This paper presents an overview of the procedures that are involved in prediction with machine learning models with special emphasis on deep learning. We study suitable objective functions for prediction in high-dimensional settings and discuss the role of regularization methods in order to...

This article predicts the relative performance of hedge fund investment styles one period ahead using time-varying conditional stochastic dominance tests. These tests allow the construction of dynamic trading strategies based on nonparametric density forecasts of hedge fund returns. During the...