Motivated by recent developments in light of the sub-prime and subsequent financial crisis we fit two different vector autoregressive generalized conditional heteroscedastic (VAR-GARCH) models to three financial indices with the aim of understanding the development of dependency structures between credit spreads and other macroeconomic variables. Our analysis includes daily quotes from June 2004 to April 2009 of the iTraxx Europe index, the Dow Jones Euro Stoxx 50 index, and the Dow Jones VStoxx index. We propose a robust, time-varying modeling approach concerning the conditional mean, and a BEKK versus DCC-GARCH approach concerning the conditional covariance. Furthermore we allow for a parsimonious model specification by setting insignificant coefficients to zero. Our empirical results indicate that the autoregressive coefficients vary strongly with time and even change their signs. Well-known interrelations, such as the negative correlation between CDS’ and stocks are lost through the financial crisis. The conditional covariance estimates in the BEKK and DCC model are fairly similar, given the difference in the number of model parameters. We found evidence of strongly varying conditional variances and correlations, with dependencies increasing after the outbreak of the financial crisis. This knowledge may help to improve decision tools in the financial industry, especially in areas such as asset pricing, portfolio selection, and risk management.     «

Motivated by recent developments in light of the sub-prime and subsequent financial crisis we fit two different vector autoregressive generalized conditional heteroscedastic (VAR-GARCH) models to three financial indices with the aim of understanding the development of dependency structures between credit spreads and other macroeconomic variables. Our analysis includes daily quotes from June 2004 to April 2009 of the iTraxx Europe index, the Dow Jones Euro Stoxx 50 index, and the Dow Jones V...     »