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2018 | OriginalPaper | Buchkapitel

A PIP-Based Approach for Optimizing a Group Stock Portfolio by Grouping Genetic Algorithm

verfasst von : Chun-Hao Chen, Chih-Hung Yu

Erschienen in: Genetic and Evolutionary Computing

Verlag: Springer Singapore

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Abstract

Recently, some approaches have been proposed for finding a group stock portfolio (GSP). However, stock price series of stocks which are useful information may not be considered in those approaches. Hence, this study takes stock price series into consideration and presents a perceptually important point (PIP)-based approach for obtaining a GSP. Since the PIP is used, the proposed approach can handle stock price series with different lengths, which means that a more useful GSP could be found and provided to investors. Each chromosome is encoded by grouping, stock, and stock portfolio parts. To measure the similarity of series in groups, the series distance is designed and used as a part of fitness function. At last, experiments were conducted on a real dataset to show the advantages of the proposed approach.

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Metadaten
Titel
A PIP-Based Approach for Optimizing a Group Stock Portfolio by Grouping Genetic Algorithm
verfasst von
Chun-Hao Chen
Chih-Hung Yu
Copyright-Jahr
2018
Verlag
Springer Singapore
DOI
https://doi.org/10.1007/978-981-10-6487-6_3