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    政大典藏 > College of Commerce > Department of MIS > Theses >  Item 140.119/87346


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    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:[Department of MIS] Theses

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