Extrapolative Bubbles and Trading Volume

Review of Financial Studies, forthcoming

55 Pages Posted: 17 Jun 2018 Last revised: 21 Sep 2021

See all articles by Jingchi Liao

Jingchi Liao

Shenzhen Stock Exchange

Cameron Peng

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

Ning Zhu

Shanghai Jiao Tong University (SJTU) - Shanghai Advanced Institute of Finance (SAIF); Tsinghua University - PBC School of Finance

Date Written: March 7, 2021

Abstract

We propose an extrapolative model of bubbles to explain the sharp rise in prices and volume observed in historical financial bubbles. The model generates a novel mechanism for volume: due to the interaction between extrapolative beliefs and disposition effects, investors are quick to buy assets with positive past returns, but also quick to sell them if the good returns continue. Using account-level transaction data on the 2014–2015 Chinese stock market bubble, we test and confirm the model’s predictions about trading volume. We quantify the magnitude of the proposed mechanism and show that it can increase trading volume by another 30 percent.

Keywords: bubbles, the disposition effect, extrapolation, volume

JEL Classification: G11, G12, G40

Suggested Citation

Liao, Jingchi and Peng, Cameron and Zhu, Ning, Extrapolative Bubbles and Trading Volume (March 7, 2021). Review of Financial Studies, forthcoming, Available at SSRN: https://ssrn.com/abstract=3188960 or http://dx.doi.org/10.2139/ssrn.3188960

Jingchi Liao

Shenzhen Stock Exchange ( email )

2012 Shennan Blvd., Futian District
Shenzhen
China

Cameron Peng (Contact Author)

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

United Kingdom

Ning Zhu

Shanghai Jiao Tong University (SJTU) - Shanghai Advanced Institute of Finance (SAIF) ( email )

Shanghai Jiao Tong University
211 West Huaihai Road
Shanghai, 200030
China

Tsinghua University - PBC School of Finance

No. 43, Chengdu Road
Haidian District
Beijing 100083
China

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
662
Abstract Views
2,714
rank
49,596
PlumX Metrics