Cross-sectional return dispersion and volatility prediction

Tianlun Fei, Xiaoquan Liu and Conghua Wen

Pacific-Basin Finance Journal, 2019, vol. 58, issue C

Abstract: We use intraday and daily data to examine the impact of cross-sectional return dispersion on volatility forecasting in the Chinese equity market. We adopt the GARCH, GJR-GARCH, and HAR models and, by augmenting them with return dispersion measures, provide empirical evidence that the return dispersion exhibits substantial information in describing the volatility dynamics by generating significantly lower forecasting errors at market and industry levels. Furthermore, the information content of the return dispersion tends to offer economic gain to a mean-variance utility investor. The findings are robust with respect to alternative volatility proxies, subsample analysis, and alternative market-wide stock indices.

Keywords: Industry effect; Chinese CSI index; Herding; Financial markets (search for similar items in EconPapers)
JEL-codes: G11 G17 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:pacfin:v:58:y:2019:i:c:s0927538x19301830

DOI: 10.1016/j.pacfin.2019.101218

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