Self Organized Features Maps SOFM and Hybrid Neuro-Genetic SOFMs in Optimal Portfolio Management

N. Loukeris, George Chalamandaris, I. Eleftheriadis
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引用次数: 1

Abstract

We investigate the optimal performance of Self Organized Feature Maps in 60 different models of plain and hybrid form to define the optimal classifier. We also apply it on a novel model of optimal portfolio selection in hedging aspects.
最优投资组合管理中的自组织特征映射SOFM和混合神经遗传SOFM
我们研究了自组织特征映射在60种不同的普通和混合形式模型中的最优性能,以定义最优分类器。并将其应用于对冲方面的一个新的最优投资组合选择模型。
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