ALPS evaluation in financial portfolio optimisation

被引:4
|
作者
Patel, S. [1 ]
Clack, C. D. [1 ]
机构
[1] UCL, Dept Comp Sci, London WC1E 6BT, England
关键词
D O I
10.1109/CEC.2007.4424554
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Hornby's Age-Layered Population Structure claims to reduce premature convergence in Evolutionary Algorithms. We provide the first evaluation of ALPS on a real-world problem - the evolution of non-linear factor models for financial portfolio optimisation. We incorporate ALPS into our GP system, coupled to an investment simulator, and provide a head-to-head comparison between ALPS GP and Standard GP. By investigating the performance of ALPS both during training and during out-of-sample validation, we provide empirical evidence of the benefits of ALPS; we show that it really does reduce convergence, and provides fitter individuals, in our problem domain. The ALPS GP system evolves non-linear factor models that out-perform not only the Standard GP system, but also the market index by a significant amount.
引用
收藏
页码:813 / 819
页数:7
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