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Herding and market volatility

Tianlun Fei and Xiaoquan Liu

International Review of Financial Analysis, 2021, vol. 78, issue C

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.

Keywords: Adverse herding; Behavioral bias; Emerging market; Realized volatility; Leverage effect (search for similar items in EconPapers)
JEL-codes: G11 G17 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:78:y:2021:i:c:s105752192100209x

DOI: 10.1016/j.irfa.2021.101880

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