IDEAS home Printed from https://ideas.repec.org/r/eee/intfor/v29y2013i4p563-574.html
   My bibliography  Save this item

Forecasting and stress testing credit card default using dynamic models

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Medina-Olivares, Victor & Calabrese, Raffaella & Crook, Jonathan & Lindgren, Finn, 2023. "Joint models for longitudinal and discrete survival data in credit scoring," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1457-1473.
  2. Nicholas Garvin & Samuel Kurian & Mike Major & David Norman, 2022. "Macrofinancial Stress Testing on Australian Banks," RBA Research Discussion Papers rdp2022-03, Reserve Bank of Australia.
  3. Kim, Hyeongjun & Cho, Hoon & Ryu, Doojin, 2018. "An empirical study on credit card loan delinquency," Economic Systems, Elsevier, vol. 42(3), pages 437-449.
  4. Luo, Sirong & Kong, Xiao & Nie, Tingting, 2016. "Spline based survival model for credit risk modeling," European Journal of Operational Research, Elsevier, vol. 253(3), pages 869-879.
  5. Medina-Olivares, Victor & Lindgren, Finn & Calabrese, Raffaella & Crook, Jonathan, 2023. "Joint models of multivariate longitudinal outcomes and discrete survival data with INLA: An application to credit repayment behaviour," European Journal of Operational Research, Elsevier, vol. 310(2), pages 860-873.
  6. Li, Aimin & Li, Zhiyong & Bellotti, Anthony, 2023. "Predicting loss given default of unsecured consumer loans with time-varying survival scores," Pacific-Basin Finance Journal, Elsevier, vol. 78(C).
  7. Medina-Olivares, Victor & Calabrese, Raffaella & Dong, Yizhe & Shi, Baofeng, 2022. "Spatial dependence in microfinance credit default," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1071-1085.
  8. Luong, Thi Mai & Scheule, Harald, 2022. "Benchmarking forecast approaches for mortgage credit risk for forward periods," European Journal of Operational Research, Elsevier, vol. 299(2), pages 750-767.
  9. Mariusz Górajski & Dobromił Serwa & Zuzanna Wośko, 2019. "Measuring expected time to default under stress conditions for corporate loans," Empirical Economics, Springer, vol. 57(1), pages 31-52, July.
  10. TOBBACK, Ellen & MARTENS, David, 2017. "Retail credit scoring using fine-grained payment data," Working Papers 2017011, University of Antwerp, Faculty of Business and Economics.
  11. Douw Gerbrand Breed & Niel van Jaarsveld & Carsten Gerken & Tanja Verster & Helgard Raubenheimer, 2021. "Development of an Impairment Point in Time Probability of Default Model for Revolving Retail Credit Products: South African Case Study," Risks, MDPI, vol. 9(11), pages 1-22, November.
  12. Douw Gerbrand Breed & Jacques Hurter & Mercy Marimo & Matheba Raletjene & Helgard Raubenheimer & Vibhu Tomar & Tanja Verster, 2023. "A Forward-Looking IFRS 9 Methodology, Focussing on the Incorporation of Macroeconomic and Macroprudential Information into Expected Credit Loss Calculation," Risks, MDPI, vol. 11(3), pages 1-16, March.
  13. Anton Gerunov, 2023. "Modern Approaches To Forecasting Firm Default Rates Over The Short To Medium Term: An Application To A Panel Of Polish Companies," Yearbook of the Faculty of Economics and Business Administration, Sofia University, Faculty of Economics and Business Administration, Sofia University St Kliment Ohridski - Bulgaria, vol. 22(1), pages 5-15, October.
  14. Michael Jacobs, 2020. "A Holistic Model Validation Framework for Current Expected Credit Loss (CECL) Model Development and Implementation," IJFS, MDPI, vol. 8(2), pages 1-36, May.
  15. Bocchio, Cecilia & Crook, Jonathan & Andreeva, Galina, 2023. "The impact of macroeconomic scenarios on recurrent delinquency: A stress testing framework of multi-state models for mortgages," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1655-1677.
  16. Sajjad Taghiyeh & David C Lengacher & Robert B Handfield, 2020. "Loss Rate Forecasting Framework Based on Macroeconomic Changes: Application to US Credit Card Industry," Papers 2006.07911, arXiv.org.
  17. Maria Rocha Sousa & João Gama & Elísio Brandão, 2013. "Introducing time-changing economics into credit scoring," FEP Working Papers 513, Universidade do Porto, Faculdade de Economia do Porto.
  18. Chrysovalantis Gaganis & Panagiota Papadimitri & Fotios Pasiouras & Menelaos Tasiou, 2023. "Social traits and credit card default: a two-stage prediction framework," Annals of Operations Research, Springer, vol. 325(2), pages 1231-1253, June.
  19. Shen, Feng & Zhang, Xin & Wang, Run & Lan, Dao & Zhou, Wei, 2022. "Sequential optimization three-way decision model with information gain for credit default risk evaluation," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1116-1128.
  20. Anastasios Petropoulos & Vasilis Siakoulis & Dionysios Mylonas & Aristotelis Klamargias, 2018. "A combined statistical framework for forecasting default rates of Greek Financial Institutions' credit portfolios," Working Papers 243, Bank of Greece.
  21. Djeundje, Viani Biatat & Crook, Jonathan, 2019. "Dynamic survival models with varying coefficients for credit risks," European Journal of Operational Research, Elsevier, vol. 275(1), pages 319-333.
  22. Wang, Zheqi & Crook, Jonathan & Andreeva, Galina, 2020. "Reducing estimation risk using a Bayesian posterior distribution approach: Application to stress testing mortgage loan default," European Journal of Operational Research, Elsevier, vol. 287(2), pages 725-738.
  23. Richard Chamboko & Jorge M. Bravo, 2016. "On the modelling of prognosis from delinquency to normal performance on retail consumer loans," Risk Management, Palgrave Macmillan, vol. 18(4), pages 264-287, December.
  24. Emma Kroell & Silvana M. Pesenti & Sebastian Jaimungal, 2022. "Stressing Dynamic Loss Models," Papers 2211.03221, arXiv.org, revised Oct 2023.
  25. Oliver Blümke, 2022. "Multiperiod default probability forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 677-696, July.
  26. Dendramis, Y. & Tzavalis, E. & Varthalitis, P. & Athanasiou, E., 2020. "Predicting default risk under asymmetric binary link functions," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1039-1056.
  27. Djeundje, Viani Biatat & Crook, Jonathan, 2018. "Incorporating heterogeneity and macroeconomic variables into multi-state delinquency models for credit cards," European Journal of Operational Research, Elsevier, vol. 271(2), pages 697-709.
  28. Yaseen Ghulam & Sophie Hill, 2017. "Distinguishing between Good and Bad Subprime Auto Loans Borrowers: The Role of Demographic, Region and Loan Characteristics," Review of Economics & Finance, Better Advances Press, Canada, vol. 10, pages 49-62, November.
  29. Lore Dirick & Gerda Claeskens & Bart Baesens, 2017. "Time to default in credit scoring using survival analysis: a benchmark study," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(6), pages 652-665, June.
  30. Richard Chamboko & Jorge Miguel Bravo, 2020. "A Multi-State Approach to Modelling Intermediate Events and Multiple Mortgage Loan Outcomes," Risks, MDPI, vol. 8(2), pages 1-29, June.
  31. Tomasz Korol & Anestis K. Fotiadis, 2022. "Implementing artificial intelligence in forecasting the risk of personal bankruptcies in Poland and Taiwan," Oeconomia Copernicana, Institute of Economic Research, vol. 13(2), pages 407-438, June.
  32. Sanchez-Barrios, Luis Javier & Andreeva, Galina & Ansell, Jake, 2016. "“Time-to-profit scorecards for revolving credit”," European Journal of Operational Research, Elsevier, vol. 249(2), pages 397-406.
  33. Thi Mai Luong, 2020. "Selection Effects of Lender and Borrower Choices on Risk Measurement, Management and Prudential Regulation," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 3-2020.
  34. Dendramis, Y. & Tzavalis, E. & Adraktas, G., 2018. "Credit risk modelling under recessionary and financially distressed conditions," Journal of Banking & Finance, Elsevier, vol. 91(C), pages 160-175.
  35. Djeundje, Viani Biatat & Crook, Jonathan, 2019. "Identifying hidden patterns in credit risk survival data using Generalised Additive Models," European Journal of Operational Research, Elsevier, vol. 277(1), pages 366-376.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.