Black Swan Events: What They Are, Real Examples, and Why You Can't Predict Them

A black swan event is something rare, enormous in its consequences, and only "obvious" after it happens. That's the whole definition. Nassim Nicholas Taleb, who popularized the term in his 2007 book The Black Swan (Investopedia), boiled it down to three traits: it's an outlier nothing in the past pointed to, it carries an extreme impact, and afterward we invent a story that makes it look predictable. His shorthand is "rarity, extreme impact, and retrospective (though not prospective) predictability." (The New York Times, book excerpt)

That last part is the one that should bother you. We don't just fail to see these things coming. We rewrite history so we can keep believing we would have.

Where the name comes from

For centuries, "all swans are white" was the kind of statement you could bet your house on, because before Europeans reached Australia, people in the Old World were convinced every swan was white (The New York Times, book excerpt). Then in January 1697, Dutch skipper Willem de Vlamingh's expedition found a river in Western Australia full of black swans and named it after them; he rowed some ten miles up what we now call the Swan River (Australian Dictionary of Biography). Taleb's point is that one sighting wiped out a "truth" built on millions of confirmations (The New York Times, book excerpt).

That's the asymmetry. A thousand white swans prove nothing. One black one proves a lot.

The turkey who trusted the data

Taleb's classic illustration is a turkey. It's fed every day for a thousand days, and every meal seems to confirm that the farmer cares about it. Its confidence peaks on the last day before Thanksgiving (Taleb and Blyth, Foreign Affairs, 2011). The story goes back to a chicken in Bertrand Russell's 1912 book The Problems of Philosophy, used to show the problem of induction (Wikipedia, "Turkey illusion").

The joke is on the turkey, but the turkey is most of us. Stable data feels like safety. Sometimes it's just the fattening period.

Real examples (and one that wasn't)

September 11, 2001. Taleb himself puts it squarely in the category. "September 11th was definitely a black swan," he told Bloomberg in March 2020 (The Sounding Line, quoting Taleb on Bloomberg). It fits all three traits: almost nobody had a frame for it, it reshaped the world, and the "warning signs" got assembled afterward.

Long-Term Capital Management, 1998. A hedge fund built on sophisticated mathematical models and led by a team that included two Nobel laureates lost 44% of its value in August 1998 alone. In September, a group of 14 banks and brokerage firms put in $3.6 billion to head off its imminent collapse (Federal Reserve History). The models assumed the future would rhyme with the past. It didn't.

The Swiss franc, January 15, 2015. The Swiss National Bank dropped its cap on the franc and caught markets by surprise, and the currency jumped as much as 30% against the euro in chaotic trading (BBC News). Days earlier, the SNB's vice-chairman had called the cap the cornerstone of its policy (swissinfo.ch). If you were short the franc with leverage, your models said you were fine right up until they didn't.

Not a black swan: COVID-19. Here's the twist people miss. Taleb got genuinely irritated when people slapped the label on the pandemic. He called it a "white swan" (The Sounding Line), something he, Bill Gates and others had predicted, and something he had warned in January 2020 should be killed "in the egg" (The New Yorker). "Black swan" isn't a fancy word for "bad surprise." If the warnings were sitting on the table and you ignored them, that's not randomness. That's negligence with good PR.

Why you can't predict them (and why that's the wrong goal)

These events live in what Taleb calls fat tails (The New Yorker), where the rare event isn't just a bit unlikely but a different universe of outcome. His complaint is that the bell curve, the default tool of forecasting, ignores large deviations while making us feel we've tamed uncertainty (The New York Times, book excerpt). Bell curves are polite. Reality isn't.

There's also a human problem. We build our sense of risk from whatever's in front of us, which means your risk model is basically your news feed. The scariest thing on your screen this week is probably not the thing that gets you.

So the useful question isn't "what's the next black swan?" Taleb has said people keep asking him for a list of the next ones, and that the question misses his point entirely (The New Yorker). The better question is: what happens to me when one hits?

How to live with them

This is where it stops being trivia and starts being strategy, and it's the idea the whole Money section is built on. Our take, building on Taleb:

• Don't be the turkey. Long stretches of calm aren't evidence of safety. Ask what would have to be true for the streak to end.
• Kill the risk of ruin first. Any bet that can wipe you out eventually will. The casino survives every gambler's lucky night because the house always wins on expected value. Be the house where you can.
• Barbell it. Keep most of your life boringly safe and put a small slice into wild, asymmetric bets with capped downside and big upside. That's the shortcut barbell, and it works for careers and portfolios. Apparently it works in the bedroom too: the erotic barbell makes the case that the lukewarm middle is what kills desire, and our kink field guide maps the far end.
• Go past robust. Taleb's bigger idea is building things that gain from disorder (Penguin Random House, Antifragile). We walk through it in how to be antifragile.

The bottom line

It's the event your model said couldn't happen, and the one everyone swears afterward was obvious. You won't forecast the next one. You can make sure it doesn't take you out, and maybe set yourself up to catch some of the upside when it lands. For the long reads that pick this apart from every angle, browse the series index.

Sources

1. Investopedia: Black Swan in the Stock Market
2. Taleb, N. N. (2007). The Black Swan, chapter excerpt, The New York Times, April 22, 2007
3. Van Lohuizen, J. (1967). Vlamingh, Willem de. Australian Dictionary of Biography, Vol. 2
4. Taleb, N. N. & Blyth, M. (2011). The Black Swan of Cairo. Foreign Affairs 90(3)
5. Wikipedia: Turkey illusion
6. The Sounding Line (March 31, 2020): Nassim Taleb on Bloomberg
7. Fleming, M. & Liu, W. Near Failure of Long-Term Capital Management. Federal Reserve History
8. BBC News (January 15, 2015): Swiss franc soars as Switzerland abandons euro cap
9. swissinfo.ch (January 15, 2015): Swiss National Bank scraps exchange rate ceiling
10. The New Yorker: The Pandemic Isn't a Black Swan but a Portent of a More Fragile Global System
11. Penguin Random House: Antifragile: Things That Gain from Disorder by Nassim Nicholas Taleb