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Hedging Salmon Price Risk Based on Fuzzy Copula-GMM Model

Author

Listed:
  • Xing Yu

    (School of Economics and Business Administration, Central China Normal University, Wuhan 430079, P. R. China)

  • Chenya Liu

    (School of Economics and Business Administration, Central China Normal University, Wuhan 430079, P. R. China)

  • Weiguo Zhang

    (��School of Management, Shenzhen University, Shenzhen 518060, P. R. China)

Abstract

Copula method can explain the dependent function or connection function which connects the joint distribution and the univariate marginal distribution. Therefore, copula has recently become a most significant important tool in the financial field of risk management, portfolio allocation, and derivative asset pricing. However, it leads to a possibilistic uncertainty in estimating the parameters of copulas because of insufficient historical data, imprecise parameter estimation, and uncertain knowledge of future prices. This paper proposes a fuzzy copula model via Kullback–Leibler (KL) divergence to model the fuzzy relations, and further to investigate the hedging issues of salmon futures. We use a new framework of hedging under fuzzy circumstances, consisting of innovative marginal distributions and fuzzy intervals. By synergizing fuzzy copula and simulations, we use the fuzzy copula-GMM to obtain the hedge ratios of salmon futures. The empirical results show that, compared with traditional probabilistic methods, the fuzzy copula-GMM hedges the salmon spot risk measured by variance more successfully.

Suggested Citation

  • Xing Yu & Chenya Liu & Weiguo Zhang, 2025. "Hedging Salmon Price Risk Based on Fuzzy Copula-GMM Model," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 24(04), pages 1221-1246, May.
    • Handle: RePEc:wsi:ijitdm:v:24:y:2025:i:04:n:s0219622023500682
    DOI: 10.1142/S0219622023500682
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