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博碩士論文 etd-0905106-112531 詳細資訊
Title page for etd-0905106-112531
論文名稱
Title
擔保債權憑證之信用價差評價—Copula分析法
The Princing Model of Credit Risk Spread in Collateralized Debt Obligation(CDO)
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
112
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2006-07-07
繳交日期
Date of Submission
2006-09-05
關鍵字
Keywords
分券、信用風險價差、擔保債權憑證
credit risk spread, Tranche, Copula, CDO, Collateralized Debt Obligation
統計
Statistics
本論文已被瀏覽 5731 次,被下載 3171
The thesis/dissertation has been browsed 5731 times, has been downloaded 3171 times.
中文摘要
在多標的資產組合之信用衍生性商品及其信用風險評價模型中,違約相關性是一個重要的聯結因子。本文嘗試運用市場上可輕易取得的無風險債券殖利率與風險債券殖利率間之信用價差,針對資產的信用品質及存續期間,推導出個別資產的違約強度,並運用Copula函數建構資產組合之關聯函數,以分析並推導出資產組合間之違約相關性;透過蒙地卡羅模擬來預估資產組合的違約時間,運用現行擔保債權憑證(CDO)的分券機制,分別求算先償分券、次償分券以及權益分券的預期損失,以及各分券之信用風險價差評價。
本文另外針對違約回復率、折現率及資產組合之相關係數等三個因子作敏感度分析,研究結果發現:對擔保債權憑證的信用風險價差影響最明顯的是違約回復率,其次是資產組合的相關係數,折現率的影響則不明顯。
Abstract
The asset combination of the multi-target credit derivatives and the pricing model of credit risk, the dependence in credit default in credit derivatives is an important connection factor. Copula functions represent a methodology which has recently become the most significant new tool to handle in a flexible way the comovement between markets, risk factors and other relevant variables studied in finance. Besides, Copula functions have been applied to the solution of the need to reach effective diversification has led to new investment products, bound to exploit the credit risk features of the assets. It is particularly for the evaluation of these new products, such as securitized assets (asset-backed securities, such as CDO and the like) and basked credit derivatives (nth to default options) that the need to account for comovement among non-normally distributed variabes has become an unavoidable task.
This article attempts utilizes the credit yield spread between the non-risk bond and the common corporation bond in the market and using Copula functions to make up the relation composition of asset combination. Then, penetrates through the Monte-Carlo Simulation to estimated the default time of asset combination and princing the credit risk spread in the tranche of the Collateralized Debt Obligation (CDO).
Besides, this article aims at the asset default recovery rate, the discount rate and the correlation coefficient of asset combination and so on three factors makes the sensitivity analysis, we find that the most effect of the credit default spread in the Collateralized Debt Obligation is asset default recovery rate, next is the correlation coefficient of asset combination, the influence of discount rate is not obvious.
目次 Table of Contents
目錄 頁次
第一章 序論
第一節 研究背景 1
第二節 研究動機與研究目的 2
第三節 研究架構及研究流程 3
第二章 擔保債權憑證相關介紹與文獻探討
第一節 資產證券化 5
第二節 擔保債權憑證的簡介 12
第三節 CDO目前在國外的發展近況 27
第四節 CDO目前在國內發展近況與相關案例 29
第五節 信用風險評價模型與文獻探討 32
第三章 研究方法
第一節 蒙地卡羅模擬 53
第二節 Copula函數介紹 56
第三節 擔保債權憑證(CDO)的信用風險價差評價模型 65
第四章 實證方法與結果分析
第一節 資料分析 79
第二節 樣本資料特性分析 82
第三節 實證結果分析 83
第四節 敏感度分析 84
第五章 結論與建議
第一節 結論 96
第二節 建議 98
參考文獻
一、中文部份 101
二、英文部份 101
三、網頁部份 103
參考文獻 References
參考文獻
一、中文部份
1.陳松男(民94)。金融工程學。新陸書局。台北市。547-580
2.陳松男(民95)。信用連結商品個案之分析與評價。新陸書局。台北市。17-55.
3.廖四郎、李福慶(民94),擔保債權憑證之評價—Copula分析法。

二、英文部份
1.Alexander J.M., R.Frey, and P. Embrechts, ‘’Quantitative Risk Management’’.n Princeton University Press.(2005).
2.Andersen, L. and J. Sidenius (2004), “Extensions to the Gaussian copula:random recovery and random factor loadings,” working paper, Bank of America, June.
3.Anson M.J.P., F.J. Fabozzi, M.Choudhry and R.R.Chen(2004), Credit derivatives—instruments, applications, and pricing, John Wiley &Sons, Inc.
4.Arvanitis, A., J. Gregory, and J. P. Laurent, ‘’Building Models for Credit Spreads’’. The Journal of Derivatives, Spring 1999, 27-43.
5.Carey M. (1998), “Credit risk in private debt portfolios,” Journal of Finance 53(.4), pages 1363-1387.
6.Cifuentes, A. and G. O’Connor (1996), The binomial expectation method applied to CBO/CLO analysis, Moody’s Special Report, Dec 13th 1996
7.CreditMetricsTM .JP. Morgan, 1997.
8.Davis, M. and V. Lo (2001), “Infectious defaults,” Quantitative Finance 1, pages 382-387.
9.Duffie, D. and K. Singleton (1999), “Modeling term structure of defaultable bonds,” Review of Financial Studies, 12, pages 687-720.
10.Galiani, S.S.(2003), “Copula functions and their application in pricing and risk managing multiname credit derivative product”, working paper,
11.Garcia, J.,T. Dwyspelaere , L. Leonard, T. Alderweireld and T.V. Gestel (2005),”Comparing bet and cash flows CDO’s ”, working paper
12.Gill K.,R. Gambel, R.V. Hrvatin, H. Katz, G. Ong and D. Carroll (2004),”Global rating criteria for collateralized debt obligations”, structured finance, Fitchratings , 13th Sep. 2004
13.Gupton, G.M. (2004),”Portfolio credit risk models”, credit derivatives –the definitive guide edited by Jon Gregory, Risk Books
14.Hull, J., and A. White, ‘’Pricing Interest Rate Derivatives Securities. ‘’Review of Financial Studies, 3(1990), 573-592.
15.Hull, J., and A. White, ‘’Valuing Credit Default Swaps I:No Counterparty Default Risk.’’ Journal of Derivatives, Fall 2000, 8, No.1, 29-40.
16.Hull, J. and A. White (2004), “Valuation of a CDO and an n-th to default CDS without Monte Carlo simulation,”Journal of Derivatives 12(2), pages 8-48.
17.Jarrow, R., D. Lando, and S. Turnbull (1997), “A Markov model for the term structure of credit spread,” Review of Financial Studies 10, pages 481- 523.
18.Jarrow, R. and S. Turnbull (1995), “Pricing derivatives on financial securities subject to credit risk,”Journal of Finance 50 , pages 53- 85.
19.Jarrow, R. and F. Yu (2001), “Counterparty risk and the pricing of defaultable securities,” The Journal of Finance 56, pages 1765- 1799.
20.Kijima, M. Markov Processes for Stochastic Modeling. London: Chapman & Hall, 1997.
21.Kijima, M. ‘’Monotonicities in a Markov Chain Model for Valuing Corporate Bonds Subject to Credit Risk. ‘’Mathematical Finance, 8(1998),229-247.
22.Kijima, M. and K. Komoribayashi, ‘’A Markov Chain Model for Valning Credit Risk Derivatives’’, Fall 1998, 97-108.
23.Lee, C.W., C.K. Kuo and J.L. Urrutia (2004), “A Poisson model with common shocks for CDO valuation,” The Journal of Fixed Income 14(3), pages 72-82.
24.Li, D.X. (2000), “On default correlation: A copula function approach,” The RiskMetrics Group working paper number 99-07
25.Li, D.X. (2002), “Valuing synthetic CDO tranches using copula function approach,”The RiskMetrics Group working paper
26.Lin, S.Y. (2004), “Two essays on credit derivatives: CB asset swap and CDO”, Working Paper
27.Meneguzzo, D. and W. Vecchiato (2004), “Copula Sensitivity in Collateralized Debt Obligations and Basket Default Swaps,” The Journal of Futures Markets, Vol. 24(1), pages 37-70.
28.Merton, R. (1974), “On the pricing of corporate debt: The risk structure of interest rates,”Journal of Finance 29, pages 449-470.
29.Schonbucher J. and D. Schubert (2001), “Copula-dependent default risk in intensity models,”working paper, Department of Statistics, Bonn University.
30.Schorin, C., S.Weinreich, (2001),”Introduction to Collateralized debt obligations’’, Investment in Collateralized debt obligation Edited by Frank.J. Fabozzi, Laurie S.Goodman
31.Sklar, A. (1959), “Fonctions de repartition a n dimensions et leurs marges,” Pub. Inst. Statisr. Univ. Paris, 8, pages 229-231.
32.Umberto C., Elisa L., and W. Vecchiato. ‘’Coupla Methods in Finance.’’ 2004(England) , Jofn Wiley & Sons, Ltd.
三、網頁部份:
1.中央銀行http://www.cbc.gov.tw/。
2.中華民國證券櫃檯買賣中心http://www.otc.org.tw/。
3.中華信用評等公司http://www.taiwanratings.com/tw/。
4.Standard & Poor's. http://www2.standardandpoors.com/。
5.Fitch Inc. http://www.fitchratings.com/。
6.Moodys.com http://www.moodys.com/cust/default.asp。
7.The Bond Market Association http://www.bondmarket.com/。
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