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Predict Stock Market Behavior: Role of Machine Learning Algorithms

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 673)


The prediction of a dynamic, volatile, and unpredictable stock market has been a challenging issue for the researchers over the past few years. This paper discusses stock market-related technical indicators, mathematical models, most preferred algorithms used in data science industries, analysis of various types of machine learning algorithms, and an overall summary of solutions. This paper is an attempt to perform the analysis of various issues pertaining to dynamic stock market prediction, based on the fact that minimization of stock market investment risk is strongly correlated to minimization of forecasting errors.


  • Machine learning algorithms
  • Stock market prediction
  • Efficient market hypothesis
  • Ensemble machine learning

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  • DOI: 10.1007/978-981-10-7245-1_38
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Correspondence to Uma Gurav .

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Gurav, U., Sidnal, N. (2018). Predict Stock Market Behavior: Role of Machine Learning Algorithms. In: Bhalla, S., Bhateja, V., Chandavale, A., Hiwale, A., Satapathy, S. (eds) Intelligent Computing and Information and Communication. Advances in Intelligent Systems and Computing, vol 673. Springer, Singapore.

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