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In order to improve the prediction accuracy, applies the Support Vector Machine (SVM) theory to the prediction of the Nonlinear Series. Based on the analysis of the basic theory for the prediction, adopts the Cross Validation method to choose the best parameters and then establishes the prediction model. For the stock index of Shanghai Stock Exchange, carries out the prediction to verify the effect of the model. Proved by the research, the method based on the Support Vector Machine theory is able to reflect the changing tendencies, and has the better prediction accuracy, at the same time the feasibility is verified by the method. KeywordsNonlinear time series; Support Vector Machine; best parameters; prediction model

Modeling for Nonlinear Series Prediction based on the Support Vector Machine Theory