IDEAS home Printed from https://ideas.repec.org/a/spr/testjl/v30y2021i2d10.1007_s11749-020-00723-1.html
   My bibliography  Save this article

Probability of default estimation in credit risk using a nonparametric approach

Author

Listed:
  • Rebeca Peláez Suárez

    (University of A Coruña)

  • Ricardo Cao Abad

    (Research Group MODES, Department of Mathematics, CITIC, University of A Coruña, ITMATI)

  • Juan M. Vilar Fernández

    (Research Group MODES, Department of Mathematics, CITIC, University of A Coruña, ITMATI)

Abstract

In this paper, four nonparametric estimators of the probability of default in credit risk are proposed and compared. They are derived from estimators of the conditional survival function for censored data. Asymptotic expressions for the bias and the variance of these probability of default estimators are derived from similar properties for the conditional survival function estimators. A simulation study shows the performance of these four estimators. Finally, an empirical study based on modified real data illustrates their practical behaviour.

Suggested Citation

  • Rebeca Peláez Suárez & Ricardo Cao Abad & Juan M. Vilar Fernández, 2021. "Probability of default estimation in credit risk using a nonparametric approach," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(2), pages 383-405, June.
    • Handle: RePEc:spr:testjl:v:30:y:2021:i:2:d:10.1007_s11749-020-00723-1
    DOI: 10.1007/s11749-020-00723-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11749-020-00723-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11749-020-00723-1?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. Glennon, Dennis & Nigro, Peter, 2005. "Measuring the Default Risk of Small Business Loans: A Survival Analysis Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(5), pages 923-947, October.
    2. 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.
    3. A. Gannoun & Jérôme Saracco & K. Yu, 2007. "Comparison of kernel estimators of conditional distribution function and quantile regression under censoring for survival analysis," Post-Print hal-00153550, HAL.
    4. Keilegom, Ingrid Van & Akritas, Michael G. & Veraverbeke, Noel, 2001. "Estimation of the conditional distribution in regression with censored data: a comparative study," Computational Statistics & Data Analysis, Elsevier, vol. 35(4), pages 487-500, February.
    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. Rebeca Peláez & Ricardo Cao & Juan M. Vilar, 2022. "Bootstrap Bandwidth Selection and Confidence Regions for Double Smoothed Default Probability Estimation," Mathematics, MDPI, vol. 10(9), pages 1-25, May.

    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. Rebeca Peláez & Ricardo Cao & Juan M. Vilar, 2022. "Bootstrap Bandwidth Selection and Confidence Regions for Double Smoothed Default Probability Estimation," Mathematics, MDPI, vol. 10(9), pages 1-25, May.
    2. DeYoung, Robert & Glennon, Dennis & Nigro, Peter, 2008. "Borrower-lender distance, credit scoring, and loan performance: Evidence from informational-opaque small business borrowers," Journal of Financial Intermediation, Elsevier, vol. 17(1), pages 113-143, January.
    3. Kaboski, Joseph & Huneeus, Federico & Larrain, Mauricio & Schmukler, Sergio & Vera, Mario, 2022. "The Distribution of Crisis Credit: Effects on Firm Indebtedness and Aggregate Risk," CEPR Discussion Papers 17061, C.E.P.R. Discussion Papers.
    4. Luís Meira-Machado & Jacobo Uña-Álvarez & Somnath Datta, 2015. "Nonparametric estimation of conditional transition probabilities in a non-Markov illness-death model," Computational Statistics, Springer, vol. 30(2), pages 377-397, June.
    5. Guido Max Mantovani & Gregory Gadzinski, 2022. "How to Rate the Financial Performance of Private Companies? A Tailored Integrated Rating Methodology Applied to North-Eastern Italian Districts," JRFM, MDPI, vol. 15(11), pages 1-18, October.
    6. Eliana Christou & Michael G. Akritas, 2019. "Single index quantile regression for censored data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(4), pages 655-678, December.
    7. Filipe, Sara Ferreira & Grammatikos, Theoharry & Michala, Dimitra, 2016. "Forecasting distress in European SME portfolios," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 112-135.
    8. Sarah Sanya & Mr. Montfort Mlachila, 2010. "Post-Crisis Bank Behavior: Lessons From Mercosur," IMF Working Papers 2010/001, International Monetary Fund.
    9. Enrique Batiz‐Zuk & Fabrizio López‐Gallo & Abdulkadir Mohamed & Fátima Sánchez‐Cajal, 2022. "Determinants of loan survival rates for small and medium‐sized enterprises: Evidence from an emerging economy," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4741-4755, October.
    10. Wolff, Christian & Bams, Dennis & Pisa, Magdalena, 2015. "Credit risk characteristics of US small business portfolios," CEPR Discussion Papers 10889, C.E.P.R. Discussion Papers.
    11. Weiyu Li & Valentin Patilea, 2018. "A dimension reduction approach for conditional Kaplan–Meier estimators," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(2), pages 295-315, June.
    12. Andrew T. Young & Matthew J. Higgins & Donald J. Lacombe & Briana Sell, 2014. "The Direct and Indirect Effects of Small Business Administration Lending on Growth: Evidence from U.S. County-Level Data," NBER Working Papers 20543, National Bureau of Economic Research, Inc.
    13. Rachdi, Mustapha & Laksaci, Ali & Demongeot, Jacques & Abdali, Abdel & Madani, Fethi, 2014. "Theoretical and practical aspects of the quadratic error in the local linear estimation of the conditional density for functional data," Computational Statistics & Data Analysis, Elsevier, vol. 73(C), pages 53-68.
    14. Legrand, Catherine & Munda, Marco & Janssen, P. & Duchateau, L., 2012. "A general class of time-varying coefficients models for right censored data," LIDAM Discussion Papers ISBA 2012041, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    15. Ilyes Abid & Farid Mkaouar & Olfa Kaabia, 2018. "Dynamic analysis of the forecasting bankruptcy under presence of unobserved heterogeneity," Annals of Operations Research, Springer, vol. 262(2), pages 241-256, March.
    16. Magdalena Pisa & Dennis Bams & Christian Wolff, 2012. "Modeling default correlation in a US retail loan portfolio," LSF Research Working Paper Series 12-19, Luxembourg School of Finance, University of Luxembourg.
    17. Debadutta Panda & Sriharsha Reddy, 2020. "Predictors of microcredit default in Indian self‐help groups," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 91(2), pages 303-318, June.
    18. Moro Russ A. & Härdle Wolfgang K. & Schäfer Dorothea, 2017. "Company rating with support vector machines," Statistics & Risk Modeling, De Gruyter, vol. 34(1-2), pages 55-67, June.
    19. Diego Valderrama & Katheryn N. Russ, 2009. "A Theory of Banks, Bonds, and the Distribution of Firm Size," Working Papers 4, University of California, Davis, Department of Economics.
    20. Matthew J. Higgins & Donald J. Lacombe & Briana S. Stenard & Andrew T. Young, 2021. "Evaluating the effects of Small Business Administration lending on growth," Small Business Economics, Springer, vol. 57(1), pages 23-45, June.

    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:spr:testjl:v:30:y:2021:i:2:d:10.1007_s11749-020-00723-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.