The theory, central to Taleb'
s critique of standard statistics, that many real-world distributions have "
fat tails"—extreme events are much more likely than the normal distribution predicts. In a normal distribution, extreme events are virtually impossible; in
fat-tailed distributions, they happen regularly. Financial markets, pandemics, wars—all are
fat-tailed.
Fat Tails Theory argues that we have been using the wrong statistical tools, underestimating risk, pretending the world is safer than it is. The theory explains why
Black Swans are not as rare as we think: they're rare in thin-tailed distributions, normal in
fat-tailed ones.
Fat Tails is the mathematics of humility, the quantification of our ignorance, the proof that we live in a world where the improbable happens—and we'd better be ready.
Example: "His risk models assumed
normal distribution, so extreme events were virtually impossible. Then the crash came—a
fat-tail event, impossible in his model, inevitable in reality.
Fat Tails Theory had warned him: the world is not normal; extremes happen. He'd ignored it. His models were precise and wrong."
