Application of a Memetic Algorithm to the Portfolio Optimization Problem

Authors:
Claus Aranha;Hitoshi Iba
Affiliations:
The University of Tokyo,;The University of Tokyo,
Venue:
AI '08 Proceedings of the 21st Australasian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Year:
2008

Citing 4
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Abstract

We use local search to improve the performance of Genetic Algorithms applied the problem of Financial Portfolio Selection and Optimization. Our work describes the Tree based Genetic Algorithm for Portfolio Optimization. To improve this evolutionary system, we introduce a new guided crossover operator, which we call the BWS, and add a local optimization step. The performance of the system increases noticeably on simulated experiments with historical data.