Forecasting Stocks in the Financial Market by Using GA-SVM Hybrid Algorithm

Subject Areas : Financial Markets and Institutions

Omid Mahdi  Ebadati ¹ (Department of Operation Management and Information Technology, Kharazmi University, Tehran)
Mohammad Ali  Jafari ² (Department of Financial Mathematics, Kharazmi University, Tehran)
Nasim  Davoodifar ³ (Department of Financial Mathematics, Kharazmi University, Tehran, Iran)

Received: 2021-10-14 Accepted : 2022-02-20 Published : 2022-02-20

Keywords: stock price, Forecast, SVM algorithm, GA Algorithm, International Financial Markets,

Abstract :

The purpose of this paper is to predict stock prices using Hybrid GA-SVM Algorithm. Predicting time series such as stock price forecasting is one of the most important issues in financial field. In real life, identifying time series movements in stock price indices is very complex. Therefore, the use of a classical model alone cannot accurately predict stock price indices. Hence, by using combined methods, uncertainty in forecasting can be reduced. In stock price forecasting in financial sector, more than 100 indicators have been created to understand stock market behavior, so, identifying the appropriate indicators is a challenging problem. One of the techniques that has recently been studied for serial forecasting is support regression Vector (SVR) or machine support vector (SVM). This study uses the GA-SVM hybrid algorithm to predict the stock price index. Experimental results show that Hybrid GA-SVM Algorithm provides a more appropriate and promising alternative to stock market forecasting.

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