DocumentCode
2486572
Title
Intelligent trading using support vector regression and multilayer perceptrons optimized with genetic algorithms
Author
Zhu, Ming ; Wang, Lipo
Author_Institution
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore
fYear
2010
fDate
18-23 July 2010
Firstpage
1
Lastpage
5
Abstract
This paper proposes an intelligent trading system using support vector regression optimized by genetic algorithms (SVR-GA) and multilayer perceptron optimized with GA (MLP-GA). Experimental results show that both approaches outperform conventional trading systems without prediction and a recent fuzzy trading system in terms of final equity and maximum drawdown for Hong Kong Hang Seng stock index.
Keywords
fuzzy systems; multilayer perceptrons; regression analysis; stock markets; support vector machines; Hong Kong Hang Seng stock index; final equity; fuzzy trading system; genetic algorithms; intelligent trading system; maximum drawdown; multilayer perceptrons; support vector regression; Artificial neural networks; Gallium; Indexes; Mathematical model; Predictive models; Support vector machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks (IJCNN), The 2010 International Joint Conference on
Conference_Location
Barcelona
ISSN
1098-7576
Print_ISBN
978-1-4244-6916-1
Type
conf
DOI
10.1109/IJCNN.2010.5596301
Filename
5596301
Link To Document