Experience Effects in Finance: Foundations, Applications, and Future Directions

October 5, 2021

Experience Effects in Finance: Foundations, Applications, and Future Directions
Ulrike Malmendier
Review of Finance, Volume 25, Issue 5, September 2021, Pages 1339–1363, https://doi.org/10.1093/rof/rfab020

This article establishes four key findings of the growing literature on experience effects in finance: (1) the long-lasting imprint of past experiences on beliefs and risk taking, (2) recency effects, (3) the domain-specificity of experience effects, and (4) imperviousness to information that is not experience-based. I first discuss the neuroscientific foundations of experience-based learning and sketch a simple model of its role in the stock market. I then distill the empirical findings on experience effects in stock-market investment, trade dynamics, and international capital flows, highlighting these four key features through a weighting function that captures impact of experience on people’s decision making. Finally, I contrast models of belief formation that rely on “learned information” with models accounting for the neuroscience evidence on synaptic tagging and memory formation.

The neuroscientific and theoretical underpinnings of experience effects as well as the empirical findings have allowed us to discern some of the key aspects of how our past experiences influence our beliefs, attitudes, and decision-making. In particular, I emphasize four baseline findings: (1) the notion of a long-lasting imprint, which is slowly altered over time as individuals accumulate new experiences, (2) the observation of a bias towards more recent experiences, (3) the domain specificity, or lack of cross-fertilization, in experience-based belief formation, and (4) the robustness of these findings to “learned knowledge,” including that of professionals and experts.

Both the theoretical and the empirical findings have then pointed us towards further implications of experience effects and these four features. The notion of a long-lasting imprint gives rise to (1) persistent cross-cohort differences, and recency bias triggers (2) a stronger (over-)reaction of younger cohorts to recent shocks than older cohorts. Moreover, domain specificity invites (3) more asset- or market-specific research; and the robustness to “learned knowledge” invites (4) more analyses of professional, highly trained subjects such as doctors, fund managers, or central bankers. An angle in need of theoretical development is work moving beyond information-based theories–in the sense “information” is currently understood. On the empirical side, the applicability of ‘experience effects’ within finance has already proven to be far-reaching.

There are also numerous applications to consumption and to inflation expectations in macro-finance, especially monetary economics. For all of these potential applications, researchers will benefit from the increasing availability of within-person “big data.” These data sources allow us to distinguish standard information-based explanations from attributing effects to personal experiences, and to make progress on answering some of the open questions.