Survivorship Bias in Investment Performance
Survivorship bias occurs when we focus on the successful outcomes (e.g., companies that show earnings increases) while ignoring the many failures, leading to overestimating the probability of success. This cognitive bias distorts our perception of skill versus randomness.
THE IDEA
The Earnings Season: Fooled by the Results
Wall Street analysts, in general, are trained to find the accounting tricks that companies use to hide their earnings. They tend to (occasionally) beat the companies at that game. But they are neither trained to reflect nor to deal with randomness (nor to understand the limitations of their methods by introspecting—stock analysts have both a worse record and higher idea of their past performance than weather forecasters). When a company shows an increase in earnings once, it draws no immediate attention. Twice, and the name starts showing up on computer screens. Three times, and the company will merit some buy recommendation.
Just as with the track record problem, consider a cohort of 10,000 companies that are assumed on average to barely return the risk-free rate (i.e., Treasury bonds). They engage in all forms of volatile business. At the end of the first year, we will have 5,000 “star” companies showing an increase in profits (assuming no inflation), and 5,000 “dogs.” After three years, we will have 1,250 “stars.” The stock review committee at the investment house will give your broker their names as “strong buys.” He will leave a voice message that he has a hot recommendation that necessitates immediate action. You will be e-mailed a long list of names. You will buy one or two of them. Meanwhile, the manager in charge of your 401(k) retirement plan will be acquiring the entire list.
We can apply the reasoning to the selection of investment categories—as if they were the managers in the example above. Assume you are standing in 1900 with hundreds of investments to look at. There are the stock markets of Argentina, Imperial Russia, the United Kingdom, Unified Germany, and plenty of others to consider. A rational person would have bought not just the emerging country of the United States, but those of Russia and Argentina as well. The rest of the story is well-known; while many of the stock markets like those of the United Kingdom and the United States fared extremely well, the investor in Imperial Russia would have no better than medium-quality wallpaper in his hands. The countries that fared well are not a large segment of the initial cohort; randomness would be expected to allow a few investment classes to fare extremely well. I wonder if those “experts” who make foolish (and self-serving) statements like “markets will always go up in any twenty-year period” are aware of this problem.
When to use it
Evaluating investment managers using a comparison group that includes managers who closed or stopped reporting, where possible.
Interpreting business success stories: When reading about a startup that succeeded, remember that many others with similar strategies failed.
Assessing medical treatments: In clinical trials, ensure that dropouts are accounted for; survivorship bias can inflate apparent efficacy.
Checking whether historical stock-market returns include markets or companies that failed, rather than assuming the surviving record represents all original choices.
FROM THEORY TO EVERYDAY LIFE
In practice
Mutual Fund Performance
Many mutual fund rankings only include funds that have survived for a certain period. This ignores funds that closed due to poor performance, making surviving funds appear to have higher average returns than is realistic. Investors are thus misled about the true probability of picking a winning fund.
Company Earnings Stars
In Taleb’s hypothetical model of 10,000 companies, chance alone would be expected to produce 1,250 with three consecutive earnings increases. Selecting those companies afterward as 'strong buys' can make the streak look more informative about future performance than the model warrants.
A MOMENT TO REFLECT
Put it to work.
When you hear about a successful company or investor, do you also consider the many similar ones that failed?
How can you adjust your decision-making to account for the fact that past success may be due to randomness rather than skill?
Think of a time you were impressed by a 'hot streak' or track record. How might survivorship bias have influenced your judgment?
Often confused with
CONTINUE THE CONVERSATION
Source texts
- Fooled by Randomness The Hidden Role of Chance in the Markets and in Life (Nassim Nicholas Taleb)