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A Copula Approach on the Dynamics of Statistical Dependencies in the US Stock Market

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  • Michael C. Munnix
  • Rudi Schafer

Abstract

We analyze the statistical dependency structure of the S&P 500 constituents in the 4-year period from 2007 to 2010 using intraday data from the New York Stock Exchange's TAQ database. With a copula-based approach, we find that the statistical dependencies are very strong in the tails of the marginal distributions. This tail dependence is higher than in a bivariate Gaussian distribution, which is implied in the calculation of many correlation coefficients. We compare the tail dependence to the market's average correlation level as a commonly used quantity and disclose an nearly linear relation.

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  • Michael C. Munnix & Rudi Schafer, 2011. "A Copula Approach on the Dynamics of Statistical Dependencies in the US Stock Market," Papers 1102.1099, arXiv.org, revised Mar 2011.
  • Handle: RePEc:arx:papers:1102.1099
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    References listed on IDEAS

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    1. Y. Malevergne & D. Sornette, 2003. "Testing the Gaussian copula hypothesis for financial assets dependences," Quantitative Finance, Taylor & Francis Journals, vol. 3(4), pages 231-250.
    2. Rudi Schafer & Markus Sjolin & Andreas Sundin & Michal Wolanski & Thomas Guhr, 2007. "Credit risk - A structural model with jumps and correlations," Papers 0707.3478, arXiv.org, revised Jul 2007.
    3. Parameswaran Gopikrishnan & Vasiliki Plerou & Luis A. Nunes Amaral & Martin Meyer & H. Eugene Stanley, 1999. "Scaling of the distribution of fluctuations of financial market indices," Papers cond-mat/9905305, arXiv.org.
    4. V. Plerou & P. Gopikrishnan & L. A. N. Amaral & M. Meyer & H. E. Stanley, 1999. "Scaling of the distribution of price fluctuations of individual companies," Papers cond-mat/9907161, arXiv.org.
    5. Michael C. Munnix & Rudi Schafer & Thomas Guhr, 2009. "Compensating asynchrony effects in the calculation of financial correlations," Papers 0910.2909, arXiv.org, revised Jul 2010.
    6. Fernandez, Viviana, 2008. "Copula-based measures of dependence structure in assets returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(14), pages 3615-3628.
    7. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    8. Tastan, Hüseyin, 2006. "Estimating time-varying conditional correlations between stock and foreign exchange markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 360(2), pages 445-458.
    9. Rosenberg, Joshua V. & Schuermann, Til, 2006. "A general approach to integrated risk management with skewed, fat-tailed risks," Journal of Financial Economics, Elsevier, vol. 79(3), pages 569-614, March.
    10. S. Drozdz & J. Kwapien & F. Gruemmer & F. Ruf & J. Speth, 2001. "Quantifying dynamics of the financial correlations," Papers cond-mat/0102402, arXiv.org.
    11. Chavez-Demoulin, V. & Embrechts, P. & Neslehova, J., 2006. "Quantitative models for operational risk: Extremes, dependence and aggregation," Journal of Banking & Finance, Elsevier, vol. 30(10), pages 2635-2658, October.
    12. Münnix, Michael C. & Schäfer, Rudi & Guhr, Thomas, 2010. "Compensating asynchrony effects in the calculation of financial correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(4), pages 767-779.
    13. Michael C. Munnix & Rudi Schafer & Thomas Guhr, 2010. "Impact of the tick-size on financial returns and correlations," Papers 1001.5124, arXiv.org, revised Jul 2010.
    14. Frahm, Gabriel & Junker, Markus & Schmidt, Rafael, 2005. "Estimating the tail-dependence coefficient: Properties and pitfalls," Insurance: Mathematics and Economics, Elsevier, vol. 37(1), pages 80-100, August.
    15. Münnix, Michael C. & Schäfer, Rudi & Guhr, Thomas, 2010. "Impact of the tick-size on financial returns and correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4828-4843.
    16. Rosenow, Bernd & Gopikrishnan, Parameswaran & Plerou, Vasiliki & Eugene Stanley, H, 2003. "Dynamics of cross-correlations in the stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 241-246.
    17. L. Kullmann & J. Kertesz & K. Kaski, 2002. "Time dependent cross correlations between different stock returns: A directed network of influence," Papers cond-mat/0203256, arXiv.org, revised May 2002.
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