Feature selection for portfolio optimization

DOI10.1007/S10479-016-2155-YzbMath1415.91253OpenAlexW3124550086MaRDI QIDQ1699122

Thomas Trier Bjerring, Omri Ross, Alex Weissensteiner

Publication date: 16 February 2018

Published in: Annals of Operations Research (Search for Journal in Brave)

Full work available at URL: https://orbit.dtu.dk/en/publications/666d40a8-99c9-4abf-a42c-afc697f451b4

zbMATH Keywords

portfolio optimizationparameter uncertaintyfeature selectionagglomerative hierarchical clustering

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Portfolio theory (91G10) Software, source code, etc. for problems pertaining to game theory, economics, and finance (91-04)

Related Items (2)

Efficient cluster-based portfolio optimization ⋮ An application of sparse-group Lasso regularization to equity portfolio optimization and sector selection

Cites Work

• Unnamed Item
• A well-conditioned estimator for large-dimensional covariance matrices
• Nonlinear shrinkage estimation of large-dimensional covariance matrices
• Cluster analysis for portfolio optimization
• The benefits of differential variance-based constraints in portfolio optimization
• Portfolio Selection with Robust Estimation
• A Generalized Approach to Portfolio Optimization: Improving Performance by Constraining Portfolio Norms
• Consistency of Single Linkage for High-Density Clusters
• Common risk factors in the returns on stocks and bonds

This page was built for publication: Feature selection for portfolio optimization