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Systemic risk of commodity markets: A dynamic factor copula approach

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  • Ouyang, Ruolan
  • Chen, Xiang
  • Fang, Yi
  • Zhao, Yang

Abstract

This study aims to measure the systemic risk of commodity markets and investigate its causal relationship with the macroeconomy. First, we propose a novel measure called the joint probability of abnormal changes (JPAC) to measure the systemic risk of commodity markets. Second, we introduce two new measures, the expected proportion of commodities in abnormal price change (EPAPC) and the contribution to systemic risk (CSR), to identify the systemic importance of each commodity. Third, we examine the relationship between JPAC and some key macroeconomic variables using mixed-frequency Granger causality tests. We conduct an empirical study using 24 commodity indices from 2015 to 2021. Our results reveal that: (1) JPAC can well capture the risk events in the real world; (2) the systemic risk of commodity markets has increased significantly since the start of the US-China trade war; (3) EPAPC and CSR indicate that energy commodities have higher systemic importance than others and are most likely to cause market fluctuations; and (4) some causal relationships between the systemic risk of commodity markets and the macroeconomy are identified. Overall, this study improves our understanding of systemic risk in commodity markets and provides important implications for policymakers in China and the US.

Suggested Citation

  • Ouyang, Ruolan & Chen, Xiang & Fang, Yi & Zhao, Yang, 2022. "Systemic risk of commodity markets: A dynamic factor copula approach," International Review of Financial Analysis, Elsevier, vol. 82(C).
  • Handle: RePEc:eee:finana:v:82:y:2022:i:c:s105752192200165x
    DOI: 10.1016/j.irfa.2022.102204
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    2. Sun, Yiqun & Ji, Hao & Cai, Xiurong & Li, Jiangchen, 2023. "Joint extreme risk of energy prices-evidence from European energy markets," Finance Research Letters, Elsevier, vol. 56(C).

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    More about this item

    Keywords

    Commodity market; Systemic risk; Factor copula; Generalized autoregressive score; Model; Macroeconomy;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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