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

TL;DR

This paper explores the complex multifractal cross-correlations between agricultural grain indices and external uncertainties using advanced multifractal analysis, revealing significant sensitivity and stronger links with geopolitical risk.

Contribution

It introduces a multifractal analysis of cross-correlations between grain markets and external uncertainties, highlighting the intrinsic multifractality and the dominant influence of geopolitical risk.

Findings

Maize shows intrinsic joint multifractality with all uncertainty proxies.

Geopolitical risk has a stronger association with grain prices than other uncertainties.

Multiple agricultural indices exhibit multifractal cross-correlations with external uncertainties.

Abstract

This study investigates the relationships between agricultural spot markets and external uncertainties via the multifractal detrending moving-average cross-correlation analysis (MF-X-DMA). The dataset contains the Grains \& Oilseeds Index (GOI) and its five sub-indices of 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 the presence of multifractal cross-correlations between agricultural markets and uncertainties. Further, statistical tests show that maize has intrinsic joint multifractality with all the uncertainty proxies, exhibiting a high degree of sensitivity. Additionally, intrinsic multifractality among GOI-GPR, wheat-GPR and soyabeans-VIX is illustrated. However, other series have apparent multifractal cross-correlations with high possibilities. Moreover, our analysis suggests that among the three kinds of external uncertainties, geopolitical risk has a relatively stronger association with grain prices.