Here is your weekly dose of financial wisdom. This edition is dedicated to decision-making under uncertainty.
The Tragedy of the Empty Suit
Experts only play a role in some professions. Nassim Taleb argues that generally things that don’t move have experts while things that move have non-experts (empty suits).
Experts who tend to be experts: astronomers, test pilots, chess masters, accountants, physicists, grain inspectors, soil judges…
Experts who tend not to be experts: stockbrokers, college admission officers, political scientists, intelligence analysts, financial forecasters…
Professions that deal with the future and base their studies on the non-repeatable past have an expert problem.
The problem with these empty suits is that they don’t know what they don’t know.
The Scandal of Prediction
“It’s very hard to predict, especially the future.” — Danish proverb
The problem of prediction mainly comes from the fact that we live in a world where extreme events are rare and unpredictable but have vast consequences (Black Swans).
Hence, it doesn’t matter how often you are right, but how large your cumulative errors are. The frequency of success doesn’t matter if failure is too costly to bear.
We are better at predicting things that don’t move (e.g. lifetime of a chair) than things that move (e.g. Tesla stock price in 5 years) because the latter is prone to Black Swans.
Moreover, if you believe in free will you can’t truly believe in social science and economic projection. You cannot predict how people will act…
Forecasting without incorporating an error rate uncovers three fallacies:
Variability matters: don’t cross a river if it’s two meters on average. The policies we need to make decisions on should depend far more on the range of possible outcomes than on the expected final number.
Forecasts degrade as the projected period lengthens: the longer into the future, the harder it is to predict.
Most variables being forecast have a random character: we live in a world with extreme events that by definition are unpredictable.
Next time you come across an expert’s forecast, question the error rate of the procedure used.
But if it’s true we are really bad at predicting, what’s the alternative? Perhaps the answer is not to try to predict what’s unpredictable…
Answers in Cemeteries
The neglect of silent evidence is endemic to the way we study comparative talent, whether entrepreneurs, investors or footballers.
We tend to ignore the cemetery because people who fail don’t write memoirs.
Yet, the cemetery is full of unknown entrepreneurs who shared the same traits as Elon Musk (courage, risk taking, optimism etc). There may be some difference in skills but what truly separates the two is luck.
Many successful people will try to convince you that their achievements couldn’t be accidental. Similarly, a gambler who wins at roulette seven times in a row will explain to you that the odds against such a streak are so low that he must have incredible skills in picking the winning numbers. But if you take into account the quantity of gamblers, it becomes obvious that such strokes of luck are bound to happen.
“Nobody accepts randomness in his own success, only in his failure.” — Nassim Taleb, Fooled by Randomness
In these situations, try using the reference point argument: don’t compute odds from the vantage point of the winner but from all those who started in the cohort.
To exercising moderate skepticism,