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    政大機構典藏 > 商學院 > 統計學系 > 學位論文 >  Item 140.119/30938
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/30938


    Title: 匯率雙出局保本型票券與以簡約模型估計違約相關係數之實證分析
    Authors: 簡鈴衿
    CHIEN, LING-JIN
    Contributors: 陳松男
    蔡紋琦

    簡鈴衿
    CHIEN, LING-JIN
    Keywords: 雙重界限選擇權
    蒙地卡羅模擬法
    Cholesky分解法
    簡約模型
    違約相關係數
    Double Barrier Options
    Monte Carlo Simulation
    Cholesky Decomposition
    Reduced-Form Model
    Default Correlation
    Date: 2005
    Issue Date: 2009-09-14
    Abstract: 本論文一共分為兩大主題,分別為匯率連結商品之評價與分析,及違約事件相關係數之估計。在結構型金融商品於市場上熱賣之後,金融業者紛紛投入財務工程領域,競相推出類似的產品。然而,自1971年世界各國開始實行浮動匯率制度之後,匯率風險較以往提高不少,因此各種不同設計的外匯衍生性商品開始不斷地問世。有鑑於此,本文希望藉由分析市場上的匯率商品:「新加坡華僑銀行一年期匯率連結結構型存款」,讓發行商和投資人了解結構型商品設計的要點與風險所在。在此商品中,本文利用多變數蒙地卡羅模擬法求出商品的近似價格,除了看發行商是否有利可尋之外,也提供發行商可行之避險策略。同時,本文也透過商品條款分析與情境分析,讓投資人了解其獲利所在與將面臨的風險。<br>由於近年來信用事件層出不窮,顯示出信用風險控管的重要性,信用衍生性商品也因而開始蓬勃發展。目前信用衍生性商品以信用違約交換為最大宗,擔保債權憑證(Collateralized Debt Obligations, CDO)為其次。由於一籃子信用衍生性商品和擔保債權憑證涉及多檔標的資產,在評價時,公司之間的違約相關係數是個重要因子,因此本文在另一個主題上,透過Robert Jarrow與Donald van Deventer(2005)提出的違約相關係數之估計方法,以簡約模型估計違約相關係數,利用台灣公司資料做實證分析,期許對連結多項標的資產之信用衍生性商品之評價有所幫助。
    Reference: 中文部份
    1. 江宏真,「組合式外幣定期存款之個案分析」,國立中央大學財務金融學系碩士論文,民國93年7月
    2. 江姿瑩,「結構型金融商品之個案分析-一籃子信用連結債券與雪球式利率連結債券」,國立政治大學金融學系碩士論文,民國94年6月
    3. 林妙宜,「公司信用風險之衡量」,國立政治大學金融學系碩士論文,民國91年7月
    4. 林公韻,「信用違約機率之預測-Robust Logistic Regression」,國立政治大學金融學系碩士論文,民國94年6月
    5. 吳振雄,「信用衍生性金融商品訂價與產品介紹」,淡江大學財務金融學系碩士論文,民國92年6月
    6. 施宜君,「信用風險之評價與應用」,國立政治大學金融學系碩士論文,民國90年6月
    7. 許家瑜,「考慮信用風險下金融商品之評價分析」,國立政治大學金融學系碩士論文,民國92年7月
    8. 陳松男,「金融工程學」,民國91年
    9. 陳松男,「結構型金融商品之設計及創新」,民國93年
    10. 陳松男,「結構型金融商品之設計及創新(二)」,民國94年
    11. 廖四郎、李福慶,「擔保債權憑證之評價-Copula分析法」,民國94年,台灣金融財務季刊,第六輯,第二期
    12. 謝曉薇,「利率浮動與路徑相依型信用連結債券之評價與分析」,國立政治大學金融學系碩士論文,民國94年7月
    英文部份
    1. A. Arvanitis, J. Gregory, and J.-P. Laurent (1999), “Building Models for Credit Spreads”, Journal of Derivatives, Spring 1999, 27-43.
    2. Allison, P. (1982), “Discrete-Time Methods for the Analysis of Event Histories”, Sociological Methodology 1, 61-99.
    3. Black, F. and J. Cox (May 1976), “Valuing Corporate Securities: Some Effects of Bond Indenture Provisions”, Journal of Finance, Vol. XXXI, No. 2, pp. 351-367.
    4. Bluhm C, L Overbeck and C Wanger (2003), “An Introduction to Credit Risk Modeling”, Chapman & Hall/ CRC.
    5. Bremaud, P. (1981), “Point Processes and Queues: Martingale Dynamics”, New York: Springer.
    6. Brown, C. (1975), “On the use of indicator variables for studying the time-dependence of parameters in a response-time model”, Biometrics 31, 863-872.
    7. Cox, D. (1970), “The Analysis of Binary Data”, Methuen.
    8. Duffie, D and Singleton, KJ (1999), “Modeling Term Structures of Defaultable Bonds”, Review of Financial Studies, Vol. 12, Issue 4, pp. 687-720.
    9. Geman and Yor (1996), “Pricing and Hedging Double-Barrier Options: A Probabilistic Approach ”, Mathematical Finance, 365-378.
    10. Geske, R. (1977), “The Valuation of Corporate Liabilities as Compound Options”, Journal of Financial and Quantitative Analysis 12, 541-552.
    11. Jarrow R and D van Deventer (January 2005), “Estimating Default Correlations Using a Reduced-Form Model”, Risk Publications.
    12. Jarrow R and P Protter (2004), “Structural Versus Reduced Form Models: A New Information Based Perspective”, Journal of Investment Management, Vol. 2, No. 2, 1-10.
    13. Jarrow R and S Chava (2002), “Bankruptcy Prediction with Industry Effects”, Forthcoming in Review of Finance.
    14. Jarrow, R., D. Lando, and S. Turnbull (1997), “A Markov Model for the Term Structure of Credit Risk Spreads”, The Review of Financial Studies, Vol. 10, No. 2, pp. 481-523.
    15. Jarrow, R., and S. Turnbull (1995), “Pricing Derivatives on Financial Securities Subject to Credit Risk”, The Journal of Finance, Vol. 50, No. 1, pp. 53-85.
    16. Jarrow, R. and F. Yu (2001), “Counterparty Risk and the Pricing of Defaultable Securities”, The Journal of Finance 56, pages 1765- 1799
    17. Justin London. (2005), “Modeling Derivatives in C++”, John Wiley & Sons, Inc.
    18. Kiefer N (1988), “Economic Duration Data and Hazard Functions”, Journal of Economic Literature, Vol. XXVI, 646-679.
    19. Kijima, Masaaki and Katsuya Komoribayashi (Fall 1998), “A Markov Chain Model for Valuing Credit Risk Derivatives”, Journal of Derivatives, Vol. 6, Kyoto University, pp. 97-108.
    20. Lando D (1998), “On Cox Processes and Credit Risky Securities”, Review of Derivatives Research 2, 99-120.
    21. Longstaff, FA and ES Schwartz (1995), “A Simple Approach to Valuing Risky and Floating Rate Debt”, Journal of Finance, 50, 789-819.
    22. Zhou, C., (1997),“A Jump-Diffusion Approach to Modeling Credit Risk and Valuing Defaultable Securities”, Finance and Economics Discussion Series 1997-15 /Board of Governors of the Federal Reserve System (U.S.).
    23. Zhou, C. (2001),“The Term Structure of Credit Spreads with Jump Risk”, Journal of Banking and Finance, 25, 2015-40.
    Description: 碩士
    國立政治大學
    統計研究所
    92354004
    94
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0923540041
    Data Type: thesis
    Appears in Collections:[統計學系] 學位論文

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