Original title: Výzkumný úkol ČVUT: Tools for Adaptive Portfolio Optimization
Authors: Procházka, Tomáš
Document type: Research reports
Year: 2025
Language: eng
Abstract: This research project presents a combination of techniques to develop a sound mathematical approach to the portfolio optimization problem. The problem is formulated as a Linear Quadratic Regulator and solved using Dynamic Programming. The key contributions include integrating multivariate regression modeling of returns with structure estimation for the regressor subset and employing exponential forgetting with an algorithm for varying forgetting factor. The optimal allocation is obtained by solving a constrained quadratic programming problem featuring a custom reward function. We highlight the importance of structure estimation and\nthe sequential approach, while also exploring the potential of modeling optimal allocation using the same regression framework as for returns.
Keywords: decision making; dynamic programming; linear quadratic regulator; multivariate linear regression; optimization; portfolio; structure estimation
Project no.: CA21169
Funding provider: EU-COST

Institution: Institute of Information Theory and Automation AS ČR (web)
Document availability information: Fulltext is available at external website.
External URL: https://library.utia.cas.cz/separaty/2025/AS/prochazka-0637014.pdf
Original record: https://hdl.handle.net/11104/0370102

Permalink: http://www.nusl.cz/ntk/nusl-692630


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