What seems impossible isn't. For centuries, people believed that swans could only be white and then it happened: a black swan was spotted. The term has evolved to represent a rare and large-impact event that makes sense only after the fact. Black Swans exist in the financial world - just think of any Black Monday.
Take the Dow Jones Industrial Average. For 91 years, from its inception in 1896 to early fall 1987, the Dow had fallen only twice by more than 10 percent in one day - and both falls had happened during the infamous 1929 stock market crash. Nothing in the Dow's history pointed to the possibility that it could fall as it did on October 19, 1987, when the unexpected and the inconceivable happened: the Dow tumbled 22.6 percent and wreaked havoc on investors' portfolios. The returns of 201 trading days were wiped out in a single day. Black Monday, a rare event, was considered a Black Swan.
A Black Swan has three attributes:
- First, it is an outlier, which means it lies outside the realm of regular expectations, because nothing in the past can convincingly point to its occurrence.
- Second, it carries an extreme impact.
- Third, despite being an outlier, plausible explanations for its occurrence can be found after the fact, thus giving it the appearance that it can be explainable and predictable.
In short, a Black Swan is characterized by rarity, extreme impact and retrospective predictability.
Professor Javier Estrada, head of the Financial Management Department at IESE, looks at the impact of Black Swans, or outliers, on the market's long-term performance. His article, "Black Swans and Market Timing: How Not to Generate Alpha," focuses on "large" daily swings, which are more common than one might think. Just a few large daily swings can more than overturn the return of a portfolio obtained over a long period of time. Interestingly, it is assumed that this should happen infrequently, if at all. Yet, the evidence shows that these swings do happen, and far more often than would be expected.
Outliers Have a Massive Impact
Estrada's research focuses on outliers that are more than three standard deviations away from the mean. He also looks at the best and worst 10, 20 and 100 daily returns. The article does not attempt to formally define a Black Swan; instead, it analyzes how the markets (and the returns) absorb the big swings.
The article's ultimate goal is to quantify the impact of outliers on long-term performance. Other questions that are answered include:
- Do investors obtain their long-term returns smoothly and steadily over time, or is their long-term performance largely determined by the return of just a few outliers?
- Are investors likely to predict successfully the best days to be in and out of the market?
- Should investors attempt to time the market?
The evidence, based on more than 160,000 daily returns from 15 international equity markets, is clear: Outliers have a massive impact on long-term performance.
On average, across all 15 markets, missing the best 10 days resulted in portfolios 50.8 percent less valuable than a passive investment; and avoiding the worst 10 days resulted in portfolios 150.4 percent more valuable than a passive investment.
Given that 10 days represent less than 0.1 percent of the days considered in the average market, the odds against successful market timing are staggering.
Good Days and Bad Days
Here's an example: $100 invested in the U.S. stock market in 1990 turned into $401 by the end of 2006, but missing the best 10, 20 and 100 days would have reduced the terminal wealth to $250, $172 and $22 respectively.
In the world of finance, most assume that returns will be normally distributed
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