Title :
Financial Time Series Data Forecasting by Wavelet and TSK Fuzzy Rule Based System
Author :
Chang, Pei-Chann ; Fan, Chin-Yuan ; Chen, Shih-Hsin
Author_Institution :
Yuan Ze Univ., Taoyuan
Abstract :
In this study, a novel approach by integrating the wavelet and Takagi-Sugeno-Kang (TSK) fuzzy rule based systems (FRBS) for financial time series data prediction is developed. The wavelet method is applied to eliminate the noises caused by random fluctuations. The data output from the wavelet is then input to the TSK fuzzy rule system for prediction of the future value of a time series data. Through the intensive experimental tests, the model has successfully forecasted the price variation for stocks with accuracy close to 97.6% in TSE index.
Keywords :
financial data processing; fuzzy set theory; time series; wavelet transforms; Takagi-Sugeno-Kang fuzzy rule based systems; financial time series data forecasting; random fluctuations; wavelet method; Artificial intelligence; Artificial neural networks; Economic forecasting; Fluctuations; Fuzzy systems; Intelligent systems; Knowledge based systems; Neural networks; Stock markets; Testing;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2874-8
DOI :
10.1109/FSKD.2007.290
