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Commodity and Equity Markets: Some Stylized Facts from a Copula Approach

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  • Delatte, Anne-Laure
  • Lopez, Claude

Abstract

In this paper, we propose to identify the dependence structure existing between the returns of equity and commodity futures and its evolution through the past 20 years. The key point is that we do not do not impose the dependence structure but let the data select it. To do so, we model the dependence between commodity (metal, agriculture and energy) and stock markets using a flexible approach that allows us to investigate whether the co-movement is : (i) symmetric and occurring most of the time, (ii) symmetric and occurring mostly during extreme events and (iii) asymmetric and occurring mostly during extreme events. We also allow for this dependence to be time-varying from January 1990 to February 2012. Our analysis uncovers three major stylized facts. First, we find that the dependence between commodity and stock markets is time varying, symmetric and occurs most of the time (as opposed to mostly in extreme events). Second, not allowing for time-varying parameters in the dependence distribution generates a bias toward evidence of tail dependence. Similarly, considering only tail dependence may lead to wrong evidence of asymmetry. Third, a growing comovement between industrial metals and equity markets is identified as early as in 2003, a comovement that spreads to all commodity classes and becomes unambiguously stronger with the global financial crisis after Fall 2008.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 39860.

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Date of creation: Jul 2012
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Handle: RePEc:pra:mprapa:39860

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Keywords: copula; commodity market; time varying; tail-dependence; comovement; equity market;

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  1. David Bicchetti & Nicolas Maystre, 2012. "The Synchronized And Long-Lasting Structural Change On Commodity Markets: Evidence From High Frequency Data," UNCTAD Discussion Papers, United Nations Conference on Trade and Development 208, United Nations Conference on Trade and Development.
  2. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 20(3), pages 339-50, July.
  3. Thierry Ane & Cecile Kharoubi, 2003. "Dependence Structure and Risk Measure," The Journal of Business, University of Chicago Press, University of Chicago Press, vol. 76(3), pages 411-438, July.
  4. Ning, Cathy, 2010. "Dependence structure between the equity market and the foreign exchange market-A copula approach," Journal of International Money and Finance, Elsevier, Elsevier, vol. 29(5), pages 743-759, September.
  5. Silvennoinen, Annastiina & Thorp, Susan, 2013. "Financialization, crisis and commodity correlation dynamics," Journal of International Financial Markets, Institutions and Money, Elsevier, Elsevier, vol. 24(C), pages 42-65.
  6. Chollete, Lorán & de la Peña, Victor & Lu, Ching-Chih, 2011. "International diversification: A copula approach," Journal of Banking & Finance, Elsevier, Elsevier, vol. 35(2), pages 403-417, February.
  7. François Longin, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, American Finance Association, vol. 56(2), pages 649-676, 04.
  8. Koedijk, Kees & Kole, Erik & Verbeek, Marno, 2006. "Selecting Copulas for Risk Management," CEPR Discussion Papers, C.E.P.R. Discussion Papers 5652, C.E.P.R. Discussion Papers.
  9. Daskalaki, Charoula & Skiadopoulos, George, 2011. "Should investors include commodities in their portfolios after all? New evidence," Journal of Banking & Finance, Elsevier, Elsevier, vol. 35(10), pages 2606-2626, October.
  10. Desmoulins-Lebeault, François & Kharoubi-Rakotomalala, Cécile, 2012. "Non-Gaussian diversification: When size matters," Journal of Banking & Finance, Elsevier, Elsevier, vol. 36(7), pages 1987-1996.
  11. Ke Tang & Wei Xiong, 2010. "Index Investment and Financialization of Commodities," NBER Working Papers 16385, National Bureau of Economic Research, Inc.
  12. Yannick Malevergne & Didier Sornette, 2003. "Testing the Gaussian copula hypothesis for financial assets dependences," Post-Print, HAL hal-00520539, HAL.
  13. Andrew J. Patton, 2006. "Modelling Asymmetric Exchange Rate Dependence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 527-556, 05.
  14. Ling Hu, 2006. "Dependence patterns across financial markets: a mixed copula approach," Applied Financial Economics, Taylor & Francis Journals, Taylor & Francis Journals, vol. 16(10), pages 717-729.
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Cited by:
  1. Duc Khuong Nguyen & Ricardo M. Sousa & Gazi Salah Uddin, 2014. "Testing for asymmetric causality from U.S. equity returns to commodity futures returns," Working Papers, Department of Research, Ipag Business School 2014-545, Department of Research, Ipag Business School.
  2. Ielpo, Florian & Chevallier, Julien, 2013. "Volatility spillovers in commodity markets," Economics Papers from University Paris Dauphine, Paris Dauphine University 123456789/11708, Paris Dauphine University.
  3. Aboura, Sofiane & Chevallier, Julien, 2014. "Volatility returns with vengeance: Financial markets vs. commodities," Economics Papers from University Paris Dauphine, Paris Dauphine University 123456789/13359, Paris Dauphine University.

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