When evidence goes wrong

There are two competing theories about financial markets:

1. Luck determines who wins and who loses in financial markets.

2. A skilled investor can expect to beat the market consistently.  


Which of the following provides evidence in this debate?

1. “I have beaten the market consistently for many years.”

2. “Many investors beat the market regularly.”

3. “Warren Buffet has beaten the market consistently.”

Answer: None of the above.

Why? Because for a given piece of information to constitute evidence for one theory and against another, it must be less compatible with one theory than another.

1, 2, and 3 are all equally compatible with both theories.


To actually test our theories, we must think of a way to differentiate the two in terms of their expected effects. For example, we might surmise that, if skillful investors can expect to consistently beat the market, more intelligent or more educated investors will on average outperform their less educated, less intelligent counterparts. Or we might suspect that investors who have outperformed the market in the past (and who we thus believe are of above average skill) are more likely to outperform the market in the future.

Of course, researchers have looked–repeatedly–at precisely this issue. And they consistently find that “skillful investors” (high-performing managers, famous financial columnists, etc.) do not outperform the market. Here are some explanations I’ve seen (the following are paraphrased commenters’ ideas):

1. “Skill might not last forever. Larry Bird would be a terrible NBA player today. Joseph Heller only wrote one good book.”

Right, but you expect Kobe Bryant to play better than an average NBA player next year. You expect a prize-winning author’s next book to be better than an average writer’s. In any given case, you might be wrong. But on average, you’ll be right.

2. “One might get only one opportunity to make skill count. Ray Kroc only got one chance to buy McDonald’s.”

Right, but is this usually true or occasionally true? If it’s usually true, “skill” becomes meaningless 99.9% of the time, and luck will almost always determine who wins and loses. If it’s only true occasionally, the high-performing, high-skilled investors should still outperform everyone else, and they don’t.

3. “Even if skill matters, there’s still a lot of luck involved. For example, only your skill relative to other investors matters, and the rationality and skill of other investors swings wildly.”

Yes, but just because we’re looking at a noisy data set doesn’t mean we shouldn’t still find a pattern, if one exists. High-skill investors should still beat everyone else on average in large data sets.

4. “As investors keep winning, they get larger funds and it’s harder to take advantage of arbitrage opportunities. Plus they get lazy and would rather play golf than look at data.”

These predictions are testable but have no empirical support. And again, just because skill (or work ethic) declines over time does not mean that the expected effects should be missing entirely.


I’ve heard a few other explanations. But let’s just end by summing up the story so far:

“Returns are due to luck.”

Skeptic: “No, some people win a lot in the stock market consistently.”

“The winners one year perform average the next.”

Skeptic: “Well, maybe X, Y, and/or Z,” where X, Y, and Z have varying levels of plausibility and relevance and none have empirical support.

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