Empirical analysis demonstrates superior hedging performance for Shanghai crude oil futures using a dual integrated method, suggesting improved risk management under global uncertainties.
To address the problem of effectively estimating hedge ratios for Shanghai crude oil futures (INE) under multiple uncertainties, this study proposes a dual integrated method with noise reduction-mixed frequency-decomposition. The method optimizes hedge ratios between INE futures and crude oil spot markets under Climate Policy Uncertainty (CPU), Global Economic Policy Uncertainty (GEPU), and Geopolitical Risk (GPR). The proposed model first denoises crude oil prices and then integrates valuable information across uncertainties and time scales, thereby improving futures-spot hedging performance. The findings reveal the presence of noise in crude oil markets and highlight the heterogeneous effects of uncertainties on futures-spot relationships, with hedge ratios exhibiting distinct multiscale characteristics. The in-sample and out-of-sample results further provide evidence that the dual integrated method outperforms the control methods in terms of hedging performance in most cases. This study not only provides a novel hedging tool for developing effective risk management strategies but also offers a scientific basis for policy decision-making.
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Zhu et al. (2026) studied this question.
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