Self-Attribution Bias and Overconfidence Among Nonprofessional Traders

44 Pages Posted: 27 Mar 2018  

Daniel Czaja

University of Giessen - Department of Financial Services

Florian Röder

University of Giessen - Department of Financial Services

Date Written: November 21, 2017

Abstract

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

Suggested Citation

Czaja, Daniel and Röder, Florian, Self-Attribution Bias and Overconfidence Among Nonprofessional Traders (November 21, 2017). Available at SSRN: https://ssrn.com/abstract=3075248 or http://dx.doi.org/10.2139/ssrn.3075248

Daniel Czaja (Contact Author)

University of Giessen - Department of Financial Services ( email )

Licher Str, 74
Giessen, 35394
Germany

Florian Röder

University of Giessen - Department of Financial Services ( email )

Licher Str, 74
Giessen, 35394
Germany

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