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Systemic Risk in Commodity Markets: What Do Trees Tell Us About Crises?

Author

Listed:
  • Delphine Lautier

    (DRM - Dauphine Recherches en Management - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique)

  • Julien Ling

    (DRM - Dauphine Recherches en Management - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique)

  • Franck Raynaud

    (EPFL - Ecole Polytechnique Fédérale de Lausanne)

Abstract

We examine the impact, on commodity derivative markets, of two financial crises: the Subprime crisis and the bankruptcy of Lehman Brothers. These crises are "external" for commodity markets: they appeared in the financial sphere. Still, because now commodity markets are highly integrated, between themselves and with other financial markets, such events could have had an impact. In order to fully comprehend this possible impact, we examine prices fluctuations in three dimensions: the observation time, the space dimension – the same underlying asset can be traded simultaneously in two different places – and the maturity of the transactions. We first focus on the efficiency of the shocks propagation: does it improve during crises? Then we concentrate on the paths of shocks propagation: are they modified? How? Finally we focus on the centrality of the prices system: does it change? Does it increase?

Suggested Citation

  • Delphine Lautier & Julien Ling & Franck Raynaud, 2014. "Systemic Risk in Commodity Markets: What Do Trees Tell Us About Crises?," Post-Print hal-01275562, HAL.
  • Handle: RePEc:hal:journl:hal-01275562
    Note: View the original document on HAL open archive server: https://hal.science/hal-01275562
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    References listed on IDEAS

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    1. R. Mantegna, 1999. "Hierarchical structure in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 11(1), pages 193-197, September.
    2. Bloch, Francis & Quérou, Nicolas, 2013. "Pricing in social networks," Games and Economic Behavior, Elsevier, vol. 80(C), pages 243-261.
    3. Markus K. Brunnermeier, 2009. "Deciphering the Liquidity and Credit Crunch 2007-2008," Journal of Economic Perspectives, American Economic Association, vol. 23(1), pages 77-100, Winter.
    4. Onnela, J.-P. & Chakraborti, A. & Kaski, K. & Kertész, J., 2003. "Dynamic asset trees and Black Monday," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 247-252.
    5. Delphine Lautier and Franck Raynaud, 2012. "Systemic Risk in Energy Derivative Markets: A Graph-Theory Analysis," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    6. Delphine Lautier & Franck Raynaud, 2012. "Systemic risk in energy derivative markets: a graph theory analysis," Post-Print halshs-00738201, HAL.
    7. Jayanth R. Banavar & Amos Maritan & Andrea Rinaldo, 1999. "Size and form in efficient transportation networks," Nature, Nature, vol. 399(6732), pages 130-132, May.
    8. Scott H. Irwin & Dwight R. Sanders, 2011. "Index Funds, Financialization, and Commodity Futures Markets," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 33(1), pages 1-31.
    9. Leo Katz, 1953. "A new status index derived from sociometric analysis," Psychometrika, Springer;The Psychometric Society, vol. 18(1), pages 39-43, March.
    10. repec:dau:papers:123456789/9709 is not listed on IDEAS
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    More about this item

    Keywords

    Commodity markets; Financial markets; Derivative markets; Market integration; Crises; Graph theory; Minimum spanning tree; Centrality;
    All these keywords.

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