Cart (Loading....) | Create Account
Close category search window

Pattern Recognition Based on Support Vector Machine: Computerizing Expertise for Predicting the Trend of Stock Market

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Yang, Yiwen ; Manage. Sch., Northwestern Polytech. Univ., Xi''an, China

This paper presents a method for forecasting the moving direction of Shanghai Stock Composite Index (CCI) through constructing the feature pattern vectors containing the characters of the market structure according to the profitunity approach and adopting SVM to perform pattern recognition. First, the market trend forecasting is considered as a pattern recognition problem. Second, the pattern vectors are formed with the help of the investing expertise, the profitunity approach which devises a set of rules of predicting market moving trend by observing some variables (designed from the market data) and their combinations. Then, the support vector machine is employed to perform the pattern recognition, mapping the pattern vectors into class space of trend moving up and down. Finally, a group of simulations are given, and the results show the good performance that the correct rate of forecasting reached about 70%.

Published in:

Computer Science and Information Engineering, 2009 WRI World Congress on  (Volume:6 )

Date of Conference:

March 31 2009-April 2 2009

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.