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Research Papers

A logistic regression point of view toward loss given default distribution estimation

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Pages 419-435 | Received 10 Oct 2016, Accepted 17 Mar 2017, Published online: 18 Jul 2017

References

  • Acharya, V.V., Bharath, S.T. and Srinivasan, A., Does industry-wide distress affect defaulted firms? Evidence from creditor recoveries. J. Financ. Econ., 2007, 85, 787–821.10.1016/j.jfineco.2006.05.011
  • Afik, Z., Arad, O. and Galil, K., Using Merton model for default prediction: An empirical assessment of selected alternatives. J. Emp. Financ., 2016, 35, 43–67.10.1016/j.jempfin.2015.09.004
  • Agresti, A., Categorical Data Analysis, 2002 (Wiley: New York).10.1002/0471249688
  • Altman, E.I., Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. J. Financ., 1968, 23, 589–609.10.1111/j.1540-6261.1968.tb00843.x
  • Altman, E.I., Market dynamics and investment performance of distressed and defaulted debt securities. 1998. Available at http://ssrn.com/abstract=164502 (accessed on 5 May 2016).
  • Altman, E.I., Distressed and defaulted bond investment returns outperformed common stocks and high-yield bonds over last 10 years. 2014. Available at http://www.mvis-indices.com/mvis-onehundred/distressed-and-defaulted-bonds-portfolios-continued-outperformance-in-2014 (accessed on 5 May 2016).
  • Altman, E.I. and Kalotay, E.A., Ultimate recovery mixtures. J. Bank. Financ., 2014, 40, 116–129.10.1016/j.jbankfin.2013.11.021
  • Altman, E. and Kishore, V.M., Almost everything you wanted to know about recoveries on defaulted bonds. Financ. Anal. J., 1996, 52, 57–64.
  • Altman, E.I. and Kuehne, B.J., The investment performance and market dynamics of defaulted bonds and bank loans: 2011 review and 2012 outlook. 2012. Available at http://people.stern.nyu.edu/ealtman/2011InvestPerf.pdf (accessed on 5 May 2016).
  • Asarnow, E. and Edwards, D., Measuring loss on default bank loans: A 24-year study. J. Comm. Lend., 1995, 77, 11–23.
  • Bastos, J.A., Forecasting bank loans loss-given-default. J. Bank. Financ., 2010, 34, 2510–2517.10.1016/j.jbankfin.2010.04.011
  • Bastos, J.A., Ensemble predictions of recovery rates. J. Financ. Serv. Res., 2014, 46, 177–193.10.1007/s10693-013-0165-3
  • Bellotti, T. and Crook, J., Loss given default models incorporating macroeconomic variables for credit cards. Int. J. Forecasting, 2012, 28, 171–182.10.1016/j.ijforecast.2010.08.005
  • Calabrese, R., Predicting bank loan recovery rates with a mixed continuous-discrete model. Appl. Stoch. Models Bus. Ind., 2014, 30, 99–114.10.1002/asmb.1932
  • Calabrese, R. and Zenga, M., Bank loan recovery rates: Measuring and nonparametric density estimation. J. Bank. Financ., 2010, 34, 903–911.10.1016/j.jbankfin.2009.10.001
  • Caselli, S., Gatti, S. and Querci, F., The sensitivity of the loss given default rate to systematic risk: New empirical evidence on bank loans. J. Financ. Serv. Res., 2008, 34, 1–34.10.1007/s10693-008-0033-8
  • Chava, S., Stefanescu, C. and Turnbull, S., Modeling the loss distribution. Manage. Sci., 2011, 57, 1267–1287.10.1287/mnsc.1110.1345
  • Duffie, D., Saita, L. and Wang, K., Multi-period corporate default prediction with stochastic covariates. J. Financ. Econ., 2007, 83, 635–665.10.1016/j.jfineco.2005.10.011
  • Ferrari, S.L.P. and Cribari-Neto, F., Beta regression for modelling rates and proportions. J. Appl. Stat., 2004, 31, 799–815.
  • Friedman, C.A. and Sandow, S., Estimating conditional probability distributions of recovery rates: A utility-based approach. 2005. Available at http://ssrn.com/abstract=874754 (accessed on 5 May 2016).
  • Hartmann-Wendels, T., Miller, P. and Töws, E., Loss given default for leasing: Parametric and nonparametric estimations. J. Bank. Financ., 2014, 40, 364–375.10.1016/j.jbankfin.2013.12.006
  • Hwang, R.C., A varying-coefficient default model. Int. J. Forecasting, 2012, 28, 675–688.10.1016/j.ijforecast.2011.11.006
  • Hwang, R.C., Chung, H. and Chu, C.K., A two-stage probit model for predicting recovery rates. J. Financ. Serv. Res., 2016, 50, 311–339.
  • Keisman, D. and Van de Castle, K., Recovering your money: Insights into losses from defaults. Stan. Poor’s Credit Week, 1999, 16, 29–34.
  • Li, P., Qi, M., Zhang, X. and Zhao, X., Further investigation of parametric loss given default modeling. 2014. Available at https://www.occ.gov/publications/publications-by-type/occ-working-papers/2012-2009/wp2014-2.pdf (accessed on 5 May 2016).
  • Loterman, G., Brown, I., Martens, D., Mues, C. and Baesens, B., Benchmarking regression algorithms for loss given default modeling. Int. J. Forecasting, 2012, 28, 161–170.10.1016/j.ijforecast.2011.01.006
  • Merton, R.C., On the pricing of corporate debt: The risk structure of interest rates. J. Financ., 1974, 29, 449–470.
  • Oliveira, M.R., Louzada, F., Pereira, G.H.A., Moreira, F. and Calabrese, R., Inflated mixture models: Applications to multimodality in loss given default, 2015. Available at http://ssrn.com/abstract=2634919 (accessed on 5 May 2016).
  • Ospina, R. and Ferrari, S.L.P., Inflated beta distributions. Stat. Pap., 2010, 51, 111–126.10.1007/s00362-008-0125-4
  • Qi, M. and Zhao, X., Comparison of modeling methods for loss given default. J. Bank. Financ., 2011, 35, 2842–2855.10.1016/j.jbankfin.2011.03.011
  • Serfling, R., Approximation Theorems of Mathematical Statistics, 1980 (Wiley: New York).10.1002/SERIES1345
  • Shumway, T., Forecasting bankruptcy more accurately: A simple hazard model. J. Bus., 2001, 74, 101–124.10.1086/jb.2001.74.issue-1
  • Siao, J.S., Hwang, R.C. and Chu, C.K., Predicting recovery rates using logistic quantile regression with bounded outcomes. Quant. Finance, 2016, 16, 777–792.10.1080/14697688.2015.1059952
  • Sigrist, F. and Stahel, W.A., Using the censored gamma distribution for modeling fractional response variables with an application to loss given default. ASTIN Bull., 2011, 41, 673–710.
  • Wei, C.Z. and Chu, C.K., A regression point of view toward density estimation. J. Nonparametr. Stat., 1994, 4, 191–201.10.1080/10485259408832610
  • Yashkir, O. and Yashkir, Y., Loss given default modeling: A comparative analysis. J. Risk Model Valid., 2013, 7, 25–59.10.21314/JRMV.2013.101
  • Zhang, J. and Thomas, L.C., Comparisons of linear regression and survival analysis using single and mixture distributions approaches in modelling LGD. Int. J. Forecasting, 2012, 28, 204–215.10.1016/j.ijforecast.2010.06.002

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