Stochastic network optimization models for investment planning
Annals of Operations Research
Multi-stage stochastic linear programs for portfolio optimization
Annals of Operations Research
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
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A multistage stochastic financial optimization manages portfolio in constantly changing financial markets by periodically rebalancing the asset portfolio to achieve return maximization and/or risk minimization. In this paper, we present a decision-making process that uses our proposed Quantum-behaved Particle Swarm Optimization (QPSO) Algorithm to solve multi-stage portfolio optimization problem. The objective function is classical return-variance function. The performance of our algorithm is demonstrated by optimizing the allocation of cash and various stocks in S&P 100 index. Experiments are conducted to compare performance of the portfolios optimized by different objective functions with Particle Swarm Optimization (PSO) algorithm and Genetic Algorithm (GA) in terms of efficient frontiers.