2692-2967ISSN (Online)
2770-0216ISSN (Print)
Volume 7 , Issue 2 , PP: 32-40, 2022 | Cite this article as | XML | Html | PDF | Full Length Article
Denis A. Pustokhin 1 * , Irina V. Pustokhina 2
Doi: https://doi.org/10.54216/AJBOR.070203
A country's economy and social structure are greatly influenced by the stock market. It is extremely difficult for investors, expert analysts, and scholars in the financial industry to forecast the stock market accurately because of the pretty unstable, parametric, non-linear dynamical, and unstable character of stock price time series. In the financial sector, stock market forecasting is a critical activity and a prominent study subject because stock market investments carry greater risk. It's conceivable, however, to reduce most of the risk through the development of computationally intelligent approaches. This paper introduces the support vector machine regression to make a model forecasting the stock market financial.
SVM , Machine Learning , Forecasting , Regression
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