In this paper, we propose three new predictive models: the multi-step nonparametric predictive regression model and the multi-step additive predictive regression model, in which the predictive variables are locally stationary time series; and the multi-step time-varying coefficient predictive...

This paper investigates the performance of a factor-augmented regression (FAR) model with a mixture of stationary and nonstationary factors in stock return prediction. For comparison purpose, we also consider a traditional FAR model with only stationary factors. In an application with a dataset...

This paper investigates the performance of a factor-augmented regression (FAR) model with a mixture of stationary and nonstationary factors in stock return prediction. For comparison purpose, we also consider a traditional FAR model with only stationary factors. In an application with a dataset...

This paper introduces a factor-augmented forecasting regression model in the presence of threshold effects. We consider least squares estimation of the regression parameters, and establish asymptotic theories for estimators of both slope coefficients and the threshold parameter. Prediction...