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Accuracy of mortgage portfolio risk forecasts during financial crises

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  • Lee, Yongwoong
  • Rösch, Daniel
  • Scheule, Harald

Abstract

This paper explores whether factor based credit portfolio risk models are able to predict losses in severe economic downturns such as the recent Global Financial Crisis (GFC) within standard confidence levels. The paper analyzes (i) the accuracy of default rate forecasts, and (ii) whether forecast downturn percentiles (Value-at-Risk, VaR) are sufficient to cover default rate outcomes over a quarterly and an annual forecast horizon. Uninformative maximum likelihood and informative Bayesian techniques are compared as they imply different degrees of uncertainty.

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  • Lee, Yongwoong & Rösch, Daniel & Scheule, Harald, 2016. "Accuracy of mortgage portfolio risk forecasts during financial crises," European Journal of Operational Research, Elsevier, vol. 249(2), pages 440-456.
    • Handle: RePEc:eee:ejores:v:249:y:2016:i:2:p:440-456
    DOI: 10.1016/j.ejor.2015.09.007
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    1. repec:uts:ppaper:v:3:y:2007:i:4:p:113-134 is not listed on IDEAS
    2. Rajan, Uday & Seru, Amit & Vig, Vikrant, 2015. "The failure of models that predict failure: Distance, incentives, and defaults," Journal of Financial Economics, Elsevier, vol. 115(2), pages 237-260.
    3. Darrell Duffie & Andreas Eckner & Guillaume Horel & Leandro Saita, 2009. "Frailty Correlated Default," Journal of Finance, American Finance Association, vol. 64(5), pages 2089-2123, October.
    4. Gene Amromin & Anna L. Paulson, 2009. "Comparing patterns of default among prime and subprime mortgages," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 33(Q II), pages 18-37.
    5. Quigley, John M. & Van Order, Robert, 1991. "Defaults on mortgage obligations and capital requirements for U.S. savings institutions : A policy perspective," Journal of Public Economics, Elsevier, vol. 44(3), pages 353-369, April.
    6. Jiménez, Gabriel & Mencía, Javier, 2009. "Modelling the distribution of credit losses with observable and latent factors," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 235-253, March.
    7. Adelino, Manuel & Gerardi, Kristopher & Willen, Paul S., 2013. "Why don't Lenders renegotiate more home mortgages? Redefaults, self-cures and securitization," Journal of Monetary Economics, Elsevier, vol. 60(7), pages 835-853.
    8. Daniel Roesch & Harald Scheule, 2007. "Multi-Year Dynamics for Forecasting Economic and Regulatory Capital in Banking," Published Paper Series 2007-2, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    9. McNeil, Alexander J. & Wendin, Jonathan P., 2007. "Bayesian inference for generalized linear mixed models of portfolio credit risk," Journal of Empirical Finance, Elsevier, vol. 14(2), pages 131-149, March.
    10. Ronel Elul & Nicholas S. Souleles & Souphala Chomsisengphet & Dennis Glennon & Robert Hunt, 2010. "What "Triggers" Mortgage Default?," American Economic Review, American Economic Association, vol. 100(2), pages 490-494, May.
    11. Sophia Rabe-Hesketh & Anders Skrondal & Andrew Pickles, 2002. "Reliable estimation of generalized linear mixed models using adaptive quadrature," Stata Journal, StataCorp LP, vol. 2(1), pages 1-21, February.
    12. Tong, Edward N.C. & Mues, Christophe & Thomas, Lyn C., 2012. "Mixture cure models in credit scoring: If and when borrowers default," European Journal of Operational Research, Elsevier, vol. 218(1), pages 132-139.
    13. Nikola Tarashev & Haibin Zhu, 2008. "Specification and Calibration Errors in Measures of Portfolio Credit Risk: The Case of the ASRF Model," International Journal of Central Banking, International Journal of Central Banking, vol. 4(2), pages 129-173, June.
    14. Gordy, Michael B., 2000. "A comparative anatomy of credit risk models," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 119-149, January.
    15. Alfred Hamerle & Thilo Liebig & Harald Scheule, 2006. "Forecasting credit event frequency – empirical evidence for West German firms," Published Paper Series 2006-1, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    16. Lee, Yongwoong & Poon, Ser-Huang, 2014. "Forecasting and decomposition of portfolio credit risk using macroeconomic and frailty factors," Journal of Economic Dynamics and Control, Elsevier, vol. 41(C), pages 69-92.
    17. D Rösch & H Scheule, 2014. "Forecasting probabilities of default and loss rates given default in the presence of selection," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(3), pages 393-407, March.
    18. Crook, Jonathan & Banasik, John, 2012. "Forecasting and explaining aggregate consumer credit delinquency behaviour," International Journal of Forecasting, Elsevier, vol. 28(1), pages 145-160.
    19. Jonathan Crook & Tony Bellotti, 2010. "Time varying and dynamic models for default risk in consumer loans," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(2), pages 283-305, April.
    20. Escanciano, J. Carlos & Olmo, Jose, 2010. "Backtesting Parametric Value-at-Risk With Estimation Risk," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 36-51.
    21. Koopman, Siem Jan & Lucas, André & Schwaab, Bernd, 2011. "Modeling frailty-correlated defaults using many macroeconomic covariates," Journal of Econometrics, Elsevier, vol. 162(2), pages 312-325, June.
    22. Crook, Jonathan N. & Edelman, David B. & Thomas, Lyn C., 2007. "Recent developments in consumer credit risk assessment," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1447-1465, December.
    23. Leow, Mindy & Mues, Christophe, 2012. "Predicting loss given default (LGD) for residential mortgage loans: A two-stage model and empirical evidence for UK bank data," International Journal of Forecasting, Elsevier, vol. 28(1), pages 183-195.
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    Cited by:

    1. Do, Hung Xuan & Rösch, Daniel & Scheule, Harald, 2018. "Predicting loss severities for residential mortgage loans: A three-step selection approach," European Journal of Operational Research, Elsevier, vol. 270(1), pages 246-259.
    2. Huy Truong Quang & Yoshinori Hara, 2019. "Managing risks and system performance in supply network: a conceptual framework," International Journal of Logistics Systems and Management, Inderscience Enterprises Ltd, vol. 32(2), pages 245-271.
    3. Bhattacharya, Arnab & Wilson, Simon P. & Soyer, Refik, 2019. "A Bayesian approach to modeling mortgage default and prepayment," European Journal of Operational Research, Elsevier, vol. 274(3), pages 1112-1124.

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