A Meta-Heuristic Ant Colony Optimization Method for Solving Portfolio Optimization
Published: 2013
Author(s) Name: Slimane Sefiane, Mohamed Benbouzian |
Author(s) Affiliation: University (Center) of Relizane, Alg
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Abstract
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.
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