Four pillars of investing
I taking a different tack in today’s post. It contains a note I have written to William J. Bernstein about a book he has written. The text is as follows:
“I just finished reading the recently published second edition of The Four Pillars of Investing. I have been an active investor in common stocks for many years. I’m always looking to learn new things about investing and your book certainly delivered on that front.
I particularly liked the sections on the psychology of investing and the business of investing. I agree with you that the vast majority of investors with asset allocations to equities are best off with index funds. For U.S. exposure, best is an S&P 500 index ETF.
I do disagree with a number of things in your book, hence this note. It is written in a spirit that we learn from intelligent discussion and debate.
Mad or wise crowds
Let me start at p.64 and the section titled “The Collective Wisdom of the Market”. I don’t think the stock market is particularly wise. You note on p.132 that markets go bonkers on the upside and on the downside. That doesn’t seem so wise.
As support for your wisdom theory, you refer on p.64 to Francis Galton’s 1906 conclusions when visitors to a fair guessed of the weight of a dressed ox. The amazing accuracy of the average of the guesses was a pure statistical phenomenon. It only worked because each of the guesses was made independently.
Let me suggest a thought experiment. Imagine that Galton had set up a blackboard and asked the first guesser to write their guess on the board for all in the crowd to see. Imagine that the second guesser then came up, and after looking at the blackboard and seeing the first guess, wrote down their figure. And so on until eight hundred or so fair goers had written their guesses on the board after having had a chance to see all previous guesses. We now know a lot about anchoring, groupthink and social proofing and other behavioural psychology phenomena.
I’ve no doubt the crowd’s guess would have been seriously affected by what the first few guessers wrote down. The difference between Galton’s observations and my thought experiment is that in mine the data are not independent. That means you can’t rely on the statistical conclusion in the thought experiment.
The stock market is very much akin to my thought experiment. There is no collective wisdom in the stock market. As Robert Shiller pointed out years ago, the stock market is much more volatile than the underlying earnings. A chart plot of earnings and prices cross only occasionally, suggesting that most of the time prices are either higher or lower than fair value.
At p.56 you write about Louis Bachelier and his 1900 doctoral dissertation suggesting the random nature of stock market prices. This idea was picked up on by Burton Malkiel in his incredibly popular book A Random Walk Down Wall Street mentioned by you at p.246 as one of the places to start to learn about financial theory.
The problem is that changes in stock prices are not random. In the super short term they are very largely random. But ‘very largely’ is not the same as random. In math and physics pure randomness can only take place when the data points are completely independent. On the super short time scale, they are subject to the blackboard phenomenon mentioned in my thought experiment. Very short-term price changes on the stock market essentially cannot be predicted, but that does not make them random. Over days, weeks, months and years stock prices become progressively less random since they will reflect underly fundamentals.
Serena Williams or Mr. Market
At p. 70 you say that most of the time investors are in a tennis game where they are playing against Serena Williams. I prefer to think I’m playing against Ben Graham and Warren Buffett’s funny little fellow Mr. Market who has incurable emotional and behavioural problems. I’m not saying the game is easy. In fact, it’s tough mostly because of our own behavioural frailties.
You suggest at p.70 that no matter how many stocks you own you won’t be properly diversified. You say this is because 4% of companies provide all the return in the stock market. This is wrong. The 4% is essentially a function of their oversized market cap. There are lots of superb companies that offer excellent real total returns that are not in the mega cap camp. The haystack offers excellent choices up and down the market cap spectrum.
You say at p.73 that Warren Buffett favors value stocks. I don’t think he would agree with you. He favours companies that make a high return on invested capital generating excess capital that can be reinvested at high rates of return.
In discussing the two customary approaches to investing ‘value’ and ‘growth’ Buffett confesses to earlier fuzzy thinking and says:
“In our opinion, the two approaches are joined at the hip: Growth is always a component in the calculation of value, constituting a variable whose importance can range from negligible to enormous and whose impact can be negative as well as positive. In addition, we think the very term ‘value investing’ is redundant. What is ‘investing’ if it is not the act of seeking value at least sufficient to justify the amount paid?” (Buffett, The Essays of Warren Buffett: Lessons for Corporate America. 1998) p.85. (Emphasis added)
Risks when market is down
You write at p.136 that investing at the market bottom in the midst of the Great Financial Crisis on March 9, 2009 would have been akin to playing financial Russian roulette at a million dollars a throw. The contrary is the case. A meltdown panic usually offers up stocks in companies at beaten down prices. During that period, I purchased shares in a clothing company I had been hoping to buy for several years at a bargain price. I was able to buy shares in Canada’s largest bank at a fraction of its book value. I was also able to buy shares in a mining company for less than the value of the cash in the till. The mines came for free. No, it was a wonderful time to be putting money into the market.
At a number of places, you write about the potential for higher returns from value stocks. It is a key point summarized on p. 257. I believe your thesis may suffer from what, on p. 194, you call the “engineer’s mistake” which results from what you call the “stationarity fallacy”. This fallacy can be a problem in all models. You point out that the relationship between current and future returns based on CAPE may not be the same. This is true for CAPE and it is also true for all price earnings ratios and all price to book value ratios. You mention in passing the rise of company investment in intangibles of lasting value. In fact, there has been a massive shift over the last 30 years. Companies are investing much more capital in intangibles than in tangibles.
But here’s the key point: The accounting treatment is different. Capital investment in tangible capital assets is capitalized. Almost all investment in intangibles capital assets is expensed. This reduces the reported earnings of companies which invest in intangibles. It even gives them a tax break. They have the asset but their taxes are reduced. In mathematics terms, the input for earnings is non stationary which leads to the ‘’engineer’s mistake”. It gets worse. Massive company investment in intangibles of lasting value is creating valuable intangible assets but not appearing on balance sheets. As a result, price to book value also suffers from the non-stationarity of the underlying data leading to a stationarity fallacy. Taken together p/e and p/b have gone off the rails as a way of valuing companies. Ironically, if you invest in so called value stocks you are investing in yesterday’s economy.
I found the book a stimulating read. Hopefully my note will give you some food for thought.
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