On the Dynamics of Industrial Stock Market Excess Returns

I study predictability and financial integration for the excess returns on ten emerging and U.S. industrial stock markets. Firstly, I examine one-factor and multi-factor linear models in a static context. I focus on the explanatory power of some common, macro, and artificial global risk factors. Estimation results suggest that emerging and U.S. industry excess returns are affected by the same global risk factors. I show that multi-factor models do a better job in explaining emerging and U.S. industry excess returns. Differently from U.S. estimates, I find that the ``emerging industry intercepts'' are positive and significantly different from zero. The result holds over four different linear factor models. My findings suggest that local risk factors may still play a key role. Secondly, I study the dynamics of the financial integration process across emerging and U.S. industrial stock markets. Examining the dynamics of the explanatory power of a multi-(artificial) factor model, where the first ten principal components extracted from a large set of variables are loaded as predictors, I show that emerging industrial stock markets are increasingly integrated. I also observe that the integration process across emerging industries has been affected by the ``emerging country shocks'' of the late Õ90s. The result is confirmed by the dynamics of the correlation coefficients between emerging and U.S. industrial stock markets. My findings suggest also that cross-industry diversification benefits are negligible.