Resolving the Excessive Trading Puzzle: An Integrated Approach Based on Surveys and Transactions

59 Pages Posted: 15 Apr 2020

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 behavioral finance literature has provided over a dozen explanations for the so-called excessive trading puzzle – retail investors trade a lot even though more trading hurts their performance. It is difficult to use transaction data to differentiate these explanations as they share similar predictions by design. To confront this challenge, we design and administer a nation-wide survey among retail investors to elicit their responses to an exhaustive list of trading motives. By merging survey responses with account-level transaction data, we validate survey responses with actual trading behaviors and compare the power of survey-based and transaction-based measures of trading motives. A horse race among survey-based trading motives suggests that overconfidence in having information advantage and gambling preference quantitatively dominate other explanations. Moreover, other popular arguments such as neglect of trading cost do not contribute to excessive trading.

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, Resolving the Excessive Trading Puzzle: An Integrated Approach Based on Surveys and Transactions (March 22, 2020). 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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