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Estimation of the optimal futures hedge ratio for equity index portfolios using a realized beta generalized autoregressive conditional heteroskedasticity model

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  • Yu‐Sheng Lai

Abstract

This paper employs a realized beta generalized autoregressive conditional heteroskedasticity model for optimal futures hedging. The model has a flexible structure and is complete because all observed returns and realized measures are jointly modeled in a system. This enables the incorporation of important features that may affect the hedge ratio estimation. The model is applied to equity indices, and substantial dependence between return and volatility indicates the essential of modeling statistical leverage. Predictive ability testing confirms the superiority of the model for reducing the hedged portfolio risk. The predictive ability of the model can translate into pronounced economic benefits, particularly for short‐term hedges.

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  • Yu‐Sheng Lai, 2018. "Estimation of the optimal futures hedge ratio for equity index portfolios using a realized beta generalized autoregressive conditional heteroskedasticity model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(11), pages 1370-1390, November.
    • Handle: RePEc:wly:jfutmk:v:38:y:2018:i:11:p:1370-1390
    DOI: 10.1002/fut.21937
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    1. Yingying Xu & Donald Lien, 2020. "Optimal futures hedging for energy commodities: An application of the GAS model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1090-1108, July.

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