Yun-Shi Dai, Ngoc Quang Anh Huynh, Qing-Huan Zheng, Wei-Xing Zhou
arXiv 24 Oct 2023 · Finance — Statistical Finance · publishedResearch in International Business and Finance (2022) · 12 citations (OpenAlex)
arXiv:2310.16849 · PDF · DOI · OpenAlex · Extracted main text
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.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Plerou, V., Gopikrishnan, P., Rosenow, B., Amaral, L., Guhr, T., Sta… (2002) Random matrix approach to cross correlations in financial data | 0.811 | 4 | 2 | 100% |
| 2 | Dai, Y.H., Xie, W.J., Jiang, Z.Q., Jiang, G.J., Zhou, W.X (2016) Correlation structure and principal components in the global crude oil market self | 0.737 | 3 | 2 | 100% |
| 3 | Adaemmer, P., Bohl, M.T., von Ledebur, E.O (2017) Dynamics between North American and European agricultural futures prices during turmoil and financialization | 0.405 | 1 | 1 | 100% |
| 4 | Alola, A.A (2022) The nexus of renewable energy equity and agricultural commodities in the United States: Evidence of regime-switching and price b… | 0.405 | 1 | 1 | 100% |
| 5 | Balli, F., Naeem, M.A., Shahzad, S.J.H., de Bruin, A (2019) Spillover network of commodity uncertainties | 0.405 | 1 | 1 | 100% |
| 6 | Boroumand, R.H., Goutte, S., Porcher, S., Porcher, T (2014) Correlation evidence in the dynamics of agricultural commodity prices | 0.405 | 1 | 1 | 100% |
| 7 | Dai, P.F., Xiong, X., Zhou, W.X (2021) A global economic policy uncertainty index from principal component analysis self | 0.405 | 1 | 1 | 100% |
| 8 | Daly, J., Crane, M., Ruskin, H.J (2008) Random matrix theory filters in portfolio optimisation: a stability and risk assessment | 0.405 | 1 | 1 | 100% |
| 9 | Dimpfl, T., Flad, M., Jung, R.C (2017) Price discovery in agricultural commodity markets in the presence of futures speculation | 0.405 | 1 | 1 | 100% |
| 10 | Eom, C., Park, J.W (2018) A new method for better portfolio investment: A case of the Korean stock market | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 55 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | The impact of geopolitical risk on the international agricultural market: Empirical analysis based on the GJR-GARCH-MIDAS model | 0.405 | 1 | 1 |