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題名 投資組合風險值評估
Evaluation of Value-At-Risk in Investment Portfolio作者 劉銘益
Liu, Ming Yi貢獻者 廖四郎<br>江振東
劉銘益
Liu, Ming Yi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
成分風險值
Value at Risk
Historical Simulation Approach
Variance-Covariance Approach
GARCH
Marginal VaR
Component VaR日期 2016 上傳時間 20-Jul-2016 16:52:51 (UTC+8) 摘要 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.參考文獻 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。廖淑惠；2002,“本益比與成長機會策略組合之投資報酬”研究未出版碩士論文,國防大學國防管理學院國防財務資源管理研究所, 台北縣。 劉佩玲；2011,“選股模型在台灣股市的實證”中華大學資訊管理學系碩士班，新竹市。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Alexander, Carol O, & Leigh, Catherlin T. (1997). On the Covariance Matrices Used in Value at Risk Models. The Journal of Derivatives, 4(3), 50-62. Banz, Rolf W. (1981). The Relationship between Return and Market Value of Common Stocks. Journal of financial economics, 9(1), 3-18. Beder, Tanya Styblo. (1995). Var: Seductive but Dangerous. Financial Analysts Journal, 51(5), 12-24. Billio, Monica, & Pelizzon, Loriana. (2000). Value-at-Risk: A Multivariate Switching Regime Approach. Journal of Empirical Finance, 7(5), 531-554. Bollerslev, Tim. (1986). Generalized Autoregressive Conditional Heteroskedasticity.Journal of econometrics, 31(3), 307-327. Bondt, Werner FM, & Thaler, Richard. (1985). Does the Stock Market Overreact? The Journal of finance, 40(3), 793-805. Christie, Andrew A. (1982). The Stochastic Behavior of Common Stock Variances: Value, Leverage and Interest Rate Effects. Journal of financial economics, 10(4), 407-432. Engel, James, Gizycki, Marianne, & Authority, Australian Prudential Regulation.(1999). Value at Risk: On the Stability and Forecasting of the Variance-CovarianceMatrix: Economic Research Department, Reserve Bank of Australia.Engle, Robert F. (1982). Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation. Econometrica: Journal of the Econometric Society, 987-1007. Fama, Eugene F, & French, Kenneth R. (1992). The Cross‐Section of Expected Stock Returns. The Journal of finance, 47(2), 427-465. Fama, Eugene F, & French, Kenneth R. (1993). Common Risk Factors in the Returns on Stocks and Bonds. Journal of financial economics, 33(1), 3-56. Fama, Eugene F, & French, Kenneth R. (1995). Size and Book‐to‐Market Factors in Earnings and Returns. The Journal of finance, 50(1), 131-155. Fama, Eugene F, & French, Kenneth R. (1998). Value Versus Growth: The International Evidence. The Journal of finance, 53(6), 1975-1999. French, Kenneth R, Schwert, G William, & Stambaugh, Robert F. (1987). Expected Stock Returns and Volatility. Journal of financial economics, 19(1), 3-29. Hallerbach, Winfried G, & Spronk, Jaap. (2002). The Relevance of Mcdm for Financial Decisions. Journal of Multi‐Criteria Decision Analysis, 11(4‐5), 187-195. Harris, Richard DF, & Guermat, Cherif. (2000). Robust Conditional Variance Estimation and Value-at-Risk. Available at SSRN 254569. Holthausen, Robert W, & Larcker, David F. (1992). The Prediction of Stock Returns Using Financial Statement Information. Journal of Accounting and Economics, 15(2), 373-411. Hong, Harrison, Lim, Terence, & Stein, Jeremy C. (2000). Bad News Travels Slowly: Size, Analyst Coverage, and the Profitability of Momentum Strategies. The Journal of finance, 55(1), 265-295. Jegadeesh, Narasimhan, & Titman, Sheridan. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of finance, 48(1), 65-91. Jorion, Philippe. (1997). Value at Risk: McGraw-Hill, New York.Jorion, Philippe. (2000). Value-at-Risk: The New Benchmark for Controlling Financial Risk. Chicago: McGraw-Hlill. Jorion, Philippe. (2007). Financial Risk Manager Handbook (Vol. 406): John Wiley & Sons.Kupiec, Paul H. (1995). Techniques for Verifying the Accuracy of Risk Measurement Models. The J. of Derivatives, 3(2). Markowitz, Harry. (1952). Portfolio Selection. The Journal of finance, 7(1), 77-91. Piotroski, Joseph D. (2000). Value Investing: The Use of Historical Financial Statement Information to Separate Winners from Losers. Journal of Accounting Research, 1-41. Rosenberg, Barr, Reid, Kenneth, & Lanstein, Ronald. (1985). Persuasive Evidence of Market Inefficiency. The Journal of Portfolio Management, 11(3), 9-16. van den Goorbergh, Rob WJ, Vlaar, Peter JG, & Bank, Nederlandsche. (1999). Value-at-Risk Analysis of Stock Returns Historical Simulation, Variance Techniques or Tail Index Estimation? (Vol. 40): De Nederlandsche Bank NV.Yeh, I, & Hsu, Tzu-Kuang. (2011). Growth Value Two-Factor Model. Journal of Asset Management, 11(6), 435-451. 描述 碩士
國立政治大學
統計學系
103354029資料來源 http://thesis.lib.nccu.edu.tw/record/#G0103354029 資料類型 thesis dc.contributor.advisor 廖四郎<br>江振東 zh_TW dc.contributor.author (Authors) 劉銘益 zh_TW dc.contributor.author (Authors) Liu, Ming Yi en_US dc.creator (作者) 劉銘益 zh_TW dc.creator (作者) Liu, Ming Yi en_US dc.date (日期) 2016 en_US dc.date.accessioned 20-Jul-2016 16:52:51 (UTC+8) - dc.date.available 20-Jul-2016 16:52:51 (UTC+8) - dc.date.issued (上傳時間) 20-Jul-2016 16:52:51 (UTC+8) - dc.identifier (Other Identifiers) G0103354029 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/99314 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 統計學系 zh_TW dc.description (描述) 103354029 zh_TW dc.description.abstract (摘要) 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。 zh_TW dc.description.abstract (摘要) 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. en_US dc.description.tableofcontents 摘要 2Abstract 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 zh_TW dc.format.extent 1728126 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0103354029 en_US dc.subject (關鍵詞) 風險值 zh_TW dc.subject (關鍵詞) 歷史模擬法 zh_TW dc.subject (關鍵詞) 變異數-共變異數法 zh_TW dc.subject (關鍵詞) GARCH zh_TW dc.subject (關鍵詞) 邊際風險值 zh_TW dc.subject (關鍵詞) 成分風險值 zh_TW dc.subject (關鍵詞) Value at Risk en_US dc.subject (關鍵詞) Historical Simulation Approach en_US dc.subject (關鍵詞) Variance-Covariance Approach en_US dc.subject (關鍵詞) GARCH en_US dc.subject (關鍵詞) Marginal VaR en_US dc.subject (關鍵詞) Component VaR en_US dc.title (題名) 投資組合風險值評估 zh_TW dc.title (題名) Evaluation of Value-At-Risk in Investment Portfolio en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 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。廖淑惠；2002,“本益比與成長機會策略組合之投資報酬”研究未出版碩士論文,國防大學國防管理學院國防財務資源管理研究所, 台北縣。 劉佩玲；2011,“選股模型在台灣股市的實證”中華大學資訊管理學系碩士班，新竹市。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Alexander, Carol O, & Leigh, Catherlin T. (1997). On the Covariance Matrices Used in Value at Risk Models. The Journal of Derivatives, 4(3), 50-62. Banz, Rolf W. (1981). The Relationship between Return and Market Value of Common Stocks. Journal of financial economics, 9(1), 3-18. Beder, Tanya Styblo. (1995). Var: Seductive but Dangerous. Financial Analysts Journal, 51(5), 12-24. Billio, Monica, & Pelizzon, Loriana. (2000). Value-at-Risk: A Multivariate Switching Regime Approach. Journal of Empirical Finance, 7(5), 531-554. Bollerslev, Tim. (1986). Generalized Autoregressive Conditional Heteroskedasticity.Journal of econometrics, 31(3), 307-327. Bondt, Werner FM, & Thaler, Richard. (1985). Does the Stock Market Overreact? The Journal of finance, 40(3), 793-805. Christie, Andrew A. (1982). The Stochastic Behavior of Common Stock Variances: Value, Leverage and Interest Rate Effects. Journal of financial economics, 10(4), 407-432. Engel, James, Gizycki, Marianne, & Authority, Australian Prudential Regulation.(1999). Value at Risk: On the Stability and Forecasting of the Variance-CovarianceMatrix: Economic Research Department, Reserve Bank of Australia.Engle, Robert F. (1982). Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation. Econometrica: Journal of the Econometric Society, 987-1007. Fama, Eugene F, & French, Kenneth R. (1992). The Cross‐Section of Expected Stock Returns. The Journal of finance, 47(2), 427-465. Fama, Eugene F, & French, Kenneth R. (1993). Common Risk Factors in the Returns on Stocks and Bonds. Journal of financial economics, 33(1), 3-56. Fama, Eugene F, & French, Kenneth R. (1995). Size and Book‐to‐Market Factors in Earnings and Returns. The Journal of finance, 50(1), 131-155. Fama, Eugene F, & French, Kenneth R. (1998). Value Versus Growth: The International Evidence. The Journal of finance, 53(6), 1975-1999. French, Kenneth R, Schwert, G William, & Stambaugh, Robert F. (1987). Expected Stock Returns and Volatility. Journal of financial economics, 19(1), 3-29. Hallerbach, Winfried G, & Spronk, Jaap. (2002). The Relevance of Mcdm for Financial Decisions. Journal of Multi‐Criteria Decision Analysis, 11(4‐5), 187-195. Harris, Richard DF, & Guermat, Cherif. (2000). Robust Conditional Variance Estimation and Value-at-Risk. Available at SSRN 254569. Holthausen, Robert W, & Larcker, David F. (1992). The Prediction of Stock Returns Using Financial Statement Information. Journal of Accounting and Economics, 15(2), 373-411. Hong, Harrison, Lim, Terence, & Stein, Jeremy C. (2000). Bad News Travels Slowly: Size, Analyst Coverage, and the Profitability of Momentum Strategies. The Journal of finance, 55(1), 265-295. Jegadeesh, Narasimhan, & Titman, Sheridan. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of finance, 48(1), 65-91. Jorion, Philippe. (1997). Value at Risk: McGraw-Hill, New York.Jorion, Philippe. (2000). Value-at-Risk: The New Benchmark for Controlling Financial Risk. Chicago: McGraw-Hlill. Jorion, Philippe. (2007). Financial Risk Manager Handbook (Vol. 406): John Wiley & Sons.Kupiec, Paul H. (1995). Techniques for Verifying the Accuracy of Risk Measurement Models. The J. of Derivatives, 3(2). Markowitz, Harry. (1952). Portfolio Selection. The Journal of finance, 7(1), 77-91. Piotroski, Joseph D. (2000). Value Investing: The Use of Historical Financial Statement Information to Separate Winners from Losers. Journal of Accounting Research, 1-41. Rosenberg, Barr, Reid, Kenneth, & Lanstein, Ronald. (1985). Persuasive Evidence of Market Inefficiency. The Journal of Portfolio Management, 11(3), 9-16. van den Goorbergh, Rob WJ, Vlaar, Peter JG, & Bank, Nederlandsche. (1999). Value-at-Risk Analysis of Stock Returns Historical Simulation, Variance Techniques or Tail Index Estimation? (Vol. 40): De Nederlandsche Bank NV.Yeh, I, & Hsu, Tzu-Kuang. (2011). Growth Value Two-Factor Model. Journal of Asset Management, 11(6), 435-451. zh_TW
