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    政大機構典藏 > 商學院 > 金融學系 > 學位論文 >  Item 140.119/124740
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/124740


    Title: 深度投資組合:以臺灣50爲例
    Deep Portfolio: the Evidence in Taiwan 50
    Authors: 張玄
    Zhang, Xuan
    Contributors: 廖四郎
    張玄
    Zhang, Xuan
    Keywords: 神經網路
    長短期記憶體
    自編碼器
    深度投資組合
    Neural networks
    LSTM
    Autoencoder
    Deep portfolio
    ETF
    Date: 2019
    Issue Date: 2019-08-07 16:12:55 (UTC+8)
    Abstract: 神經網路因其强大的對特徵提取能力,近年來廣泛的應用在金融領域,如資產定價、風險管理、投資組合構建。與傳統的投資組合理論相比,神經網路可以對數據閒複雜的非綫性特徵更爲敏感;此外,更容易通對樣本外驗證防止模型過擬合。在本研究中,通過神經網路對臺灣50指數與其成分股完成選股和構造投資組合追蹤臺灣50指數,實現用較少的股票數量達到采用完全複製發的元大0050ETF追蹤誤差。
    Neural networks have been applied to financial applications more recently, such as asset pricing, risk management and constructing portfolios. Compared with standard financial methods only capture the linearity of data, the neural networks can take more non-linearity into account. Another advantage of neural network is that it is easier to reduce over-fitting and improve the performance on the validation set. In this study we use dense and LSTM neural networks to select stocks from stock universe and construct a portfolio to track Taiwan 50 Index. The result shows that deep portfolio with less stocks can have less tracking error than a fully replicated ETF (Yuanta 0050).
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    Description: 碩士
    國立政治大學
    金融學系
    106352041
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0106352041
    Data Type: thesis
    DOI: 10.6814/NCCU201900192
    Appears in Collections:[金融學系] 學位論文

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