Correlation structure analysis of the global agricultural futures market

Yun-Shi Dai, Ngoc Quang Anh Huynh, Qing-Huan Zheng and Wei-Xing Zhou

Research in International Business and Finance, 2022, vol. 61, issue C

Abstract: This paper adopts the random matrix theory (RMT) to analyze the correlation structure of the global agricultural futures market from 2000 to 2020. It is found that the distribution of correlation coefficients is asymmetric and right skewed, and many eigenvalues of the correlation matrix deviate from the RMT prediction. The largest eigenvalue reflects a collective market effect common to all agricultural futures, the other largest deviating eigenvalues can be implemented to identify futures groups, and there are modular structures based on regional properties or agricultural commodities among the significant participants of their corresponding eigenvectors. Except for the smallest eigenvalue, other smallest deviating eigenvalues represent the agricultural futures pairs with highest correlations. This paper can be of reference and significance for using agricultural futures to manage risk and optimize asset allocation.

Keywords: Econophysics; Agricultural futures; Random matrix theory; Correlation matrix (search for similar items in EconPapers)
JEL-codes: C1 P4 Z13 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:riibaf:v:61:y:2022:i:c:s0275531922000654

DOI: 10.1016/j.ribaf.2022.101677

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