An svm-based approach for stock market trend prediction

In this paper, an SVM-based approach is proposed for stock market trend prediction. The proposed approach consists of two parts: In the feature selection part, a correlation-based SVM filter is applied to rank and select a good subset of financial indexes. And the stock indicators are evaluated based on the ranking. In the prediction model part, a so called quasi-linear SVM is applied to predict stock market movement direction in term of historical data series by using the selected subset of financial indexes as the weighted inputs.

The quasi-linear SVM is an SVM with a composite quasi-linear kernel function, which approximates a nonlinear separating boundary by multi-local linear classifiers with interpolation.

Experimental results on Taiwan stock market datasets demonstrate that the proposed SVM-based stock market trend prediction method produces better generalization performance over the conventional methods in terms of the hit ratio. Moreover, the experimental results also show that the proposed SVM-based stock market trend prediction system can find out a good subset and evaluate stock indicators which provide useful information for investors.

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An SVM-based approach for stock market trend prediction. N2 - In this paper, an SVM-based approach is proposed for stock market trend prediction.

AB - In this paper, an SVM-based approach is proposed for stock market trend prediction. Cookies are used by this site. To decline or learn more, visit our Cookies page. Home Profiles Research Units Research Output. An SVM-based approach for stock market trend prediction Yuling Lin, Haixiang Guo, Jinglu Hu.

Abstract In this paper, an SVM-based approach is proposed for stock market trend prediction. Original language English Title of host publication Proceedings of the International Joint Conference on Neural Networks DOIs http: ASJC Scopus subject areas Software Artificial Intelligence.

An SVM-based approach for stock market trend prediction — Waseda University

Cite this Apa Standard Harvard Vancouver Author BIBTEX RIS Lin, Y. In Proceedings of the International Joint Conference on Neural Networks [] DOI: Proceedings of the International Joint Conference on Neural Networks. Lin Y, Guo H, Hu J.

In Proceedings of the International Joint Conference on Neural Networks. TY - CHAP T1 - An SVM-based approach for stock market trend prediction AU - Lin,Yuling AU - Guo,Haixiang AU - Hu,Jinglu PY - Y1 - N2 - In this paper, an SVM-based approach is proposed for stock market trend prediction.

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