We introduce a forecasting method that closely matches the econometric properties required by the theory on exchange rate prediction. Our approach formally models (i) when (and if) explanatory variables enter or leave a regression model, (ii) the degree of parameter instability, (iii) the...

This paper introduces a Bayesian version for Dynamic Model Averaging for predicting aggregate stock returns. Our suggested approach simultaneously accounts for many sources of uncertainty. It is designed to handle (i) parameter instability, (ii) time-varying volatility, (iii) model uncertainty...