Taming the Bias Zoo

53 Pages Posted: 15 Apr 2020 Last revised: 21 Sep 2021

See all articles by Hongqi Liu

Hongqi Liu

Chinese University of Hong Kong, Shenzhen

Cameron Peng

London School of Economics & Political Science (LSE) - Department of Finance

Wei A. Xiong

Shenzhen Stock Exchange

Wei Xiong

Princeton University - Department of Economics; National Bureau of Economic Research (NBER)

Multiple version iconThere are 2 versions of this paper

Date Written: March 22, 2020

Abstract

The success of behavioral economics has led to a new challenge—many biases offering observationally similar predictions for a targeted financial anomaly. To tame this bias zoo, we combine subjective survey responses with observational data to propose a new approach, one that is robust to question-specific biases introduced through surveys. We illustrate this approach by administering a nationwide survey of Chinese retail investors to elicit their trading motives. In cross-sectional regressions of respondents’ actual turnover on survey-based trading motives, perceived information advantage and gambling preference dominate other motives, even though they are not the most prevalent biases simply based on survey responses.

Keywords: excessive trading, survey, gambling preference, overconfidence

JEL Classification: G02, G11

Suggested Citation

Liu, Hongqi and Peng, Cameron and Xiong, Wei A. and Xiong, Wei, Taming the Bias Zoo (March 22, 2020). Journal of Financial Economics (JFE), Forthcoming, Available at SSRN: https://ssrn.com/abstract=3558848 or http://dx.doi.org/10.2139/ssrn.3558848

Hongqi Liu

Chinese University of Hong Kong, Shenzhen ( email )

Cameron Peng (Contact Author)

London School of Economics & Political Science (LSE) - Department of Finance ( email )

United Kingdom

Wei A. Xiong

Shenzhen Stock Exchange ( email )

2012 Shennan Blvd., Futian District
Shenzhen
China

Wei Xiong

Princeton University - Department of Economics ( email )

Princeton, NJ 08544-1021
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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