Survivorship Bias

We often hear stories about successful people. Entrepreneurs who built global companies, investors who made fortunes in the stock market, and individuals who overcame difficult circumstances to become famous can be inspiring. But there is something we tend to overlook. We rarely hear as much about the people who didn't succeed. Imagine that 100 people in a small town decide to start their own businesses. Five become extremely successful, while the other 95 either close their businesses or fail to earn as much as they had hoped. However, the news and television programs are much more likely to feature the five successful entrepreneurs. If we only hear their stories, we might mistakenly believe that starting a successful business is easier than it actually is. This is an example of survivorship bias, which occurs when we focus on the people or things that succeeded or survived while overlooking those that failed or disappeared. As a result, we may reach conclusions that do not accurately reflect reality. One of the most famous examples of survivorship bias comes from military aircraft during World War II. At the time, the Allied forces were trying to reduce the number of aircraft lost to enemy fire. Adding armor could improve an aircraft's protection, but additional weight could also reduce its flight performance. Therefore, deciding which parts of the aircraft needed the most protection was an important problem. Researchers examined the damage on aircraft that had returned from missions. Some areas had many bullet holes, while others had relatively few. Wouldn't it make sense to reinforce the areas with the most bullet holes? A statistician named Abraham Wald studied the problem from a different perspective. He recognized that examining only the aircraft that returned could leave out crucial information. If an aircraft could be hit repeatedly in a particular area and still make it home, that area might be relatively capable of withstanding damage. On the other hand, areas with fewer bullet holes on returning aircraft might be the very places where damage was more likely to cause an aircraft to crash. Therefore, rather than simply reinforcing the areas with the most bullet holes, researchers needed to account for the aircraft that never returned. Looking only at the planes in front of them could not provide a complete picture. A similar problem occurs in stock investing. Today, we are familiar with companies such as Apple, Microsoft, and NVIDIA, which have experienced tremendous growth. Looking at their historical stock prices, it may seem that anyone who bought their shares many years ago could have made a fortune. Indeed, some companies have delivered extraordinary returns over long periods. But does that mean anyone could have become wealthy simply by buying shares of promising companies and holding them for many years? Not necessarily. Many companies that once attracted considerable attention from investors eventually lost ground to competitors, experienced financial difficulties, or went bankrupt. Some businesses that once dominated their industries no longer exist. We easily remember the companies that survived and became successful, while the names of unsuccessful companies gradually fade from memory. The important point is that we could not necessarily have predicted today's winners in the past. We now know which companies experienced remarkable growth, but investors 10 or 20 years ago could not have known with certainty which businesses would succeed among the many available choices. Survivorship bias can also distort the way we analyze historical investment performance. For example, imagine someone selecting the companies currently included in the S&P 500 and calculating how much money an investor would have made by investing in them 20 years ago. The S&P 500 is a stock market index that tracks approximately 500 leading large publicly traded U.S. companies. However, the companies included in the S&P 500 today are not the same as those included 20 years ago. Over time, some companies were removed because their businesses declined, while others were added. Some disappeared through mergers, acquisitions, or delistings. What happens if we calculate historical returns using only the companies that are still in the index today? We are effectively choosing investments using information about the future that investors did not have at the time. As a result, the calculated returns may look better than what investors could realistically have achieved. Of course, not every company removed from an index is a failed business. Some disappear because they are acquired in deals that benefit their shareholders. The important lesson is that a fair evaluation of historical investment performance must consider the full range of companies that investors could actually have chosen at that time. Survivorship bias can also appear when comparing investment funds. If we examine only funds that have remained active and produced strong returns over many years, it may seem that professional investors generally achieve excellent results. But the picture can change when we also include funds that closed because of poor performance or were merged into other funds. So how can we avoid survivorship bias? The most important habit is to ask what might be missing from the information we see. When we hear about a successful investor, we should consider whether other investors used similar strategies but failed. When we examine a company whose stock price rose dramatically, we should also investigate what happened to other companies that attracted attention during the same period. We also need to distinguish between a successful outcome and a high probability of success. Just because someone made a fortune through a risky investment does not mean that the investment strategy was likely to succeed. That person may have been fortunate, while others who made similar decisions suffered substantial losses. This does not mean that studying successful people or companies is pointless. Success stories can offer valuable lessons. However, to understand why someone succeeded, we should also examine the cases in which people faced similar circumstances but failed. Ultimately, survivorship bias teaches us that what we cannot see can be just as important as what we can see. Understanding why certain companies survived and succeeded in the stock market matters, but understanding why others disappeared matters just as much. Good investment decisions begin not with simply following visible success stories, but with examining both successes and failures.