Title :
Stock forecasting using Support Vector Machine
Author :
Lai, Lucas K C ; Liu, James N K
Author_Institution :
Dept. of Comput., Hong Kong Polytech. Univ., Hong Kong, China
Abstract :
This paper compares the performance in financial market prediction of a Neural Network approach and an approach using the regression feature of SVM. The historical values used are those of the Hang Sang Index (HSI) from 2002 to 2007 and data for January 2007 and January 2008. SVM performs well in the short term forecast.
Keywords :
neural nets; stock markets; support vector machines; Hang Sang index; SVM; financial market prediction; neural network approach; stock forecasting; support vector machine; Artificial neural networks; Cybernetics; Forecasting; Indexes; Machine learning; Support vector machines; Time series analysis; Classification; Regression and Neural Network; Support Vector Machine;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-6526-2
DOI :
10.1109/ICMLC.2010.5580999
