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Published, Version of Record (VoR)Open Access Discount via Drexel Libraries Read and Publish Program 2025CC BY V4.0, Open
Journal article
Multi-Period Portfolio Optimization Model with Cone Constraints and Discrete Decisions
Journal of risk and financial management, v 18(4), 218
18 Apr 2025
Featured in Collection : Research Supported by Drexel Libraries' OA Programs
Abstract
This work develops a practical multi-period optimization approach that incorporates real-world constraints, including discrete decisions and conic risk constraints. Expanding upon earlier single-period models, our framework employs a binary scenario tree derived from monthly returns of randomly selected S&P 500 stocks to represent market evolution across multiple periods. The formulation captures essential portfolio constraints, such as transaction fees, sector diversification, and minimum investment thresholds, resulting in a robust and comprehensive optimization approach. To efficiently solve the resulting mixed-integer second-order cone programming (MISOCP) problem, we employ an outer approximation algorithm with a warmstart strategy, which significantly improves solution runtimes and computational efficiency. Numerical experiments demonstrate the model’s effectiveness, showing an average improvement of 10.71% in iteration count and 15.24% in computational time when using the warmstart approach.
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Details
- Title
- Multi-Period Portfolio Optimization Model with Cone Constraints and Discrete Decisions
- Creators
- Ümit Sağlam - East Tennessee State UniversityHande Y Benson (Corresponding Author) - Drexel University, Decision Sciences (and Management Information Systems)
- Publication Details
- Journal of risk and financial management, v 18(4), 218
- Publisher
- MDPI
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Decision Sciences (and Management Information Systems)
- Scopus ID
- 2-s2.0-105003473823
- Other Identifier
- 991022047817104721