Decision making based on grey model and support vector machine

Abstract

In order to improve the effectiveness of market preference early warning analysis algorithm, a new method based on gray kernel AR- SVM model is proposed. Firstly, we used support vector machine (SVM) algorithm to construct the financial market risk warning analysis model, which includes no extreme risk and extreme risk in two cases, and used SVM algorithm to find the optimal classification process based on the training set; Secondly, the SVM model is prone to extreme risk warning “failure” in the market preference prediction problem in the market preference data records are processed by the improved gray model, and the mixed kernel function was used to improve the SVM algorithm, which realized the sample data to improve the prediction performance of autoregressive model. Finally, the SVM algorithm is used to improve the accuracy of the market model. The experimental results show that the proposed method is effective in the analysis of market preference data.