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題名 固定比例債務憑證之研究:考量動態價差與信用傳染模型
A study on CPDOs: considering dynamic spread movements and credit contagion
作者 陳哲偉
貢獻者 江彌修
陳哲偉
關鍵詞 信用風險
信用傳染
固定比例債務憑證
信用指數
日期 2011
上傳時間 30-Oct-2012 11:24:16 (UTC+8)
摘要 本研究以 Variance-Gamma 動態信用價差模型與 Giesecke et al. (2011) 之動態違
約傳染模型為基礎, 同時利用 Dorn (2010) 之固定比例債務憑證評價公式, 分析利用不同
時期下 iTraxx Europe 市場報價進行校準下, 固定比例債務憑證評價與風險分析結果有
何變動。
研究結果發現, 在僅考慮價差風險下利用金融風暴前之信用指數市價校準, 此商品所
得評價結果低於原先承諾之票面利息, 但所得風險程度仍高於以往部分文獻與發行商原先
宣稱之低風險。 而在考慮至今包含金融風暴時期之信用指數市價校準下, 則顯露出此商品
不管是評價或風險表現皆迅速變差, 代表以往部分文獻與發行商可能因無法預期信用指數
市場會有大幅度波動下, 而低估了固定比例債務憑證之風險。
同時考慮價差風險與違約風險下, 利用至今包含金融風暴之信用指數市價校準後, 可
得到固定比例債務憑證評價結果遠高於其所承諾之票面利息, 同時此產品違約機率等風險
指標皆顯示相當高之違約與損失可能性, 代表固定比例債務憑證在考慮較為波動之信用市
價校準, 同時考慮較為完整之風險面後, 呈現出相當高之風險程度, 並不如原先發行機構
所承諾之高報酬低風險之產品。
參考文獻 [1] Azizpour, S.,K. Giesecke and G. Schwenkler,2011,Exploring the Sources of
Default Clustering,Working Paper
[2] Brigo, D.,A. Dalessandro,M. Neugebauer and F. Triki,2007, A Stochastic Pro-
cesses Toolkit for Risk Management,Working Paper
[3] Brigo, D.,A. Pallaviciniz and R. Torresetti,2010, Calibration of CDO Tranches
with the Dynamical Generalized-Poisson Loss Model,Risk, 70-75
[4] Cont, R. and P. Tankov,2004,Financial Modelling with Jump Processes,CRC:UK
[5] Cont, R. and P. Tankov,2009, Constant Proportion Portfolio Insurance in the
Presence of Jumps in Asset Prices,Mathematical Finance,Vol. 19, 379-401
[6] Cont, R. and C. Jessen,2012, CPDOs:Modeling and Risk Analysis,Quantitative
Finance, 1-20
[7] Cont, R., editor,2009, Frontiers in quantitative finance : volatility and credit
risk modeling,Wiley:USA
[8] Cousin, A.,D. Dorobantu and D. Rulli" e,2011, An extension of Davis and Lo’s
contagion model,Working Paper
[9] Davis, M. and V. Lo,2000, Infectious defaults,Quantitative Finance,Vol.1,382-
397.
[10] Das, S.,D. Duffie,N. Kapadia and L. Saita,2007, Common Failings: How Cor-
porate Defaults are Correlated, Journal of Finance,Vol.62,93-117
[11] DBRS,2007, CPDOs Laid Bare: Structure, Risk and Rating Sensitivity,Risk
and Rating Sensitivity,1-40
[12] Duffie, D. and N. Garleanu,2001, Risk and Valuation of Collateralized Debt
Obligations,Financial Analysts Journal,Vol.57,41-59
[13] Duffie, D. and K. Singleton,2003, Credit risk : pricing, measurement, and
management,Princeton Press:USA
[14] Duffie, D.,A. Eckner,G. Horel,L. Saita,2009, Frailty Correlated Default, Jour-
nal of Finance,Vol.64,2089-2123
[15] Dorn, J.,2010, Modeling of CPDOs - Identifying optimal and implied lever-
age,Journal of Banking & Finance,Vol.34,1371-1382
[16] Figueroa-Lópezy, J.,S. Lancettey,K. Leez, andY. Mi,2011, Estimation of NIG
and VG models for high frequency financial data,Handbook of Modeling High-
Frequency Data in Finance,Wiley:USA
[17] Lando, D.,2004, Credit risk modeling : theory and applications,Princeton
Press:USA
[18] Linden, A.,M. Neugebauer,S. Bund,2007, First Generation CPDO:Case Study
on Performance and Ratings,Working Paper
[19] Garcia, J.,S. Goossens and W. Schoutens,2007, Lets Jump Together Pricing
of Credit Derivatives: From Index Swaptions to CPPIs,K.U.leuven Section of
Statistics Technical Report,1-14
[20] Glasserman, P.,2003,Monte Carlo methods in financial engineering,Springer:USA
[21] Giesecke, K.,K. Spiliopoulos and R. Sowers,2011, Default Clustering in Large
Portfolios:Typical Events,The Annals of Applied Probability, To Appear
[22] Giesecke,K. ,K. SpiliopouLlos,R. Sowers and J. Sirignano,2012, Large Portfolio
Asymptotic for Loss From Default,Mathematical Finance, To Appear
[23] Gordy, M. and S. Willemann,2010, Constant Proportion Debt Obligations: A
Post-Mortem Analysis of Rating Models,Management Science ,Vol. 58 ,476-
492
[24] Joossens, W. and W. Schoutens,2008, An Overview of Portfolio Insurances:
CPPI and CPDO,JRC Scientific and Technical Reports, 1-34
[25] Jorion, P. and G. Zhang,2007, Good and Bad Credit Contagion: Evidence
from Credit Default,Journal of Financial Economics,Vol. 84,860-883
[26] Jorion, P. and G. Zhang,2009, Credit Contagion from Counterparty Risk,The
Journal of Finance,Vol. 64,2053　2087,
[27] Madan, D., P. Carr and E. Chang,1998, The Variance Gamma Process and
Option Pricing,European Finance Review,Vol.2,79-105
[28] Marjolin, B. and O. Toutain,2007, A description of Moody’s tools for moni-
toring CPDO transactions,Working Paper
[29] Moosbrucker, T.,2006, Pricing CDOs with Correlated Variance Gamma Dis-
tributions,Working Paper
[30] O’Kane, D.,2008, Modelling single-name and multi-name credit derivatives,Wiley:USA
[31] Rösch, D. and B. Winterfeldt,2007, Estimating Credit Contagion in a Standard
Factor Model,Risk,1-19
[32] Schoutens, W.,2003, Levy processes in finance : pricing financial derivatives,Wiley:USA
[33] Schoutens, W. and J. Cariboni,2009, Levy processes in credit risk,Wiley:USA
[34] Torresetti, R. and A, Pallavicini,2009, Stressing Rating Criteria Allowing for
Default Clustering: the CPDO case,Working Paper
[35] UBS,2007, A Primer on Constant Proportion Debt Obligations,Working Paper
[36] Wong, E. and C. Chanlder,2007, Quantitative Modeling Approach To Rating
Index CPDO Structures,Working Paper
描述 碩士
國立政治大學
金融研究所
99352020
100
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0099352020
資料類型 thesis
dc.contributor.advisor 江彌修zh_TW
dc.contributor.author (Authors) 陳哲偉zh_TW
dc.creator (作者) 陳哲偉zh_TW
dc.date (日期) 2011en_US
dc.date.accessioned 30-Oct-2012 11:24:16 (UTC+8)-
dc.date.available 30-Oct-2012 11:24:16 (UTC+8)-
dc.date.issued (上傳時間) 30-Oct-2012 11:24:16 (UTC+8)-
dc.identifier (Other Identifiers) G0099352020en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/54586-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 金融研究所zh_TW
dc.description (描述) 99352020zh_TW
dc.description (描述) 100zh_TW
dc.description.abstract (摘要) 本研究以 Variance-Gamma 動態信用價差模型與 Giesecke et al. (2011) 之動態違
約傳染模型為基礎, 同時利用 Dorn (2010) 之固定比例債務憑證評價公式, 分析利用不同
時期下 iTraxx Europe 市場報價進行校準下, 固定比例債務憑證評價與風險分析結果有
何變動。
研究結果發現, 在僅考慮價差風險下利用金融風暴前之信用指數市價校準, 此商品所
得評價結果低於原先承諾之票面利息, 但所得風險程度仍高於以往部分文獻與發行商原先
宣稱之低風險。 而在考慮至今包含金融風暴時期之信用指數市價校準下, 則顯露出此商品
不管是評價或風險表現皆迅速變差, 代表以往部分文獻與發行商可能因無法預期信用指數
市場會有大幅度波動下, 而低估了固定比例債務憑證之風險。
同時考慮價差風險與違約風險下, 利用至今包含金融風暴之信用指數市價校準後, 可
得到固定比例債務憑證評價結果遠高於其所承諾之票面利息, 同時此產品違約機率等風險
指標皆顯示相當高之違約與損失可能性, 代表固定比例債務憑證在考慮較為波動之信用市
價校準, 同時考慮較為完整之風險面後, 呈現出相當高之風險程度, 並不如原先發行機構
所承諾之高報酬低風險之產品。		zh_TW
dc.description.tableofcontents 1 第一章
前言
1
2 第二章
基本假設與模型設定
7
2.1
固定比例債務憑證基本模型 . . . . . . . . . . . . . . . . . . . . . . . .
7
2.1.1
符號定義 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8
2.1.2
基本模型定義
. . . . . . . . . . . . . . . . . . . . . . . . . . .
9
2.2
信用指數價差風險模型 . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.2.1
符號定義 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.2.2
Lévy過程 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.2.3
Variance-Gamma過程 . . . . . . . . . . . . . . . . . . . . . . . 15
2.3
信用違約風險模型 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.3.1
符號定義 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.3.2
模型設定 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.3.3
模擬方法 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.4
固定比例債務憑證之評價 . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.4.1
分券之期望損失 . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.4.2
溢酬收入端 (Premium Leg) . . . . . . . . . . . . . . . . . . . . 22
2.4.3
違約支出端 (Default Leg) . . . . . . . . . . . . . . . . . . . . . 23
2.4.4
合理信用價差
. . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2.5
校準方法 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.5.1
信用指數價差校準 . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.5.2
信用違約風險模型校準 . . . . . . . . . . . . . . . . . . . . . . . 25
3 第三章
數值結果與分析
27
3.1
信用指數價差模型參數估計 . . . . . . . . . . . . . . . . . . . . . . . . 29
3.2
信用違約損失模型參數校準 . . . . . . . . . . . . . . . . . . . . . . . . 30
3.3
固定比例債務憑證評價與風險分析 . . . . . . . . . . . . . . . . . . . . . 34
3.3.1
考慮價差風險下之評價與風險分析 . . . . . . . . . . . . . . . . . 34
3.3.2
考慮價差風險與違約風險下之評價與風險分析 . . . . . . . . . . . 40
3.4
敏感度分析 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
3.4.1
信用價差模型偏態參數 . . . . . . . . . . . . . . . . . . . . . . . 46
3.4.2
信用價差模型峰態參數 . . . . . . . . . . . . . . . . . . . . . . . 47
3.4.3
信用價差模型波動度參數
. . . . . . . . . . . . . . . . . . . . . 48
3.4.4
個體違約強度均數回歸速度 . . . . . . . . . . . . . . . . . . . . 48
3.4.5
個體長期平均違約強度 . . . . . . . . . . . . . . . . . . . . . . . 49
3.4.6
個體違約強度波動度 . . . . . . . . . . . . . . . . . . . . . . . . 50
3.4.7
系統性風險波動度 . . . . . . . . . . . . . . . . . . . . . . . . . 51
3.4.8
系統性風險長期平均強度
. . . . . . . . . . . . . . . . . . . . . 51
3.4.9
系統性風險均數回歸速度
. . . . . . . . . . . . . . . . . . . . . 52
3.4.10 系統性風險敏感係數 . . . . . . . . . . . . . . . . . . . . . . . . 53
3.4.11 傳染性風險敏感係數 . . . . . . . . . . . . . . . . . . . . . . . . 54
3.4.12 起始信用指數價差 . . . . . . . . . . . . . . . . . . . . . . . . . 54
3.4.13 無風險利率敏感度分析 . . . . . . . . . . . . . . . . . . . . . . . 55
4 第四章
結論與後續研究建議
56
4.1
結論 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
4.2
後續研究建議
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
5 參考文獻
58		zh_TW
dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0099352020en_US
dc.subject (關鍵詞) 信用風險zh_TW
dc.subject (關鍵詞) 信用傳染zh_TW
dc.subject (關鍵詞) 固定比例債務憑證zh_TW
dc.subject (關鍵詞) 信用指數zh_TW
dc.title (題名) 固定比例債務憑證之研究:考量動態價差與信用傳染模型zh_TW
dc.title (題名) A study on CPDOs: considering dynamic spread movements and credit contagionen_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) [1] Azizpour, S.,K. Giesecke and G. Schwenkler,2011,Exploring the Sources of
Default Clustering,Working Paper
[2] Brigo, D.,A. Dalessandro,M. Neugebauer and F. Triki,2007, A Stochastic Pro-
cesses Toolkit for Risk Management,Working Paper
[3] Brigo, D.,A. Pallaviciniz and R. Torresetti,2010, Calibration of CDO Tranches
with the Dynamical Generalized-Poisson Loss Model,Risk, 70-75
[4] Cont, R. and P. Tankov,2004,Financial Modelling with Jump Processes,CRC:UK
[5] Cont, R. and P. Tankov,2009, Constant Proportion Portfolio Insurance in the
Presence of Jumps in Asset Prices,Mathematical Finance,Vol. 19, 379-401
[6] Cont, R. and C. Jessen,2012, CPDOs:Modeling and Risk Analysis,Quantitative
Finance, 1-20
[7] Cont, R., editor,2009, Frontiers in quantitative finance : volatility and credit
risk modeling,Wiley:USA
[8] Cousin, A.,D. Dorobantu and D. Rulli" e,2011, An extension of Davis and Lo’s
contagion model,Working Paper
[9] Davis, M. and V. Lo,2000, Infectious defaults,Quantitative Finance,Vol.1,382-
397.
[10] Das, S.,D. Duffie,N. Kapadia and L. Saita,2007, Common Failings: How Cor-
porate Defaults are Correlated, Journal of Finance,Vol.62,93-117
[11] DBRS,2007, CPDOs Laid Bare: Structure, Risk and Rating Sensitivity,Risk
and Rating Sensitivity,1-40
[12] Duffie, D. and N. Garleanu,2001, Risk and Valuation of Collateralized Debt
Obligations,Financial Analysts Journal,Vol.57,41-59
[13] Duffie, D. and K. Singleton,2003, Credit risk : pricing, measurement, and
management,Princeton Press:USA
[14] Duffie, D.,A. Eckner,G. Horel,L. Saita,2009, Frailty Correlated Default, Jour-
nal of Finance,Vol.64,2089-2123
[15] Dorn, J.,2010, Modeling of CPDOs - Identifying optimal and implied lever-
age,Journal of Banking & Finance,Vol.34,1371-1382
[16] Figueroa-Lópezy, J.,S. Lancettey,K. Leez, andY. Mi,2011, Estimation of NIG
and VG models for high frequency financial data,Handbook of Modeling High-
Frequency Data in Finance,Wiley:USA
[17] Lando, D.,2004, Credit risk modeling : theory and applications,Princeton
Press:USA
[18] Linden, A.,M. Neugebauer,S. Bund,2007, First Generation CPDO:Case Study
on Performance and Ratings,Working Paper
[19] Garcia, J.,S. Goossens and W. Schoutens,2007, Lets Jump Together Pricing
of Credit Derivatives: From Index Swaptions to CPPIs,K.U.leuven Section of
Statistics Technical Report,1-14
[20] Glasserman, P.,2003,Monte Carlo methods in financial engineering,Springer:USA
[21] Giesecke, K.,K. Spiliopoulos and R. Sowers,2011, Default Clustering in Large
Portfolios:Typical Events,The Annals of Applied Probability, To Appear
[22] Giesecke,K. ,K. SpiliopouLlos,R. Sowers and J. Sirignano,2012, Large Portfolio
Asymptotic for Loss From Default,Mathematical Finance, To Appear
[23] Gordy, M. and S. Willemann,2010, Constant Proportion Debt Obligations: A
Post-Mortem Analysis of Rating Models,Management Science ,Vol. 58 ,476-
492
[24] Joossens, W. and W. Schoutens,2008, An Overview of Portfolio Insurances:
CPPI and CPDO,JRC Scientific and Technical Reports, 1-34
[25] Jorion, P. and G. Zhang,2007, Good and Bad Credit Contagion: Evidence
from Credit Default,Journal of Financial Economics,Vol. 84,860-883
[26] Jorion, P. and G. Zhang,2009, Credit Contagion from Counterparty Risk,The
Journal of Finance,Vol. 64,2053　2087,
[27] Madan, D., P. Carr and E. Chang,1998, The Variance Gamma Process and
Option Pricing,European Finance Review,Vol.2,79-105
[28] Marjolin, B. and O. Toutain,2007, A description of Moody’s tools for moni-
toring CPDO transactions,Working Paper
[29] Moosbrucker, T.,2006, Pricing CDOs with Correlated Variance Gamma Dis-
tributions,Working Paper
[30] O’Kane, D.,2008, Modelling single-name and multi-name credit derivatives,Wiley:USA
[31] Rösch, D. and B. Winterfeldt,2007, Estimating Credit Contagion in a Standard
Factor Model,Risk,1-19
[32] Schoutens, W.,2003, Levy processes in finance : pricing financial derivatives,Wiley:USA
[33] Schoutens, W. and J. Cariboni,2009, Levy processes in credit risk,Wiley:USA
[34] Torresetti, R. and A, Pallavicini,2009, Stressing Rating Criteria Allowing for
Default Clustering: the CPDO case,Working Paper
[35] UBS,2007, A Primer on Constant Proportion Debt Obligations,Working Paper
[36] Wong, E. and C. Chanlder,2007, Quantitative Modeling Approach To Rating
Index CPDO Structures,Working Paper		zh_TW