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Examining dynamics: Unraveling the impact of oil price fluctuations on forecasting agricultural futures prices

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  • Zhang, Wei
  • Wu, Jiayi
  • Wang, Shun
  • Zhang, Yong

Abstract

This research aims to explore the complex dynamics governing the correlation between oil futures prices and Chinese agricultural futures prices, with a specific emphasis on unveiling the crucial role played by oil futures prices in predicting the trajectory of agricultural futures prices. The study utilizes the Vector Error Correction-Dynamic Conditional Correlation-Multivariate Generalized Autoregressive Conditional Heteroskedasticity (VEC-DCC-MGARCH) model to dissect the interplay among oil, soybean, and corn price series. Additionally, this study integrates the innovative Spatio-temporal Information Recombination Hypergraph Neural Network (STIR-HGNN) model to analyze how oil futures prices contribute to improving the accuracy of forecasting agricultural product prices. Findings indicate numerous connections between oil prices and agricultural futures prices, highlighting the significant role of oil prices in forecasting agricultural futures price movements. The empirical insights derived from this study serve as a valuable compass for futures market participants, urging them to leverage these findings to refine and optimize their market strategies, enhancing their capacity to navigate and capitalize on the intricate complexities inherent in these interconnected markets.

Suggested Citation

  • Zhang, Wei & Wu, Jiayi & Wang, Shun & Zhang, Yong, 2025. "Examining dynamics: Unraveling the impact of oil price fluctuations on forecasting agricultural futures prices," International Review of Financial Analysis, Elsevier, vol. 97(C).
    • Handle: RePEc:eee:finana:v:97:y:2025:i:c:s1057521924007026
    DOI: 10.1016/j.irfa.2024.103770
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