A copula approach on the dynamics of statistical dependencies in the US stock market

Michael C. Münnix and Rudi Schäfer

Physica A: Statistical Mechanics and its Applications, 2011, vol. 390, issue 23, 4251-4259

Abstract: We analyze the statistical dependence 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. Instead of using a given parametric copula with a predetermined shape, we study the empirical pairwise copula directly. We find that the shape of this copula resembles the Gaussian copula to some degree, but exhibits a stronger tail dependence, for both correlated and anti-correlated extreme events. By comparing the tail dependence dynamically to the market’s average correlation level as a commonly used quantity we disclose the average level of error of the Gaussian copula, which is implied in the calculation of many correlation coefficients.

Keywords: Financial correlations; Statistical dependencies; Copula; Market dynamics (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:390:y:2011:i:23:p:4251-4259

DOI: 10.1016/j.physa.2011.06.032

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