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Clustering Stock Exchange data by Using Evolutionary Algorithms for Portfolio Management

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  • Malek Khojasteh Nejad

Abstract

In present paper, imperialist competitive algorithm and ant colony algorithm and particle swarm optimization algorithm have been used to cluster stocks of Tehran stock exchange. Also results of the three algorithms have been compared with three famous clustering models so called k-means, Fcm and Som. After clustering, a portfolio has been made by choosing some stocks from each cluster and using NSGA-II algorithm. Results show superiority of ant colony algorithms and particle swarm optimization algorithm and imperialist competitive to other three methods for clustering stocks. Due to diversification of the portfolio, portfolio risk will be reduced while using data chosen from the clusters. The more efficient the clustering, the lower the risk is. Also, using clustering for portfolio management reduces time of portfolio selection.

Suggested Citation

  • Malek Khojasteh Nejad, 2014. "Clustering Stock Exchange data by Using Evolutionary Algorithms for Portfolio Management," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 55-66.
    • Handle: RePEc:ers:journl:v:xvii:y:2014:i:4:p:55-66
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    References listed on IDEAS

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    1. Eleftherios J. Thalassinos & Evagelos D. Politis, 2011. "International Stock Markets: A Co-integration Analysis," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 113-130.
    2. Eleftherios Thalassinos & Diana-Mihaela Pociovalisteanu, 2007. "A Time Series Model for the Romanian Stock Market," European Research Studies Journal, European Research Studies Journal, vol. 0(3-4), pages 57-72.
    3. Socha, Krzysztof & Dorigo, Marco, 2008. "Ant colony optimization for continuous domains," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1155-1173, March.
    4. Ji, Junzhong & Song, Xiangjing & Liu, Chunnian & Zhang, Xiuzhen, 2013. "Ant colony clustering with fitness perception and pheromone diffusion for community detection in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(15), pages 3260-3272.
    5. Eleftherios I. Thalassinos & Bozhana Venediktova & Daniela Staneva-Petkova & Vicky Zampeta, 2013. "Way of Banking Development Abroad: Branches or Subsidiaries," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(3), pages 69-78.
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    Cited by:

    1. Tatyana A. Skvortsova & Yuriy A. Kolesnikov & Tatyana A. Mosienko & Nikolay G. Romanenko, 2017. "The Formation of Authorized Capital in Economic Organizations," European Research Studies Journal, European Research Studies Journal, vol. 0(3B), pages 369-378.

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    More about this item

    Keywords

    Portfolio Management; Data mining; Imperialist Competitive Algorithm; Ant Colony Algorithm; Particle Swarm Optimization Algorithm;
    All these keywords.

    JEL classification:

    • F21 - International Economics - - International Factor Movements and International Business - - - International Investment; Long-Term Capital Movements
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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