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Stress-Testing for Portfolios of Commodity Futures with Extreme Value Theory and Copula Functions

In: Computational Management Science

Author

Listed:
  • Pierre-Antoine Mudry

    (University of St. Gallen)

  • Florentina Paraschiv

    (University of St. Gallen)

Abstract

In this paper, we performed a stress-testing for a portfolio of commodity futures, which mimics the dynamics of the DJ-UBS index. We identified extreme events that impacted commodity prices over time, and looked at correlation structures in a dynamic way, with copula functions. In line with Basel III financial regulations, we derived baseline, historical, and hybrid scenarios and discussed their advantages and shortfalls. We found that the financialization of commodity markets led to an increase in correlations and in the probability for joint extremes. However, we identified structural breaks in commodity markets that temporarily led to a breakdown of expected statistical patterns and of traditional dependence structures among commodities. This fact shows the need for forward-looking stress testing techniques, like hybrid and hypothetical scenarios, as encouraged by financial regulators.

Suggested Citation

  • Pierre-Antoine Mudry & Florentina Paraschiv, 2016. "Stress-Testing for Portfolios of Commodity Futures with Extreme Value Theory and Copula Functions," Lecture Notes in Economics and Mathematical Systems, in: Raquel J. Fonseca & Gerhard-Wilhelm Weber & João Telhada (ed.), Computational Management Science, edition 1, pages 17-22, Springer.
    • Handle: RePEc:spr:lnechp:978-3-319-20430-7_3
    DOI: 10.1007/978-3-319-20430-7_3
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    Cited by:

    1. Alessandro Staino & Emilio Russo & Massimo Costabile & Arturo Leccadito, 2023. "Minimum capital requirement and portfolio allocation for non-life insurance: a semiparametric model with Conditional Value-at-Risk (CVaR) constraint," Computational Management Science, Springer, vol. 20(1), pages 1-32, December.
    2. Caifeng Liu & Wenfeng Pan & Hongcheng Zhou, 2023. "RCML: A Novel Algorithm for Regressing Price Movement during Commodity Futures Stress Testing Based on Machine Learning," JRFM, MDPI, vol. 16(6), pages 1-12, May.

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