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    政大機構典藏 > 商學院 > 統計學系 > 學位論文 >  Item 140.119/99314
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/99314


    Title: 投資組合風險值評估
    Evaluation of Value-At-Risk in Investment Portfolio
    Authors: 劉銘益
    Liu, Ming Yi
    Contributors: 廖四郎
    江振東

    劉銘益
    Liu, Ming Yi
    Keywords: 風險值
    歷史模擬法
    變異數-共變異數法
    GARCH
    邊際風險值
    成分風險值
    Value at Risk
    Historical Simulation Approach
    Variance-Covariance Approach
    GARCH
    Marginal VaR
    Component VaR
    Date: 2016
    Issue Date: 2016-07-20 16:52:51 (UTC+8)
    Abstract: 近年來隨著金融自由化與國際化的發展,各國投資者面對更大的投資機會。然而在享有更多投資機會的同時,卻也使投資者面對更高之風險,進而促使投資者必須針對該風險值加以評估,並採行相關的規避措施。如何利用投資組合的觀念,以規避投資風險且獲得特定的報酬,成為當前投資人最重要的課題。有鑑於此,本研究將風險值的概念與投資組合理論予以合併。

    本文以Markowitz 的平均數-變異數模型(M-V模型)及成長價值指標(Growth Value Index ,GVI) 對在臺灣證券交易所上市之金融類股股票、傳產類股股票、電子類股股票及上市公司,分別進行篩選,以選出最適完整性投資組合,並進一步針對該最適投資組合運用歷史模擬法(Historical Simulation Approach)、變異數-共變異數法(Variance-Covariance Approach)及GARCH模型進行風險值分析,並透過Kupiec (1995) 之非條件與條件涵蓋比率檢定,評估各種風險值模型預測能力之績效。

    實證結果顯示,各種風險值模型的樣本外預測結果顯示,以GARCH模型估計之風險值預測效果為最佳,並將投資組合的風險值細分為邊際風險值(marginal VaR)和成份風險值(component VaR),藉由這項分析,可以提供管理者在作風險管理時更明確的決策方向。
    Recently, with the development of liberalization and globalization in financial markets, investor is faced with more investment opportunity and investment risk simultaneously, and this makes investor evaluate VaR. Therefore, it becomes the most significant topic for investor to utilize the concept of investment portfolio to select and adopt suitable risk measure method to evaluate risk and further control risk. Based on this reason, this study combines the concept of VaR with the theory of portfolio.

    This thesis utilize Markowitz’s Mean-Variance approach and Growth Value Index(GVI) to select each optimal stock portfolio from Taiwan’s Financial Stock、Taiwan’s traditional Stock、Taiwan’s Electronic Stock and publicly traded company in Taiwan Stock Exchange. Furthermore, employing Historical Simulation Approach、Variance-Covariance Approach and GARCH to evaluate the VaR of that optimal portfolio. Finally, through Kupiec test (1995) to evaluate each model’s forecasting performance.

    Empirical study shows that from the results of the out-of-sample forecasting, we can find that GARCH is the best one to forecast the VaR, and decompose the portfolio VaR with marginal VaR and component VaR .This kind of analysis can provide managers with more accurate decision in making risk management.
    Reference: 中文部分
    李麗華;2000,“風險值應用於資產分配之研究--以股票市場為例”國立東華大學企業管理學系,花蓮縣。

    柏婉貞, 黃柏農;2007,“台股指數期貨與現貨市場日內報酬波動與交易量非線性行為之研究“

    楊宗庭;2001,“共同基金風險值的評估與應用”國立臺灣大學財務金融學研
    究所,台北市

    廖偉真, 雷立芬;2010,“不同樣本頻率之股市波動性估計 ─GARCH、TGARCH 與 EGARCH 之比較”臺灣銀行季刊, 第六十一卷第四期。

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    賴瀅纕;2005,“Fama-French 三因子模型於台灣股市之實證研究“長庚大學。
    英文部分
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    Description: 碩士
    國立政治大學
    統計學系
    103354029
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0103354029
    Data Type: thesis
    Appears in Collections:[統計學系] 學位論文

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