Evaluating the performance of futures hedging using factors-driven realized volatility

Xing Yu, Yanyan Li, Xue Gong and Nan Zhang

International Review of Financial Analysis, 2022, vol. 84, issue C

Abstract: The complexity and uncertainty of the financial market mainly stem from the rich market internal transaction information and a wide range effect of external factors. To this end, this paper proposes the combination factors-driven forecasting method to predict realized volatilities of the CSI 300 index and index futures. Based on the volatilities predicted by the proposed method, we further evaluate the ex-ante hedging performance in comparison to the conventional HAR model as well as GARCH-type models. The empirical results indicate that the factors-driven realized volatility model significantly dominates the other commonly used models in terms of hedging effectiveness. Furthermore, the superiority of the proposed method is robust in different market conditions, including significant rising or falling and abnormal market fluctuations in the COVID-19 pandemic, and in different index markets. Therefore, this paper improves the prediction accuracy of volatility by integrating market internal transaction information and external factor information, and the proposed method in this paper can be used by investors to obtain an excellent hedging effect.

Keywords: Factors-driven realized volatilities; Out-of-sample forecasting; Ex-ante-hedge-ratio; Hedging effectiveness (search for similar items in EconPapers)
JEL-codes: G11 G13 G15 G17 (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:84:y:2022:i:c:s1057521922003623

DOI: 10.1016/j.irfa.2022.102412

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