The following information was submitted:
Transactions: INTERNATIONAL JOURNAL of EDUCATION AND INFORMATION TECHNOLOGIES
Transactions ID Number: 19-335
Full Name: Ching Long Su
Position: Associate Professor
Age: ON
Sex: Male
Address: 396 Chang Jung Rd., Sec. 1, Kway Jen, Tainan 71101, Taiwan, R.O.C.
Country: TAIWAN
Tel: 2785-123 ext. 6057
Tel prefix: 886-6
Fax:
E-mail address: clsu@mail.cjcu.edu.tw
Other E-mails:
Title of the Paper: A Self-Organized Neuro-Fuzzy System for Stock Market Dynamics Modeling and Forecasting
Authors as they appear in the Paper: Ching Long Su, Chuen Jyh Chen, Shih Ming Yang
Email addresses of all the authors: clsu@mail.cjcu.edu.tw,cjchen@mail.au.edu.tw,smyang@mail.ncku.edu.tw
Number of paper pages: 13
Abstract: A self-organized, five-layer neuro-fuzzy model is developed to model the dynamics of stock market by using technical indicators. The model effectiveness in prediction and forecasting is validated by a set of data containing four indicators: the stochastic oscillator (%K and %D), volume adjusted moving average (VAMA) and ease of movement (EMV) from TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index). A modified moving average method is proposed to predict the input set for the neuro-fuzzy model in forecasting stock price. Simulation results show that the model is effective in prediction and accurate in forecasting. The input error from the prediction of the modified moving average method is attenuated significantly by the neuro-fuzzy model to yield better forecasting results.
Keywords: Neuro-fuzzy system, Sugeno fuzzy system, Forecasting, VAMA, EMV
EXTENSION of the file: .doc
Special (Invited) Session: A Self-Organized Neuro-Fuzzy System for Stock Market Dynamics Modeling and Forecasting
Organizer of the Session: 646-783
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