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...

We propose a novel spatial panel quantile regression method to investigate the impact of crude oil and carbon prices and neighboring fuel prices on regional retail fuel prices in the EU markets. This approach captures the changing price shock propagation and cross-market dependency of retail...

We estimate and test long-run risk models using international macroeconomic and financial data. The benchmark model features a representative agent who has recursive preferences with a time preference shock, a persistent component in expected consumption growth, and stochastic volatility in...