Bayesian Portfolio Regularization

• Applicant: Professor Dr. Winfried Franz Xaver Pohlmeier
• Subject Area: Statistics and Econometrics
• Term: from 2016 to 2019
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 321011636

Stylized facts on the performance of portfolio models indicate that the empirical counterparts of theoretically optimal portfolio strategies show a very poor performance compared to approaches based on simpler and theoretically inferior strategies. The goal of the proposed research project is to develop a new class of Bayesian regularization strategies to achieve robust and high-performing portfolio models. The Bayesian approach applied directly to the estimation of the portfolio weights provides a unifying framework for a large range of different regularization strategies as well as for model selection and evaluation.Besides the theoretical contributions the project will also provide empirical evidence on the quality of the proposed new strategies for a variety of assets and markets. Special attention will be given to estimation strategies in high-dimensional settings.

• DFG Programme: Research Grants