Predictive Returns using Machine Learning Techniques

  • Raimondo Grova Raimondo Grova

In the paper, the econometrics and machine learning field in asset pricing are summarized. A complete review and comparison of techniques including Ordinary Least Squares,
Elastic Net, Random Forest and Neural Networks for stock return prediction is performed. All approaches are tested using a predictive out-of-sample R2 to observe their behavior under an unstudied sample. Furthermore a portfolio using long-short strategy is constructed. Results show that machine learning algorithm are raising hope in the asset field but remain inaccurate for the moment.

Netspar, Network for Studies on Pensions, Aging and Retirement, is a thinktank and knowledge network. Netspar is dedicated to promoting a wider understanding of the economic and social implications of pensions, aging and retirement in the Netherlands and Europe.

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