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Joint multifractality in cross-correlations between grains & oilseeds indices and external uncertainties

Author

Listed:
  • Ying-Hui Shao

    (Shanghai University of International Business and Economics)

  • Xing-Lu Gao

    (East China University of Science and Technology)

  • Yan-Hong Yang

    (Shanghai University)

  • Wei-Xing Zhou

    (East China University of Science and Technology
    East China University of Science and Technology
    East China University of Science and Technology)

Abstract

This study investigates the relationships between agricultural spot markets and external uncertainties through multifractal detrending moving-average cross-correlation analysis (MF-X-DMA). The dataset contains the Grains & Oilseeds Index (GOI) and its five subindices for wheat, maize, soyabeans, rice, and barley. Moreover, we use three uncertainty proxies, namely, economic policy uncertainty (EPU), geopolitical risk (GPR), and Volatility Index (VIX). We observe multifractal cross-correlations between agricultural markets and uncertainties. Furthermore, statistical tests reveal that maize has intrinsic joint multifractality with all the uncertainty proxies, highly sensitive to external shocks. Additionally, intrinsic multifractality among GOI-GPR, wheat-GPR, and soyabeans-VIX is illustrated. However, other series have apparent multifractal cross-correlations with high probabilities. Moreover, our analysis suggests that among the three types of external uncertainties, GPR has the strongest association with grain prices, excluding maize and soyabeans.

Suggested Citation

  • Ying-Hui Shao & Xing-Lu Gao & Yan-Hong Yang & Wei-Xing Zhou, 2025. "Joint multifractality in cross-correlations between grains & oilseeds indices and external uncertainties," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-32, December.
    • Handle: RePEc:spr:fininn:v:11:y:2025:i:1:d:10.1186_s40854-024-00669-5
    DOI: 10.1186/s40854-024-00669-5
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