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 25 June 2023:
1. Vision Pro – Benedict Evans
There’s a strong echo here of mobile 20 years ago. From the late 1990s to 2007, we had mobile internet devices that were OK but not great, and slowly improving, we knew they would eventually be much better, and we thought ‘mobile internet’ would be big – but we didn’t know that smartphones would replace PCs as the centre of tech, and connect five billion people. Then the iPhone came, and the timeline broke.
Apple’s Vision Pro isn’t an iPhone moment, or at least, not exactly. At $3,500, it’s very expensive in the context of today’s consumer electrics market, where the iPhone launched for $600 (without subsidy, and then rapidly switched to $200 at retail with an operator subsidy). And where the iPhone was a more-or-less drop-in replacement for the phone you already had, nine years after Meta bought Oculus, VR is still a new device and a new category for almost everyone. Indeed, the Vision Pro actually looks a bit more like the original Macintosh, which was over $7,000 (adjusted for inflation) when it launched in 1984, and most people didn’t know why they needed one.
I think the price and the challenge of category creation are tightly connected. Apple has decided that the capabilities of the Vision Pro are the minimum viable product – that it just isn’t worth making or selling a device without a screen so good you can’t see the pixels, pass-through where you can’t see any lag, perfect eye-tracking and perfect hand-tracking. Of course the rest of the industry would like to do that, and will in due course, but Apple has decided you must do that.
This is the opposite decision to Meta: indeed Apple seems to have taken the opposite decision to Meta in most of the important trade-offs in making this. Meta, today, has roughly the right price and is working forward to the right device: Apple has started with the right device and will work back to the right price. Meta is trying to catalyse an ecosystem while we wait for the right hardware – Apple is trying to catalyse an ecosystem while we wait for the right price. So the Vision is a device pulled forward from years into the future, at a price that reflects that. It’s as though Apple had decided to sell the 2007 iPhone in 2002 – what would the price have been?…
…Apple didn’t say AR or VR, and it certainly didn’t say ‘metaverse.’ Metaverse (as I wrote here last year) has become an entirely meaningless word – you cannot know what someone else means when they say it. But when Mark Zuckerberg talks about it, it sounds like a place – a new environment somehow different from ‘the internet.’ Meta talks about what it will be ‘like’ in the ‘metaverse.’ But Apple makes computers, and Apple thinks this is a computer, that runs software, that could be all sorts of things. For Meta, the device places you in ‘the metaverse’ and there could be many experiences within that. For Apple, this device itself doesn’t take you anywhere – it’s a screen and there could be five different ‘metaverse’ apps. The iPhone was a piece of glass that could be anything – this is trying to be a piece of glass that can show anything.
This reminds me a little of when Meta tried to make a phone, and then a Home Screen for a phone, and Mark Zuckerberg said “your phone should be about people.” I thought “no, this is a computer, and there are many apps, some of which are about people and some of which are not.” Indeed there’s also an echo of telco thinking: on a feature phone, ‘internet stuff’ was one or two icons on your portable telephone, but on the iPhone the entire telephone was just one icon on your computer. On a Vision Pro, the ‘Meta Metaverse’ is one app amongst many. You have many apps and panels, which could be 2D or 3D, or could be spaces. Developers can make whatever they want…
…That makes it unlikely that media companies and games companies will invest much in creating custom experiences any time soon. Apple has been spending a lot of money shooting 3D content itself and Disney’s Bob Iger took the stage briefly to show an obviously hasty ‘sizzle reel’ of ideas, while lots of developers are interested in experimenting, but this isn’t going to have millions of apps in 2024. On the other hand, that may not matter for the people who do buy it – part of the benefit of the AR thesis, and Apple’s broader ecosystem leverage, is that almost all your iPad and iPhone apps will already work. There just won’t be much VR.
Where does that leave Meta?
Mark Zuckerberg, speaking to a Meta all-hands after Apple’s event, made the perfectly reasonable point that Apple hasn’t shown much that no-one had thought of before – there’s no ‘magic’ invention. Everyone already knows we need better screens, eye-tracking and hand-tracking, in a thin and light device. Meta is still selling millions of Quests, and it’s not clear how many people will switch or postpone a purchase give the price and timing of the Vision Pro. There will be voices saying that Meta should push even harder to build up its commanding position ahead of Apple’s proposition becoming more mass-market in, say, 2025 or 2026. It could also pursue the Android strategy of licensing a platform to the rest of the industry, leading the ‘open’ side of the market against Apple’s closed side (except that the Android team had a whole industry of phone OEMs hungry for a way to make the jump to smartphones, and who are the hungry VR OEMs today?). It’s worth remembering that Meta isn’t in this to make a games device, nor really to sell devices at all per se – rather, the thesis is that if VR is the next platform, Meta has to make sure it isn’t controlled by a platform owner who can screw them, as Apple did with IDFA in 2021. (This is also one reason Android was created, yet Google seems to have dropped out of VR entirely, though the Quest runs Android.)
On the other hand, the Vision Pro is an argument that current devices just aren’t good enough to break out of the enthusiast and gaming market, incremental improvement isn’t good enough either, and you need a step change in capability. That was also the idea behind the much less ambitious (and flopped) Quest Pro. Who won that argument? Meta just announced the Quest 3 for later in the year (just such an incremental improvement), but should it pause after that and work on a jump forward of its own? Can it? Should it be trying to compete with Apple at frontier hardware tech?
2. The AI feedback loop: Researchers warn of ‘model collapse’ as AI trains on AI-generated content – Carl Franzen
The age of generative AI is here: only six months after OpenAI‘s ChatGPT burst onto the scene, as many as half the employees of some leading global companies are already using this type of technology in their workflows, and many other companies are rushing to offer new products with generative AI built in.
But, as those following the burgeoning industry and its underlying research know, the data used to train the large language models (LLMs) and other transformer models underpinning products such as ChatGPT, Stable Diffusion and Midjourney comes initially from human sources — books, articles, photographs and so on — that were created without the help of artificial intelligence.
Now, as more people use AI to produce and publish content, an obvious question arises: What happens as AI-generated content proliferates around the internet, and AI models begin to train on it, instead of on primarily human-generated content?
A group of researchers from the UK and Canada have looked into this very problem and recently published a paper on their work in the open access journal arXiv. What they found is worrisome for current generative AI technology and its future: “We find that use of model-generated content in training causes irreversible defects in the resulting models.”…
…As another of the paper’s authors, Ross Anderson, professor of security engineering at Cambridge University and the University of Edinburgh, wrote in a blog post discussing the paper: “Just as we’ve strewn the oceans with plastic trash and filled the atmosphere with carbon dioxide, so we’re about to fill the Internet with blah. This will make it harder to train newer models by scraping the web, giving an advantage to firms which already did that, or which control access to human interfaces at scale. Indeed, we already see AI startups hammering the Internet Archive for training data.”…
…In essence, model collapse occurs when the data AI models generate ends up contaminating the training set for subsequent models.
“Original data generated by humans represents the world more fairly, i.e. it contains improbable data too,” Shumailov explained. “Generative models, on the other hand, tend to overfit for popular data and often misunderstand/misrepresent less popular data.”
Shumailov illustrated this problem for VentureBeat with a hypothetical scenario, wherein a machine learning model is trained on a dataset with pictures of 100 cats — 10 of them with blue fur, and 90 with yellow. The model learns that yellow cats are more prevalent, but also represents blue cats as more yellowish than they really are, returning some green-cat results when asked to produce new data. Over time, the original trait of blue fur erodes through successive training cycles, turning from blue to greenish, and ultimately yellow. This progressive distortion and eventual loss of minority data characteristics is model collapse. To prevent this, it’s important to ensure fair representation of minority groups in datasets, in terms of both quantity and accurate portrayal of distinctive features. The task is challenging due to models’ difficulty learning from rare events.
This “pollution” with AI-generated data results in models gaining a distorted perception of reality. Even when researchers trained the models not to produce too many repeating responses, they found model collapse still occurred, as the models would start to make up erroneous responses to avoid repeating data too frequently.
“There are many other aspects that will lead to more serious implications, such as discrimination based on gender, ethnicity or other sensitive attributes,” Shumailov said, especially if generative AI learns over time to produce, say, one race in its responses, while “forgetting” others exist…
…Fortunately, there are ways to avoid model collapse, even with existing transformers and LLMs.
The researchers highlight two specific ways. The first is by retaining a prestige copy of the original exclusively or nominally human-produced dataset, and avoiding contaminating with with AI-generated data. Then, the model could be periodically retrained on this data, or refreshed entirely with it, starting from scratch.
The second way to avoid degradation in response quality and reduce unwanted errors or repetitions from AI models is to introduce new, clean, human-generated datasets back into their training.
However, as the researchers point out, this would require some sort of mass labeling mechanism or effort by content producers or AI companies to differentiate between AI-generated and human-generated content. At present, no such reliable or large-scale effort exists online…
…While all this news is worrisome for current generative AI technology and the companies seeking to monetize with it, especially in the medium-to-long term, there is a silver lining for human content creators: The researchers conclude that in a future filled with gen AI tools and their content, human-created content will be even more valuable than it is today — if only as a source of pristine training data for AI.
3. Bill Nygren, Alex Fitch – First Citizens Bank: The Bank Buyers – Matt Reustle, Bill Nygren, and Alex Fitch
Bill: [00:02:30] Obviously, everybody knows what a bank is, but I don’t think there’s a lot of thought as to how you actually operate a bank. And certainly, in the wake of all the problems recently with SVB and the First Republic, we’ve learned that a lot of people in both the government and the media don’t really understand how banking works.
So I’m going to just start with an example. Let’s say I wanted to open a bank, and I put $100,000 in cash. So I’ve got $100,000 of equity, no debt. And then you come along and say, you’ve got $900,000 that you’d like to invest in a savings account. So now I’ve got $1 million in cash, $900,000 in deposits, and $100,000 in equity.
My deal with you is I’ll give you something like 150 basis points less than I can earn on T-bills, and that’s enough to cover my expenses for recordkeeping, processing your transactions, and running a branch banking network. So if I collect 5% on the T-bills I invest in, that’s $50,000. I pay you $32,000 of interest, that’s 3.5% on your money, and a net interest income of about $18,000 before my expenses.
And then I have about 100 basis points of expenses, leaving me with $8,000 before tax, $6,000 after. So I’m earning a 6% ROE on my investment. Now clearly, that’s a very low-risk bank, but it doesn’t return enough to be worth my $100,000 investment. So nobody would run a bank on those terms.
So I get smarter, and I say Alex wants to buy a house. So instead of $1 million in T-bills, I decided to write a mortgage to Alex. I collect 150 basis points over treasuries. So now that same math works out to me earning a 17% return on equity. And you can start to see the attraction of banking. But there are three huge risks that I’ve created: credit risk, liquidity risk, and duration risk. So start with credit. What happens if Alex stops paying on his mortgage.
Well, then I don’t have the money to pay you back on your deposits. So credit risk is always the most important risk that banks have to focus on. The other risk of liquidity is I’m giving you daily withdrawal rights on your money, but Alex doesn’t have to give me his mortgage back until 30 years go by. So I’ve got a huge asset-liability mismatch and managing that is a very important aspect of running a good bank. Lastly, what happens if rates go up?
I can’t change the rate Alex is paying on his mortgage because that’s contractual, but you expect higher rates on your safe bank’s account because rates are now higher. So I’ve also got a big duration risk in the bank and that too has to be managed to have a long-term successful bank. So to us, it’s kind of disingenuous when you hear people saying today as they look at what happened to Silicon Valley, that banks shouldn’t be run in a risky way. Banking is all about risk.
You’re taking short-term deposits. You’re making long-term loans. You’re expecting people to pay back that money. You’re making an estimate of how long the deposits will stay with you. And all of the banking is to get enough diversification in your depositors and your borrowers so that instead of me dealing with a 1% or 2% chance that Alex defaults on his mortgage, I’ve got enough mortgages out there that I can make a pretty good guess that 1% or 2% of the people will default.
And as analysts looking at the banking industry, we look at it and say, it’s generally a commodity business, it’s hard to run a bank so well that it’s a better-than-average business, but the people become even more important in banking than they are in most industries because the leverage is so high.
In most industries, if a management team risks 10% of their assets, they’re also risking about 10% of their equity. In banking, if you risk 10% of your assets, you’re putting the entire equity at risk. So to us, the people become exceptionally important in banking as well as the quantitative analysis of how good a job they’re doing, managing the risks that they’re underwriting…
…Matt: [00:14:36] This business sounds very interesting. It was a very detailed answer there with a lot that I want to tap into. But just from the early description, as you mentioned, it’s the perhaps most important bank that no one has heard of, not hosting conference calls, this deep history of M&A. Share a bit more about that management team and who the leadership is today, how long they’ve been around, and how much they’ve changed the business model. Is the M&A and all of those deals and acquisitions, is that something that’s specifically happened within their tenure?
Alex: [00:15: 06] The bank has been run by the same family for three generations. R.P. Holding took over as CEO in 1935. And again, what’s been a more than 80-year run of consistent management by the holding family. R.P.’s son, Lewis, took over in the 1950s. He was the CEO of the bank until 2008 when Frank Holding took over. Frank Holding is still the CEO today. Really, the Holding family is deeply intertwined with this bank.
Frank and his four sisters own something like 24% of the shares outstanding. They control around 40% of the vote. Frank started in the business at 22, working his way up through junior roles in the bank. His sister, Hope, started at the bank in 1986. Today, she owns almost 5% of the company and is the Vice Chairman. His brother-in-law, Peter Bristow, is the bank president. The business is very intertwined with the family in for more than 80 years, they’ve been running it.
The strategy has evolved over time. For a long time, I think they were organically focused on opening branches in adjacent geographies. The acquisitions started before Frank. They’ve started branching out into various markets through takeovers of banks in other states, but it really accelerated under Frank. He took over in 2008 and you had the financial crisis. And so from 2009 to 2011, there was a lot of opportunity in failed banks through FDIC auctions.
So from 2009 to ’11, they completed something like a half-dozen FDIC-assisted takeovers with meaningful gains associated with taking over those businesses. And in the subsequent 12 years, continued down that path. Doesn’t feel like there are FDIC auctions and bank failures every year given how newsworthy the recent ones have been, but there are. And they’ve relatively consistently found opportunities to buy failed banks through these FDIC auctions at what have been very attractive prices.
That’s become really a core competency, and it’s not the type of advantage you typically think about a bank having. But at this point, they seem to have a real muscle memory around integrating FDIC transactions. They know the processes. They know how they’re going to bid. They know on the next day, how they’re going to begin the integrations, how they’re going to structure employee retention packages, how they’re going to communicate depositors.
Every step of that process, they’ve mapped out and executed on the north of 15x now. It gives them a real skill set here that the vast majority of large banks have never even considered building. And when you have something like the Silicon Valley failure come up, that can turn into a real asset.
Matt: [00:17:54] Do they have much competition in these auctions? You mentioned, it just seems like a specialty or something that other banks don’t even consider doing. But when they are participating in these, are there others that they’re often participating against or others who have operated a somewhat similar strategy?
Bill: [00:18:11] There are certainly others that compete in FDIC auctions. But I think the FDIC’s own summary of what happened after SVB got sold to Citizens is pretty interesting because they criticize themselves for not offering the opportunity to a large enough set of bidders to perhaps extract the highest price, they could have from SVB.
They haven’t publicly said exactly who they restricted, but it’s been written in various places that they told hedge funds, they couldn’t bid on the portfolio. They told the top 10 banks not to bother bidding. They told banks that were smaller than SVB that they were too small that they needed a larger bank than SVB to assure that the public would be comfortable that the rescue would have staying power. They ruled out banks that would meet a capital raise to be able to buy SVB.
And then I’ve also read that they ruled out banks that previously hadn’t purchased from the FDIC. So if you consider that First Citizens was barely larger than SVB, at least before the deposit run started at SVB, you are probably talking about only 20 or so banks that were large enough to compete. And of those, the overwhelming majority were not experienced at FDIC takeovers or needed capital. I think it’s fair to guess that it was a very, very small number of banks that would have put a bid in on SVB.
Alex: [00:19:48] It reminds me of that quote that for a lot of management teams, it’s better to succeed conventionally than fail unconventionally. This is an area that requires specific knowledge and specific experience. And for the vast majority of management teams that were allowed to bid, you can imagine the dynamic internally that they’re taking on a lot of risk for something they don’t fully understand.
They don’t even know what questions to ask, being asked to build out this competency in a couple of days and potentially risk their career on this major decision, the likes of which they’ve never made before. You contrast that with Frank’s family and their business, they don’t have to worry about losing their jobs due to some perceived short-term issue. There’s a certain decisiveness that comes with being the ultimate owner and acting like an ultimate owner.
Now they care quite a bit about ensuring First Citizens succeed that they maintain this legacy, their family’s worth, their position in the community. But there’s an ability to act more decisively than when you’re a hired CEO who has to be more concerned about others questioning his decisions in the short term…
…Matt: [00:32:39] This is a more thematic question. Bill, you might be the right person to answer this. I think with SVB and the rate at which that run on the bank happened, especially compared to quarterly results, which showed there was a racing mismatch and an interest rate exposure, but it seemed to happen very quickly. And you would not refer to those as sticky assets. Once it started, it happened very quickly.
Do you think that that was signal or indicative of anything having changed with the overall markets and the ability to move funds faster, technology, and the way that information can spread? Do you think there’s anything that happened with that event, which should be a broader concern for the overall system?
Bill: [00:33:22] It has certainly made all bankers attuned to how easy it is to shift funds. It doesn’t mean getting in your car, driving to a branch, waiting in line; instead, you’re pulling out your iPhone and you move funds in seconds. But while there’s been a lot of focus on how technology has made it easier for depositors to transfer funds out of a bank, I think the real thing here was, at SVB, how much of the money was tied to the same industry and some non-financially sophisticated people who look to the same leaders to help them with their financial decisions.
So you have one of those leaders tweet that he thinks people should move money out of SVB. And most of the depositors at SVB were probably followers of that person. I think where Alex has talked about First Citizens having generational relationships, SVB couldn’t possibly have been in a more different position. They couldn’t make a reasonable estimate of how sticky their deposits were because they haven’t had them for long enough. When I was talking in the introduction about the three risks, credit risk wasn’t a problem at SVB.
Liquidity risk was a big problem because they had very liquid deposits and not-so-liquid assets and then duration mismatch was a problem because the deposit side of the balance sheet floated completely with interest rates and the asset side did not. So one of the issues is not only the investment community, but also the regulators were so backward looking and thinking about banking risk that credit risk is what got all the banks in trouble in the GFC.
So the focus in the regulatory environment has been on minimizing credit risk. And ironically, we’ve had some of the large bank managements that we’ve talked to post-SVB say that regulators were actually pushing them to extend duration by buying mortgage backs just like SVB had done. So it’s funny. You think about you want to protect your capital base and you also want to protect your income stream, but sometimes those are at odds with each other.
And the regulators were more worried about what would happen to the earnings of the banking system if low rates or negative rates persisted or came into being than they were about what happens if rates go from nothing to 5% to 6% in a very short period of time. So I think there are some pretty unique factors at work here in addition to this technology change that’s attracted all the focus of how easy it is now for people to change where they bank.
Matt: [00:36:16] Absolutely. Very interesting and a lot to learn from that experience. With all that in mind, as investors, when you are generally approaching banks, I think you’ve referenced some of the metrics here in terms of ROE, book value. How do you think about this as value investors yourselves? How do you think about the industry? And with all of those qualitative factors in mind and thinking about those when approaching any investment, how do you think about the actual valuation of banks?
Bill: [00:36:45] I think if you look at the past generation or two, where banks trade versus the S&P 500, they’ve typically sold at about two-thirds of the S&P 500 multiple. We think that kind of makes sense. I think it’s hard to argue that this is a better-than-average industry and difficult to say why banks should sell at 18x earnings when the S&P 500 sells there.
But at Oakmark, we’re always looking for opportunities of where prices get out of line with both their history and what we think fundamental value is. And today, the average bank sells at probably less than half of the S&P 500 multiple. So a larger discount than it has historically. And also, we would argue the industry itself is in much better shape than it was at the time of the GFC, especially regarding credit risk. We think there’s an unusual opportunity in banking.
I mentioned earlier to us getting an opinion about the people in charge of various banks is one of the most important things because of the leverage and the opaqueness of the financial accounting, capital allocation is hugely important. One of the reasons that we think the industry is more attractive today than it was pre-GFC is almost all of the leadership teams of the large banks agree that when they cannot grow at the rate they want to making loans to creditworthy customers, they’re all willing to grow by shrinking the denominator today.
When there are organic growth opportunities, returning capital to the shareholders, both through dividends and share repurchase is central to our philosophy at Oakmark that we want managements that are comfortable giving capital back to the owners when they don’t have good growth opportunities. I think book value is a good starting point. A well-run bank ought to be worth book value.
It’s probably hard to get much more than twice that in terms of what the underlying value could be. And it’s funny. I started in this business a little over 40 years ago, and one of the rules of thumb back then was that if you’re looking at a bank, the PE should roughly equate to its return on equity. So if it earns 8% on equity, it should sell at 8x earnings. If it earns 15% on equity, it could sell at 15x earnings.
And through all of the changes in the past 40 years and whether interest rates have been near zero or up over 10%, the math behind that very simple PE should about equal return on equity still approximately holds today. So for us, that’s one of the other metrics that we would look at is how big a discount PE is available in the market relative to the return on equity the company is achieving…
…Bill: [00:40:47] One last thing I’d throw in there, Matt. First Citizens has two classes of stock. There’s the regular Class A stock that has normal voting rights and then when Alex mentioned earlier that the family has about 40% voting control despite not owning nearly that much of the underlying share base, it’s because their Class B shares have super voting rights.
And a strange anomaly in the market today is investors are so concerned about illiquidity that these super voting shares that don’t trade nearly as frequently as the regular vote shares, actually trade at about a 10% discount to the normal voting shares.
So especially for individual investors who don’t need to accumulate a large position to be meaningful to their assets and who can be in complete control of when they decide to liquidate a position in First Citizens, to us to get paid 10% to get extra voting rights seems like it makes a really good deal an even better deal.
Matt: [00:41:57] That’s very interesting. Same dividend rights and everything else. It’s just a matter of liquidity that explains that discount?
Bill: [00:42:05] Yes.
Matt: [00:42:06] When you look at the business model moving forward, there used to be these general rules of thumb with where interest rates were and whether that would be positive or negative for the banks. Just thinking about First Citizens specifically, they have the acquisition and integration of the acquisition, which will, I assume, take some time to fully integrate and to smooth out.
But anything else that you think about as a key driver of the business model and not that I’m asking you to make a rate call, but how important are interest rates in terms of impacting their earnings outlook and anything else that’s a key variable in driving the outlook for the business?
Alex: [00:42:47] It’s an interesting and kind of ironic dynamic the industry has found itself in for a really long period of time through the 2010s. We were sitting here thinking we need to get off this 0% interest rate floor because the high-quality deposit franchise and the low-quality deposit franchise, they can both pay roughly the same amount when rates are zero and the high-quality deposit franchises as a result, under-earn.
So there was this idea that higher rates would be extremely helpful because you’d be able to flex that high-quality deposit franchise value and actually realize some of it by paying less than lower-quality peers on your liabilities. That happened, and you’ve seen meaningful net interest margin expansion for those banks, but now the industry has found itself in a different predicament, which is that the unrealized losses have increased so much from higher interest rates that at this point, it’s not clear if the banks are still beneficiaries of rates being this high.
And in a lot of circles, for some banks, there’s fear around what if rates go higher, those unrealized losses could expand…
…Bill: [00:54:23] When I started in this industry, I think there were 14,000 some banks a little more than 40 years ago, and we have maybe 25% of that number today, just over 3,000. I think both in politics and in the communities at large, people have a misperception that the small number of banks relative to what we used to have means banking has become more inconvenient. We actually have more than twice as many branches today as we had 40 years ago.
So the distance somebody has to drive to their local bank has actually gone down. My hope is that from a regulatory perspective and even just a political perspective that this drumbeat that we need to keep all the small banks independent that, that might die down. There are such strong economies of scale in banking that to earn the same rate of return, a small bank has to take incrementally much more risk, and it’s not good for the system.
And when the small banks get acquired, they inherit better technology, more economies of scale, better regulatory compliance. I think it’s actually good for the system to see more mergers and acquisitions in banking. And people say like, oh, wouldn’t it be awful if we get down to a world where we only had 20 banks in the United States? I’m not so sure why that would be a bad thing.
4. When The Stock Market Plunges… Will You Be Brave Or Will You Cave? – Jason Zweig
In fact, if I could give you only one piece of financial advice, it would be this: Spend less time studying your investments and more time studying yourself. That’s because how much money you make in an investment often depends far more on how you behave than on how it does. “It’s people that lose money,” says Patrick Chitwood, an investment adviser in Birmingham with a Ph.D. in psychology. “It’s not investments.”
To see what I mean, look at PBHG Growth Fund. In the second half of 1990, when the U.S. stock market slipped 6%, this small-stock fund skidded 21%. Over the next two years, investors yanked out nearly all their money, shriveling PBHG’s assets from $12.5 million to $3.5 million. Bad move: From the end of 1990 through 1995, PBHG Growth’s 35.1% annual return transformed a $5,000 investment into $22,503. Someone who fled PBHG and earned the overall market average of 16.6% annually would have turned $5,000 into just $10,776 — less than half what PBHG produced.
That huge $11,727 difference is the price of poor self-knowledge. Chances are, most of the people who bailed out of PBHG had honestly believed they were long-term investors who could stomach the fund’s high risks. They were wrong…
…In 1975, Steven Spielberg’s movie about a killer shark hit the theaters, and suddenly Americans were terrified of going into the ocean — even though there had been a grand total of only 66 shark attacks in U.S. waters over the preceding 10 years.
“We tend to judge the probability of an event by the ease with which we can call it to mind,” explains Kahneman. But that’s a bad way to assess risk; an event does not become more likely to recur just because it is recent or memorable. In 1975, for instance, the odds of being attacked by a shark in U.S. waters were about one in 300,000,000 — and, since sharks don’t go to the movies, the odds certainly didn’t worsen after the film was released. But because Jaws was so vivid and fresh in people’s minds, it drowned out all the statistical proof that beaches were safe.
Similarly, after the October 1987 stock market crash, panicked investors virtually stopped buying stock mutual funds for the next year and a half. Instead, investors snapped up bonds and cash — despite the overwhelming historical evidence that stocks had outperformed them both over the long run…
…Then there’s the “near miss.” Say the winning number in a lottery was 865304. John picked 361204; Mary picked 965304; Peter picked 865305. Which of them is the most upset? Most people agree that Peter feels the worst, because he came “closest” (even though all losing numbers are equally incorrect). As Kahneman explains, “People become more frustrated in a situation where a more desirable alternative is easy to imagine.”…
…A group of people was asked which is longer, the Panama Canal or the Suez Canal, and then asked how certain they were that their answer was correct. Among those who were 60% certain, 50% of them got the answer right — meaning that this group was 10% too sure. But among those who were 90% certain, only 65% got the answer right, meaning that this group was 25% too sure.
The more convinced we are of our knowledge, the bigger the gap is likely to be between what we actually know and what we think we do. Such overconfidence leads us to inflate the value of our own skill, leading to what psychologists call the illusion of control. Years ago, when a Spanish national lottery winner was asked how he selected the ticket number, he answered that he was positive his lucky number ended with 48 — because, he said, “I dreamed of the number seven for seven straight nights. And seven times seven is 48.”
No wonder Kahneman says that “When people take risks, it’s often because they don’t understand the odds. One of the hardest challenges is to know just how little you really know.” If you overestimate your skills and knowledge, you may be unrealistically optimistic about your investment prospects. That will worsen your shock when the market tumbles, increasing the odds that you will panic and bail out at the bottom.
One group of people is asked to assess the probability that the population of Turkey is more than 5 million; another is asked the likelihood that Turkey’s population is less than 65 million. Then both groups are asked for their best guess of Turkey’s population. The first group guesses 17 million; the second, 35 million. (The correct answer: roughly 63 million.)…
…According to a recent study by the American Stock Exchange, 38% of young middle-class investors check their investment returns at least once a week, 17% check them monthly, 10% check yearly — and the rest “never” check. While never is not often enough, once a week is way too often. The more frequently you check on your investments, the more volatile they will look to you. My advice: Force yourself to check the value of your investments no more than once a month…
…If you make a habit of dollar-cost averaging into a particular mutual fund — investing a fixed amount at regular intervals — you’ll stand a better chance of sticking with it than if you’d thrown in a big chunk of money all at once. Think of Ulysses in Homer’s Odyssey, who resisted the deadly lure of the Sirens’ songs by having his crew “tie me hard…to hold me fast in position upright against the mast.”…
…Let me leave you with these thoughts. Successful investors control the controllable. You can’t prevent the market from crashing someday, but you can control what you do about it. The more honestly you understand your own attitudes toward risk, the more likely you are to thrive no matter what the market throws at you.
5. Charlie Silk’s 150-Bagger – Peter Lynch
My candidate for the world’s greatest amateur investor is Charles Silk. I met this fellow Bostonian halfway around the world, at a reception at the Bible Lands Museum in Jerusalem in 1992. We were part of a trade mission to Israel sponsored by the state of Massachusetts. It turned out we had a few friends and many stocks in common. On a bus ride to historic sites, we had our first extended chat. Not about historic sites, but about Blockbuster Entertainment, Charlie’s most successful pick.
Charlie bought Blockbuster many splits ago, in 1984, for $3 a share. It wasn’t called Blockbuster yet. It was called Cook Data Services, which fit into Charlie’s area of expertise. He had had his own data-processing company, which had fallen on hard times, and he was forced to shut it down. He was sitting home, doing telemarketing for a software outfit and wishing he could find another way to make a living.
Cook Data Services solved his problem. The shares he bought for $3 apiece a worth $450 today, so his $10,000 investment became a living in itself. Thanks to this one exciting stock, he was able to abandon telemarketing and devote himself to his favorite hobby – looking for more exciting stocks…
…Call Charlie a lucky man for stumbling onto Cook Data Services, but luck didn’t make him a millionaire. The hard part was holding on to the stock long enough to get the full benefit. After the price had doubled and then tripled, he didn’t say to himself, I’ll take my profits and run, like many investors who invent arbitrary rules for when to sell. He wasn’t scared out when the price dropped, as it did several times, and he ignored the highly publicized negative comments made by forecasters and “experts” who knew less about Blockbuster than he did. He had the discipline to hold on as long as the fundamentals of the company were favorable. It was not a guess on his part. He was doing his homework all along.
In my investing career, the best gains usually have come in the third or fourth year, not in the third or fourth week or the third or fourth month. It took eight years for Charlie to get his 150-bagger, but in a way, he’d been preparing for the opportunity since college…
…He searches for good stocks among small companies that are relatively debt free and have been beaten down in the market, to the point that they’re selling for less than cash in their bank accounts. “I’m paying nothing for the company itself,” Charlie says in his rich Boston accent. “The only thing I’m risking is my patience.”…
…Now we move forward to 1984. Another hot IPO market was followed by a collapse at the end of that year. Small high-tech stocks suffered the most. For Charlie, it was 1974 all over again, except this time he didn’t have to bother with pink sheets. NASDAQ had launched its computerized trading system.
He surveyed this latest wreckage. Cook Data Services caught his eye. It sold software programs to oil and gas companies – right up Charlie’s alley. It came public in 1983 at $16 a share and quickly rose to $21.50, but the price had fallen to $8 when Charlie began tracking it. He was still tracking when year-end selling dropped the price to $3.
This was the kind of risk Charlie liked to take: a company with no debt and $4 a share in cash, selling for $3. But cash in itself is no guarantee of success. If a company is sick to begin with, it has to spend its cash to stay alive. Cook Data was quite healthy. Its revenues had increased four years in a row. “To produce a record like that,” Charlie says, “they had to have something on the ball.” His $10,000 investment was as much as he could scrape up. It made him one of the largest shareholders.
A few months after Charlie bought his shares, Cook Data announced it was moving away from data services and into the “consumer area.” The company’s president, David Cook, had an ex-wife who was a movie buff apparently; she still had some influence and convinced him to open a video superstore in Dallas…
…One of the most interesting things the company sent Charlie was an independent study on the future of the video-rental industry. “When I read that thing,” Charlie says, “I found out that 30 percent of American households owned VCRs, and that eventually 60-70 percent would own these machines. [This estimate turned out to be conservative.] All these millions of people with VCRs were going to need an endless supply of tapes.”
It got more interesting when he went to the library and looked up company filings in the SEC’s Official Summary of Security Transactions and Holdings. He saw that two different groups, the Sanchezes from Texas and Scott and Lawrence Beck from Illinois, had become major shareholders. Scott Beck was coauthor of the video study and obviously impressed by this own research. Charlie also learned that revenues from the Dallas superstore had more than doubled in the first three months of operation. His sources at the company confirmed these numbers and told him how crowded the store was. It was amazing, they said. People were driving from as far as 30 miles away…
…In six months from 1984 to early 1985, he’d already made five times his money. Some of his friends were urging him to be sensible and to take his wonderful profit. This is where many investors would have tripped up, but having missed some spectacular gains in the 1970s, Charlie kept focus where it belonged – not on the stock price but on the company itself…
…A week or so before the offering, Charlie was reading Alan Abelson’s column in Barron’s, when he came to a pan of Blockbuster. Abelson’s argument: Who needs another video store?
Abelson’s comment produced a spate of selling that caused the stock price to drop 15 percent. Charlie was a fan of Abelson’s, but he was confident that he knew more about Blockbuster. The sales figures from Blockbuster showed that people were flocking to the new superstores…
…Toward the middle of 1987, Charlie started worrying about the stock market in general and the fact that he had too much money riding on one issue. So he sold a portion of his shares in the high 30s, just before the big correction in October of that year. Short term, this proved to be a smart move, because Blockbuster stock promptly fell by half, to $16. But longer term, he would have been better off to hold on to every share to get all of Blockbuster’s tenfold gain over the next four years.
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