Abstract
This paper investigates the dynamic hedging performance of the high frequency data based realized minimum-variance hedge ratio (RMVHR) approach. We comprehensively examine a number of popular time-series models to forecast the RMVHR for the CSI 300 index futures, and evaluate the out-of-sample dynamic hedging performance in comparison to the conventional hedging models using daily prices, as well as the vector heterogeneous autoregressive model using intraday prices. Our results show that the dynamic hedging performance of the RMVHR-based methods significantly dominates that of the conventional methods in terms of both hedging effectiveness and tracking error volatility in the out-of-sample forecast period. Furthermore, the superiority of the RMVHR-based methods is robust in different market structures and different volatility regimes, including China's abnormal market fluctuations in 2015 and the US financial crisis in 2008.
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