Well maybe not ten, but Scott Sumner hits a bunch of my pet peeves in this post:
Commenters often present me with market anomalies, which supposedly “prove” the efficient markets hypothesis is wrong. I always respond that they’re just engaging in data mining. They retort that no theory that can’t be disproved is worth anything. But the EMH can be disproved. The tests have been done, and it passes. Sort of.
OK, that “Sort of” is a little odd, but clearly at this point, Scott is saying the EMH is a falsifiable theory. Let’s continue:
Finance professors have done many different tests of the EMH, and I’d guess 90% of the published tests (but only 5% of the actual tests) show that the EMH is wrong. (Yes, I’m pulling these numbers out of thin air, but you get the point.) They’ve found January effects, small stock effects and value stock effects. They’ve found the market does better when P/E ratios are low. They found the market does worse on rainy days (a study published in the AER!).
Boom, that’s it, right? These are all things that, prima facie, shouldn’t be true if the EMH is right. In fact, Scott himself agrees that these tests “show that the EMH is wrong”; don’t take my word for it. So case closed, right? Nope:
Of course you’d expect to find 5 anomalies for every 100 tests you do, and for the most part you only get published if you find an anomaly, and finance professors have a lot of computer power, so . . .
Here’s my analogy. Suppose Stephen Wynn was concerned that some mysterious gamblers were getting away with cheating at one of his casinos. He’d heard rumors, but had no proof, or even suspects. You are statistician brought in to investigate. You study 600 slot machines, and find 30 of them produced three cherries more often than you’d expect from mere chance. You suggest that the anomalous slot machines be destroyed. How should the casino owner react to that “investigation?” I’m guessing Wynn wouldn’t be impressed.
I’m not sure that’s a good analogy. But doesn’t matter, suppose it is. Let’s move on to what really bugs me:
To find out whether cheating is occurring you need to look at whether the winnings of gamblers are serially correlated. Are those who win once, more likely to win next time. That’s the proper test, indeed the only practical test, of whether people are cheating the casino. And it’s also the only test of the EMH. Don’t look for “the system,” the secret way to beat the stock market. Look for whether other people have found it. Look to see whether people who did better than average one year, tended to do better than average the next year. Don’t look for market anomalies—look for evidence that other people have found market anomalies.
Of course the study has been done. I recall that Fama and French found that mutual returns were approximately serially uncorrelated, but not exactly. There appears to be a slight serial correlation among the very best funds (top 3%), but not enough to give the average investor any advantage.
And that’s what I would have expected. The EMH is approximately true; indeed it’s almost impossible for me to imagine any other model of financial markets. But it’s not precisely true, again, just as you’d expect. After all, if the EMH were perfectly true then no one would have any incentive to estimate fundamental values.
Huh? This is the same trick that the evolutionary biologists pull–”Our theory is so right, that even when the data don’t support it, it just proves how right it is.”
Note that I’m not saying, “The EMH is wrong,” or even that, “Evolutionary biology doesn’t fit the data.” What I have said over and over is that the EMH is a way of viewing the world. No matter what happens, Scott Sumner would say, “See? Just what I would have expected.”
Don’t believe me? Look at this:
A smart person like Eugene Fama should have been able to come up with both the EMH, and its limits, by just sitting in a room and thinking. Much as David Hume got the QTM by imagining what would happen if everyone in England woke up one morning with twice as much gold in their purses. Or Fisher’s theory of inflation and nominal interest rates. Or Cassel’s purchasing power parity. Or Friedman/Phelps’ natural rate hypothesis. Or Muth and rational expectations. Certain ideas are simply logical, and that’s why I have no doubt that despite all those economists on the left arguing the EMH has been discredited, it will still be taught in every top econ/finance grad program 100 years from now, whereas fiscal stimulus will be long gone from macro textbooks.
See? If you can derive a theory by sitting in a room and thinking, then it is not an empirical theory. So let’s drop the charade and stop pointing to all of Fama et al.’s “tests” of it. Just admit it is a very useful way of viewing the world, like supply and demand. Have the courage, as Ludwig von Mises did, to say that it is an a priori approach that could not possibly be falsified.
But instead, just about every EMH supporter I have read thinks it is an empirical claim, open to falsification. They just don’t realize that they can explain everything. If sophisticated hedge funds are making a bunch of money, that just proves how hard it is to “beat the market”; you need to spend a bunch of quants and computers.
And if the hedge funds all blow up, while guys like Mark Thornton called the housing bubble in 2004? Nope, just shows Thornton got lucky, and how hard it is to beat the market. (I’m not exaggerating; that’s exactly what Jeremy Siegel said in the WSJ, defending the EMH, as I explain at the bottom of this article.)
So whether hedge funds make a killing or blow up, it just shows how rational markets are. The EMH–a scientific theory, subject to falsification–passes its test with flying colors.