In an integrated world capital market, the same pricing kernel is applicable to all securities. We apply this idea to the stock returns of different countries. We investigate the underlying determinants of cross-country stock return correlations. First, we determine, for a given, measured degree of commonality of country outputs, what should be the degree of correlation of national stock returns. We propose a framework that contains a statistical model for output and an intertemporal financial market model for stock returns. We then attempt to match the correlations generated by the model with measured correlations. Our results show that under the hypothesis of market segmentation, the model correlations are much smaller than observed correlations. However, assuming world markets are integrated, our model correlations closely match observed correlations. * Dumas and Ruiz acknowledge gratefully the support of the HEC Foundation. Ruiz acknowledges also gratefully the support of IFM 2 . Dumas is also affiliated with the University of Pennsylvania (as an Adjunct Professor), the NBER and the CEPR. Harvey is also affiliated with the NBER. The comments of Enrique Arzac,

In an integrated world capital market, the same pricing kernel is applicable to all securities. We apply this idea to the stock returns of different countries. We investigate the underlying determinants of cross-country stock return correlations. First, we determine, for a given, measured degree of commonality of country outputs, what should be the degree of correlation of national stock returns. We propose a framework that contains a statistical model for output and an intertemporal financial market model for stock returns. We then attempt to match the correlations generated by the model with measured correlations. Our results show that under the hypothesis of market segmentation, the model correlations are much smaller than observed correlations. However, assuming world markets are integrated, our model correlations can be matched with observed correlations. #

Short abstract: The authors describe the development of an innovative decision-support system that uses forecasting, discrete-event simulation, and optimization to provide an integrated approach to revenue and capacity management.