Portfolio selection using hybrid algorithm of data envelopment analysis based on Kohonen neural network and Cuckoo algorithm

In stock markets, one of the main issues in which investors are involved is how to select stocks. If the investors select stocks rationally, he can achieve efficiencies greater than the market average. It is of great importance to find techniques that help investors in selecting stocks in particular...

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Published inJournal of information & optimization sciences Vol. 37; no. 4; pp. 549 - 567
Main Authors Faezy Razi, Farshad, Shadloo, Naeimeh
Format Journal Article
LanguageEnglish
Published Taylor & Francis 03.07.2016
Subjects
Cuckoo algorithm
Data envelopment analysis (DEA)
Kohonen neural network
Multiple-criteria decision-making
Portfolio optimization
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ISSN0252-2667
2169-0103
DOI10.1080/02522667.2015.1103483

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Abstract In stock markets, one of the main issues in which investors are involved is how to select stocks. If the investors select stocks rationally, he can achieve efficiencies greater than the market average. It is of great importance to find techniques that help investors in selecting stocks in particular at stock exchange. Investors are always looking for a set of stocks in the financial markets which is more profitable and less risky. The objective of this study is to presents a new model for portfolio selection. For portfolio selection, this model uses a hybrid algorithm of Data Envelopment Analysis (DEA) based Kohonen neural network and cuckoo search algorithm. The data are clustered using Kohonen neural network and then the efficiency is calculated separately for each cluster using DEA model based on the nature of the output. Pareto-optimal combination of risk and efficiency is analyzed via cuckoo algorithm.
AbstractList In stock markets, one of the main issues in which investors are involved is how to select stocks. If the investors select stocks rationally, he can achieve efficiencies greater than the market average. It is of great importance to find techniques that help investors in selecting stocks in particular at stock exchange. Investors are always looking for a set of stocks in the financial markets which is more profitable and less risky. The objective of this study is to presents a new model for portfolio selection. For portfolio selection, this model uses a hybrid algorithm of Data Envelopment Analysis (DEA) based Kohonen neural network and cuckoo search algorithm. The data are clustered using Kohonen neural network and then the efficiency is calculated separately for each cluster using DEA model based on the nature of the output. Pareto-optimal combination of risk and efficiency is analyzed via cuckoo algorithm.
Author Faezy Razi, Farshad
Shadloo, Naeimeh
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SubjectTerms Cuckoo algorithm
Data envelopment analysis (DEA)
Kohonen neural network
Multiple-criteria decision-making
Portfolio optimization
Title Portfolio selection using hybrid algorithm of data envelopment analysis based on Kohonen neural network and Cuckoo algorithm
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