IDEAS home Printed from https://ideas.repec.org/a/fgv/epgrbe/v70y2016i4a56564.html
   My bibliography  Save this article

A Macroeconomic Model of Credit Risk in Uruguay

Author

Listed:
  • Illanes, Gabriel
  • Pena, Alejandro
  • Sosa Rodriguez, Andrés Ricardo

Abstract

This paper deals with credit risk in the Uruguayan aggregate economy andtherefore correspond to financial stability purposes. To analyze the risk associ-ated with a portfolio of loans a nonlinear parametric model based on Merton’sapproach is used, in which a default event occurs if the returns of the economicagent falls below a certain threshold that depends on macroeconomic variables. The estimated models can help to understand the relationship between creditrisk and macroeconomic indicators. The results obtained can be consideredfor estimating the credit risk module in the stress tests framework of the localbanking system. ”Elasticities” of impact of the relevant macroeconomic factoron credit risk are reported for corporate and households lending, both in localcurrency and dollars. The parameters are obtained by the statistical technique ofMaximum Likelihood, where the function to maximize contains a latent randomfactor that is assumed to have normal distribution.

Suggested Citation

  • Illanes, Gabriel & Pena, Alejandro & Sosa Rodriguez, Andrés Ricardo, 2016. "A Macroeconomic Model of Credit Risk in Uruguay," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 70(4), December.
    • Handle: RePEc:fgv:epgrbe:v:70:y:2016:i:4:a:56564
    as

    Download full text from publisher

    File URL: https://periodicos.fgv.br/rbe/article/view/56564
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hamerle, Alfred & Liebig, Thilo & Scheule, Harald, 2004. "Forecasting Credit Portfolio Risk," Discussion Paper Series 2: Banking and Financial Studies 2004,01, Deutsche Bundesbank.
    2. Robert A. Jarrow & Stuart M. Turnbull, 2008. "Pricing Derivatives on Financial Securities Subject to Credit Risk," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 17, pages 377-409, World Scientific Publishing Co. Pte. Ltd..
    3. Rosch, Daniel, 2005. "An empirical comparison of default risk forecasts from alternative credit rating philosophies," International Journal of Forecasting, Elsevier, vol. 21(1), pages 37-51.
    4. Rösch, Daniel, 2003. "Correlations and Business Cycles of Credit Risk: Evidence from Bankruptcies in Germany," University of Regensburg Working Papers in Business, Economics and Management Information Systems 380, University of Regensburg, Department of Economics.
    5. Lucas, Andre & Klaassen, Pieter, 2006. "Discrete versus continuous state switching models for portfolio credit risk," Journal of Banking & Finance, Elsevier, vol. 30(1), pages 23-35, January.
    6. rea cipollini & giuseppe missaglia, 2005. "Business cycle effects on Portfolio Credit Risk: scenario generation through Dynamic Factor analysis," Finance 0502010, University Library of Munich, Germany.
    7. repec:zbw:bofrdp:2004_018 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

    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. Petr Jakubík, 2006. "Does Credit Risk Vary with Economic Cycles? The Case of Finland," Working Papers IES 2006/11, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Apr 2006.
    2. Gabriel Illanes & Alejandro Pena & Andrés Sosa, 2014. "Un Modelo Macroeconómico del Riesgo de Crédito en Uruguay," Documentos de trabajo 2014002, Banco Central del Uruguay.
    3. Hamerle, Alfred & Knapp, Michael & Wildenauer, Nicole, 2005. "Auswirkungen unterschiedlicher Assetkorrelationen in Mehr-Sektoren-Kreditportfoliomodellen," University of Regensburg Working Papers in Business, Economics and Management Information Systems 409, University of Regensburg, Department of Economics.
    4. Bonfim, Diana, 2009. "Credit risk drivers: Evaluating the contribution of firm level information and of macroeconomic dynamics," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 281-299, February.
    5. Bruneau, C. & de Bandt, O. & El Amri, W., 2012. "Macroeconomic fluctuations and corporate financial fragility," Journal of Financial Stability, Elsevier, vol. 8(4), pages 219-235.
    6. Petr Jakubík, 2007. "Credit Risk and the Finnish Economy," Czech Economic Review, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, vol. 1(3), pages 254-285, November.
    7. Feng, D. & Gourieroux, C. & Jasiak, J., 2008. "The ordered qualitative model for credit rating transitions," Journal of Empirical Finance, Elsevier, vol. 15(1), pages 111-130, January.
    8. J. Crook & T. Bellotti, 2012. "Asset correlations for credit card defaults," Applied Financial Economics, Taylor & Francis Journals, vol. 22(2), pages 87-95, January.
    9. Petr JAKUBÍK, 2007. "Macroeconomic Environment and Credit Risk (in English)," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 57(1-2), pages 60-78, March.
    10. Trueck, Stefan & Rachev, Svetlozar T., 2008. "Rating Based Modeling of Credit Risk," Elsevier Monographs, Elsevier, edition 1, number 9780123736833.
    11. 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.
    12. Jeremy Leake, 2003. "Credit spreads on sterling corporate bonds and the term structure of UK interest rates," Bank of England working papers 202, Bank of England.
    13. Pesaran, M. Hashem & Schuermann, Til & Treutler, Bjorn-Jakob & Weiner, Scott M., 2006. "Macroeconomic Dynamics and Credit Risk: A Global Perspective," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(5), pages 1211-1261, August.
    14. A. Itkin & V. Shcherbakov & A. Veygman, 2019. "New Model For Pricing Quanto Credit Default Swaps," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(03), pages 1-37, May.
    15. repec:zbw:bofitp:2012_003 is not listed on IDEAS
    16. Hong-Ming Yin & Jin Liang & Yuan Wu, 2018. "On a New Corporate Bond Pricing Model with Potential Credit Rating Change and Stochastic Interest Rate," JRFM, MDPI, vol. 11(4), pages 1-12, December.
    17. Zhang, Dalu, 2014. "Vine copulas and applications to the European Union sovereign debt analysis," International Review of Financial Analysis, Elsevier, vol. 36(C), pages 46-56.
    18. Rafal M. Wojakowski & M. Shahid Ebrahim & Aziz Jaafar & Murizah Osman Salleh, 2019. "Can Loan Valuation Adjustment (LVA) approach immunize collateralized debt from defaults?," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 28(2), pages 141-158, May.
    19. Augusto Castillo, 2004. "Firm and Corporate Bond Valuation: A Simulation Dynamic Programming Approach," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 41(124), pages 345-360.
    20. John Y. Campbell & Glen B. Taksler, 2003. "Equity Volatility and Corporate Bond Yields," Journal of Finance, American Finance Association, vol. 58(6), pages 2321-2350, December.
    21. Regis Houssou & Olivier Besson, 2010. "Indifference of Defaultable Bonds with Stochastic Intensity models," Papers 1003.4118, arXiv.org.

    More about this item

    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:fgv:epgrbe:v:70:y:2016:i:4:a:56564. 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: Núcleo de Computação da FGV EPGE (email available below). General contact details of provider: https://edirc.repec.org/data/epgvfbr.html .

    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.