How Useful are Historical Data for Forecasting the Long-Run Equity Return Distribution?

We provide an approach to forecasting the long-run (unconditional distribution of equity returns making optimal use of historical data in the presence of structural breaks. Our focus is on learning about breaks in real time and assessing their impact on out-of-sample density forecasts. Forecasts use a probability-weighted average of submodels, each of which is estimated over a different history of data. The paper illustrates the importance of …