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Proceedings of the 6th International Conference on Financial Innovation and Economic Development (ICFIED 2021)
This paper uses the SVM (support vector machine) method to model the multi-factor stock selection and conducts research in Chinese Stock Market. The CSI 300 Index accounts for about 60% of the market value of Chinese Stock Market, we uses the principal component analysis for dimensionality reduction, reducing the number of original factors to 13, and the cumulative contribution rate reached 78.5372%, which reduced the complexity of SVM classification. In terms of model building, since thedoi:10.2991/aebmr.k.210319.139 fatcat:5f2who43dzdzndvnjvlwsg7vua