DocumentCode :
2127453
Title :
The Forecasts Performance of Gray Theory, BP Network, SVM for Stock Index
Author :
Niu, Fengqin ; Nie, Shuangshuang ; Wang, Weihong
Author_Institution :
Sch. of Manage., Donghua Univ., Shanghai
fYear :
2008
fDate :
21-22 Dec. 2008
Firstpage :
708
Lastpage :
712
Abstract :
In order to evaluate the performance of several forecasts, the paper firstly uses three forecasting methods, namely grey model (GM (1,1)), BP neural networks and support vector machines (SVM), to forecast the Shanghai Industrial Index, the Shanghai Commercial Index, the Shanghai Real Estate Index, the Shanghai Public Utilities Index. Through evaluating the results of these forecasting methods, it is argued that, for forecasting concussing stock market, the forecast effects of BP network method is obviously better than the forecast effects of GM (1, 1) method and SVM method; GM (1, 1) method and SVM method are more suitable for forecasting stable stock market.
Keywords :
backpropagation; economic forecasting; economic indicators; grey systems; neural nets; stock markets; support vector machines; BP neural network; Shanghai Commercial Index; Shanghai Industrial Index; Shanghai Public Utilities Index; Shanghai Real Estate Index; forecast performance; gray theory; grey model; stock index; stock market; support vector machine; Artificial intelligence; Artificial neural networks; Economic forecasting; Knowledge acquisition; Knowledge management; Mathematical model; Neural networks; Predictive models; Stock markets; Support vector machines; BP neural networks; Performance Evaluation; Stock Index; grey model; support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Knowledge Acquisition and Modeling, 2008. KAM '08. International Symposium on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3488-6
Type :
conf
DOI :
10.1109/KAM.2008.161
Filename :
4732920
Link To Document :
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