《Evolving And Clustering Fuzzy Decision Tree For Financial Time Series Data Forecasting》.pdf

ARTICLE IN PRESS Expert Systems with Applications xxx (2008) xxx–xxx Contents lists available at ScienceDirect Expert Systems with Applications journal homepag e: /locate/eswa Evolving and clustering fuzzy decision tree for financial time series data forecasting Robert K. Lai a, Chin-Yuan Fan b, Wei-Hsiu Huang b, Pei-Chann Chang c,* a Department of Computer Science and Engineering, Yuan Ze University, Taoyuan 32026, Taiwan, ROC b Department of Industries Management, Yuan Ze University, Taoyuan 32026, Taiwan, ROC c Department of Information Management,Yuan Ze University, Taoyuan 32026, Taiwan, ROC a r t i c l e i n f o a b s t r a c t Article history: Stock price predictions have always been a subject of interest for investors and professional analysts. Available online xxxx Nevertheless, determining the best time to buy or sell a stock remains very difficult because there are many factors that may influence the stock prices. This paper establishes a novel financial time series-fore- Keywords: casting model by evolving and clustering fuzzy decision tree for stocks in Taiwan Stock Exchange Corpo- Fuzzy theory ration (TSEC). This forecasting model integrates a data clustering technique, a fuzzy decision tree (FDT), Decision tree and genetic algorithms (GA) to construct a decision-making system based on historical data and technical Step-wise regression