| 研究生: |
劉銘益 |
|---|---|
| 論文名稱: |
投資組合風險值評估 Evaluation of Value-At-Risk in Investment Portfolio |
| 指導教授: |
廖四郎
江振東 |
| 學位類別: |
碩士
Master |
| 系所名稱: |
商學院 - 統計學系 Department of Statistics |
| 論文出版年: | 2016 |
| 畢業學年度: | 104 |
| 語文別: | 中文 |
| 論文頁數: | 73 |
| 中文關鍵詞: | 風險值 、歷史模擬法 、變異數-共變異數法 、GARCH 、邊際風險值 、成份風險值 |
| 外文關鍵詞: | Value at Risk(VaR), Historical Simulation Approach, Variance-Covariance Approach, GARCH, Marginal VaR, Component VaR |
| 相關次數: | 點閱:41 下載:4 |
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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.
摘要 2
Abstract III
目錄 IV
表目錄 VI
圖目錄 VII
第壹章 緒論 1
第一節 研究動機 1
第二節 研究目的 4
第三節 研究流程與架構 5
第貳章 文獻參考 7
第一節 投資組合的相關文獻 7
第二節 選股指標相關文獻 8
第三節 風險值模型 10
第參章 研究方法 14
第一節 最適資產配置 14
第二節 成長價值雙因子模型 18
第三節 風險值模型 19
第四節 風險值模型驗證 23
第五節 邊際風險值與成份風險值 25
第肆章 實證結果 27
第一節 資料來源與處理 27
第二節 最適資產配置與成長價值雙因子模型之結果 28
第三節 風險值計算 36
第四節 風險值準確性驗證 39
第五節 投資組合風險值結構--邊際風險值與成份風險值 42
第伍章 結論 51
第陸章 建議 53
參考文獻 54
附錄 57
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