By learning to overcome their biases, investors gain a vital tool to help them reach their financial goals.
Nearly 18 years ago, pioneer behavioral scientist Richard Thaler called for the “end of behavioral finance” as a separate discipline—because all of finance would soon be behavioral (Thaler 1999). Behavioral finance as a distinct approach is very much alive and well, and it is being applied in a variety of contexts within the industry. In this article, let’s take a brief tour through the history of behavioral finance—from a practitioner’s perspective—and see where things might take us over the next 10 years.
Where It All Started
Over the past three decades, researchers in economics and psychology have cataloged dozens of different biases that affect how investors make choices and cause them to deviate from their ideal economic outcome. This work has challenged the once common view in economics (and finance) that individuals are narrowly selfish and rational, using all available information to maximize their expected utility.
For example, investors often have different risk preferences based on how options are described: A serious medical procedure with a 90% survival rate elicits a very different response than one presented having a 10% mortality rate. This observation builds on the work of two trailblazers in the field, psychologists Daniel Kahneman and Amos Tversky, who began their work on what is known as Prospect Theory in the 1970s. Their insights, and those of other behavioral researchers, had broad implications for understanding human decision-making, and its consequences for finance became clear right away. In a sample study, researchers found that a related bias causes investors to hold on to losing stocks far longer than they should, to avoid realizing a loss (aka the disposition effect).
Researchers discovered numerous other biases that specifically affect financial behavior as well, such as illusory superiority (the vast majority of investors think they are better than average), overconfidence (beliefs about oneself outpacing the reality), and recency bias (believing that past performance predicts future performance). Behavioral research like this has come to broad public awareness in books such as Thaler and Cass Sunstein’s Nudge (2008), Dan Ariely’s Predictably Irrational (2008), and Kahneman’s best-selling book Thinking, Fast and Slow (2011).
Behavioral Finance in the Finance Industry
For practitioners in finance, the wealth of research from the 1970s to today has increasingly seeped into practical work, especially recently. Ten years ago, at Barclays, Greg Davies set up one of the first applied behavioral science teams in finance. “I had to start every single meeting with, ‘Has anyone heard of behavioral finance?’” he says. “I was often faced with reactions between skepticism and indifference” (Davies 2017). Now, behavioral finance is well known, and the interest is palpable. Michael Liersch, Merrill Lynch’s head of behavioral finance and goals-based consulting, says, “I get so many calls a day from advisors who are eager and excited…about behavioral finance” (Liersch 2017).
The intersection between behavioral finance and practice can been seen in terms of four distinct themes: cataloging investor biases, arbitraging market anomalies, developing tools to avoid and overcome these biases, and exploiting people’s biases for profit.
Much of the early work in the field—and a significant portion of the materials that practitioners develop and promulgate today— focuses on cataloging and educating investors about their numerous biases. The implicit or explicit assumption is that savvy investors, properly informed and educated about these biases, can overcome them. In reality, the effectiveness of this approach has been difficult to establish in the field.1
Side by side with the study of individual biases, researchers and practitioners have investigated how investment mistakes might aggregate up into market anomalies such as asset-price bubbles and crashes, the equity premium, and the small-cap premium. Significant debate occurred, and continues to occur, about whether and how behavioral anomalies could persist over time (Sornette et al., 2016), with some researchers arguing that limits to arbitrage, including trading costs and industry incentives, allow them to persist (for example, Barberis and Thaler 2003). The implication of this work is a potential for profit: If arbitrage is possible, well-informed, behaviorally savvy investors might exploit these predictable irrationalities.