Asset allocation under predictability and parameter uncertainty using Lasso

DOI10.1007/s10287-020-00367-4OpenAlexW2946340222MaRDI QIDQ2221462

Andrea Rigamonti, Alex Weissensteiner

Publication date: 2 February 2021

Published in: Computational Management Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10287-020-00367-4

zbMATH Keywords

cross-validationparameter uncertaintyportfolio selectionLASSOreturn predictability

Mathematics Subject Classification ID

Operations research and management science (90Bxx)

Cites Work

• Computing efficient frontiers using estimated parameters
• Sparse and stable Markowitz portfolios
• A Generalized Approach to Portfolio Optimization: Improving Performance by Constraining Portfolio Norms
• SHARPE RATIO MAXIMIZATION AND EXPECTED UTILITY WHEN ASSET PRICES HAVE JUMPS
• A cross-validatory method for dependent data

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