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

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 imp...

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Bibliographic Details
Published in:The journal of futures markets 2018-11, Vol.38 (11), p.1370-1390
Main Author: Lai, Yu‐Sheng
Format: Article
Language:English
Subjects:
Dominance
EGARCH
estimation uncertainty
futures hedge ratio
Hedging
high‐frequency data
Leverage
Portfolios
Predictions
predictive ability testing
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Summary: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.
ISSN:0270-7314
1096-9934
DOI:10.1002/fut.21937