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Over the weekend I finished reading Nassim Taleb’s Fooled By Randomness. It’s a great read, the kind that helps you stay on your toes and forces you to look at your investment process (or really any decision process) with a critical eye. Taleb’s intent is to show how—and why—most people, especially in the investment profession, take the quality of their knowledge too seriously. He argues that randomness plays a much larger role than most of us think or would like to admit. His message, however, is not “it is all random,” but rather just that “it is more random than we think,” and that our decision processes should take this randomness into account. There is a plethora of thought-provoking ideas presented in the book, and I thought I’d share a random few with you.

On mistakes
"A mistake is not something to be determined after the fact, but in light of the information until that point." (p.56)

We know all about this here at Special Ops. This is why we insist on extra-comfy margins of safety and are constantly looking at our upside-vs.-downside scenarios. We cannot in hindsight say that a portfolio stock that has fallen was a mistake just because it fell. We knew it could fall, we just liked our odds that it would move in the other direction. Of course, on the other hand, we could call a stock that has risen a mistake if we miscalculated the risk-return when we purchased it, given the available information. We are process-oriented, not results-oriented. Over time, the former produces better results (ironically) than the latter.

Problem of induction
As the scientists among us (not me!) probably know, there are two kinds of theories: those that have been proven wrong and those that have not yet been proven wrong. That may sound dismal, but it touches on an important divide in the ways we learn things. Basically, there are two paths.

We can deduce our knowledge, where we go from the general to the specific: All public companies must pay taxes. ROIC is a public company. Therefore, ROIC must pay taxes.

Or we can induce our knowledge, where we go from the specific to the general: Over the last 100 days, HTH has not purchased a distressed bank. Therefore, HTH will never purchase a distressed bank.

You can see the problems with the second conclusion. The problem of induction is also known as the black swan problem. After seeing 1000 white swans, you cannot conclude that all swans are white, but seeing just one black swan can prove that NOT all swans are white. The infrequency of rare events does not make them any less real, but it can lull us into a false sense of confidence. Just because something hasn’t happened before doesn’t mean that it won’t—and, just as importantly, just because that something has happened before doesn’t mean it will repeat. The concept of the past’s past is useful—when that rare event happened in the first place, nothing in the past at the time could have foretold its occurrence.

Firehouse effect
If you put a group of individuals in a community, over time you might observe that they suddenly seem to have a lot in common—they might watch the same TV shows, read the same books, vote in the same way. This is known as the firehouse effect, named for the similarities studies have shown to develop among firemen in the same firehouse. Such convergence is a part of human nature…and we must fight it with all we’ve got. That’s one reason we have TMF services with conflicting philosophies, and it’s also one of the best functions of these boards. We love to answer questions—and have members ask and answer questions—but we also love that you all are so open about challenging us (and each other!). One key takeaway from Taleb’s book is that we are not programmed to understand randomness, regardless of how active we are in countering it. Instead, the best solution is to install checks and bias-correction mechanisms into your decision processes. This is a perfect example.

Has anybody else read Fooled By Randomness, or have a recommendation on something similar? And if you guys like these notes, I can post more—as I said, there are a bunch of great tidbits in the book.

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