This paper considers predictive regressions, where y_t is predicted by all p lags of x, here with x being autoregressive of order q, PR(p,q). The literature considers model properties in the cases where p=q. We demonstrate that the current augmented regression method can still reduce the bias in...

Forecasting stock market movements is a challenging task from the practitioners' point of view. We explore how model selection via the least absolute shrinkage and selection operator (LASSO) approach can be better used to forecast stock closing prices using real-world datasets of daily stock...

The inquiries to return predictability are traditionally limited to the first two moments, mean and volatility. Analogously, literature on portfolio selection also stems from a moment-based analysis with up to the fourth moment being considered. This paper develops a distribution-based framework...