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Probability of default in collateralized credit operations

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  • 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
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    Cited by:

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    2. 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.
    3. 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.
    4. 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.
    5. 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).
    6. 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.

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    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

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