臺灣博碩士論文加值系統

本文以Cousin, Dorobantu and Rullière (2010)的模型為基礎，將由總體因素造成的直接違約相關性和傳染現象同時納入資產違約相關性的來源，進而求算債權群組損失分配和債權群組各期預期損失，並用於評價擔保債權信用憑證和分析其風險特徵。
本文並對合成型的擔保信用憑證作評價以及敏感度分析，發現當單一資產直接違約機率的期望值增加時，會使得各分劵的信用價差上升。當傳染機率 上升時，也會使各分券的信用價差上升。但當直接違約機率的變異數 增加時，對各分券的影響則不一致，因為 上升代表直接違約相關性 上升，故使債權群組損失分配產生厚尾性，資產共同存活和共同違約的機率增加。因為權益分券原先即預期遭受不小的損失，分券價差主要受資產同時存活機率的影響，故 上升時，同時存活機率的上升使權益分券信用價差下降，而先償分券原先預期幾乎不會遭受損失，分券價差主要受資產同時違約機率的影響，故 上升時，同時違約機率的上升使先償分券信用價差下降。故我們可看出直接違約相關性 和傳染發生機率對於各分券信用價差的影響並不相同，故金融海嘯時期市場標準模型-高斯因子結構模型的失效可能原因之一為沒有考慮傳染效應。
本文最後以模型的參數對市場報價做校準，可發現信用危機後，模型的校準效果較好，故此違約傳染模型可用來描述信用危機後的信用風險市場。也發現信用危機後，資產直接違約的機率的期望值及變異數皆上升，故此違約傳染模型的參數能捕捉到此現象。

第一章 導論 1
第二章　文獻回顧 3
第一節 信用風險模型與違約傳染模型 3
第二節 DAVIS AND LO的傳染模型 8
第三章　模型設定 11
第一節 模型基本設定 13
第二節 單期模型 14
第三節 跨期模型 17
第四節 模型結合BETA分配 19
第五節 模型演算法 21
第六節 合成型擔保債權憑證評價方法 23
第七節 合成型擔保債權憑證風險特徵 26
第四章 數值分析 27
第一節 違約狀態及傳染型式對違約次數的影響 27
第二節 模型參數對違約次數的影響 31
第三節　 模型評價合成型擔保擔保債權憑證 38
第四節　 在傳染模型下合成型擔保債權憑證的風險特徵 49
第五節　 校準 54
第五章　結論 57
附錄 59
參考文獻 63

1. Andersen, L., J. Sidenius, and S., Basu, 2003, “All Your Hedges in One Basket,” Risk, 16, 67-72
2. Areski, C. , D. Rullière, and D., Dorobantu, 2010, “An Extension of Davis and Lo’s Contagion Model,” (working paper, University of Leon).
3. Azizpour, S., Giesecke, K., 2008, “Self-exciting corporate defaults: contagion vs. frailty,” (working paper, Stanford University).
4. Black, F. and J. C. Cox, 1976, “Valuing corporate securities：effects of bond indenture provisions,” Journal of Finance 31, 351-367.
5. Das, S.R., Duffie, D., Kapadia, N., Saita, L., 2007, “Common failings: how corporate defaults are correlated,” Journal of Finance 62(1), 93-117
6. Duffie, D. and K. Singleton, 1999, “Modeling term structures of defaultable bonds,” Review of Financial Studies 12, 687-720
7. Barro, D. and A. Basso, 2010, “Credit contagion in a network of firms with spatial interaction,” European Journal of Operation Research, 205, 459-468
8. Egloff, D., Leippold, M. and Vanini, P., 2007 ,”A simple model of credit contagion,” Journal of Banking & Finance, Elsevier, vol. 31(8), 2475-2492
9. Graziano, G. and Rogers, C., 2006, “Pricing k-th to default swaps under default contagion, the matrix-analytic approach,” Journal of Computational Finance ,12(1), 49-78.
10. Hull, J. and A. White, 2004, “Valuation of a CDO and nth to Default CDS without Monte Carlo Simulation,” Journal of Derivatives, 12 8-23
11. Hull, J. and A. White, 2008, “Dynamic Models of Portfolio Credit Risk: a Simplified Approach,” Journal of Derivatives, 15,9-28
12. Laurent, J.P. and J. Gregory, 2003, “Basket default swaps, CDO’s and factor copulas,” ( working paper, ISFA Actuarial School, University of Lyon)
13. Li, D.X., 2000, “On Default Correlation: A Copula Approach,” Journal of Fixed Income, 9 43-54
14. Serafin, M.J., O.P. Perez, F.A. Embriz and F. Dey, 2010, “Systemic Risk, Financial Contagion and Financial Fragility,” Journal of Economic Dynamics & Control, 34, 2358-2374
15. Merton, R., 1974, “On the Pricing of Corporate Debt：The Risk Structure of Interest Rates,” Journal of Finance, 29 449-470.
16. Jarrow, R., and Yu, F., 2001, “Counterparty risk and the pricing of defaultable securities,” Journal of Finance, 56, 1765-1799
17. Jarrow, R. and S. Turnbull, 1995, “Pricing Derivatives on Financial Securities Subject to Credit Risk”, Journal of Finance, 50, 53-85.
18. Jarrow, R., D. Lando, and S. Turnbull, 1997, “A Markov Model for the Term Structure of Credit Spread,” Reviw of Financial Studies 10,481-523.
19. Jorion, P and Zhang, G., 2009, “Credit contagion from counterparty risk.” Journal of Finance, 64, 2053-2087
20. Kraft, H., Steffensen, M., 2007, “Bankruptcy counterparty risk, and contagion,” Review of Finance, 11, 209-252.
21. R sch, D., Winterfeldt, B., 2008, “Estimating credit contagion in a standard factor model,” Risk, August 2008, S. 78-82
22. Sakata, A., Hisakado, M., Mori, S., 2007, “Infectious Default Model with Recovery and Continuous Limits,” Journal of the Physical Society of Japan, Vol. 76, No. 5.
23. Sch nbucher, P., Schubert, D., 2001, “Copula Dependent Default Risk in Intensity Models,” (working paper, Bonn University)
24. Sch nbucher, P.J., 2006, “Portfolio Losses and The Term-Structure of Loss Transition Rates: a New Methodology for The Pricing of Portfolio Credit Derivatives,” (working paper, ETH Z rich.)
25. Van der Voort, M., 2006, “An Implied Loss Model,” (working paper, Bonn University)
26. Yu, F., (2007),”Correlated Defaults in Intensity-Based Models.” Mathematical Finance 17(2), 155-173