A heuristic algorithm for a portfolio optimization model applied to the Milan stock market
Computers and Operations Research
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Improving Portfolio Efficiency: A Genetic Algorithm Approach
Computational Economics
Evolutionary multi-objective optimization: a historical view of the field
IEEE Computational Intelligence Magazine
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This paper is concerned with asset allocation under real constraints when VaR is the risk measure to minimize. Our paper makes a contribution in several ways, we use a risk measure that is not linear programming solvable, we introduce real constraints, such as minimum transaction units and non-linear cost structure and, finally, we avoid the use of smoothing techniques. The approach we propose is based on multi-objective genetic algorithms. The results presented show the adequacy of the method for the portfolio optimization problem and emphasize the importance of dealing with real constraints during the optimization process.