The introduction of the Euro has been one of the most important events for global financial markets in the last decade. Detken and Hartmann (2000, 2002) and Perée and Steinherr (2001) show that the Euro has become one of the three major currencies in the world after its introduction, taking its place alongside the U.S. dollar and the Japanese yen. An immediate consequence of the adoption of the common currency has been the convergence of Euro-zone interest rates and the integration of fixed-income markets (Adjaouté and Danthine, 2003; Hartmann et al., 2003). Another important dimension of the elimination of exchange rate risk across countries within the Euro area, as a result of the adoption of a single currency, is its effect on the dependence or comovement of equity markets within the Euro area. The impact of the introduction of the Euro on the dependence of equity markets within Europe is an important issue with significant implications for portfolio diversification and thus asset management, risk management and international asset pricing.
To assess this impact of the Euro, this paper provides a comprehensive analysis of the financial market co-movement of 17 European countries during the period 1994-2003 using a new econometric methodology. 1 In particular, we directly assess financial market dependence or co-movement across countries by estimating time-varying copula dependence models for stock market indices following the methodology of Patton (2006a). As shown by Patton and explained in more detail in Section 3, copulas offer significant advantages over other econometric techniques in analyzing the co-movement of financial time-series, consisting in the fact that they can model dependence beyond linear correlation and provide a high degree of flexibility. In particular, marginal distributions and the joint distribution can be considered separately, while traditionally, either the marginals or the joint distribution are arbitrarily specified as normal distributions. Consequently, copulas have recently become increasingly popular in various finance applications, such as modeling default correlations for credit risk management (Li, 2000), modeling portfolio allocations (Hennessy and Lapan, 2002), pricing foreign exchange rate quanto options (Bennett and Kennedy, 2003), pricing multivariate contingent claims (Rosenberg, 2003), and modeling time-varying dependence (Patton, 2006a,b).