Joint multifractality in cross-correlations between grains & oilseeds indices and external uncertainties
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, s...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-01-01
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| Series: | Financial Innovation |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40854-024-00669-5 |
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| Summary: | 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. |
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| ISSN: | 2199-4730 |