Financial Asset Allocation and Portfolio Optimization Strategies Based on Stochastic Optimization Methods

Financial market uncertainty necessitates sophisticated asset allocation and portfolio optimization strategies for enhanced returns and risk mitigation. This study explores stochastic optimization methods to overcome the limitations of traditional models in complex market environments. By employing expected utility theory and the Lagrange multiplier method, we develop an optimization model that facilitates fair equity pricing and enables dynamic allocation of financial assets, outperforming traditional approaches in simulated markets. Specifically, our method yields mean allocations for state-owned and non-state-owned enterprises at 17.4112 and 16.9297, respectively, demonstrating its superiority. Analysis of bank asset portfolios reveals significant improvements in asset structure and yields, underscoring the effectiveness of stochastic optimization in financial asset management, offering substantial benefits in efficiency and investment returns. © 2024 Tao Yang, published by Sciendo.