期刊
EXPERT SYSTEMS WITH APPLICATIONS
卷 34, 期 2, 页码 1126-1132出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2006.12.021
关键词
fuzzy time-series model; adaptive expectation model; TAIEX forecasting; fuzzy linguistic variable
Time-series models have been used to make predictions in the areas of stock price forecasting, academic enrollment and weather, etc. However, in stock markets, reasonable investors will modify their forecasts based on recent forecasting errors. Therefore, we propose a new fuzzy time-series model which incorporates the adaptive expectation model into forecasting processes to modify forecasting errors. Using actual trading data from Taiwan Stock Index (TAIEX) and, we evaluate the accuracy of the proposed model by comparing our forecasts with those derived from Chen's [Chen, S. M. (1996). Forecasting enrollments based on fuzzy time-series, Fuzzy Sets and Systems, 81, 311-319] and Yu's [Yu, Hui-Kuang. (2004). Weighted fuzzy time-series models for TAIEX forecasting. Physica A, 349, 609-624] models. The comparison results indicate that our model surpasses in accuracy those suggested by Chen and Yu. (C) 2007 Published by Elsevier Ltd.
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