In this paper the relatively new technique of neural nets is integrated in a traditional model of portfolio choice. On the basis of Arrow’s State Preference Model the investment decision depends on the expectation building process which consists of two components. The individual information...

Machine learning (ML) is a novel method that has applications in asset pricing and that fits well within the problem of measurement in economics. Unlike econometrics, ML models are not designed for parameter estimation and inference, but similar to econometrics, they address, and may be better...

This paper deals with identification and inference on the unobservable conditional factor space and its dimension in large unbalanced panels of asset returns. The model specification is nonparametric regarding the way the loadings vary in time as functions of common shocks and individual...

In the feld of empirical asset pricing, the challenges of high dimensionality, non-linear relationships, and interaction efects have led to the increasing popularity of machine learning (ML) methods. This study investigates the performance of ML methods when predicting diferent measures of stock...