A0593
Title: Ensembles of portfolio rules
Authors: Federico Nardari - University of Melbourne (Australia)
Rainer Alexander Schuessler - University of Rostock (Germany) [presenting]
Abstract: A framework for combining portfolio rules while mitigating the impact of estimation error is proposed. The main goal is to integrate heterogeneous rules that previously proposed combination methods cannot accommodate, enabling researchers and investors to leverage established and ongoing advances in portfolio choice. The proposed framework relies on the pseudo, out-of-sample returns of the considered rules, thus avoiding estimation of the PRs return moments. The optimal combination is determined by an ensemble approach that maximizes the utility generated jointly by the candidate rules while allowing for learning about the PRs' relative performance. Based on out-of-sample evaluations of over forty years, substantial utility gains are documented for the approach compared to both individual rules and previously proposed combination strategies.
