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Symmetry 2017, 9(9), 168; https://doi.org/10.3390/sym9090168

An Agent-Based Co-Evolutionary Multi-Objective Algorithm for Portfolio Optimization

AGH University of Science and Technology, Department of Computer Science, 30-059 Kraków, Poland
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Received: 19 June 2017 / Revised: 8 August 2017 / Accepted: 17 August 2017 / Published: 23 August 2017
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Abstract

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. View Full-Text
Keywords: portfolio optimization; multi-objective optimization; agent-based co-evolutionary algorithms; co-evolutionary algorithms; genetic algorithms portfolio optimization; multi-objective optimization; agent-based co-evolutionary algorithms; co-evolutionary algorithms; genetic algorithms
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Dreżewski, R.; Doroz, K. An Agent-Based Co-Evolutionary Multi-Objective Algorithm for Portfolio Optimization. Symmetry 2017, 9, 168.

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