Recency (Availability) Bias – Economics – Investopedia
Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and behavioral finance. Adam received his master's in economics from The New School for Social Research and his Ph.D. from the University of Wisconsin-Madison in sociology. He is a CFA charterholder as well as holding FINRA Series 7, 55 & 63 licenses. He currently researches and teaches economic sociology and the social studies of finance at the Hebrew University in Jerusalem.
In behavioral economics, recency bias (also known as availability bias) is the tendency for people to overweight new information or events without considering the objective probabilities of those events over the long run.
Availability bias matters for the financial markets, as memory of recent market news or events can lead investors to irrationally believe that a similar event is more likely to occur again than its objective probability. As a result, investors may make decisions to sell into bear markets, or buy into bubbles, since crashes and bubbles can be salient in the minds of individuals as they occur.
A well-known example of recency bias is that people tend to overreact to news of a shark attack that has recently occurred. Shark attacks, especially deadly ones, are extremely rare—killing just a handful of people each year. In 2021, for example, there were only 73 reported unprovoked shark attacks worldwide, in line with the previous five-year average of 72 incidents. Nevertheless, many fewer people swim in the ocean following reports of a shark attack, with many people believing the odds are far greater than they actually are. Indeed, after the 1975 blockbuster movie Jaws came out, the notion of an unprovoked shark attack became incredibly salient, leading to far fewer swimmers than in previous years.
For investors, availability bias affects the trading decisions that people make based on recent events or headlines, expecting such events to be more frequent than they actually are. During a market crash, people may adopt a negative outlook that assumes a bear trend will continue, even though the drawdown may merely be a correction. On the other hand, during asset bubbles, when prices reach levels that are no longer supported by fundamentals, people may continue buying under the false belief that the rally can only continue.
Whether it’s sharks or stocks, overweighting recent (i.e., available) information is irrational since it does not accurately reflect the true probabilities of future events.
Recency bias can be difficult to counteract because it plays on human emotions of fear and greed, which are powerful forces. Moreover, our brains are wired to put the most emphasis on recent events that are fresh in our memories as older events fade out of mind.
For investors, the best way to combat recency bias is to have an investment strategy and stick with it, regardless of short-term market volatility. Plan in advance how and when to rebalance your portfolio and when to reevaluate your long-term investment allocation. Of course, this is often easier said than done, as people may become overwhelmed with the impulse to take some action based on current events. One way to help ensure a hands-off approach is to use an automated investment program like a robo-advisor, which removes the human emotion from trading decisions.
One example of recency bias is in the case of the “hot hand,” or the sense that following a string of successes, an individual is likely to continue being successful. This was first identified in the sport of basketball (hence the hot hand), whereby players who have scored a number of baskets in a row are thought to keep scoring. As a result, players may pass that person the ball more often, even though their actual performance may not actually be above average.
In the markets, investors are similarly tempted to invest with fund managers who have recently outperformed the market over the course of several years, feeling that they, too, have the hot hand. In reality, portfolio managers who have had an unusually long winning streak often underperform their peers in future years.
Availability bias of the hot hand can even come into play when outcomes are independent of what has happened before, such as flipping a coin or the roll of a die. In this case, the bias takes on the form of the gambler’s fallacy, whereby people believe that a random event is more likely to occur just because it has in the past—or, alternatively, that it is likely to occur because it has not happened recently and so it is “due” to hit (even when the probabilities remain exactly the same per roll, spin, or flip).
Florida Museum. “International Shark Attack File: Yearly Worldwide Shark Attack Summary.”
Sunstein, Cass, and Richard Zeckhauser, via EconPapers. “Overreaction to Fearsome Risks.” Environmental and Resource Economics, vol. 48, no. 3, 2011, pp. 435–449.
Francis, Beryl, via JSTOR. “Before and After ‘Jaws’: Changing Representations of Shark Attacks.” The Great Circle: Journal of the Australian Association for Maritime History, vol. 34, no. 2, 2012, pp. 44–64.
Nofsinger, John R., and Abhishek Varma, via Ideas. “Availability, Recency, and Sophistication in the Repurchasing Behavior of Retail Investors.” Journal of Banking & Finance, vol. 37, no. 7, 2013, pp. 2572–2585.
Miller, Joshua B., and Adam Sanjurjo, via SSRN. “Surprised by the Gambler’s and Hot Hand Fallacies? A Truth in the Law of Small Numbers.” Econometrica, vol. 86, no. 6, 2018, pp. 2019–2047.
Goetzmann, William N., and Nadav Peles, via Wiley Online Library. “Cognitive Dissonance and Mutual Fund Investors.” The Journal of Financial Research, vol. 20, no. 2, 2014, pp. 145–158.
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