DocumentCode
1803195
Title
A new stock price prediction method based on pattern classification
Author
Zhanggui, Zeng ; Hong Yau ; Fu, Alan M N
Author_Institution
Sch. of Electr. & Inf. Eng., Sydney Univ., NSW, Australia
Volume
6
fYear
1999
fDate
36342
Firstpage
3866
Abstract
In this paper, a new method is proposed to predict the trend of a stock price based on pattern analysis. The probabilistic relaxation algorithm is employed to classify the probability vectors of the patterns related to a considered stock price. A series of experiments have been carried out on the real stock price to verify the effectiveness of the proposed method
Keywords
forecasting theory; neural nets; pattern classification; probability; relaxation theory; stock markets; pattern analysis; pattern classification; probabilistic relaxation algorithm; probability vector classification; stock price prediction method; stock price trend; Australia; Investments; Nonlinear filters; Pattern analysis; Pattern classification; Performance analysis; Prediction methods; Probability; Risk analysis; Stochastic systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location
Washington, DC
ISSN
1098-7576
Print_ISBN
0-7803-5529-6
Type
conf
DOI
10.1109/IJCNN.1999.830772
Filename
830772
Link To Document