Self-Attribution Bias and Overconfidence Among Nonprofessional Traders
44 Pages Posted: 27 Mar 2018
Date Written: November 21, 2017
This paper investigates the self-attribution bias among nonprofessional traders. By using a unique dataset of more than 45,000 public comments of nonprofessional traders at a social trading platform, we create a more direct measure for the self-attribution bias than prior works. We find that one component of the self-attribution bias, the self-enhancement bias, leads to future underperformance. Evidence identifies overconfidence resulting from biased self-enhancement as a possible driver. Due to social interaction, traders' biased self-enhancement also disadvantageously affects their investors as those traders attract higher investment flows.
Keywords: Self-attribution bias, overconfidence, social interaction, textual analysis
JEL Classification: D14, G11, G41
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