Stock Price Combination Forecast Model Based on Regression Analysis and SVM
Feng Yuan Kong, Guo Ping Song
Abstract
Feng Yuan Kong, Guo Ping Song
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.
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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