Forecasting financial and macroeconomic variables using data reduction methods: New empirical evidence
利用数据降维方法预测金融与宏观变量：新的实证证据
In this paper, we empirically assess the predictive accuracy of a large group of models that are specified using principle components and other shrinkage techniques, including Bayesian model averaging and various bagging, boosting, least angle regression and related methods. Our results suggest that model averaging does not dominate other well designed prediction model specification methods, and that using “hybrid” combination factor/shrinkage methods often yields superior…