Cross-sectional return dispersion and volatility prediction

    Research output: Journal PublicationArticlepeer-review

    8 Citations (Scopus)
    35 Downloads (Pure)


    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.

    Original languageEnglish
    Article number101218
    JournalPacific Basin Finance Journal
    Publication statusPublished - Dec 2019


    • Chinese CSI index
    • Financial markets
    • Herding
    • Industry effect

    ASJC Scopus subject areas

    • Finance
    • Economics and Econometrics


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