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Stock Market Prediction Techniques: A Review Paper

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Second International Conference on Sustainable Technologies for Computational Intelligence

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1235))

Abstract

Due to the non-linear and highly volatile nature of the Stock market, it has become a very challenging task for researchers to make accurate predictions. Improving the efficiency of predictions has become the main goal of many researchers. From the traditional approach of working with historical dossiers to using the latest machine learning and deep learning techniques, researchers are busy finding out the best possible ways of accurate predictions. Many new models are suggested that can make good estimations of stock prices. Investors are interested in knowing both the immediate next-day prices and as well as future share prices in the long run. This paper inspects the algorithms and techniques that are useful for making accurate predictions.

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Author information

Authors and Affiliations

  1. School of Computer Application, Lovely Professional University, Jalandhar, India

    Kirti Sharma & Rajni Bhalla

Authors
  1. Kirti Sharma
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  2. Rajni Bhalla
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Editor information

Editors and Affiliations

  1. The PNG University of Technology, Lae, Papua New Guinea

    Ashish Kumar Luhach

  2. CHRIST (Deemed to be University), Bangalore, India

    Ramesh Chandra Poonia

  3. University of Eastern Finland, Kuopio, Finland

    Xiao-Zhi Gao

  4. Namibia University of Science and Technology, Windhoek, Namibia

    Dharm Singh Jat

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Sharma, K., Bhalla, R. (2022). Stock Market Prediction Techniques: A Review Paper. In: Luhach, A.K., Poonia, R.C., Gao, XZ., Singh Jat, D. (eds) Second International Conference on Sustainable Technologies for Computational Intelligence. Advances in Intelligent Systems and Computing, vol 1235. Springer, Singapore. https://doi.org/10.1007/978-981-16-4641-6_15

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