Time‐Varying Investor Herding in Chinese Stock Markets

• Published date: 01 December 2018
• Date: 01 December 2018
• DOI: http://doi.org/10.1111/irfi.12158

Time-Varying Investor Herding

in Chinese Stock Markets*

HAIQI LI

†

,YING LIU

‡

AND SUNG Y. PARK

§

†

College of Finance and Statistics, Hunan University, Changsha, China

‡

College of Finance and Statistics, Hunan University, Changsha, 410006, China and

§

School of Economics, Chung-Ang University, Seoul, South Korea

ABSTRACT

We develop several new time-varying coefficient regression models to investigate

herding behavior in Chinese stock markets. We find evidence that herding

behavior occurs during turbulent periods rather than periods of relative tranquil-

ity, which does not appear when using a conventional fixed-coefficient regres-

sion model. Moreover, the US return dispersion had a significant influence on

Chinese stock markets before 2015 but not in 2015. Finally, the herding shows

significant asymmetry.

JEL Codes: C32; G02; G14

Accepted: 29 August 2017

I. INTRODUCTION

Research interest in herding behavior has increased over the last decade. Herd-

ing generally refers to the phenomenon in which a group of investors ignore

their own information and imitate others’behavior or the market consensus

(Bikhchandani and Sharma 2001) by trading in the same direction over a period

of time. Although there are rational and irrational types of herding behavior,

this behavior may lead to synchronized movements in asset prices that deviate

from their economic fundamentals. Therefore, it is important to investigate

whether herding behavior exists in particular financial markets over a period of

time. The recent empirical literature related to herding behavior focused on

cross-sectional correlation dispersions in stock returns in response to market

movements. Two well-known measures of stock return dispersion are the cross-

sectional standard deviation (CSSD) proposed by Christie and Huang (1995)

and the cross-sectional absolute deviation (CSAD) put forward by Chang

et al. (2000). A stream of research uses these measures to examine herding

behavior. For example, Chang et al. (2000) studied herding behavior in five

* This project was supported by the National Natural Science Foundation of China (NSFC)

(No.71773026) and the Ministry of Education of Humanities and Social Sciences Project of China

(No. 17YJA790041).

© 2017 International Review of Finance Ltd. 2017

International Review of Finance, 18:4, 2018: pp. 717–726

DOI: 10.1111/irfi.12158