The early‐warning system of stock market crises with investor sentiment: Evidence from China

• Author: Rengui Zhang,Xueshen Xian,Haowen Fang
• Published date: 01 January 2019
• Date: 01 January 2019
• DOI: http://doi.org/10.1002/ijfe.1667

RESEARCH ARTICLE

The early‐warning system of stock market crises with

investor sentiment: Evidence from China

Rengui Zhang

1

| Xueshen Xian

2

| Haowen Fang

1

1

School of Economics, Shenzhen

Polytechnic, Shenzhen, China

2

School of Economics and Commerce,

Finance and Security Center, South China

University of Technology, Guangzhou,

China

Correspondence

Rengui Zhang, School of Economics,

Shenzhen Polytechnic, Shenzhen 518055,

China.

Email: mathsren@foxmail.com

Abstract

Using a database of the trading data in the Chinese stock market over January

2005 to June 2012, this paper studies the stock market crisis based on the per-

spective of behavioural finance. Investor sentiment is based on B‐W method,

and the possibility of the Shanghai stock market crisis was predicted by the

logit model. The empirical results show that investor sentiment, which is more

significant than the macroeconomic variables, has a significant positive impact

on stock market crisis after controlling for the economic variables. Moreover,

our results offer an empirical explanation for the financial anomaly of mean

reversion. Both in‐sample and out‐sample data tests show that the logit model

with investor sentiment is able to predict stock crises.

KEYWORDS

behaviour finance, investor sentiment, mean reversion, stock market crises, the logit model

1|INTRODUCTION

At present, the traditional financial theory is difficult to

explain many anomalies in the financial market, such

as excess volatility, the equity premium puzzle, and the

puzzle of closed‐end funds. For example, stock prices

drop an average of 22.6% during the crash of October

1987 in America. The decrease is much larger than what

can be explained by changes in economic variables

(Black, 1988). Figure 1 illustrates Chinese gross domestic

product (GDP) and Shanghai stock index between 2014

and 2015. In 2015, the growth of GDP slowed to 6.9%,

hitting a new low of 25 years. However, Shanghai

composite index has more than doubled and rose to its

highest level (5,178) in June 2015 and then dropped

sharply. The big move is too hairy for a large number of

investors. The structure of investors dominated by indi-

vidual investors has always been regarded as one of the

main factors, which lead China stock market to extreme

fluctuation. Individual investors are affected by investor

sentiment more easily than institutional investors.

Zouaoui, Nouyrigat, and Beer (2011) find that the impact

of investor sentiment on stock markets is more pro-

nounced in countries that are culturally more prone to

herd‐like behaviour and overreaction or in countries with

low institutional involvement.

Based on investor sentiment, behaviour finance offers

satisfactory explanations for these anomalies. A number

of theoretical and empirical studies (Barberis, Shleifer, &

Vishny, 1998, Daniel, Hirshleifer, & Subrahmanyam,

1998, Baker & Wurgler, 2006, Kumar & Lee, 2006, Statman

et al., 2012, Yang & Zhang, 2014; Yang & Zhou, 2015, Liang,

Yang, Zhang, & Cai, 2017) have shown that investor senti-

ment has a systematic impact on stock return. For example,

Stambaugh, Yu, and Yuan (2012) explored the role of inves-

tor sentiment in a broad set of anomalies in cross‐sectional

stock returns. Their results show that each anomaly is

stronger (its long–short strategy is more profitable) follow-

ing high levels of sentiment. Second, the short leg of each

strategy is more profitable following high sentiment.

Finally, sentiment exhibits no relation to returns on the

long legs of the strategies.

There are many kinds of traditional financial early‐

warning models without investor sentiment (Kaminsky,

Received: 4 March 2018 Revised: 3 July 2018 Accepted: 9 September 2018

DOI: 10.1002/ijfe.1667

Int J Fin Econ. 2019;24:361–369. © 2018 John Wiley & Sons, Ltd.wileyonlinelibrary.com/journal/ijfe 361