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Sefiane, Slimane
- A Meta-Heuristic Ant Colony Optimization Method for Solving Portfolio Optimization
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Authors
Affiliations
1 University (Center) of Relizane, DZ
1 University (Center) of Relizane, DZ
Source
International Journal of Financial Management, Vol 3, No 4 (2013), Pagination: 1-8Abstract
This paper proposes a meta-heuristic ant colony optimization method to solve the portfolio optimization problem. The objective is to maximize the portfolio return and to minimize the portfolio risk simultaneously. To do so, the optimization problem is formulated as a total cost function to be minimized. The computational results on an example of five (05) stock portfolios not only show that the proposed method is capable and effective in finding the optimum portfolio return with the minimum of risk but also provides better solutions than another meta-heuristics based on genetic algorithms with respect to convergence time and efficiency.Keywords
Meta-heuristics Optimization Methods, Ant Colony Optimization Method, Multi-objective, Portfolio Optimization
References
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- A Cuckoo Optimisation Algorithm for Solving Financial Portfolio Problem
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Authors
Affiliations
1 Institute of Economic and Commercial Sciences, University (Center) of Relizane, DZ
2 University of Mostaganem, DZ
1 Institute of Economic and Commercial Sciences, University (Center) of Relizane, DZ
2 University of Mostaganem, DZ
Source
International Journal of Banking, Risk and Insurance, Vol 5, No 2 (2017), Pagination: 47-53Abstract
Over the years, different solution methods to financial portfolio optimisation problems have been developed and applied. In recent years, however, there has been an increasing use of heuristic methods as alternative to other methods. In this study, a newly developed heuristic method called Cuckoo Optimisation Algorithm (COA) is presented to solve financial portfolio optimisation problems. The results on a five stock application example show that the proposed cuckoo algorithm solves the portfolio optimisation problem more optimally than genetic algorithm and ant colony algorithm.Keywords
Financial Portfolio Optimisation, Approxi-Mate Methods, Cuckoo Optimisation Algorithm.References
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