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    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/56891

    Title: 基於EEMD與類神經網路建構台指期貨交易策略
    A study of Trading Strategies of TAIEX Futures by using EEMD-based Neural Network Learning Paradigms
    Authors: 陳原孝
    Chen,Yuan Hsiao
    Contributors: 蕭又新
    Chen,Yuan Hsiao
    Keywords: 總體經驗模態
    Ensemble Empirical Mode Decomposition
    Artificial Neural Network
    Trading strategy
    Forecasting model
    Date: 2012
    Issue Date: 2013-02-01 16:55:52 (UTC+8)
    Abstract: 金融市場瞬息萬變,股價漲跌似乎沒有顯著的規則,這意味著股價的行為特徵是不可精確預知和不確定的,為了在市場上增加收益和減少投資風險,研究人員不得不試圖建立一個有效預測金融市場的模型,它可以估算這種不確定性的影響,很可惜的,至今仍然沒有一個模型接近成功的。沒有成功的模型並不代表它是不存在的,相反的,研究人員需要建立更多的預測模型,以提供市場判斷的經驗法則。
    Financial market changes constantly and Stock Price Volatility (SPV) seems to be no significant rules. This means behavioral characteristic of the stock price cannot foresee and uncertain accurately. In order to increase revenue and reduce investment risk in the market, researchers had to try to establish an effective prediction model of financial markets. It can estimate the impact of this uncertainty. It's a great pity that there is not a model that is close successfully yet. That does not represent it does not exist successful model. Instead, researchers need to establish more predictive models to offer the market to judge the rule of thumb.
    The forecasting results of TAIEX Index futures by ARMA Model and two types of EEMD-ANN Models were compared in two kinds of markets – trend and fluctuation. In addition, two trading strategies were tested after the future prices are forecasted. The study attempted to identify a suitable forecasting model.
    Moreover, the factors for price fluctuation of TAIEX were also analyzed in the study. Through EEMD, they could be decomposed to IMFs with various physical meanings and more important IMFs were selected to be analyzed in accordance with the statistic value.
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    Description: 碩士
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0997550051
    Data Type: thesis
    Appears in Collections:[應用物理研究所 ] 學位論文

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