Comparison of AIS and PSO for constrained portfolio optimization
Faculty / School
Faculty of Computer Sciences (FCS)
Department
Department of Computer Science
Was this content written or created while at IBA?
Yes
Document Type
Conference Paper
Publication Date
11-17-2009
Conference Name
2009 International Conference on Information and Financial Engineering
Conference Location
Singapore
Conference Dates
17-20 April 2009
ISBN/ISSN
70449453555 (Scopus)
First Page
50
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Keywords
Artificial immune systems, Computational intelligence, Markowitz mean-variance theory, Particle swarm optimization, Portfolio optimization
Abstract / Description
This paper applies two computational intelligence techniques, namely particle swarm optimization and artificial immune systems, to constrained portfolio optimization. The portfolio selection model considered in this paper is based on the classical Markowitz mean-variance theory enhanced with floor and ceiling constraints. Several experiments are conducted using the stocks listed on the Karachi Stock Exchange 30 Index (KSE30). The performances of both computational intelligence techniques are compared on two criteria:
(a) maximization of expected return
(b) maximization of return-to-variance ratio.
The results are also compared with the ones obtained through Microsoft Excel Solver.
DOI
https://doi.org/10.1109/ICIFE.2009.32
Recommended Citation
Abbas, A., & Haider, S. (2009). Comparison of AIS and PSO for constrained portfolio optimization., 50. https://doi.org/10.1109/ICIFE.2009.32
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