Fund trend prediction based on least squares support vector regression

Yilan Bao

doi:10.1117/12.920286

13 January 2012 Fund trend prediction based on least squares support vector regression

Yilan Bao

Proceedings Volume 8350, Fourth International Conference on Machine Vision (ICMV 2011): Computer Vision and Image Analysis; Pattern Recognition and Basic Technologies; 83502S (2012) https://doi.org/10.1117/12.920286
Event: Fourth International Conference on Machine Vision (ICMV 11), 2011, Singapore, Singapore

Abstract

It is well-known that accurate prediction of fund trend is very important to get high profits from fund market. In the paper, least squares support vector regression (LSSVR) is adopted to predict fund trend. LSSVR higher the non-linear prediction ability than other prediction methods .The trading price of fund "kexun" from 2007-3-1 to 2007-3-30 is used as our experimental data, and the trading price from 2007-3-26 to 2007-3-30 is used as the testing data. The forecasting results of BP neural network and least squares support vector regression are given. The experimental results show that the forecasting values of LSSVR are nearer to actual values that those of BP neural network.

Citation Download Citation

Yilan Bao "Fund trend prediction based on least squares support vector regression", Proc. SPIE 8350, Fourth International Conference on Machine Vision (ICMV 2011): Computer Vision and Image Analysis; Pattern Recognition and Basic Technologies, 83502S (13 January 2012); https://doi.org/10.1117/12.920286

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