An SVM-based approach for stock market trend prediction

Yuling Lin, Haixiang Guo, Jinglu Hu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

44 Citations (Scopus)

Abstract

In this paper, an SVM-based approach is proposed for stock market trend prediction. The proposed approach consists of two parts: feature selection and prediction model. 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.

Original languageEnglish
Title of host publication2013 International Joint Conference on Neural Networks, IJCNN 2013
DOIs
Publication statusPublished - 2013 Dec 1
Event2013 International Joint Conference on Neural Networks, IJCNN 2013 - Dallas, TX, United States
Duration: 2013 Aug 42013 Aug 9

Publication series

NameProceedings of the International Joint Conference on Neural Networks

Conference

Conference2013 International Joint Conference on Neural Networks, IJCNN 2013
CountryUnited States
CityDallas, TX
Period13/8/413/8/9

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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  • Cite this

    Lin, Y., Guo, H., & Hu, J. (2013). An SVM-based approach for stock market trend prediction. In 2013 International Joint Conference on Neural Networks, IJCNN 2013 [6706743] (Proceedings of the International Joint Conference on Neural Networks). https://doi.org/10.1109/IJCNN.2013.6706743