Selective hedging strategies for crude oil futures based on market state expectations

Xing Yu, Xilin Shen, Yanyan Li and Xue Gong

Global Finance Journal, 2023, vol. 57, issue C

Abstract: This paper studies the ex-ante selective hedging strategies of crude oil futures contracts based on market state expectations and compares the hedging performances to the traditional minimum variance routine hedging strategies. The main advantage of the proposed method is that it achieves a trade-off between return and risk, rather than hedges risk at all costs. Specifically, we first use a multi-input Hidden Markov Model(HMM) to identify the market state, assess the market’s herding impact, and then integrate the findings of identification and measurement to forecast the price trend. We offer an adjustment criterion for the hedge ratios driven by GARCH22GARCH is the abbreviation of Generalized AutoRegressive Conditional Heteroskedasticity.-type models based on the anticipated market state. We conducted an empirical analysis to examine the hedging effect of WTI and Brent crude oil futures, the results indicate that the proposed state-dependent hedging strategies are superior to the traditional model-driven hedging strategies concerning the hedged portfolio based on four criteria. The robustness check reveals that the proposed hedging strategies still outperform in different market situation. The findings can help traders in the crude oil markets, and the methodology can be applied to other energy markets.

Keywords: Selective hedging; Multi-input HMM; Herding effect; Model-driven hedging strategies; State-dependent hedging strategies (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:glofin:v:57:y:2023:i:c:s1044028323000406

DOI: 10.1016/j.gfj.2023.100845

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