The selection of strategies and analyses is wrongly constructed by many trading and investing strategies: they ignore an essential factor, known as survivorship bias. This cognitive bias may be highly distorting our perception of success and failure in financial markets. Without recognizing this bias, traders build flawed strategies based on incomplete data with unrealistic expectations and, ultimately, losses.
Let’s take the example of a revealing historical experience from World War II to illustrate this problem. The insight into how the U.S. military managed return aircraft is interesting in this regard. As such, the case of analyzing return aircraft sums the great lessons survivorship bias gives. These lessons leap from the financial landscapes of the late 20th century into the current setup.
We will discuss survivorship bias in this article, including its impacts on trading and backtesting. As a bonus, we’ll go over some practical steps you can take to avoid being a part of this problem. By the end of it, you will learn how to shape more robust investment strategies with regard to imperceptible failures that often help create market outcomes.
Understanding Survivorship Bias
What Is Survivorship Bias?
Survivorship bias is what one calls the logical fallacy of overemphasizing surviving entities and forgetting those which failed. It’s an optimistic observation because we only see the “survivors.” In trading terms, it comes out in performance where only successful stocks or trading strategies are cited, instead of the thousands that fail.
Historical Example: World War II Planes
The U.S. military in the period studied sent back aircraft to determine where they should be reinforced. Initially, they noticed spots with patterns of bullet holes and deduced that those areas ought to receive more armor. Statistician Abraham Wald countered with an explanation: the military should reinforce parts of aircraft that received no damage at all. Why? Those aircraft returned that had the hits in those damaged areas and managed to return; those that were hit in the undamaged areas probably did not survive.
This crucial lesson shows looking beyond the failures would lead to bad decisions-an insight directly applicable to trading and investing.
The Survivorship Bias in Trading
Backtesting and Performance Metrics
The survivorship bias can grossly distort the results of backtesting. In fact, most traders testing strategies against historical data use datasets that comprise only currently listed stocks. This means that delisted stocks, which could have been bankrupted or failed, are not included in such datasets. Thus, the outlook becomes skewed towards a certain group of surviving stocks, which may have looked excellent, but it does not reflect the actual reality that the universe of stocks could have faced.
A study by Hendrik Bessembinder indicates that, if short-term Treasury bills are taken as a kind of proxy for short-term investment, the vast majority of publicly traded corporations have not outperformed this measure. In other words, whereas only a few exceptional performers garner much attention, millions of others failed or simply performed abysmally.
Published in the literature and online about trading, it appears that there are yet an endless array of strategies that focus on tracking history’s great performances based on past performances. Perhaps someone publishes an article on Seeking Alpha that entails an all-star strategy. The issue is that if that strategy only selects winners based off this historical basis, it risks falling victim to survivorship bias. In actuality, most stocks do not continue to perpetuate their past successes; most stagnate or decline.
Reality-Life Examples of Survivorship Bias
Example Mutual Funds Performance
A classic example of survivorship bias in mutual funds is reporting only the performance of those who are still active. If a fund underperforms to the point where it’s closed, its performance data are typically not included in the overall calculation. This artificially creates a sense that mutual funds, as a whole, consistently put their money in places that deliver strong results when, in truth, many funds fail to survive over the long haul.
Example 2: Stock Market Indices
Indices of the S&P 500 and other stock market tracking indexes only include firms that meet specific, discretionary criteria on performance and on market capitalization. The past performance of such an index is actually computed only of those companies which have passed the scrutiny of the market by remaining in it. This can give the illusion that an index has performed better than it really has, since failures among those firms not included in the index are not considered in computation.
Elimination of Survivorship Bias in Trading
1. Utilize Databases with a Full Listing
Beat the bias by using databases like Norgate Data that encompass listings of stocks and delisted stocks. That may give you the complete picture of the performance of the stocks instead of only those surviving ones.
2. Make Use of ETFs and Indices
Another excellent strategy of minimizing exposure to survivorship bias is investing in ETFs or index funds tracking a broad universe of companies, which contain quite a diverse universe of stocks that are closer to market performance.
3. Strong Backtesting Mechanisms
It is important to include delisted stocks and failures in the data set when backtesting a trading strategy so that there are more realistic expectations for later performance.
4. Do Not Be Afraid of Failure in Strategy Development
The trader also needs to take an account of what works – but also what doesn’t work. From the point of view of analyzing failures in strategy development, it can be implied why certain strategies or moves didn’t pan out, which helps the trader improve the approach.
Conclusion
Survivorship bias is a hidden pitfall that leads to wrong trading strategies and erroneous performance results. Based strictly on success stories, a trader might miss the broader landscape of failures that affect the outcome of the market.
In order to be able to get practical techniques that turn out to represent market realities for a trader or investor of any caliber, the understanding and recognition of survivorship bias are important. Using rich sources of data, with diversified investment vehicles, and refining your backtesting method can all help toward these ends.