Application of a Memetic Algorithm to the Portfolio Optimization Problem

被引：0
|
作者：
Aranha, Claus [1 ]
Iba, Hitoshi [1 ]
机构：
[1] Univ Tokyo, Tokyo 1138654, Japan
来源：
AI 2008: ADVANCES IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS | 2008年 / 5360卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：512 / 521
页数：10
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