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SVM-Based Stock Market Price Prediction Methods: An Advanced Review

Vijay Kumar Vishwakarma*, Narayan P. Bhosale**

*-** Department of Computer Science, Indira Gandhi National Tribal University (A Central University), Amarkantak, Madhya Pradesh, India.

Periodicity:September - November'2022
DOI : https://doi.org/10.26634/jcom.10.3.19183

Abstract

This paper offers a concise analysis of the strategies currently in use for stock price prediction by retail investors. The price may increase or decrease according to the quarterly results, financial news flow, technical behavior, or market sentiment resulting from recent developments worldwide. This paper discussed the accuracy of many proposed approaches and methodologies for predicting stock price movement. The Support Vector Machine (SVM) is the foundation of the approaches, with additional parameters and variables.

Keywords

Data Science, Machine Learning, Stock Price Prediction, SVM.

How to Cite this Article?

Vishwakarma, V. K., and Bhosale, N. P. (2022). SVM-Based Stock Market Price Prediction Methods: An Advanced Review. i-manager’s Journal on Computer Science, 10(3), 13-20. https://doi.org/10.26634/jcom.10.3.19183

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