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HYBRID GARCH Models and Intra-Daily Return Periodicity

Author

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  • Chen Xilong

    (SAS Institute)

  • Ghysels Eric

    (The University of North Carolina at Chapel Hill)

  • Wang Fangfang

    (University of Illinois at Chicago)

Abstract

We use the HYBRID GARCH model of Chen, Ghysels, and Wang (2009) to predict future volatility at daily horizons using intra-daily returns. The latter requires us to address intra-daily periodic patterns. We propose two approaches and compare their relative merits. The first approach uses raw intra-daily data-with the HYBRID process capturing the intra-daily periodic patterns-whereas the second approach involves pre-adjusted intra-daily returns. We find that the former approach dominates both in-sample and out-of-sample, although for different HYBRID GARCH model specifications.

Suggested Citation

  • Chen Xilong & Ghysels Eric & Wang Fangfang, 2011. "HYBRID GARCH Models and Intra-Daily Return Periodicity," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-28, February.
    • Handle: RePEc:bpj:jtsmet:v:3:y:2011:i:1:n:11
    DOI: 10.2202/1941-1928.1095
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    References listed on IDEAS

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    7. Xu, Yanyan & Huang, Dengshi & Ma, Feng & Qiao, Gaoxiu, 2019. "Liquidity and realized range-based volatility forecasting: Evidence from China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1102-1113.

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