, said Ryan Manuel, managing director of Bilby, a Hong Kong-based artificial intelligence firm that analyzes Chinese government documents.

The focus on local failings also brings political benefits for Mr. Xi, said Mr. Manuel. “By having local governments take the blame for failing to implement policy adequately, Xi’s not going to take all the heat.”

In recent months, Mr. Xi has reiterated demands for political loyalty, such as by ordering party inspectors to ensure compliance with the central leadership’s edicts, while making efforts to regain public trust. 

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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. We currently have a vested interest in TSMC and Visa. 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 05 March 2023:

1. Planning for AGI and beyond – Sam Altman

If AGI is successfully created, this technology could help us elevate humanity by increasing abundance, turbocharging the global economy, and aiding in the discovery of new scientific knowledge that changes the limits of possibility.

AGI has the potential to give everyone incredible new capabilities; we can imagine a world where all of us have access to help with almost any cognitive task, providing a great force multiplier for human ingenuity and creativity.

On the other hand, AGI would also come with serious risk of misuse, drastic accidents, and societal disruption. Because the upside of AGI is so great, we do not believe it is possible or desirable for society to stop its development forever; instead, society and the developers of AGI have to figure out how to get it right…

…Although we cannot predict exactly what will happen, and of course our current progress could hit a wall, we can articulate the principles we care about most:

1. We want AGI to empower humanity to maximally flourish in the universe. We don’t expect the future to be an unqualified utopia, but we want to maximize the good and minimize the bad, and for AGI to be an amplifier of humanity.
2. We want the benefits of, access to, and governance of AGI to be widely and fairly shared. We want to successfully navigate massive risks. In confronting these risks, we acknowledge that what seems right in theory often plays out more strangely than expected in practice.
3. We believe we have to continuously learn and adapt by deploying less powerful versions of the technology in order to minimize “one shot to get it right” scenarios…

…As our systems get closer to AGI, we are becoming increasingly cautious with the creation and deployment of our models. Our decisions will require much more caution than society usually applies to new technologies, and more caution than many users would like. Some people in the AI field think the risks of AGI (and successor systems) are fictitious; we would be delighted if they turn out to be right, but we are going to operate as if these risks are existential.

At some point, the balance between the upsides and downsides of deployments (such as empowering malicious actors, creating social and economic disruptions, and accelerating an unsafe race) could shift, in which case we would significantly change our plans around continuous deployment…

…The first AGI will be just a point along the continuum of intelligence. We think it’s likely that progress will continue from there, possibly sustaining the rate of progress we’ve seen over the past decade for a long period of time. If this is true, the world could become extremely different from how it is today, and the risks could be extraordinary. A misaligned superintelligent AGI could cause grievous harm to the world; an autocratic regime with a decisive superintelligence lead could do that too.

AI that can accelerate science is a special case worth thinking about, and perhaps more impactful than everything else. It’s possible that AGI capable enough to accelerate its own progress could cause major changes to happen surprisingly quickly (and even if the transition starts slowly, we expect it to happen pretty quickly in the final stages). We think a slower takeoff is easier to make safe, and coordination among AGI efforts to slow down at critical junctures will likely be important (even in a world where we don’t need to do this to solve technical alignment problems, slowing down may be important to give society enough time to adapt).

Successfully transitioning to a world with superintelligence is perhaps the most important—and hopeful, and scary—project in human history. Success is far from guaranteed, and the stakes (boundless downside and boundless upside) will hopefully unite all of us.

2. Berkshire Hathaway 2022 Shareholder Letter – Warren Buffett

A common belief is that people choose to save when young, expecting thereby to maintain their living standards after retirement. Any assets that remain at death, this theory says, will usually be left to their families or, possibly, to friends and philanthropy.

Our experience has differed. We believe Berkshire’s individual holders largely to be of the once-a-saver, always-a-saver variety. Though these people live well, they eventually dispense most of their funds to philanthropic organizations. These, in turn, redistribute the funds by expenditures intended to improve the lives of a great many people who are unrelated to the original benefactor. Sometimes, the results have been spectacular.

The disposition of money unmasks humans. Charlie and I watch with pleasure the vast flow of Berkshire-generated funds to public needs and, alongside, the infrequency with which our shareholders opt for look-at-me assets and dynasty-building.

Who wouldn’t enjoy working for shareholders like ours?…

…Charlie and I allocate your savings at Berkshire between two related forms of ownership. First, we invest in businesses that we control, usually buying 100% of each. Berkshire directs capital allocation at these subsidiaries and selects the CEOs who make day-by-day operating decisions. When large enterprises are being managed, both trust and rules are essential. Berkshire emphasizes the former to an unusual – some would say extreme – degree. Disappointments are inevitable. We are understanding about business mistakes; our tolerance for personal misconduct is zero.

In our second category of ownership, we buy publicly-traded stocks through which we passively own pieces of businesses. Holding these investments, we have no say in management.

Our goal in both forms of ownership is to make meaningful investments in businesses with both long-lasting favorable economic characteristics and trustworthy managers. Please note particularly that we own publicly-traded stocks based on our expectations about their long-term business performance, not because we view them as vehicles for adroit purchases and sales. That point is crucial: Charlie and I are not stock-pickers; we are business-pickers.

Over the years, I have made many mistakes. Consequently, our extensive collection of businesses currently consists of a few enterprises that have truly extraordinary economics, many that enjoy very good economic characteristics, and a large group that are marginal. Along the way, other businesses in which I have invested have died, their products unwanted by the public. Capitalism has two sides: The system creates an ever-growing pile of losers while concurrently delivering a gusher of improved goods and services. Schumpeter called this phenomenon “creative destruction.”…

…The math isn’t complicated: When the share count goes down, your interest in our many businesses goes up. Every small bit helps if repurchases are made at value-accretive prices. Just as surely, when a company overpays for repurchases, the continuing shareholders lose. At such times, gains flow only to the selling shareholders and to the friendly, but expensive, investment banker who recommended the foolish purchases.

Gains from value-accretive repurchases, it should be emphasized, benefit all owners – in every respect. Imagine, if you will, three fully-informed shareholders of a local auto dealership, one of whom manages the business. Imagine, further, that one of the passive owners wishes to sell his interest back to the company at a price attractive to the two continuing shareholders. When completed, has this transaction harmed anyone? Is the manager somehow favored over the continuing passive owners? Has the public been hurt?

When you are told that all repurchases are harmful to shareholders or to the country, or particularly beneficial to CEOs, you are listening to either an economic illiterate or a silver-tongued demagogue (characters that are not mutually exclusive)…

…I have been investing for 80 years – more than one-third of our country’s lifetime. Despite our citizens’ penchant – almost enthusiasm – for self-criticism and self-doubt, I have yet to see a time when it made sense to make a long-term bet against America. And I doubt very much that any reader of this letter will have a different experience in the future.

3. Does Long-Term Investing Work Outside of the United States? – Ben Carlson

Elroy Dimson, Paul Marsh and Mike Staunton published a book the early-2000s called Triumph of the Optimists: 101 Years of Global Investment Returns that looked at the historical record of equity markets around the globe since the year 1900…

..And lucky for us, the authors update the data on an annual basis for the Credit Suisse Global Investment Returns Yearbook. The latest edition was just released and it’s filled with data and charts about the long-run returns in stock markets around the globe…

…The U.S. is near the top but it’s not like they’re running away with it like Secretariat… Sure, there have been some complete washouts over the years (Russia’s stock market was basically shut down for 75 years following World War I) but returns in other countries have been anywhere from OK to respectable to strong…

…The MSCI World ex-USA dates back to 1970. These were the annual returns1 from 1970 through January 2023:

• S&P 500: 10.5%
• MSCI ex-USA: 8.4%

That’s a pretty good lead for the old US of A but it’s not like the rest of the world has been chopped liver over the past 50+ years. And the majority of the U.S. outperformance has come since the 2008 financial crisis.

These were the annual return through the end of 2007:

• S&P 500: 11.1%
• MSCI ex-USA: 10.9%

It was pretty darn close before the most recent cycle saw U.S. stocks slaughter the rest of the world. And it’s not like U.S. stocks have outperformed always and everywhere.

4. AI-generated comic artwork loses US Copyright protection – Benj Edwards

On Tuesday, the US Copyright Office declared that images created using the AI-powered Midjourney image generator for the comic book Zarya of the Dawn should not have been granted copyright protection, and the images’ copyright protection will be revoked…

…Last September, in a story that first appeared on Ars Technica, Kashtanova publicly announced that Zarya of the Dawn, which includes comic-style illustrations generated from prompts using the latent diffusion AI process, had been granted copyright registration. At the time, we considered it a precedent-setting case for registering artwork created by latent diffusion.

However, as the letter explains, after the Copyright Office learned that the work included AI-generated images through Kashtanova’s social media posts, it issued a notice to Kashtanova in October stating that it intended to cancel the registration unless she provided additional information showing why the registration should not be canceled. Kashtanova’s attorney responded to the letter in November with an argument that Kashtanova authored every aspect of the work, with Midjourney serving merely as an assistive tool.

That argument wasn’t good enough for the Copyright Office, which describes in detail why it believes AI-generated artwork should not be granted copyright protection. In a key excerpt provided below, the Office emphasizes the images’ machine-generated origins:

Based on the record before it, the Office concludes that the images generated by Midjourney contained within the Work are not original works of authorship protected by copyright. See COMPENDIUM (THIRD ) § 313.2 (explaining that “the Office will not register works produced by a machine or mere mechanical process that operates randomly or automatically without any creative input or intervention from a human author”). Though she claims to have “guided” the structure and content of each image, the process described in the Kashtanova Letter makes clear that it was Midjourney—not Kashtanova—that originated the “traditional elements of authorship” in the images…

…It’s possible that the ruling may eventually be reconsidered as the result of a cultural shift in how society perceives AI-generated art—one that may allow for a new interpretation by different members of the US Copyright Office in the decade ahead. For now, AI-powered artwork is still a novel and poorly understood technology, but it may eventually become the standard way visual arts emerge. Not allowing for copyright protection would potentially preclude its use by large and powerful media conglomerates in the future. So the story of AI and copyrights is not over yet.

5. Even a Brain-Eating Amoeba Can’t Hide From This Cutting-Edge Diagnosis Tech – Ron Winslow

When a middle-aged man who had suffered a seizure was admitted to the University of California San Francisco Medical Center in 2021, doctors seeking the cause for his condition quickly became stumped.

After pathologists spent two weeks peering through microscopes and monitoring petri dishes, doctors knew something serious was harming the patient’s brain; they had no idea what it was or how to treat it.

They turned to an emerging strategy known as unbiased diagnosis. It ultimately confirmed an illness so rare and so deadly, few doctors have ever seen it: brain-eating amoeba disease. The patient’s brain had been invaded by a single-cell critter called Balamuthia mandrillaris, one of at least three types of amoebas known to infect human brains.

The unbiased approach is called metagenomic next-generation sequencing, a powerful technology that analyzes all of the genetic material in a patient’s tissue sample and as a result can screen for a wide range of disease-causing microbes in a single test…

…The conventional search for the cause of an infection involves examining patient tissue under a microscope or culturing samples in a petri dish to see if bacteria or other microbes grow. But doctors have to be looking for a particular bug to find it. Such tests are typically ordered after doctors weigh the details of a case and form a hunch about the cause of the infection—a biased approach…

… Metagenomics is the future of medical diagnostics, said Eric Topol, director of Scripps Research Translational Institute, La Jolla, Calif. “It should be the present,” he said, but not many hospitals are equipped to do it.

A metagenomics test spells out the order of the four letters that make up the genetic code in all the DNA and RNA in a patient sample and compares the result against human and nonhuman genome sequences stored in databases such as the National Institutes of Health’s GenBank. 

A typical sample might yield 100 million snippets of genetic material, Dr. DeRisi said. Some 99% would be human. Those sequences are computationally stripped away and the remaining 1 million pieces are screened against all the sequences in GenBank in an effort to find a match…

…A biased diagnosis can be likened to the card game Go Fish, said Natasha Spottiswoode, an infectious disease physician at UCSF who has overseen care of the Balamuthia patient. A player holding a green fish card asks another, “Do you have any green fish?” If the answer is no, the question on the next turn may be, “Do you have any red fish?” 

For an unbiased query, “What you really want to ask is, ‘Do you have any fish at all?’” Dr. Spottiswoode said. “And then figure out what color they are.” 

In 2014, Dr. DeRisi was among a team of researchers and clinicians at UCSF who reported on one of the first patients to be successfully treated based on metagenomics sequencing—a 14-year-old boy whose treatable, but potentially fatal Leptospirosis bacterial brain infection went undiagnosed for several months until the test was performed.

The case convinced Dr. DeRisi and his colleagues that a metagenomics test should be deployed as a clinical tool for diagnosing brain infections and eventually led UCSF to offer the tests to other hospitals. Innovation in semiconductor technology is helping make the service possible, Dr. DeRisi said. “If we dial back 10 or 12 years ago, we couldn’t do this,” he said. “If we didn’t have increases in computer storage, memory and speed, we’d be sunk.”…

…Metagenomics has limitations. The test can pick up dormant or otherwise clinically irrelevant microbes, making it difficult to interpret results. It can miss pathogens that are detected by conventional means. UCSF’s brain infection test costs about $2,000, far less than the cost of a day in the ICU, but still a potential impediment to regular use. Insurance reimbursement is spotty. Turnaround time can be as long as six or seven days, Dr. DeRisi said.

6. James Revell – Wise: Moving Money Around the World – Zack Fuss and James Revell

James: [00:11:24] Maybe I’ll start with just providing a bit more context and background on the cross-border money transfer market, and that can set up this counter-position Wise has. So if you think about cross-border money transfers, it goes back thousands of years. There are history books written on this. Ultimately, back in the day, it would have been gold bullion or precious metal spices being loaded on to ships and transferred across borders.

Obviously, that is quite impractical, causes security concerns, costs and all sorts. Over time, we’re talking 11th, 12th century now, the bill of exchange was created, whereby you could essentially create an IOU which meant you didn’t need to transfer actual money or currency across borders, it’s more a paper-based exchange of value that could be redeemed at a bank. These were posted at the time.

And then that has grown into telex messaging when cross-Atlantic cables are laid and this electronic means that of communication between bank arrive. And so the history of cross-border transfers, if you think about it, money stopped moving across borders a long time ago. It was a lot of credits and debits of accounts with each banks held with each other, moving numbers around on ledgers as opposed to money actually being sent on a ship or through this kind of pipe. It’s just a series of relationships between banks.

That’s known as correspondent banking, and we can come back to some of the problems with that model. But maybe just to set up then how big this market is. So I think there’s about GBP 100 trillion of volume transferred across borders every year. If you cut out, say, the really big enterprise government or interbank transfers, you’re left with about GBP 2 trillion of personal cross-border transfers and about GBP 9 trillion of small businesses transferring money across borders. So this is a colossal market.

And that flows through to, say, a revenue line of anywhere between GBP 100 million and GBP 200 billion paid in fees by customers. In terms of the split of that market, about 2/3 still sits with banks, about 10% to 20% with money transfer operators like the Western Unions and the MoneyGrams and the rest is split up between the remaining players. The market is growing. So on average, growing about 5% per annum over the past decade. But interestingly, fees are reducing.

There’s some pressure on fee down was largely caused by Wise, but also by regulatory attention. But 2008, 2009, it was about 9% in fees. It’s now like, say, close to 6%, 7%. The tailwinds behind this market is largely been driven by globalization. So international trade and supply chains, global e-commerce, international traveler migration. And it’s received, like I said, a lot of regulatory attention. So the G20 and the FSB are really focused on this right now.

UN have set of goal that by 2030, cross-border transfer fees should be close to 3%. And why that is, is because it’s a very inefficient way of doing things. These are very high. And largely, unfortunately, the people that suffer are normally immigrants, trying to work overseas and transfer money every month back home to support their families. And so that’s one reason I think the regulatory attention has come. The other reason is because financial crime and the proceeds of crime transferring across borders, if that’s in cash, that causes a problem.

So underpinning this market is what’s known as correspondent banking which is the relationship between banks around the world. So if you’re, say, Commonwealth Bank of Australia, you need to transfer money to Barclays in the U.K., you may not have a direct relationship or say, you’re a credit union in Australia, it would very unlikely to have a relationship with the bank in the U.K. And so you’ll contact a bank in Australia who will contact a bank in, say, the U.K. who will then contact the recipients bank.

This chain of communication between banks is called correspondent banking. And what they’re doing is basically transferring the request and the amount of money they need to spend as well as the customer information. Now the way the banks do this communication is reliant upon an organization called SWIFT. So SWIFT is owned by 200 banks. It’s used by over 11,000 of them and it stands for the Society of Worldwide Interbank Financial Telecommunications.

So it’s essentially an electronic communication network that tries to put in place a common language and some standards around how a cross-border transfers work, what format data needs to come in. So you may have heard of SWIFT code or an IBAN number, these are identifiers that banks use globally to help them manage this complex network of communication, which underpins these transfers.

That doesn’t take away the individual effort put on to banks in order to complete transfers. And so maybe just to run through the process quickly. First of all, you’ve got to find a bank so you want to transfer money to Thailand, as a bank, you may need to go through three or four different banks to get to the recipients banking and so you’ve got to find a way of getting to the recipient bank.

Every step of the way you need to validate the data, you needed to complete the regulatory checks, you then need to potentially transform the data for the next bank along in the chain, you need to transmit it. You then need to sort out funding on the back end. So settling crediting and debiting accounts, this could be like a $50 transfer. And these six banks all need to communicate, they all need to settle funds and they all need to reconcile and make sure that all ticks were completed, all data has been transferred accurately and everyone’s got the money they need.

That’s set up, you can see that there’s a ton of problems caused by that. The first and the most obvious one, which has been growing over the past 10 years, particularly since the GFC, the regulatory and compliance burden along that chain is huge. So making sure that there’s no anti-money laundering going on. There’s no counterterrorism financing going on. You’ve got your sanctions checks, you’ve got to protect data.

So you’ve got be mindful of privacy, you’ve got prudential worries about liquidity and bank regulations and consumer protections like if something goes wrong, you got to solve disputes. So there’s an enormous amount of complexity just on the regulation and compliance side. There are interesting things like opening hours. So banks communicating across the world, they have different opening hours.

The way banks transfer money domestically between each other is normally done in a batch process model, whereby it’s only operating five days a week and at certain times of that day. So if you span a weekend, your money is not moving. There’s also a lot of paper and legacy technology involved. There’s liquidity and foreign exchange risks.

So if transfers between banks aren’t done simultaneously, which often they are, that creates liabilities between banks, which is problems and banks charge fees for that. So correspondent banking has a lot of inefficiency built in, and that flows through. So those are supply side problems flow through to problems for customers like our poor Kristo and Taavet back in 2008. It’s incredibly expensive. Every hand off along the chain, they need to be paid. It’s slow.

Each step along the chain, obviously, there’s some waiting time involved and it’s opaque. Often upfront where the transfer starts, you have no idea how much it’s going to cost when it comes out the other end. And ultimately, it’s inconvenient…

…Zack: [01:03:30] And then as you kind of reflect upon what you’ve learned about this business as you studied it and the broader payment space, what is a lesson that you can take from this business and apply to others from an investor’s perspective? And then some of the other early stage or late-stage growth companies that you look at, what are lessons you’d like to see them borrow from Wise and apply to their own business as operators?

James: [01:03:48] The one thing we haven’t really touched upon, which I think Wise has, and being an operator myself is something that I could have learned from. The way they organize their people and prioritize their culture, I think, is relatively unique. I attended a talk with someone from TransferWise back in 2018. You talked about the way they prioritize resource allocation internally.

So what they have is they have small teams, so they have over — I think it’s over 100 teams, small, highly autonomous empowered, cross-functional teams each working on a solution or a feature. And that team is empowered to create its own vision, its own mission, its own objectives. To the extent it can even go and seek its own legal advice. So it’s fully — each team is fully autonomous. And they basically vie for prioritization amongst each other.

So it’s a lot of mini businesses within a business. Why I think that is fascinating. It has some problems, which potentially we can touch on. But why that resonates with me is the thesis around having very highly aligned but very loosely coupled people within your organization to overcome this inertia and this slowdown that occurs as the business gets bigger.

So if you have low alignment and high autonomy, you have very empowered silos, but they’re doing their own thing. They might not be pulling in the same direction. There’s probably some duplication or overlap or potentially even pulling in opposite directions. On the flip side, you can have very high alignment but low autonomy, which is basically a command and control type structure. Both of these can exist and do exist quite regularly, but they really struggle to scale.

Reed Hastings talks about this high alignment loose coupling where you tell people what to do, not how to do it. And I think this is what these small many businesses within the business is what Wise has managed to organize as they’ve grown up. And key to it is having that super clear mission, super clear vision, you’ve got your customer at the center of everything, you know why you exist, and that creates the alignment.

There’s a huge amount of trust and transparency within the business. And I think this culture focusing on one thing, you see in other scale economy shared businesses. There’s been great breakdowns on Floor & Decor or Costco, where it’s a relentless focus on one thing, retaining operational improvements and the benefit of unit cost efficiencies back to the customer. But it is that one thing focus and just doing that one thing really well and organizing a culture behind it. For us, as people and culture investors, that is so powerful, and I think it’s one of the untold stories of this business.

7. Will High Risk-Free Rates Derail the Stock Market? – Ben Carlson

Because of the Fed’s interest rate hikes, investors are being offered a gift right now in the form of relatively high yields on essentially risk-free securities (if such a thing exists). You don’t have to go further out on the risk curve to find yield right now.

Short-term bonds with little-to-no interest rate or duration risk are offering 5% yields.

The big question for asset allocators is this: Will higher risk-free rates impact the demand for stocks and other risk assets which leads to poor returns?

This makes sense in theory. Why take more risk when that 5% guaranteed yield is sitting there for the taking?

The relationship between risk-free rates and stock market returns is not as sound as it would seem in theory…

…The highest average yields occurred in the 1980s, which was also one of the best decades ever for stocks. Yields were similarly elevated in the 1970s and 1990s but one of those decades experienced subpar returns while the other saw lights-out performance…

…I also looked at the performance of the stock market when 3-month T-bill yields averaged 5% for the entirety of a year (which could happen this year). That’s been the case in 25 of the last 89 years.

The annualized return for the S&P 500 in those 25 years was 11%. So in years with above-average risk-free rates, the stock market has actually seen above-average returns.

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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. We currently have a vested interest in Costco and Wise. Holdings are subject to change at any time.