Empirical copulas for CDO tranche pricing using relative entropy

International Journal of Theoretical and Applied Finance

Volumn 10, Issue 4, 2007, Pages 679-701

  Dempster, Michael A H ^a,b   Medova, Elena A ^a,b   Yang, Seung W ^a,b  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^b Cambridge Systems Associates Limited   (United Kingdom)

Author keywords

CDO; Copula; Entropy; Non parametric estimation; Portfolio credit risk

Indexed keywords

EID: 34547363860     PISSN: 02190249     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0219024907004391     Document Type: Article

References (19)

1. Bear Stearns, Valuing and hedging synthetic CDO tranches using base correlations, Technical Report (2004).
2. J. M. Borwein, R. Choski and P. Maréchal, Probability distributions of assets inferred from option prices via the principle of maximum entropy, SIAM Journal on Optimization 14(2) (2003) 464-478.
3. C. G. Broyden, The convergence of a class of double rank minimization algorithms, Journal of the Institute of Mathematics and its Applications 6 (1970) 76-90 and 222-231.
4. P. W. Buchen and M. Kelly, The maximum entropy distribution of an asset inferred from option prices, Journal of Financial and Quantitative Analysis 31(1) (1996) 143-159.
5. X. Burtschell, J. Gregory and J. P. Laurent, A comparative anaylsis of CDO pricing models, Working Paper, BNP Paribas (2005).
6. S. Das, D. Duffie, N. Kapadia and L. Saita, Common failings: How corporate defaults are correlated, Journal of Finance 62(1) (2007) 55-92.
7. A. Decarreau, D. Hilhorst, C. Lemaréchal and J. Navaza, Dual methods in entropy maximization: Application to some problems in crystallography, SIAM Journal on Optimization 2(2) (1992) 173-197.
8. R. Fletcher, A new approach to variable metric algorithms, Computer Journal 13 (1970) 317-322.
9. B. R. Frieden, Physics from Fisher Information (Cambridge University Press, Cambridge, 1998).
10. D. Goldfarb, A family of variable metric methods derived by variational means, Mathematics of Computation 24 (1970) 23-26.
11. G. D. Graziano and L. C. G. Rogers, A dynamic approach to the modelling of correlation credit derivatives using Markov chains, Working Paper, University of Cambridge (2006).
12. R. J. Hawkins and B. R. Frieden, Financial probabilities from Fisher information, eprint, arXiv:cond-mat/0302579 (2006).
13. J. Hull and A. White, Valuing credit derivatives using an implied copula approach, Journal of Derivatives 14(2) (2006) 8-28.
14. J. C. Jackwerth and M. Rubinstein, Recovering probability distributions from option prices, Journal of Finance 51 (1996) 1611-31.
15. E. T. Jaynes, Information theory and statistical mechanics, Physical Review 106 (1957) 620-630.
16. M. S. Joshi, Applying importance sampling to pricing single tranches of CDOs in a one-factor Li model, Wilmott March (2005).
17. N. Metropolis, A. W. Rosenbluth, M. N. Rosenbluth and A. H. Teller, Equations of state calculations by fast computing machines, Journal of Chemical Physics 21(1) (1953) 1087-1092.
18. A. Mortensen, Semi-analytical valuation of basket credit derivatives in intensity-based models, Journal of Derivatives 13(4) (2006) 8-26.
19. D. F. Shanno, Conditioning of quasi-Newton methods for function minimization, Mathematics of Computation 24 (1970) 647-657.