Skip to main navigation Skip to search Skip to main content

Time-varying comovement and changes of comovement structure in the Chinese stock market: A causal network method

  • Beihang University

Research output: Contribution to journalArticlepeer-review

Abstract

The driving force for the comovement in stock returns is a long-standing debate between classical asset pricing theory and behavioral finance theory. It has become critically important recently for understanding systemic risk and risk contagion in the market. In this study, we propose complex networks enabled new methods to measure the causal comovement of individual stocks and the comovement structure of the market, which facilitate the examination of all kinds of hypotheses of comovement theories in a unified framework. Using a sample of the Chinese stock market from Jan. 1, 2006 to Dec. 31, 2016, we find that the degree of comovement generally intensifies over time, with a drastic increase from 2011 to 2015, while the comovement structure of the market changes with different market situations. Most importantly, our study reveals the driving force of causal comovement among individual stocks; that is, sentiment-based factors related to the market index indeed induce excess causal comovement in returns beyond that can be justified by fundamental factors including beta coefficient, book-to-market ratio, liquidity, profitability and volatility. Our study also reveals the determinants of comovement structure, which are attributable to the change of investors' behaviors in different periods. It turns out that investors in the Chinese stock market care about risk-return relationship in normal periods, while they seem to care only about risk in crisis periods.

Original languageEnglish
Pages (from-to)181-204
Number of pages24
JournalEconomic Modelling
Volume81
DOIs
StatePublished - Sep 2019

Keywords

  • Common factors
  • Comovement measure
  • Comovement structure
  • Panel data model
  • Topology of causal network

Fingerprint

Dive into the research topics of 'Time-varying comovement and changes of comovement structure in the Chinese stock market: A causal network method'. Together they form a unique fingerprint.

Cite this