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研究生:蔡宗益
研究生(外文):Tsung-yi Tsai
論文名稱:ValuationofaCDOwithImpliedCorrelationandBaseCorrelation
論文名稱(外文):Valuation of a CDO with Implied Correlation and Base Correlation
指導教授:陳安行陳安行引用關係
指導教授(外文):An-sing Chen
學位類別:碩士
校院名稱:國立中正大學
系所名稱:財務金融所
學門:商業及管理學門
學類:財務金融學類
論文種類:學術論文
論文出版年:2007
畢業學年度:95
語文別:英文
論文頁數:36
中文關鍵詞:擔保債權憑證
外文關鍵詞:Base correlationCopulaImplied correlationCDO
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Abstract
In general, the implied correlation is higher for equity and most senior tranches than for mezzanine tranches, which is known as the correlation smile. This paper uses Gaussian Copula and One-Factor Gaussian Copula methods to price CDO products, and compares two methods to examine why correlation smile occurs. We change different correlation dependency structures, and different copula functions in this paper. We want to test if the loss distribution or the correlation structures led to correlation smiles. We will use Base Correlation to solve this problem, and use implied correlation and base correlation in Taiwan product.
Abstract
In general, the implied correlation is higher for equity and most senior tranches than for mezzanine tranches, which is known as the correlation smile. This paper uses Gaussian Copula and One-Factor Gaussian Copula methods to price CDO products, and compares two methods to examine why correlation smile occurs. We change different correlation dependency structures, and different copula functions in this paper. We want to test if the loss distribution or the correlation structures led to correlation smiles. We will use Base Correlation to solve this problem, and use implied correlation and base correlation in Taiwan product.
Contents
1. Introduction 2
2. Literature Review 5
3. Methodology 7
3.1 Gaussian Copula 7
3.1.1 Survival Function 7
3.1.2 Hazard Rate Function 8
3.1.3 Simulation method for Gaussian Copula 9
3.2 Factor Copula 10
3.2.1 Factor-based Model 10
3.2.2 Factor Model and Copula Function 10
3.2.3 Implementation of the Model 12
3.3 Pricing CDO tranches 13
3.4 Measures of Implied correlation 15
3.4.1 Compound Correlations 15
3.4.2 Base Correlations 15
4. Empirical Results 16
4.1 Homogeneous CDO 16
4.2 Heterogeneous CDO 20
4.3 Different Copulas 27
4.4 Base correlation 28
4.5 Numerical Results 30
5. Conclusion 31
References ………………………………………………………………………….33
References
1.Andersen, L. and Sidenius, J. (2004), “Extensions to the Gaussian Copula:random recovery and random factor loadings,” Journal of Credit Risk, Vol. 1, 29-70.

2.Andersen, L., Sidenius, J., and S. Basu (2003), “All your hedges in one basket,” Risk Magazine, November 2003.

3.Cifuentes, A. and G. O’Connor (1996), “The binomial expectation method applied to CBO/CLO analysis,” Moody’s Special Report, December 1996.

4.Duffie, D. and K. Singleton (1999), “Modeling term structures of defaultable bonds,” Review of Financial Studies, Vol. 12, 687-720.

5.Gregory, J. and Laurent, J-P (2003), “Basket default swaps, CDO’s and Factor Copulas,” Working paper, BNP Paribas.

6.Gregory, J. and Laurent, J-P (2004), “In the core of correlation,” Working paper, BNP Paribas,

7.Gregory, J., Burtschell, X. and Laurent, J-P (2005), “Beyond the Gaussian copula: stochastic and local correlation,” Working paper, BNP Paribas.

8.Gibson, M (2004). “Understanding the risk of synthetic CDOs,” Working paper.

9.Gupton, G.M., C.C. Finger and M. Bhatia (1997), “CreditMetrics-technical document,” Morgan Guaranty Trust Company.

10.Hull J. and A. White(2004),”Valuation of a CDO and nth to default CDS without Monte Carlo simulation,” Journal of Derivatives, winter 2004, pp. 8-23.

11.Hull J. and A. White(2006), “The Perfect Copula,” Working paper, University of Toronto.

12.Hull J. and A. White(2006),”Valuing Credit Derivatives Using an Implied Copula Approach,” Journal of Derivatives, Vol. 14, winter 2006, pp 8-28.

13.Laurent, J.P. and J. Gregory (2003), “Basket default swaps, CDO’s and factor copulas,” Working paper, ISFA Actuarial School, University of Lyon.

14.Laurent, J.P. and J. Gregory (2004), “In the core of correlation,” Risk Magazine, October, pp. 87-91

15.Li, D. X. (2000), “on default correlation: A copula Function approach,” Journal of Fixed Income, Vol. 9, 43-54.

16.McGinty, L. and Ahluwalia, R. (2004), “Credit correlation: A guide,” JP Morgan Technical paper.

17.McGinty, L., Ahuwalia, R., and Beinstein, E. (2004), “A relative value framework for credit correlation,” JP Morgan Technical paper.

18.Meneguzzo, D. and W. Vecchiato (2004), “Copula sensitivity in collateralized debt obligations and basket default swaps,” The Journal of Futures Markets, Vol. 24, pages 37-70.

19.Svenja Hager and Rainer Schobel, “A note on the Correlation smile,” Eberhard-Karls-Universität Tübingen, Discussion Paper No. 297.

20.Vasicek, O., 1987, “The loan loss distribution,” Working Paper, KMV Corporation.
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