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
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;
Conference_Titel :
Neural Networks (IJCNN), The 2010 International Joint Conference on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-6916-1
DOI :
10.1109/IJCNN.2010.5596301
