What is survivorship bias?

In finance, survivorship bias is the tendency to view stocks or funds that have ‘survived’ as an accurate representation of overall performance, while disregarding those stocks that have failed or been removed from the market due to poor performance or other factors. This can lead to traders making misguided decisions.

Highlights

Survivorship bias examples

Traders over-concentrating on stocks and funds that have been successful in the past and ignoring those that have failed could lead to an unbalanced portfolio. Moreover, it could lead to traders overestimating the performance of the entire stock market. 

Surviving stocks have generally outperformed the market, therefore only using them as a sample could result in an incorrect assessment of the overall market conditions.

Examples of survivorship bias can be found throughout the finance sector. In 2020, trader and software developer, Michael Harris, tested and wrote about the effect of survivorship bias on cross-sectional momentum on the Price Action Lab Blog.

In his test, Harris tested a trend following strategy on two different samples of quotes, one of the samples included delisted stocks and the other didn’t, hence serving as an example of survivorship bias.

The test was done on stocks from the Dow Jones Index (US30) and the S&P 500 (US500), in both cases ignoring the portfolio with survivorship bias performed significantly better, leading Harris to conclude:

“Not taking into account survivorship bias can lead to highly misleading results. In many cases, when survivorship and other sources of bias are added together, the actual results are random.”

Risks of survivorship bias

Survivorship bias could lead to overestimating the good performance of a trading strategy. Since stocks and funds that have failed would be excluded when evaluating the strategy’ performance, traders would be unaware of the full extent of the strategy’s losses.

It could also lead to a lack of diversification in portfolios, as traders focus on the strategies that they believe have proven successful in the past.

Other risks associated with this bias could include:

• Overconfidence. Survivorship bias could lead traders to overestimate their abilities and become overconfident in their trading decisions. This could lead to excessive risk-taking or a false sense of security, both of which may result in significant losses. 

• Ignoring risk. Traders may ignore the potential risks associated with a particular trading strategy or asset class as a result of the bias. 

• Overlooking other factors. Survivorship bias can also lead traders to overlook other important factors in their trading decisions, such as fundamental or technical analysis. This can lead to poor decision making and increased risk of losses.

Addressing survivorship bias

So, what steps can be taken to potentially mitigate survivorship bias in trading?

• Including data from failed stocks. This data could be used to get a better understanding of the risks associated with trading in stocks or funds that don’t survive.

• Using a wide range of data sources. Using a variety of data sources, including historical data, news sources and even competitor data could potentially help traders avoid survivorship bias.

• Backtesting tools. These tools enable traders to test their strategies in different market environments, this may help minimise survivorship bias.

• Using a diverse set of strategies. It could be harder to fall victim to survivorship bias when traders are not overly dependent on a single strategy.

• Test strategies over a longer time-frame. Traders should also test their strategies over a longer time-frame to ensure that their strategies are not overly dependent on recent market conditions.

Conclusion

Survivorship bias may be explained as the tendency to focus on the performance of stocks or funds that have survived over a given period of time, while ignoring those that have been delisted or gone bankrupt. This bias can lead to skewed results when analysing past performance.

There are a number of steps traders may take to minimise survivorship bias, including making sure they look at data from failed stocks and funds and testing strategies over longer periods of time to ensure that their data isn’t overly reliant on the market conditions of that time period.

However, it’s important to keep in mind that even if traders are able to mitigate the effects of the bias, there is always risk involved in trading. As a result, traders should be sure to do their own thorough research before making any decision and to never trade with more money than they can afford to lose.