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A Hybrid PSO-Fuzzy Based Algorithm for Clustering Indian Stock Market Data

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Computational Intelligence, Communications, and Business Analytics (CICBA 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 776))

Abstract

Partitioning data points into several homogeneous sets is known as clustering. This paper proposes a hybrid clustering algorithm based on Different Length Particle Swarm Optimization (DPSO) algorithm and is applied to a study of Indian stock market volatility. The heterogeneous data items of stock market are fuzzified to homogeneous data items for efficient clustering. Each data item has 7 attributes. Three evaluation criteria are used for computing the fitness of particles of the clustering algorithm. Different length particles are encoded in the PSO to minimize the user interaction with the program hence also the running time. The single point crossover operator of Genetic Algorithm is used here for differencing between two particles. The performance of the proposed algorithm is demonstrated by clustering stock market data of size 2014 \(\times \) 7. The results are compared with some well known existing algorithms.

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Authors and Affiliations

  1. Department of Information Technology, Calcutta Business School, Kolkata, 743503, India

    Somnath Mukhopadhyay

  2. Department of Finance, Calcutta Business School, Kolkata, 743503, India

    Tamal Datta Chaudhuri

  3. Department of Computer Science and Engineering, University of Kalyani, Kalyani, 713248, India

    J. K. Mandal

Authors
  1. Somnath Mukhopadhyay
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  2. Tamal Datta Chaudhuri
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  3. J. K. Mandal
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Corresponding author

Correspondence to Somnath Mukhopadhyay .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Kalyani, Kalyani, West Bengal, India

    J. K. Mandal

  2. Department of Computer and System Sciences, Visva Bharati University, Bolpur Santiniketan, West Bengal, India

    Paramartha Dutta

  3. Department of Information Technology, Calcutta Business School, Kolkata, India

    Somnath Mukhopadhyay

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Mukhopadhyay, S., Chaudhuri, T.D., Mandal, J.K. (2017). A Hybrid PSO-Fuzzy Based Algorithm for Clustering Indian Stock Market Data. In: Mandal, J., Dutta, P., Mukhopadhyay, S. (eds) Computational Intelligence, Communications, and Business Analytics. CICBA 2017. Communications in Computer and Information Science, vol 776. Springer, Singapore. https://doi.org/10.1007/978-981-10-6430-2_37

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  • DOI: https://doi.org/10.1007/978-981-10-6430-2_37

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6429-6

  • Online ISBN: 978-981-10-6430-2

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