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    政大機構典藏 > 商學院 > 資訊管理學系 > 學位論文 >  Item 140.119/87346
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/87346


    Title: 應用類神經網路於預測國外股價指數期約
    Forecasting Foreign Stock Index Futures: An Application of Neural Networks
    Authors: 賴俊霖
    Lai, Charles C.
    Contributors: 蔡瑞煌
    徐燕山

    Ray, Tsaih
    Hsu, Yenshan

    賴俊霖
    Lai, Charles C.
    Keywords: 理解神經網路
    S&P 500 指數期貨
    類神經網路
    股價指數期貨
    Reasoning neural networks
    S&P 500 index futures
    Artificial neural networks
    Stock index futures
    Date: 1996
    Issue Date: 2016-04-28 11:55:06 (UTC+8)
    Abstract: 本研究嘗試整合類神經網路與法則基礎(rule-based)系統技術,以建立S&P 500指數期貨的交易策略。本研究不同於先前研究之處有下列二方面:一、本研究採用法則基礎系統的方式提供神經網路的訓練範例;二、本研究以理解神經網路(Reasoning Neural Networks)取代後向傳導網路(Back propagation networks)以解決局部最小值與隱藏結點數未知的困境,而實證結果也顯示理解神經網路之表現優於後向傳導網路。首先,由期貨的日價格資料計算出十種技術分析指標值,用這些指標值來表示期貨市場內的各種可能狀況(case)。接著,我們提出FFM(Futures Forecast Model)與EFFM(Extended Futures Forecast Model)來處理市場的各種狀況,預測出隔日的期貨價格改變方向。以法則基礎方法所建立的FFM是用來處理明顯的狀況(obvious cases),並且提供類神經網路好的訓練範例。而EFFM包括四個理解神經網路系統與一個決策機置(voting mechanism),它被用來處理那些不明顯的狀況(non-obvious
    This research adopts a hybrid approach to implementing the
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    Description: 碩士
    國立政治大學
    資訊管理學系
    83356022
    Source URI: http://thesis.lib.nccu.edu.tw/record/#B2002002862
    Data Type: thesis
    Appears in Collections:[資訊管理學系] 學位論文

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