Application of the Improved Differential Evolution Algorithm in Portfolio

Aiming at the NP hard problem of portfolio optimization, an improved differential evolution algorithm is proposed. In this algorithm, the mutation operator and crossover operator are set up adaptively, and then according to the characteristics of the mutation itself, two kinds of mutation operators...

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Bibliographic Details
Published inITM Web of Conferences Vol. 11; p. 1006
Main Authors Ning, Gui-Ying, Cao, Dun-Qian, Zhou, Yong-Quan
Format Journal Article Conference Proceeding
LanguageEnglish
Published Les Ulis EDP Sciences 2017
Subjects
Algorithms
Empirical analysis
Evolutionary algorithms
Mutation
Optimization
Portfolio management
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Summary:Aiming at the NP hard problem of portfolio optimization, an improved differential evolution algorithm is proposed. In this algorithm, the mutation operator and crossover operator are set up adaptively, and then according to the characteristics of the mutation itself, two kinds of mutation operators with global search ability and local search ability are improved .The improved algorithm can improve the convergence speed and ensure the precision of the algorithm. Through five stocks of the same type and 20 different types of stocks for empirical analysis, the results show that the proposed algorithm has a certain guiding role in solving the problem of portfolio optimization.
ISSN:2271-2097
2431-7578
2271-2097
DOI:10.1051/itmconf/20171101006