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Forecasting the Stock Market with Linguistic Rules Generated from the Minimize Entropy Principle and the Cumulative Probability Distribution Approaches

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Department of Information Management, National Yunlin University of Science and Technology,123, section 3, University Road, Touliu, Yunlin 640, Taiwan
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Department of Digital Technology and Game Design, Shu-Te University, 59 Hun Shan Rd., Yen Chau, Kaohsiung County 82445, Taiwan
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Department of Information Management and Communication, Wenzao Ursuline College of Languages, 900, Mintsu 1st Road, Kaohsiung 807, Taiwan
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Author to whom correspondence should be addressed.
Entropy 2010, 12(12), 2397-2417; https://doi.org/10.3390/e12122397
Received: 28 October 2010 / Revised: 18 November 2010 / Accepted: 22 November 2010 / Published: 3 December 2010
To forecast a complex and non-linear system, such as a stock market, advanced artificial intelligence algorithms, like neural networks (NNs) and genetic algorithms (GAs) have been proposed as new approaches. However, for the average stock investor, two major disadvantages are argued against these advanced algorithms: (1) the rules generated by NNs and GAs are difficult to apply in investment decisions; and (2) the time complexity of the algorithms to produce forecasting outcomes is very high. Therefore, to provide understandable rules for investors and to reduce the time complexity of forecasting algorithms, this paper proposes a novel model for the forecasting process, which combines two granulating methods (the minimize entropy principle approach and the cumulative probability distribution approach) and a rough set algorithm. The model verification demonstrates that the proposed model surpasses the three listed conventional fuzzy time-series models and a multiple regression model (MLR) in forecast accuracy. View Full-Text
Keywords: minimize entropy principle approach; cumulative probability distribution approach; rough set theory; stock market forecasting minimize entropy principle approach; cumulative probability distribution approach; rough set theory; stock market forecasting
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Su, C.-H.; Chen, T.-L.; Cheng, C.-H.; Chen, Y.-C. Forecasting the Stock Market with Linguistic Rules Generated from the Minimize Entropy Principle and the Cumulative Probability Distribution Approaches. Entropy 2010, 12, 2397-2417.

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