Innovative Stock Portfolio Optimization: An Integrated Approach Using PSO Algorithm and Worst-Case CVaR with Dynamic Copula for Enhanced Performance
Subject Areas : اقتصادی
Vahid saee
1
,
yaghub pourkarim
2
*
,
Seyedali Paytakhti oskoii
3
,
Rasoul Baradaran Hassanzadeh
4
,
Mahdi zeynali
5
1 - Department of Accounting, Ta.c, Islamic Azad University, Tabriz, Iran
2 - Islamic Azad University / Tabriz Branch / Management, Economics and Accounting / Accounting
3 - Department of Economics, Tabriz Branch, Islamic Azad University, Tabriz, Iran
4 -
5 - Department of Accounting, Tabriz Branch, Islamic Azad University, Tabriz, Iran
Keywords: Portfolio Optimization, Mean-Variance Model, Dynamic Copula, Optimization, Metaheuristic Algorithm,
Abstract :
Portfolio optimization is a key concept in investment management that creates an optimal mix of return and risk in asset allocation. Modern Portfolio Theory (MPT), which accounts for correlations between assets and uses mean-variance analysis, is a key step in portfolio construction. However, the realities of the financial markets—which tend to reveal complexities and the need to manage heavy-tail risks and ephemeral dependencies—has prompted the need to develop much richer techniques, such as Conditional Value-at-Risk (CVaR) optimization frameworks and multi-objective processes. In this research, we introduce a new multi-objective model for optimal portfolio selection that utilizes, among other things, dynamic copula approaches to accurately quantify the linear and nonlinear nonparametric dependencies between assets, with the PSO algorithm to optimize the portfolio. This new model incorporates more sophisticated risk management metrics, such as Worst-Case Conditional Value-at-Risk (WCVaR) and expected return, and proposes a methodology for optimizing portfolios in dynamic investment environments. The findings indicate that the proposed model demonstrates significant superiority over classical approaches such as the Markowitz mean-variance model and equally weighted portfolios across performance metrics including the risk-adjusted Sharpe ratio and stability during market turbulence. By enabling dynamic asset allocation management and maintaining equilibrium between competing objectives (such as return maximization and risk minimization), this model presents an efficient solution for institutional and professional investors.
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