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

详细信息    查看全文

• 作者：Michael C.  ; Mü ; nnix^a ;   ; ^b ;   ; ^{michael@muennix.com} ; Rudi  ; Schä ; fer^a
• 关键词：Financial correlations ; Statistical dependencies ; Copula ; Market dynamics
• 刊名：Physica A
• 出版年：2011
• 出版时间：1 November 2011
• 年：2011
• 卷：390
• 期：23-24
• 页码：4251-4259
• 全文大小：1279 K

文摘

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.