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Stock market prediction and Portfolio selection models: a survey

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Abstract

Stock data is known to be chaotic in nature and it is a challenging task to predict the non-linear patterns of such data. Forming an optimal portfolio of stocks is yet another challenging task and limitations do exist in every portfolio model in some form or the other. In order to resolve such problems, many artificial intelligence models have appeared in literature which are also known as intelligent models. Prediction of stocks as well as investing in appropriate stocks has remained in focus among investors, industrialists as well as among academicians. This paper surveys important published articles in the related area available in literature. This survey highlights traditional mathematical models available in articles which have appeared decades back till artificial intelligence based models available in recent articles.

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Acknowledgements

Research support from School of Computer and Information Sciences, University of Hyderabad is highly acknowledged. The authors would like to thank Institute for Development and Research in Banking Technology, for its constant support and cooperation.

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  1. School of Computer and Information Sciences, University of Hyderabad, Hyderabad, 500046, India

    Akhter Mohiuddin Rather & Arun Agarwal

  2. Institute for Development and Research in Banking Technology, Castle Hills, Masab Tank, Hyderabad, 500057, India

    V. N. Sastry

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  1. Akhter Mohiuddin Rather
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  2. V. N. Sastry
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  3. Arun Agarwal
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Correspondence to Akhter Mohiuddin Rather.

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Rather, A.M., Sastry, V.N. & Agarwal, A. Stock market prediction and Portfolio selection models: a survey. OPSEARCH 54, 558–579 (2017). https://doi.org/10.1007/s12597-016-0289-y

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