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Research Papers

Rating frailty, Bayesian updates, and portfolio credit risk analysis*

, &
Pages 777-797 | Received 18 Dec 2020, Accepted 22 Nov 2021, Published online: 13 Jan 2022

References

  • Aalen, O., Borgan, O. and Gjessing, H., Survival and Event History Analysis: A Process Point of View, 2008 (Springer Science & Business Media: Berlin).
  • Andrieu, C. and Thoms, J., A tutorial on adaptive MCMC. Stat. Comput., 2008, 18(4), 343–373.
  • Azizpour, S., Giesecke, K. and Schwenkler, G., Exploring the sources of default clustering. J. Financ. Econ., 2018, 129(1), 154–183.
  • Balan, T.A. and Putter, H., A tutorial on frailty models. Stat. Methods. Med. Res., 2020, 29(11), 3424–3454.
  • Basel Committee on Banking Supervision. Basel III: Finalising post-crisis reforms, 2017.
  • Bhattacharya, A., Wilson, S.P. and Soyer, R., A Bayesian approach to modeling mortgage default and prepayment. Eur. J. Oper. Res., 2019, 274(3), 1112–1124.
  • Black, F., Interest rates as options. J. Finance., 1995, 50(5), 1371–1376.
  • Chava, S., Stefanescu, C. and Turnbull, S., Modeling the loss distribution. Manage. Sci., 2011, 57(7), 1267–1287.
  • Coval, J., Jurek, J. and Stafford, E., The economics of structured finance. J. Econ. Perspect., 2009a, 23(1), 3–25.
  • Coval, J.D., Jurek, J.W. and Stafford, E., Economic catastrophe bonds. Am. Econ. Rev., 2009b, 99(3), 628–66.
  • Das, S.R., Duffie, D., Kapadia, N. and Saita, L., Common failings: How corporate defaults are correlated. J. Finance., 2007, 62(1), 93–117.
  • Duan, J.-C., Sun, J. and Wang, T., Multiperiod corporate default prediction – a forward intensity approach. J. Econom., 2012, 170(1), 191–209.
  • Duffie, D., Eckner, A., Horel, G. and Saita, L., Frailty correlated default. J. Finance., 2009, 64(5), 2089–2123.
  • Duffie, D., Saita, L. and Wang, K., Multi-period corporate default prediction with stochastic covariates. J. Financ. Econ., 2007, 83(3), 635–665.
  • Eraker, B., Johannes, M. and Polson, N., The impact of jumps in volatility and returns. J. Finance., 2003, 58(3), 1269–1300.
  • Giesecke, K. and Kim, B., Risk analysis of collateralized debt obligations. Oper. Res., 2011, 59(1), 32–49.
  • Gilks, W.R., Richardson, S. and Spiegelhalter, D.J., Markov Chain Monte Carlo in Practice, 1996 (Chapman and Hall: London).
  • Gilks, W.R. and Wild, P., Adaptive rejection sampling for Gibbs sampling. Appl. Stat., 1992, 41(2), 337–348.
  • Hilscher, J. and Wilson, M., Credit ratings and credit risk: Is one measure enough?. Manage. Sci., 2017, 63(10), 3414–3437.
  • Huang, J.-Z. and Huang, M., How much of the corporate-treasury yield spread is due to credit risk?. Rev. Asset Pricing Stud., 2012, 2(2), 153–202.
  • Johannes, M. and Polson, N., MCMC methods for continuous-time financial econometrics. In Handbook of Financial Econometrics: Applications, pp. 1–72, 2010 (Elsevier: Amsterdam).
  • Kass, R.E. and Raftery, A.E., Bayes factors. J. Am. Stat. Assoc., 1995, 90(430), 773–795.
  • Koopman, S.J., Lucas, A. and Schwaab, B., Modeling frailty-correlated defaults using many macroeconomic covariates. J. Econom., 2011, 162(2), 312–325.
  • Kou, S., Yu, C. and Zhong, H., Jumps in equity index returns before and during the recent financial crisis: A Bayesian analysis. Manage. Sci., 2017, 63(4), 988–1010.
  • Lee, Y., Rösch, D. and Scheule, H., Accuracy of mortgage portfolio risk forecasts during financial crises. Eur. J. Oper. Res., 2016, 249(2), 440–456.
  • Li, H., Wells, M.T. and Yu, C.L., A Bayesian analysis of return dynamics with Lévy jumps. Rev. Financ. Stud., 2008, 21(5), 2345–2378.
  • Moody's, Global approach to rating collateralized loan obligations (2017). Available at: https://www.moodys.com/researchdocumentcontentpage.aspx?docid=PBS1072545.
  • Neal, R.M., Slice sampling. Ann. Stat., 2003, 31(3), 705–741.
  • Neal, R.M., MCMC using Hamiltonian dynamics. In Handbook of Markov Chain Monte Carlo, edited by S. Brooks, A. Gelman, G. Jones, and X.-L. Meng, 2011 (Chapman & Hall/CRC: Boca Raton, FL).
  • Newton, M.A. and Raftery, A.E., Approximate Bayesian inference with the weighted likelihood bootstrap. J. R. Stat. Soc. Seri. B, 1994, 56(1), 3–48.
  • Paola Rebora, A.S. and Reilly, M., bshazard: Nonparametric smoothing of the hazard function. R package version 1.1., 2018,
  • Stulz, R.M., The shrinking universe of public firms: Facts, causes, and consequences. NBER Reporter 2018(2). Available from https://www.nber.org/reporter/2018number2/stulz.html,
  • Welling, M. and Teh, Y.W., Bayesian learning via stochastic gradient Langevin dynamics. In Proceedings of the 28th International Conference on Machine Learning (ICML-11), pp. 681–688, 2011 (Omnipress: Madison, WI).
  • Wienke, A., Frailty Models in Survival Analysis, 2010 (Chapman & Hall/CRC: Boca Raton, FL).
  • Yu, C.L., Li, H. and Wells, M.T., MCMC estimation of Lévy jump models using stock and option prices. Math. Financ., 2011, 21(3), 383–422.

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