期刊
EXPERT SYSTEMS WITH APPLICATIONS
卷 38, 期 8, 页码 10161-10169出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2011.02.075
关键词
Expert system; Swarm Intelligence (SI); Particle Swarm Optimization (PSO); Portfolio management (PM); Optimal portfolio; Sharp Ratio (SR)
One of the most studied problems in the financial investment expert system is the intractability of portfolios. The non-linear constrained portfolio optimization problem with multi-objective functions cannot be efficiently solved using traditionally approaches. This paper presents a meta-heuristic approach to portfolio optimization problem using Particle Swarm Optimization (PSO) technique. The model is tested on various restricted and unrestricted risky investment portfolios and a comparative study with Genetic Algorithms is implemented. The PSO model demonstrates high computational efficiency in constructing optimal risky portfolios. Preliminary results show that the approach is very promising and achieves results comparable or superior with the state of the art solvers. (C) 2011 Elsevier Ltd. All rights reserved.
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