Journal
SYMMETRY-BASEL
Volume 9, Issue 9, Pages -Publisher
MDPI
DOI: 10.3390/sym9090168
Keywords
portfolio optimization; multi-objective optimization; agent-based co-evolutionary algorithms; co-evolutionary algorithms; genetic algorithms
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Funding
- AGH University of Science and Technology Statutory Fund
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Algorithms based on the process of natural evolution are widely used to solve multi-objective optimization problems. In this paper we propose the agent-based co-evolutionary algorithm for multi-objective portfolio optimization. The proposed technique is compared experimentally to the genetic algorithm, co-evolutionary algorithm and a more classical approach-the trend-following algorithm. During the experiments historical data from the Warsaw Stock Exchange is used in order to assess the performance of the compared algorithms. Finally, we draw some conclusions from these experiments, showing the strong and weak points of all the techniques.
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