Open Access
Volume 28, 2024
Page(s) 110 - 131
Published online 15 April 2024
  1. D. Lando, Credit Risk Modeling: Theory and Applications. Princeton University Press (2004). [Google Scholar]
  2. P. Protter, Stochastic integration and differential equations, Vol. 21, 2nd edn. Springer-Verlag, Berlin, Heidelberg (2005). [Google Scholar]
  3. T. Bielecki, A. Cousin, S. Crépey and A. Herbertsson, In search of a grand unifying theory. Creditflux Newsl. Anal. (2013) 20–21. [Google Scholar]
  4. Y. Jiao and S. Li, Generalized density approach in progressive enlargement of filtrations. Electron. J. Probab. 20 (2015) 1–21. [Google Scholar]
  5. S.N. Ethier and T.G. Kurtz, Markov Processes: Characterization and Convergence. Wiley (1986). [Google Scholar]
  6. X. Guo and Y. Zeng, Intensity process and compensator: a new filtration expansion approach and the Jeulin-Yor Theorem. Ann. Appl. Probab. 18 (2008) 120–142. [Google Scholar]
  7. Y. Zeng, Compensators of Stopping Times. Ph.D. thesis, Cornell University Mathematics Department (2006). [Google Scholar]
  8. S. Janson, S. M’Baye and P. Protter, Absolutely continuous compensators. Int. J. Theor. Appl. Finance 14 (2011) 335–351. [Google Scholar]
  9. A.W. Marshall and I. Olkin, A multivariate exponential distribution. J. Am. Stat. Assoc. 62 (1967) 30–44. [Google Scholar]
  10. D.R. Cox and P.A.W. Lewis, Multivariate Point Processes. Berkeley Symp. Math. Stat. Probab. (1972) 401–448. [Google Scholar]
  11. P.J. Diggle and R.K. Milne, Bivariate Cox processes: some models for bivariate spatial point patterns. J. Roy. Stat. Soc. B (Methodological) 45 (1983) 11–21. [Google Scholar]
  12. T.C. Brown, B.W. Silverman and R.K. Milne, A class of two-type point processes. Zeitsch. Wahrscheinlichkeitstheorie Verwandte Gebiete 58 (1981) 299–308. [Google Scholar]
  13. W. Li, Probability of default and default correlations. J. Risk Financial Manag. 9 (2016) 2016. [Google Scholar]
  14. T.R. Bielecki, M. Jeanblanc and A.D. Sezer, Joint densities of hitting times for finite state Markov processes. Turkish J. Math. 42 (2018) 586–608. [Google Scholar]
  15. K. Giesecke, A Simple Exponential Model for Dependent Defaults. J. Fixed Income 13 (2003) 74–83. [Google Scholar]
  16. S. Crépey, T.R. Bielecki and D. Brigo, Counterparty Risk and Funding: A Tale of Two Puzzles. Chapman & Hall (2014). [Google Scholar]
  17. Y. Sun, R. Mendoza-Arriaga and V. Linetsky, Marshall-–Olkin distributions, subordinators, efficient simulation, and applications to credit risk. Adv. Appl. Probab. 49 (2017) 481–514. [Google Scholar]
  18. D. Brigo, J.-F. Mai and M. Scherer, Markov multi-variate survival indicators for default simulation as a new characterization of the Marshall–Olkin law. Stat. Probab. Lett. 114 (2016) 60–66. [Google Scholar]
  19. F. Lindskog and A.J. McNeil, Common Poisson shock models: applications to insurance and credit risk modelling. ASTIN Bull. 33 (2003) 209–238. [Google Scholar]
  20. D. Gueye and M. Jeanblanc, Generalized Cox model for default times. Working paper, June 2021. [Google Scholar]
  21. D. Lando, On Cox processes and credit risky securities. Rev. Derivat. Res. 2 (1998) 99–120. [Google Scholar]
  22. A. Aksamit and M. Jeanblanc, Enlargement of Filtration with Finance in View. SpringerBriefs in Quantitative Finance, 1st edn. Springer, Cham (2017). [Google Scholar]
  23. T. Aven, A theorem for determining the compensator of a counting process. Scand. J. Stat. 12 (1985) 69–72. [Google Scholar]
  24. R. Jarrow, P. Protter and A. Quintos, Computing the probability of a financial market failure: a new measure of systemic risk. Ann. Oper. Res. (2022). [Google Scholar]
  25. E.J. Gumbel, Bivariate exponential distributions. J. Am. Stat. Assoc. 55 (1960) 698–707. [Google Scholar]
  26. W. Young, On multiple integration by parts and the second theorem of the mean. Proc. Lond. Math. Soc. 2 (1916) 273–293. [Google Scholar]
  27. T. Britton and E. Pardoux, Stochastic Epidemic Models. Springer International Publishing, Cham (2019) 5–19, Chapter 1. [Google Scholar]
  28. J. Swaine, E. Brown, J.S. Lee, A. Mirza and M. Kelly, How a collapsed pool deck could have caused a Florida condo building to fall. The Washington Post, August 12, 2021. [Google Scholar]
  29. H. Petroski, What lessons will be learned from the Florida Condo Collapse? The deadly catastrophic failure has put a lens on building maintenance. Am,. Scientist 109 (2021) 278–281. [Google Scholar]
  30. B. Walpole, Quest for answers begins following Florida building collapse. Am. Soc. Civil Eng., Civil Eng. Source (2021). [Google Scholar]
  31. G. Chen, E.C.W. Chen III, D. Hoffman, R. Luna and A. Sevi, Analysis of the interstate 10 twin bridges collapse during hurricane Katrina. Science and the Storms – The USGS Response to the Hurricanes of 2005 (2007) 35–42. [Google Scholar]
  32. A.B. Hanson and M. Brown, Cause of Montana Amtrak derailment that killed 3, injured dozens still under investigation. Great Falls Tribune, October 27, 2021. [Google Scholar]
  33. H. Chernoff, A Measure of asymptotic efficiency for tests of a hypothesis based on the sum of observations. Ann. Math. Stat. 23 (1952) 493–507. [Google Scholar]
  34. M. Chiani, D. Dardari and M.K. Simon, New exponential bounds and approximations for the computation of error probability in fading channels. IEEE Trans. Wireless Commun. 2 (2003) 840–845. [Google Scholar]
  35. G.K. Karagiannidis and A.S. Lioumpas, An improved approximation for the Gaussian Q-function. IEEE Commun. Lett. 11 (2007) 644–646. [Google Scholar]
  36. I.M. Tanash and T. Riihonen, Improved coefficients for the Karagiannidis-Lioumpas approximations and bounds to the Gaussian Q-function. IEEE Commun. Lett. 25 (2021) 1468–1471. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.