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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/73929

    Title: The application of adaptive neuro-fuzzy inference system(anfis) for dynamic trading decision support system : evidence from taiex stock index futures
    Other Titles: 適應性類神經模糊推論系統在動態交易決策的應用 : 臺灣股票指數期貨的實證研究
    Authors: 何東翰;Ho, Tung-Han
    Contributors: 淡江大學財務金融學系碩士班
    李沃牆;Li, Wo-Chiang
    Keywords: 類神經網路;適應性模糊推論系統(ANFIS);基因演算法;Adaptive Neuro-Fuzzy Inference System(ANFIS);Neural Networks;Genetic Algorithms
    Date: 2011
    Issue Date: 2011-12-28 17:33:39 (UTC+8)
    Abstract: 股票市場的預測非常重要,因為成功的預測能帶來相當大的獲利。然而,能夠成功的預測是非常複雜而且困難的。
    Stock market prediction is important because successful prediction of stock prices may promise attractive benefits. Yet, these tasks are highly complicated and very difficult.
    This thesis extends the Adaptive Neuro-Fuzzy Inference System (ANFIS), to create a trading decision support system that is capable of using fuzzy reasoning combined with the pattern recognition capability of neural networks to be used in forecasting and trading the futures of Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX).
    This study, as a result, proposes an approach of artificial intelligence by integrating fuzzy theory with neural networks to achieve the optimization of trading rules. The result indicates that integrating fuzzy theory with neural networks has produced a trading decision support system which overcomes the physical limitations of human experts and traders in taking decisions of trading and improve the investment performance. The experimental results indicate that ANFIS can be a useful tool for economists and practitioners dealing with the forecasting of the stock index future price and increase the returns of a trader''s portfolio.
    Appears in Collections:[Graduate Institute & Department of Banking and Finance] Thesis

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