International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences
E-ISSN: 2349-7300

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Online Scholarly International Journal Since 2013

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Learning of SVM Centered Indian Stock Market Forecast Procedures

Authors: Nitin Rameshrao Talhar, Awesha Tomar, Tapasya Ghorpade, Namrata Sakore, Mayuri Zile

DOI: 10.17605/OSF.IO/YCZNEShort DOI: ggnbs3

Country: India View / Download Full Text PDF File


Abstract: Investing money has never been a risk-free process. Many models have been designed for the prediction of stock market returns. In this survey paper, we present an analysis of the various works done in the field of support vector machines for the prediction of stock market returns. Accuracies of various methods are analyzed and the best performing model
is chosen. We then present our proposed model, explain its methodologies and scope. The various variables, dataset and their impact on the accuracy of the prediction are explained
for each model. Thus helping investors to select their preferred model for prediction.

Keywords: Stock Market, Support Vector Machines


Paper Id: 483

Published On: 2019-03-31

Published In: Volume 7, Issue 2, March-April 2019

Cite This: Learning of SVM Centered Indian Stock Market Forecast Procedures - Nitin Rameshrao Talhar, Awesha Tomar, Tapasya Ghorpade, Namrata Sakore, Mayuri Zile - IJIRMPS Volume 7, Issue 2, March-April 2019. DOI 10.17605/OSF.IO/YCZNE

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