Glossary · Economic ideas
Black swan
A black swan is a rare, unexpected event with huge effects that people explain only afterwards, like a market crash or a pandemic.
Also called: black swan event, tail risk, fat tails, outlier
Falls worse than −17.0% in a month. A bell curve expects one such month in about 2,600 years.
In plain words
For centuries Europeans were sure that all swans were white: every swan anyone had seen was white. Then, in 1697, Dutch explorers found black swans in Australia. One sighting overturned a “fact” built on millions of observations. The writer Nassim Nicholas Taleb used that story to name a black swan: a rare event nobody expected, with enormous effects, which afterwards everyone explains as if it had been obvious.
In markets, black swans are the crashes and shocks that models said were next to impossible: the crash of October 1987, the 2008 financial crisis, the market panic of March 2020.
Taleb’s lesson is not to predict them (by definition you can’t) but to be ready for them: not to depend on anything that a single rare event could wipe out.
Example
Months that “shouldn’t happen”
Many financial models assume that monthly returns follow a bell curve. A century of US stock prices shows how badly that fails in the tails.
- Since 1926, the S&P 500’s price has changed by +0.6% in an average month, with a typical swing (standard deviation) of 4.4%.
- A fall of more than four standard deviations, worse than −17.0% in a month, should come about once in 2,600 years on a bell curve.
- In fact it happened 5 times in 1,210 months. The worst: −26.5% in Nov 1929, then −24.0% in Apr 1932.
Rare is not the same as impossible. Models that say “once in a thousand years” are often wrong about the tails.
One level deeper
Taleb’s book The Black Swan came out in 2007, a year before the financial crisis that seemed to prove his point. His three marks of a black swan: it lies outside regular expectations, it has an extreme impact, and people invent explanations for it afterwards that make it look predictable.
Statisticians call the underlying problem fat tails: in many real-world data sets, from stock returns to city sizes to book sales, extreme values are far more common than a normal, bell-shaped distribution predicts. A model that assumes a bell curve will underestimate the chance of disaster.
Not every crash is a black swan: many were widely warned about, just not timed. Taleb argues that the best defense is to be robust: little debt, some spare cash, no single point of failure.
Every month of the S&P 500 since 1926
Each bar is one month’s change in the S&P 500’s price. Most months sit in a calm band of a few percent; then, every few decades, a month drops off the chart. The biggest jumps came in the early 1930s too: wild months tend to come in clusters. The line marks four standard deviations below the average month: −17.0%.
The numbers behind the chart
| Date | Change in the month |
|---|---|
| Jan 1926 | 1.5% |
| Dec 1930 | −6.7% |
| Dec 1940 | −4.1% |
| Dec 1950 | −0.4% |
| Dec 1960 | 2.4% |
| Dec 1970 | 6.8% |
| Dec 1980 | −1.6% |
| Dec 1990 | 4.3% |
| Dec 2000 | −3.4% |
| Dec 2010 | 3.6% |
| Dec 2020 | 4.1% |
| Dec 2022 | −0.1% |
| Dec 2023 | 5.0% |
| Dec 2024 | 1.4% |
| Dec 2025 | 1.7% |
| Oct 2026 | 0.7% |
Why it matters
The events that shape history and markets most are often the ones nobody planned for: wars, pandemics, crashes, breakthroughs.
Risk models that ignore fat tails can make a portfolio or a bank look far safer than it is, which was part of what went wrong in 2008.
Preparing for the unknown, with savings, low debt and diversification, helps whatever the next shock turns out to be.
A common mistake
Myth: A “once in a century” event won’t happen in my lifetime.
In fact: Markets have had several of them. Since 1926 the S&P 500 has had 5 months that a bell curve would expect about once in 2,600 years. Labels like “once in a century” usually come from models that underestimate the tails.
Questions people ask
What is an example of a black swan event?
The crash of October 19, 1987, when the Dow Jones index fell 22.6% in one day; the 2008 financial crisis; the market crash of March 2020. (Taleb himself called the pandemic a white swan: it had been widely predicted, even if markets were caught off guard.)
Who came up with the black swan theory?
Nassim Nicholas Taleb, a former options trader turned writer, in Fooled by Randomness (2001) and The Black Swan (2007).
What are fat tails?
A distribution has fat tails when extreme outcomes happen much more often than a normal bell curve predicts. Stock market returns are a classic example.
Read more on BigCapital
About the numbers
- The numbers on this page are recalculated from the data every night; the sources are listed at the end of the page.
- S&P Composite price and total return since 1871, and US consumer prices: Robert J. Shiller, Online Data (shillerdata.com); total return with dividends reinvested monthly, calculated by BigCapital.
- Monthly changes use monthly averages of daily S&P 500 closes, which smooth out single-day crashes such as October 19, 1987. The average, the standard deviation and the bell-curve odds are computed from the same months since 1926.
- This page explains a term. It is not investment advice.