Does Probability Weighting Drive Lottery Preferences?

Benjamin Blau (), Jared DeLisle and Ryan J. Whitby

Journal of Behavioral Finance, 2020, vol. 21, issue 3, 233-247

Abstract: We propose a test of the theory of skewness preferences. The probability weighting feature that is the basis of their theory relies on investors overweighting the probability of extreme, positive returns. The resulting investor preferences for positive skewness in return distributions will lead to excess demand, contemporaneous price premiums, and negative expected returns. We use the well-documented 52-week high bias as a method to truncate investors’ weighted probability of expected right-tail events. We find evidence supporting the theoretical framework of Barberis and Huang as the negative return premiums associated with positive skewness is driven almost entirely by stocks that are farther away from the their 52-week high. No negative premiums related to skewness are detected when stock prices are close to the 52-week high.

Date: 2020
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DOI: 10.1080/15427560.2019.1672167

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