Abstract:
We estimate a number of multivariate regime switching VAR models on a long monthly data set for eight variables that include excess stock and bond returns, the real T-bill yield, predictors used in the finance literature (default spread and the dividend yield), and three macroeconomic variables (inflation, real industrial production growth, and a measure of real money growth). Heteroskedasticity may be accounted for by making the covariance matrix a function of the regime. We find evidence of four regimes and of time-varying covariances. We provide evidence that the best in-sample fit is provided by a four state model in which the VAR(1) component fails to be regime-dependent. We interpret this as evidence that the dynamic linkages between financial markets and the macroeconomy have been stable over time. We show that the four-state model can be helpful in forecasting applications and to provide one-step ahead predicted Sharpe ratios.