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...

This paper studies dividend growth predictability without restricting conditioning information set to dividend yield alone. We highlight that predictability crucially hinges on how dividend growth is constructed. Dividend growth without reinvestment is significantly predictable both in-sample...