IDEAS home Printed from https://ideas.repec.org/a/eee/ecofin/v25y2013icp276-292.html
   My bibliography  Save this article

Probability of default in collateralized credit operations

Author

Listed:
  • Divino, Jose Angelo
  • Rocha, Líneke Clementino Sleegers

Abstract

The goal of this paper is to identify the major determinants of the probability of default in a mortgage credit operation, which is backed by collateral. We use an exclusive data set with 268,036 loan contracts and apply logistic regression and Cox proportional hazards model in the estimation. The discriminatory power of the estimated models is analyzed by several accuracy indicators. The inclusion of time-dependent macroeconomic variables in addition to covariates representing characteristics of the contract and individuals improved the overall performance. Logistic regression showed a higher discriminatory power than Cox proportional hazards model according to all accuracy indicators. It is worth mentioning the negative relationship between the probability of default and the economy base interest rate. Decreases in the base interest rate lead banks to lose revenue from treasury operations and expand credit operations to compensate the loss. This strategy brings individuals with a higher probability of default to the financial market.

Suggested Citation

  • Divino, Jose Angelo & Rocha, Líneke Clementino Sleegers, 2013. "Probability of default in collateralized credit operations," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 276-292.
    • Handle: RePEc:eee:ecofin:v:25:y:2013:i:c:p:276-292
    DOI: 10.1016/j.najef.2012.06.015
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1062940812000666
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.najef.2012.06.015?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Veronica Balzarotti & Michael Falkenheim & Andrew Powell, 2002. "On the Use of Portfolio Risk Models and Capital Requirements in Emerging Markets: The Case of Argentina," The World Bank Economic Review, World Bank, vol. 16(2), pages 197-212, August.
    2. G Andreeva, 2006. "European generic scoring models using survival analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(10), pages 1180-1187, October.
    3. Vasso Ioannidou & Steven Ongena & José-Luis Peydró, 2015. "Monetary Policy, Risk-Taking, and Pricing: Evidence from a Quasi-Natural Experiment," Review of Finance, European Finance Association, vol. 19(1), pages 95-144.
    4. John Geanakoplos, 2009. "The Leverage Cycle," Cowles Foundation Discussion Papers 1715R, Cowles Foundation for Research in Economics, Yale University, revised Jan 2010.
    5. T Bellotti & J Crook, 2009. "Credit scoring with macroeconomic variables using survival analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(12), pages 1699-1707, December.
    6. J Banasik & J N Crook & L C Thomas, 1999. "Not if but when will borrowers default," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 50(12), pages 1185-1190, December.
    7. M Stepanova & L C Thomas, 2001. "PHAB scores: proportional hazards analysis behavioural scores," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(9), pages 1007-1016, September.
    8. 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.
    9. Jose Angelo Divino & Edna Souza Lima & Jaime Orrillo, 2013. "Interest rates and default in unsecured loan markets," Quantitative Finance, Taylor & Francis Journals, vol. 13(12), pages 1925-1934, December.
    10. Pradeep Dubey & John Geanakoplos & Martin Shubik, 2005. "Default and Punishment in General Equilibrium," Econometrica, Econometric Society, vol. 73(1), pages 1-37, January.
    11. Dirk Tasche, 2006. "Validation of internal rating systems and PD estimates," Papers physics/0606071, arXiv.org.
    12. Gary Whalen, 1991. "A proportional hazards model of bank failure: an examination of its usefulness as an early warning tool," Economic Review, Federal Reserve Bank of Cleveland, vol. 27(Q I), pages 21-31.
    13. Maria Stepanova & Lyn Thomas, 2002. "Survival Analysis Methods for Personal Loan Data," Operations Research, INFORMS, vol. 50(2), pages 277-289, April.
    14. John Geanakoplos, 2010. "The Leverage Cycle," NBER Chapters, in: NBER Macroeconomics Annual 2009, Volume 24, pages 1-65, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Hammoudeh, Shawkat & McAleer, Michael, 2013. "Risk management and financial derivatives: An overview," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 109-115.
    2. 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.
    3. Onkar Shivraj Swami & B. Nethaji & Jyoti Prakash Sharma, 2022. "Determining Risk Factors that Diminish Asset Quality of Indian Commercial Banks," Global Business Review, International Management Institute, vol. 23(2), pages 372-384, April.
    4. Ortas, E. & Salvador, M. & Moneva, J.M., 2015. "Improved beta modeling and forecasting: An unobserved component approach with conditional heteroscedastic disturbances," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 27-51.
    5. Schweikert, Jochen & Höchstötter, Markus, 2018. "Epidemiological spreading of mortgage default," Working Paper Series in Economics 112, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    6. Carvalho, Jaimilton & Orrillo, Jaime & da Silva, Fernanda Rocha Gomes, 2020. "Probability of default in collateralized credit operations for small business," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. 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).
    3. repec:syb:wpbsba:03/2013 is not listed on IDEAS
    4. T Bellotti & J Crook, 2009. "Credit scoring with macroeconomic variables using survival analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(12), pages 1699-1707, December.
    5. Andreeva, Galina & Ansell, Jake & Crook, Jonathan, 2007. "Modelling profitability using survival combination scores," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1537-1549, December.
    6. Li, Zhiyong & Li, Aimin & Bellotti, Anthony & Yao, Xiao, 2023. "The profitability of online loans: A competing risks analysis on default and prepayment," European Journal of Operational Research, Elsevier, vol. 306(2), pages 968-985.
    7. Jose Angelo Divino & Edna Souza Lima & Jaime Orrillo, 2013. "Interest rates and default in unsecured loan markets," Quantitative Finance, Taylor & Francis Journals, vol. 13(12), pages 1925-1934, December.
    8. 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.
    9. Arno Botha & Tanja Verster & Roelinde Bester, 2024. "The TruEnd-procedure: Treating trailing zero-valued balances in credit data," Papers 2404.17008, arXiv.org, revised Nov 2024.
    10. Ewa Wycinka, 2015. "Modelling Time to Default Or Early Repayment as Competing Risks (Modelowanie czasu do zaprzestania splat rat kredytu lub wczesniejszej splaty kredytu jako zdarzen konkurujacych )," Problemy Zarzadzania, University of Warsaw, Faculty of Management, vol. 13(55), pages 146-157.
    11. Dirick, Lore & Claeskens, Gerda & Vasnev, Andrey & Baesens, Bart, 2022. "A hierarchical mixture cure model with unobserved heterogeneity for credit risk," Econometrics and Statistics, Elsevier, vol. 22(C), pages 39-55.
    12. 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.
    13. 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.
    14. L N Allen & L C Rose, 2006. "Financial survival analysis of defaulted debtors," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(6), pages 630-636, June.
    15. Bellotti, Tony & Crook, Jonathan, 2013. "Forecasting and stress testing credit card default using dynamic models," International Journal of Forecasting, Elsevier, vol. 29(4), pages 563-574.
    16. Calabrese, Raffaella & Crook, Jonathan, 2020. "Spatial contagion in mortgage defaults: A spatial dynamic survival model with time and space varying coefficients," European Journal of Operational Research, Elsevier, vol. 287(2), pages 749-761.
    17. Leow, Mindy & Crook, Jonathan, 2014. "Intensity models and transition probabilities for credit card loan delinquencies," European Journal of Operational Research, Elsevier, vol. 236(2), pages 685-694.
    18. Bengui, Julien & Phan, Toan, 2018. "Asset pledgeability and endogenously leveraged bubbles," Journal of Economic Theory, Elsevier, vol. 177(C), pages 280-314.
    19. Liu, Fan & Hua, Zhongsheng & Lim, Andrew, 2015. "Identifying future defaulters: A hierarchical Bayesian method," European Journal of Operational Research, Elsevier, vol. 241(1), pages 202-211.
    20. 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.
    21. 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.

    More about this item

    Keywords

    Probability of default; Logistic regression; Survival analysis; Collateral; Accuracy indicators;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecofin:v:25:y:2013:i:c:p:276-292. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620163 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.