Herding and market volatility

Research output: Journal PublicationArticlepeer-review

2 Citations (Scopus)

Abstract

In this paper, we explore the impact of investor herding behavior on stock market volatility. We adopt a direct herding measure based on the variation of cross-sectional stock betas. The measure can be readily separated into positive and adverse components, whereby investors herd towards and away from the market portfolio, respectively. Using A-shares listed in the Chinese equity market from August 2005 to March 2021, we show that the market volatility is Granger caused by the measure, and that there exists an asymmetric effect between positive and adverse herding on volatility. Furthermore, we provide robust evidence that the information contained in the herding measure helps generate significantly improved volatility forecasts and add economic value to investors. Our paper not only contributes to the volatility forecasting literature but also advances our understanding of herding in the equity market.

Original languageEnglish
Article number101880
JournalInternational Review of Financial Analysis
Volume78
DOIs
Publication statusPublished - Nov 2021

Keywords

  • Adverse herding
  • Behavioral bias
  • Emerging market
  • Leverage effect
  • Realized volatility

ASJC Scopus subject areas

  • Finance
  • Economics and Econometrics

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