Forecasting stock returns with model uncertainty and parameter instability
模型不确定性与参数不稳定性下的股票收益预测
Summary We compare several representative sophisticated model averaging and variable selection techniques of forecasting stock returns. When estimated traditionally, our results confirm that the simple combination of individual predictors is superior. However, sophisticated models improve dramatically once we combine them with the historical average and take parameter instability into account. An equal weighted combination of the historical average with the standard…