Estimation of the optimal futures hedge ratio for equity index portfolios using a realized beta generalized autoregressive conditional heteroskedasticity model. Issue 11 (14th June 2018)

• Record Type: Journal Article
• Authors: Lai, Yu‐Sheng
• Is Part Of: Journal of futures markets. Volume 38:Issue 11(2018)
• Page Start: 1370
• Page End: 1390
• Publication Date: 2018-06-14
• Subjects: EGARCH -- estimation uncertainty -- futures hedge ratio -- high‐frequency data -- predictive ability testing; Commodity exchanges -- Periodicals; Foreign exchange futures -- Periodicals; 332.632
• DOI: 10.1002/fut.21937
• Languages: English
• ISSNs: 0270-7314

Abstract

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.