This paper addresses the problem of investment optimization using genetic control. Time series for stock values are obtained from data available on the www and asset prices are predicted using adaptive algorithms. A portfolio is optimized with the genetic algorithm based on a recursive model of portfolio composition obtained on-the-fly using genetic programming. These two steps are integrated into an automatic system - the final result is a real-time system for updating portfolio composition for each asset.
CITATION STYLE
Werner, J. C., & Fogarty, T. C. (2002). Genetic control applied to asset managements. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2278, pp. 192–201). Springer Verlag. https://doi.org/10.1007/3-540-45984-7_19
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