Fooled by Randomness (2001) is a collection of essays on the impact of randomness on financial markets and life itself. Through a mixture of statistics, psychology and philosophical reflection, the author outlines how randomness dominates the world.
The basis of all empirical science is a process called induction: we infer things about the nature of the world based on our observations. Thus from seeing hundreds of white swans, we might infer (mistakenly) that all swans are white.
Unfortunately, this approach carries an inherent problem, illustrated by the famous example of black swans as stated by philosopher John Stuart Mill: “No amount of observations of white swans can allow the inference that all swans are white, but the observation of a single black swan is sufficient to refute that conclusion”.
This is known as the problem of induction, and it means no theory can ever be proved right, only wrong (by a single “black swan”). Hence theories are constantly being proved wrong and replaced by better ones.
A similar mindset can be prudent in investing as well: Always consider the possibility that your theories and assumptions may be proved wrong, and examine how such a development would affect your portfolio.
A financial risk manager who ignores this advice saying, “This has never happened before, hence it won’t tomorrow either,” may well be unpleasantly surprised one day.
In fact, he also errs by assuming the past is a relevant sample of what the future holds. What if things have changed? How could you infer anything about the color of swans if their pigmentation was constantly changing?
Yet wherever people are involved, like in the stock market, there will be constant change through adaptation. For example, if stock prices always rose on Mondays, rational investors would all buy stocks on Sundays, thus changing the market dynamic and eliminating the effect.
We can never be sure any theory is right – things constantly change and the next observation may prove us wrong.