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Do Investors Overweight Personal Experience? Evidence from IPO Subscriptions

Journal of Finance 2008 63(6), 2679-2702 open access

We find a strong positive link between past IPO returns and future subscriptions at the investor level in Finland. Our setting allows us to trace this effect to the returns personally experienced by investors; the effect is not explained by patterns related to the IPO cycle, or wealth effects. This behavior is consistent with reinforcement learning, where personally experienced outcomes are overweighted compared to rational Bayesian learning. The results provide a microfoundation for the argument that investor sentiment drives IPO demand. The paper also contributes to understanding how popular investment styles develop, and has implications for the marketing of financial products.

What drives stock market participation? The role of institutional, traditional, and behavioral factors

Markku Kaustia; Andrew Conlin; Niilo Luotonen

Journal of Banking & Finance 2023 148, 106743 open access

We analyze stock market participation in 19 European countries, providing a composite view of the interplay and relative importance of established participation drivers. We jointly control for nearly all relevant drivers found in prior studies, which tend to introduce one novel variable at a time and often omit risk-aversion. Excellent full model predictive power decomposes into institutional (country) fixed effects (about 30% of total), traditional individual-level variables (50%), and more recently identified behavioral variables (20%). We sketch a hierarchical framework where factors’ effects vary by agents’ proneness to participate. We also challenge and complement existing interpretations given to sociability, IQ, trust, and life experiences.

In statistics, samples are drawn from a population in a data‐generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence‐generating process (EGP). We claim that EGP variation across researchers adds uncertainty—nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer‐review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.

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Do Investors Overweight Personal Experience? Evidence from IPO Subscriptions

What drives stock market participation? The role of institutional, traditional, and behavioral factors

Nonstandard Errors