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題名 聯合系統與獨特風險下之信用違約交換評價
Joint pricing of CDS spreads with Idiosyncratic and systematic risks
作者 王聖文
Wang, Sheng-Wen
貢獻者 翁久幸<br>廖四郎
Weng, Ruby Chiu-Hsing<br>Liao, Szu-Lang
王聖文
Wang, Sheng-Wen
關鍵詞 信用違約交換
系統風險
獨特性風險
狀態空間模型
Variance Gamma過程
credit default swaps
systematic risk
idiosyncratic risk
state-space model
Variance Gamma process
日期 2009
上傳時間 9-May-2016 11:42:12 (UTC+8)
摘要 本研究透過聯合系統與獨特風險綜合評估違約的強度，假設市場上經濟變數或資訊影響系統之違約強度，然若直接考慮所有經濟變數到模型中將可能會有共線性或維度過高之疑慮，因此透過狀態空間模型來設定狀態變數以及經濟變數之關係並將萃取三大狀態變數分別用以描述市場實質活動面、通貨膨脹以及信用環境。另外，將透過結構式模型來計算獨特性風險大小，當個別潛在的變數低於一定數值將導致個別的違約事件發生。而因布朗運動可能無法描述或校準市場上違約之鋒態以及偏態，將進一步考慮Variance Gamma過程用以更準確描述真實違約狀況。最後透過結合以上兩個風險綜合評估下，考慮一個聯合違約模型來評價信用違約交換之信用價差。
Systematic and idiosyncratic risks are supposed to jointly trigger the default events. This paper identifies three fundamental risks to capture the systematic movement: real activity, inflation, and credit environment. Since most macroeconomic variables fluctuate together, the state-space model is imposed to extract the three variables from macroeconomic data series. In the idiosyncratic part, the structural model is applied. That is, idiosyncratic default
     is triggered by the crossing of a barrier. For improvement of the underlying lognormal distribution, we assume the process for the potential variable of the firm follows a Variance Gamma process, sufficient dimensions of which can fit the skewed and leptokurtic distributions. Under the specific setting of combinations of the two risks (the so-called joint default model), we price credit default swaps.
參考文獻 Ang, A. and M. Piazzesi. A no-arbitrage vector autoregression of term structure dynamics
     with macroeconomic and latent variables. Journal of Monetary Economics, 50:745–787,
     2003.
     Black, F. and J. Cox. Valuing corporate securities: some effects on bonds indenture provisions.
     Journal of Finance, 31:31–367, 1976.
     Bodie, Z., A. Kane, and A. Marcus. Essentials of Investments. McGraw Hill, 2005.
     Brigo, D. and F. Mercurio. Interest Rate Models - Theory and Practice with Smile, Inflation
     and Credit. Springer, 2006.
     Cariboni, J. and W. Schoutens. Pricing credit default swaps under Lévy models. Journal
     of Computational Finance, 10:1–21, 2007.
     Carlin, B. P., N. G. Polson, and D. S. Stoffer. A Monte Carlo approach to nonnormal
     and nonlinear state-space modeling. Journal of the American Statistical Association, 87:
     493–500, 1992.
     Carter, C. K. and P. Kohn. On Gibbs sampling for state space models. Biometrika, 81:
     541–553, 1994.
     Cont, R. and P. Tankov. Financial Modelling With Jump Processes. Chapman & Hall/CRC,
     2003.
     Das, S., D. Duffie, N. Kapadia, and L. Saita. Common failings: How corporate defaults are
     correlated. The Journal of Finance, 62:93–117, 2007.
     Davis, M. and V. Lo. Infectious defaults. Quantitative Finance, 1:382–387, 2001.
     Duffie, D. and K. J. Singleton. Modeling term structures of defaultable bonds. Review of
     Finance Studies, 12:687–720, 1999.
     Duffie, D., S. Leandro, and K. Wang. Multi-period corporate default prediction with
     stochastic covariates. Working Paper, Stanford University.
     Fu, M. C. Variance-gamma and Monte Carlo. Working Paper.
     Gelman, A., J. B. Carlin, H. S. Stern, D. B. Rubin, and A. Gelman. Bayesian Data Analysis.
     Chapman & Hall/CRC, 2003.
     Geman, S. and D. Geman. Stochastic relaxation, Gibbs distributions and the Bayesian
     restoration of images. IEEE Transactions in Pattern Analysis and Machine Intelligence,
     6:721–741, 1984.
     Hastings, W. Monte Carlo sampling methods using Markov chains and their applications.
     Biometrika, 57:97–109, 1970.
     Jorion, P. Value at Risk. McGraw Hill, 2007.
     Kalman, R. E. A new approach to linear filtering and prediction problems. Transactions of
     the ASME-Journal of Basic Engineering, 82 (Series D):35–45, 1960.
     Kim, C. J. and C. R. Nelson. State-Space Models with Regime Switching: Classical and
     Gibbs-Sampling Approaches with Applications. The MIT Press, 1999.
     Kou, S. G. A jump diffusion model for option pricing. Management Science, 48:
     1086a˛V1101, 2002.
     Lu, B. and L.Wu. Systematic movements in macroeconomic release and the term structure
     of interest rates. Working paper.
     Madan, D. B. andW. Schoutens. Break on through to the single side. In Statistics Technical
     Report, 2007.
     Madan, D. B., P. Carr, and E. C. Chang. The variance gamma process and option pricing.
     European Finance Review, 2:79–105, 1998.
     Merton, R. On the pricing of corporate debt: the risk structure of interest rates. Journal of
     Finance, 29:449–470, 1974.
     Merton, R. C. Option pricing when underlying stock returns are discontinuous. Journal of
     Financial Economics, 3:125–144, 1976.
     Metropolis, N., A. W. Rosenbluth, M. N. Rosenbluth, A. H. Teller, and E. Teller. Equation
     of state calculations by fast computing machines. The Journal of Chemical Physics, 23:
     1083–1953, 1953.
     Ross, S. M. Introduction to Probability Models. Academic Press, 2006.
     Ross, S. A. The arbitrage theory of capital asset pricing. Journal of Economic Theory, 13:
     341–360, 1976.
     Schoutens, W. Lévy Process in Finance: Pricing Financial Derivatives. Wiley, 2003.
     Sharp, W. F. A simplified model for portfolio analysis. Management Science, 9:277–293,
     1963.
     Shreve, S. E. Stochastic Calculus for Finance II: Continuous-Time Models. Springer, 2008.
     Vasicek, O. An equilibrium characterization of the term structure. Journal of Financial
     Economics, 5:177–188, 1977.
     Welch, G. and G. Bishop. An introduction to the Kalman filter. Technical report, TR
     95-041, University of North Carolina at Chapel Hill, 2006.
     Wu, L. and F. X. Zhang. A no-arbitrage analysis of macroeconomic determinants of the
     credit spread term structure. Management Science, 54:1160–1175, 2008.
描述 碩士
國立政治大學
統計學系
95354010
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0953540102
資料類型 thesis
dc.contributor.advisor 翁久幸<br>廖四郎zh_TW
dc.contributor.advisor Weng, Ruby Chiu-Hsing<br>Liao, Szu-Langen_US
dc.contributor.author (Authors) 王聖文zh_TW
dc.contributor.author (Authors) Wang, Sheng-Wenen_US
dc.creator (作者) 王聖文zh_TW
dc.creator (作者) Wang, Sheng-Wenen_US
dc.date (日期) 2009en_US
dc.date.accessioned 9-May-2016 11:42:12 (UTC+8)-
dc.date.available 9-May-2016 11:42:12 (UTC+8)-
dc.date.issued (上傳時間) 9-May-2016 11:42:12 (UTC+8)-
dc.identifier (Other Identifiers) G0953540102en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/94726-
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) 95354010zh_TW
dc.description.abstract (摘要) 本研究透過聯合系統與獨特風險綜合評估違約的強度，假設市場上經濟變數或資訊影響系統之違約強度，然若直接考慮所有經濟變數到模型中將可能會有共線性或維度過高之疑慮，因此透過狀態空間模型來設定狀態變數以及經濟變數之關係並將萃取三大狀態變數分別用以描述市場實質活動面、通貨膨脹以及信用環境。另外，將透過結構式模型來計算獨特性風險大小，當個別潛在的變數低於一定數值將導致個別的違約事件發生。而因布朗運動可能無法描述或校準市場上違約之鋒態以及偏態，將進一步考慮Variance Gamma過程用以更準確描述真實違約狀況。最後透過結合以上兩個風險綜合評估下，考慮一個聯合違約模型來評價信用違約交換之信用價差。zh_TW
dc.description.abstract (摘要) Systematic and idiosyncratic risks are supposed to jointly trigger the default events. This paper identifies three fundamental risks to capture the systematic movement: real activity, inflation, and credit environment. Since most macroeconomic variables fluctuate together, the state-space model is imposed to extract the three variables from macroeconomic data series. In the idiosyncratic part, the structural model is applied. That is, idiosyncratic default
     is triggered by the crossing of a barrier. For improvement of the underlying lognormal distribution, we assume the process for the potential variable of the firm follows a Variance Gamma process, sufficient dimensions of which can fit the skewed and leptokurtic distributions. Under the specific setting of combinations of the two risks (the so-called joint default model), we price credit default swaps.		en_US
dc.description.tableofcontents 謝辭 i
     摘要 ii­
     Abstract iii
     Contents iv
     List of Figures vi
     List of Tables vii
     1 Introduction 1
     2 State-Space Models and the Gibbs Sampler 4
     2.1 State-Space Models and the Kalman Filter . . . . . . . . . . . . . . . . . . 4
     2.2 Parameter estimation and the Gibbs Sampler . . . . . . . . . . . . . . . . . 7
     2.2.1 Generating State Vectors . . . . . . . . . . . . . . . . . . . . . . . 9
     2.2.2 Generating Hyperparameters . . . . . . . . . . . . . . . . . . . . . 10
     2.3 Data Description and Estimation Results . . . . . . . . . . . . . . . . . . . 11
     3 Lévy Process 14
     3.1 Introduction to Lévy Process . . . . . . . . . . . . . . . . . . . . . . . . . 14
     3.2 Variance Gamma Process . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
     3.3 The Monte Carlo Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . 18
     4 Identification of the Systematic and Idiosyncratic Risks 20
     4.1 Identification of the Systematic Risk . . . . . . . . . . . . . . . . . . . . . 20
     4.2 Identification of the Idiosyncratic Risk . . . . . . . . . . . . . . . . . . . . 25
     5 The Joint Default Model 28
     5.1 The Joint Default Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
     5.2 CDS Spreads Pricing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
     6 Conclusion 34
     References 36		zh_TW
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0953540102en_US
dc.subject (關鍵詞) 信用違約交換zh_TW
dc.subject (關鍵詞) 系統風險zh_TW
dc.subject (關鍵詞) 獨特性風險zh_TW
dc.subject (關鍵詞) 狀態空間模型zh_TW
dc.subject (關鍵詞) Variance Gamma過程zh_TW
dc.subject (關鍵詞) credit default swapsen_US
dc.subject (關鍵詞) systematic risken_US
dc.subject (關鍵詞) idiosyncratic risken_US
dc.subject (關鍵詞) state-space modelen_US
dc.subject (關鍵詞) Variance Gamma processen_US
dc.title (題名) 聯合系統與獨特風險下之信用違約交換評價zh_TW
dc.title (題名) Joint pricing of CDS spreads with Idiosyncratic and systematic risksen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) Ang, A. and M. Piazzesi. A no-arbitrage vector autoregression of term structure dynamics
     with macroeconomic and latent variables. Journal of Monetary Economics, 50:745–787,
     2003.
     Black, F. and J. Cox. Valuing corporate securities: some effects on bonds indenture provisions.
     Journal of Finance, 31:31–367, 1976.
     Bodie, Z., A. Kane, and A. Marcus. Essentials of Investments. McGraw Hill, 2005.
     Brigo, D. and F. Mercurio. Interest Rate Models - Theory and Practice with Smile, Inflation
     and Credit. Springer, 2006.
     Cariboni, J. and W. Schoutens. Pricing credit default swaps under Lévy models. Journal
     of Computational Finance, 10:1–21, 2007.
     Carlin, B. P., N. G. Polson, and D. S. Stoffer. A Monte Carlo approach to nonnormal
     and nonlinear state-space modeling. Journal of the American Statistical Association, 87:
     493–500, 1992.
     Carter, C. K. and P. Kohn. On Gibbs sampling for state space models. Biometrika, 81:
     541–553, 1994.
     Cont, R. and P. Tankov. Financial Modelling With Jump Processes. Chapman & Hall/CRC,
     2003.
     Das, S., D. Duffie, N. Kapadia, and L. Saita. Common failings: How corporate defaults are
     correlated. The Journal of Finance, 62:93–117, 2007.
     Davis, M. and V. Lo. Infectious defaults. Quantitative Finance, 1:382–387, 2001.
     Duffie, D. and K. J. Singleton. Modeling term structures of defaultable bonds. Review of
     Finance Studies, 12:687–720, 1999.
     Duffie, D., S. Leandro, and K. Wang. Multi-period corporate default prediction with
     stochastic covariates. Working Paper, Stanford University.
     Fu, M. C. Variance-gamma and Monte Carlo. Working Paper.
     Gelman, A., J. B. Carlin, H. S. Stern, D. B. Rubin, and A. Gelman. Bayesian Data Analysis.
     Chapman & Hall/CRC, 2003.
     Geman, S. and D. Geman. Stochastic relaxation, Gibbs distributions and the Bayesian
     restoration of images. IEEE Transactions in Pattern Analysis and Machine Intelligence,
     6:721–741, 1984.
     Hastings, W. Monte Carlo sampling methods using Markov chains and their applications.
     Biometrika, 57:97–109, 1970.
     Jorion, P. Value at Risk. McGraw Hill, 2007.
     Kalman, R. E. A new approach to linear filtering and prediction problems. Transactions of
     the ASME-Journal of Basic Engineering, 82 (Series D):35–45, 1960.
     Kim, C. J. and C. R. Nelson. State-Space Models with Regime Switching: Classical and
     Gibbs-Sampling Approaches with Applications. The MIT Press, 1999.
     Kou, S. G. A jump diffusion model for option pricing. Management Science, 48:
     1086a˛V1101, 2002.
     Lu, B. and L.Wu. Systematic movements in macroeconomic release and the term structure
     of interest rates. Working paper.
     Madan, D. B. andW. Schoutens. Break on through to the single side. In Statistics Technical
     Report, 2007.
     Madan, D. B., P. Carr, and E. C. Chang. The variance gamma process and option pricing.
     European Finance Review, 2:79–105, 1998.
     Merton, R. On the pricing of corporate debt: the risk structure of interest rates. Journal of
     Finance, 29:449–470, 1974.
     Merton, R. C. Option pricing when underlying stock returns are discontinuous. Journal of
     Financial Economics, 3:125–144, 1976.
     Metropolis, N., A. W. Rosenbluth, M. N. Rosenbluth, A. H. Teller, and E. Teller. Equation
     of state calculations by fast computing machines. The Journal of Chemical Physics, 23:
     1083–1953, 1953.
     Ross, S. M. Introduction to Probability Models. Academic Press, 2006.
     Ross, S. A. The arbitrage theory of capital asset pricing. Journal of Economic Theory, 13:
     341–360, 1976.
     Schoutens, W. Lévy Process in Finance: Pricing Financial Derivatives. Wiley, 2003.
     Sharp, W. F. A simplified model for portfolio analysis. Management Science, 9:277–293,
     1963.
     Shreve, S. E. Stochastic Calculus for Finance II: Continuous-Time Models. Springer, 2008.
     Vasicek, O. An equilibrium characterization of the term structure. Journal of Financial
     Economics, 5:177–188, 1977.
     Welch, G. and G. Bishop. An introduction to the Kalman filter. Technical report, TR
     95-041, University of North Carolina at Chapel Hill, 2006.
     Wu, L. and F. X. Zhang. A no-arbitrage analysis of macroeconomic determinants of the
     credit spread term structure. Management Science, 54:1160–1175, 2008.		zh_TW