Advice, Gullibility, and Predictions

Of Note: Advice, gullibility, and predictions

Of note: “Investing Experts Urge ‘Do as I Say, Not as I Do’” in the Wall Street Journal of January 3, 2009, which talks of how even Nobel winners find it difficult to follow their own advice. A conclusion we may draw: it is critical in all matters, including and perhaps especially competitive strategy of all kinds, to take into account how we humans actually behave, not how we or “they” should behave.

Of note: “Why We Keep Falling for Financial Scams” in the WSJ of the same date. Intriguing article about gullibility and how smart people fall can make bad decisions. The concept of a “feedback loop theory of investor bubbles” (by Yale economist Robert Shiller) in scams and other investment crazes is powerful. (See also It’s Working!)

Of note: “The Doomsayers Who Got It Right,” the WSJ, January 2, 2009. A somewhat alarming article because it implies that we ought to listen to the doomsayers who “got it right,” which is alarming because they are saying more doom. (Note the possible feedback loop theory of investor anti-bubbles.) I don’t know if the doomsayers are right or wrong; it’s largely and perhaps entirely unknowable.

In any case, what we want is not to find a person who said something that came true and then listen to what that person says for the future. Unfortunately, and with absolutely zero disrespect intended, we don’t know whether a person is right because of luck or because of perspicacity, especially because those who got it right use different methods and rationales. Remember too that the people who predicted incorrectly were as smart, articulate, persuasive, and renowned as those who got it right. And timing is important. One of the predictors in the WSJ article made his calls eight years in advance. Acting on his calls at the time he made them would have meant missing out on seven years of stock-market advances.

Rather, what we really want is to find a theory (in the sense of a model or system, not in the sense of an idea) that repeatedly, not anecdotally, predicts future events well. That’s how it works in science, where the scientific method is designed to foster testing, evaluating, and enhancing models, not people. I am not saying it’s easy. I am saying it is possible and it doesn’t have to be perfect to make an improvement.

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