2010•Applied Mechanics and MaterialsRequires access

Stock Price Combination Forecast Model Based on Regression Analysis and SVM

Feng Yuan Kong, Guo Ping Song

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Abstract

According to the features of stock price change, a new forecast model, based on the regression analysis and SVM, is proposed to solve the problem of the stock price prediction. First, the regression analysis model is used to forecast stock prices, and then SVM was established to forecast and correct the error. The combined predictive values are obviously better than single method. Empirical analysis shows that the stock price based model based the regression analysis and SVM model significantly improved the forecast accuracy, it shows that the method in this paper is worth to be extended and applied.

About this research paper

What this paper is about

According to the features of stock price change, a new forecast model, based on the regression analysis and SVM, is proposed to solve the problem of the stock price prediction. First, the regression analysis model is used to forecast stock prices, and then SVM was established to forecast and correct the error. The combined predictive values are obviously better than single method. Empirical analysis shows that the stock price based model based the regression analysis and SVM model significantly improved the forecast accuracy, it shows that the method in this paper is worth to be extended and applied.

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Available abstract

According to the features of stock price change, a new forecast model, based on the regression analysis and SVM, is proposed to solve the problem of the stock price prediction. First, the regression analysis model is used to forecast stock prices, and then SVM was established to forecast and correct the error. The combined predictive values are obviously better than single method. Empirical analysis shows that the stock price based model based the regression analysis and SVM model significantly improved the forecast accuracy, it shows that the method in this paper is worth to be extended and applied.

Key concepts: Support vector machine, Econometrics, Stock price, Stock (firearms), Regression analysis, Regression, Computer science, Time series

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