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Performance Forecasting of National Stock Exchange of India Using Symbolic Versus Numerical Methodology

  • Sachin KamleyEmail author
  • Shailesh Jaloree
  • Ramjeevan Singh Thakur
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 34)

Abstract

Though stock market holds instability in nature and due to instability, its knowledge representation and forecast procedure is exceptionally complicated. For the previous couple of decades, various tools and techniques are developed to forecast symbolic and numerical stock prices. However, these tools and techniques have been totally failed to make inferences from stock market knowledge base. During this direction, backward reasoning and back-propagation methods are adopted for symbolic and numerical forecasting, respectively. This study mainly highlights the performance comparison of both the approaches. The common LISP 3.0 and MATLAB R2011a tool are used to make inferences from stock market knowledge base. Finally, experimental results had shown that back-propagation method performs significantly well as compared to backward reasoning method.

Keywords

Stock market Artificial intelligence Backward reasoning Back-propagation Common LISP 3.0 MATLABR2011a 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Sachin Kamley
    • 1
    Email author
  • Shailesh Jaloree
    • 2
  • Ramjeevan Singh Thakur
    • 3
  1. 1.S.A.T.IVidishaIndia
  2. 2.Department of Appl. Math’s and C.ScS.A.T.IVidishaIndia
  3. 3.Department of Computer ApplicationsMaulana Azad National Institute of TechnologyBhopalIndia

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