Forecasting macroeconomic variables using diffusion indexes in short samples with structural change / Anindya Banerjee, Massimiliano Marcellino, Igor Masten -- Predictive inference under model misspecification / Nii Ayi Armah, Norman R. Swanson -- Forecasting persistent data with possible...

This paper extends the machine learning methods developed in Han et al. (2019) for forecasting cross-sectional stock returns to a time-series context. The methods use the elastic net to refine the simple combination return forecast from Rapach et al. (2010). In a time-series application focused...

Asset returns change with fundamentals and other factors, such as technical information and sentiment over time. In modeling time-varying expected returns, this article focuses on the out-of-sample predictability of the aggregate stock market return via extensions of the conventional predictive...