In the latest chapter of his life-long and eventually triumphal effort to promote index investing, John Bogle explains what lays at the foundation of his philosophy: ‘my first-hand experience in trying but failing to select winning managers’ (p. 6). In 1966, as the new 37-year old CEO of Wellington Management Company, Bogle decided to merge the firm with ‘a small equity fund manager that jumped on the Go-Go bandwagon of the late 1960s, only to fail miserably in the subsequent bear market. A great — but expensive — lesson’ (p. 7), which cost him his job.
It reminded me of another self-confessed failure, as recounted by Eugene Fama, who in his young days worked as a stock market forecaster for his economics professor, Harry Ernst: ‘Part of my job was to invent schemes to forecast the market. The schemes always worked on the data used to design them. But Harry was a good statistician, and he insisted on out-of-sample tests. My schemes invariably failed those tests’. (My Life in Finance, p. 3).
I can’t help seeing both incidents as instances of Festinger’s cognitive dissonance. It runs more or less like this: 1) I know a lot about economics and stock markets. 2) I am smart — truth be told, very smart. 3) I could use my brains to predict stock prices/select winning managers and make a lot of money. 4) I can’t. Therefore: it must be impossible. I think this goes a long way towards explaining the popularity and intuitive appeal of the Efficient Market Theory in academia.
The theoretical underpinnings of the EMT were set by the Master himself, Paul Samuelson, who in 1965 gave the world the Proof that Properly Anticipated Prices Fluctuate Randomly, followed in 1973 by the Proof that Properly Discounted Present Values of Assets Vibrate Randomly.
Typical academics are keen to take these as conclusive demonstrations — derived from first principles, like Euclidean theorems — of the impossibility of market beating. But the Master knew better. At the end of ‘Fluctuate’ he wrote:
I have not here discussed where the basic probability distributions are supposed to come from. In whose minds are they ex ante? In there any ex post validation of them? Are they supposed to belong to the market as a whole? And what does that mean? Are they supposed to belong to the “representative individual”, and who is he? Are they some defensible or necessitous compromise of divergent expectation patterns? Do price quotations somehow produce a Pareto-optimal configuration of ex ante subjective probabilities? This paper has not attempted to pronounce on these interesting questions.
And at the end of ‘Vibrate’:
In summary, the present study shows (a) there is no incompatibility in principle between the so-called random-walk model and the fundamentalists’ model, and (b) there is no incompatibility in principle between behaviour of stocks’ prices that behave like random walk at the same time that there exists subsets of investors who can do systematically better than the average investors.
Then in 1974 he reiterated the point in crystal clear terms, addressed to both academics and practitioners on the first issue of the Journal of Portfolio Management:
What is at issue is not whether, as a matter of logic or brute fact, there could exist a subset of the decision makers in the market capable of doing better than the averages on a repeatable, sustainable basis. There is nothing in the mathematics of random walks or Brownian movements that (a) proves this to be impossible, or (b) postulates that it is in fact impossible. (Challenge to Judgment, p. 17, his italics).
And for the EMT zealots:
Many academic economists fall implicitly into confusion on this point. They think that the truth of the efficient market or random walk (or, more precisely, fair-martingale) hypothesis is established by logical tautology or by the same empirical certainty as the proposition that nickels sell for less than dimes.
The nearest thing to a deductive proof of a theorem suggestive of the fair-game hypothesis is that provided in my two articles on why properly anticipated speculative prices do vibrate randomly. But of course, the weasel words “properly anticipated” provide the gasoline that drives the tautology to its conclusion. (p. 19).
There goes ‘Bogle’s truth’. And the irony of it is that in his latest piece Bogle reminisces on how, as he read it at the time, ‘Dr. Samuelson’s essay … struck me like a bolt of lightning’ (p. 6). A hard, obnubilating blow indeed.
There was, nevertheless, a legitimate reason for the fulmination. Samuelson’s Challenge to Judgment was a call to practitioners:
What is interesting is the empirical fact that it is virtually impossible for academic researchers with access to the published records to identify any member of the subset with flair. This fact, though not an inevitable law, is a brute fact. The ball, as I have already noted, is in the court of those who doubt the random walk hypothesis. They can dispose of the uncomfortable brute fact in the only way that any fact is disposed of — by producing brute evidence to the contrary. (p. 19).
He was referring to Jensen (1968) and the copious subsequent literature presenting lack of evidence on identifying a consistent subset of long-term outperforming funds. What Samuelson missed, however — and still goes largely unnoticed — is that the ‘risk adjustments’ to fund and index returns used in these studies are based on definitions of risk — as volatility, beta and the like — that presume market efficiency. To his credit, Eugene Fama has always been very clear on this point, which he calls the joint hypothesis problem:
Market efficiency can only be tested in the context of an asset pricing model that specifies equilibrium expected returns. […] As a result, market efficiency per se is not testable. […] Almost all asset pricing models assume asset markets are efficient, so tests of these models are joint tests of the models and market efficiency. Asset pricing and market efficiency are forever joined at the hip. (My Life in Finance, p. 5–6).
Typically, outperforming funds are explained away, and their returns driven to statistical insignificance, by the ‘higher risk’ they are deemed to have assumed. But such risk is defined and measured according to some version of the EMT! It is — as James Tobin wryly put it — a game where you win when you lose (see Tobin’s comment to Robert Merton’s essay in this collection).
It was precisely in defiance of this game that Warren Buffett wrote his marvellous Superinvestors piece, which sits up there next to Ben Graham’s masterwork in every intelligent investor’s reading list. As in his latest shareholder letter, Buffett used the coin-flipping story, fit for humans as well as orangutans, to point out that past outperformance can be the product of chance. But then he drew attention to an important difference:
If (a) you had taken 225 million orangutans distributed roughly as the U.S. population is; if (b) 215 winners were left after 20 days; and if © you found that 40 came from a particular zoo in Omaha, you would be pretty sure you were on to something. So you would probably go out and ask the zookeeper about what he’s feeding them, whether they had special exercises, what books they read, and who knows what else. That is, if you found any really extraordinary concentrations of success, you might want to see if you could identify concentrations of unusual characteristics that might be causal factors. (p. 6).
Hence he proceeded to illustrate the track record of his nine Superinvestors, stressing that it was not an ex post rationalisation of past results but a validation of superior stock picking abilities that he had pre-identified ex ante.
So let’s do a thought experiment and imagine that Buffett 2007 went back 40 years to 1967 and wagered a bet: ‘I will give 82,000 dollars (about 500,000 2007 dollars in 1967 money) to any investment pro who can select five funds that will match the performance of the S&P500 index in the next ten years’. Would Buffett 1967 have taken the bet? Sure — he would have said — in fact, I got nine! And after nine years, one year prior to the end of the bet, he would have proclaimed his victory (I haven’t done the calculation on Buffett’s Tables, but I guess it’s right). Now let’s teleport Buffett 2016 to 1976. What would he have said? Would he have endorsed those funds or recommended investing in the then newly launched Vanguard S&P index fund?
Here is then why I am disoriented — and I’m sure I’m not alone — by Mr. Buffett’s current stance on index investing. To be clear: 1) I am sympathetic to his aversion to Buffett impersonators promoting mediocre and expensive hedge funds. 2) I think index funds can be the right choice for certain kinds of savers. 3) I think Jack Bogle is an earnest and honourable man. However, as a grateful and impassioned admirer of Buffett 1984, Buffett 2016 puzzles me. Like the former, the latter agrees with Paul Samuelson against ‘Bogle’s truth’: long term outperformance, while difficult and therefore uncommon — no one denies it — is possible. But while Buffett 1984 eloquently expanded on the ‘intellectual origin’ (p. 6) of such possibility, and on the ex ante characteristics of superior investors, Buffett 2016’s message is: forget about it, don’t fall for ex post performance and stick to index funds.
Notice this is not a message for the general public: it is addressed to Berkshire Hathaway’s shareholders — hardly the know-nothing savers who may be better served by basic funds. Buffett is very clear about this: buying a low-cost S&P500 index fund is his ‘regular recommendation’ (p. 24), to large and small, individual as well professional and institutional investors — noticeably including the trustees of his family estate (2013 shareholder letter, p. 20).
Great! There goes a life-long dedication to intelligent investing. You may as well throw away your copy of Security Analysis. Alternatively, you may disagree with Mr. Buffett — nobody is perfect — and hope he reconsiders his uncharacteristically unfocused analysis. From the Master who taught us how to select good stocks one would expect equivalent wisdom on how to select good funds. It is not the same thing, but there are many similarities. As in stock picking, there are many wrong things one can do in fund picking. Past performance is no guarantee of future performance. Expensive stocks as well as expensive funds deceptively draw investors’ attention. There is no reason why large stocks or large funds should do better than small ones. Don’t go with the crowd. And so on. Similarly, just like Mr. Buffett taught us how to do the right things in stock picking, he could easily impart comparable advice in fund picking.
Here is the first one that comes to mind: look at the first ten stocks in a fund and ask the fund manager why he holds them. If he makes any reference to their index weight, run away.
Originally published at Bayes.