Futures hedging in crude oil markets: A trade-off between risk and return. (January 2023)

• Record Type: Journal Article
• Authors: Yu, Xing; Li, Yanyan; Lu, Junli; Shen, Xilin
• Is Part Of: Resources policy. Volume 80(2023)
• Publication Date: 2023-01
• Subjects: Futures hedging -- Market state dependent -- Model driven strategy -- Synchronous movement intensity; Mines and mineral resources -- Periodicals; Ressources minérales -- Périodiques; Ressources naturelles -- Gestion -- Périodiques; Environnement -- Politique gouvernementale -- Périodiques; 333.8
• DOI: 10.1016/j.resourpol.2022.103147
• Languages: English
• ISSNs: 0301-4207

Abstract

Abstract: Risk and return are two fundamentals that have an impact on an investor's or hedger's investing choices. Based on the proposed synchronous movement intensity index, this paper aims to improve the hedging performance by adjusting the model-driven hedge ratio and realize the trade-off between return and risk in futures hedging. First, without loss of generality, we forecast crude oil spot and futures volatility using 10 GARCH-type models, including three linear models and seven nonlinear models, to obtain the ex-ante hedging ratio under the minimum variance framework. Then, we develop a novel and tractable method to identify the market state based on the index of consistency intensity, in which the index portrays the synchronous degree of stock price movements in the energy sector. Last but not least, we propose the hedge ratio adjustment criteria based on the identified state, and adjust the ratio driven by GARCH-type models of futures in accordance with the market state. Empirical results of crude oil futures markets indicate that the proposed state-dependent hedging model is superior to the commonly used models in terms of three criteria including mean of returns, variance, and ratio of mean to variance of returns for measuring hedging effect. We apply the DM test to make a statistical inference and discover that while the mean and the ratio of mean to variance of returns are increasing, the variance and hedging effectiveness of the hedged portfolio based on the modified methods are not significantly affected. Furthermore, the superiority of the proposed method is robust to different market conditions, including significant rising or falling trends, large basis, and COVID-19 pandemic. We also test the robustness of the proposed method with respect to the baseline model, quantile, and evaluation window. Overall, this paper provides a more realistic approach for crude oil risk managers to hedge crude oil price risk, some corresponding implications are also concluded. Highlights: We develop a novel and tractable method to identify the market state based on the market state consistency intensity index. We propose the state dependent hedge ratio adjustment criteria based on the proposed index. We improve the hedging performance by adjusting the model-driven hedge ratio and study the issue of the risk-return tradeoff for the hedged portfolio. The novel method we proposed can be used by investors to provide a more realistic hedging way.