IDEAS home Printed from https://ideas.repec.org/p/col/000094/005544.html
   My bibliography  Save this paper

Un Modelo de Alerta Temprana para el Sistema Financiero Colombiano

Author

Listed:
  • José Eduardo Gómez González
  • Inés Paola Orozco

Abstract

En este trabajo se presenta un modelo estadístico de alerta temprana, que utiliza modelos de duración para evaluar el estado corriente y pronosticar el estado futuro de la salud financiera de los bancos en Colombia. En el artículo se discuten las ventajas que tiene utilizar modelos de duración como modelos estadísticos de alerta temprana frente a los más comúnmente utilizados modelos de respuesta binaria. Se argumenta que el modelo aquí presentado, que estudia la probabilidad de deterioro de los créditos a partir la salud financiera de las contrapartes de los bancos, puede ser un buen complemento a un modelo de alerta temprana que estudie directamente la probabilidad de quiebra de las entidades financieras. La capacidad de pronóstico dentro de muestra del modelo es buena, y podría pensarse que la capacidad de pronóstico fuera de muestra también es buena, ya que la muestra de créditos comerciales utilizada en las estimaciones es bastante representativa.

Suggested Citation

  • José Eduardo Gómez González & Inés Paola Orozco, 2009. "Un Modelo de Alerta Temprana para el Sistema Financiero Colombiano," Borradores de Economia 5544, Banco de la Republica.
  • Handle: RePEc:col:000094:005544
    as

    Download full text from publisher

    File URL: http://www.banrep.gov.co/docum/ftp/borra565.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Mr. Robert Billings & Ms. Brenda Gonzalez-Hermosillo & Ceyla Pazarbasioglu, 1996. "Banking System Fragility: Likelihood Versus Timing of Failure: An Application to the Mexican Financial Crisis," IMF Working Papers 1996/142, International Monetary Fund.
    2. Carree, Martin A., 2003. "A hazard rate analysis of Russian commercial banks in the period 1994-1997," Economic Systems, Elsevier, vol. 27(3), pages 255-269, September.
    3. Lennox, Clive, 1999. "Identifying failing companies: a re-evaluation of the logit, probit and DA approaches," Journal of Economics and Business, Elsevier, vol. 51(4), pages 347-364, July.
    4. 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.
    5. Philip Bunn & Victoria Redwood, 2003. "Company accounts based modelling of business failures and the implications for financial stability," Bank of England working papers 210, Bank of England.
    6. José E. Gómez-Gonzalez & Nicholas M. Kiefer, 2009. "Bank Failure: Evidence From The Colombian Financial Crisis," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 3(2), pages 15-31.
    7. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    8. Daley, J. & Matthews, K. & Whitfield, K., 2008. "Too-big-to-fail: Bank failure and banking policy in Jamaica," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(3), pages 290-303, July.
    9. Martin, Daniel, 1977. "Early warning of bank failure : A logit regression approach," Journal of Banking & Finance, Elsevier, vol. 1(3), pages 249-276, November.
    10. Geroski,Paul A. & Gregg,Paul, 1997. "Coping with Recession," Cambridge Books, Cambridge University Press, number 9780521622769.
    11. Henrik Andersen, 2008. "Failure prediction of Norwegian banks: A Logit approach," Working Paper 2008/02, Norges Bank.
    12. Arena, Marco, 2008. "Bank failures and bank fundamentals: A comparative analysis of Latin America and East Asia during the nineties using bank-level data," Journal of Banking & Finance, Elsevier, vol. 32(2), pages 299-310, February.
    13. Olivier BROSSARD (LEREPS-GRES ) & Frédéric DUCROZET (PSE - Crédit Agricole) & Adrian ROCHE (EconomiX - Crédit Agricole), 2007. "An Early Warning Model for EU banks with Detection of the Adverse Selection Effect," Cahiers du GRES (2002-2009) 2007-08, Groupement de Recherches Economiques et Sociales.
    14. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    15. Kolari, James & Glennon, Dennis & Shin, Hwan & Caputo, Michele, 2002. "Predicting large US commercial bank failures," Journal of Economics and Business, Elsevier, vol. 54(4), pages 361-387.
    16. Lando, David & Skodeberg, Torben M., 2002. "Analyzing rating transitions and rating drift with continuous observations," Journal of Banking & Finance, Elsevier, vol. 26(2-3), pages 423-444, March.
    17. E. Nur Ozkan-Gunay & Mehmed Ozkan, 2007. "Prediction of bank failures in emerging financial markets: an ANN approach," Journal of Risk Finance, Emerald Group Publishing, vol. 8(5), pages 465-480, November.
    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. Li Xian Liu & Shuangzhe Liu & Milind Sathye, 2021. "Predicting Bank Failures: A Synthesis of Literature and Directions for Future Research," JRFM, MDPI, vol. 14(10), pages 1-24, October.
    2. Michael Halling & Evelyn Hayden, 2008. "Bank failure prediction: a two-step survival time approach," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The IFC's contribution to the 56th ISI Session, Lisbon, August 2007, volume 28, pages 48-73, Bank for International Settlements.
    3. Jos� Eduardo Gómez-González, 2012. "Failing and Merging as Competing Alternatives during Times of Financial Distress: Evidence from the Colombian Financial Crisis," International Economic Journal, Taylor & Francis Journals, vol. 26(4), pages 655-671, October.
    4. Meral Varish Kiefer, 2014. "Bank failures and mergers in Turkey: 1992-2014," Journal of Economic and Financial Studies (JEFS), LAR Center Press, vol. 2(5), pages 31-49, October.
    5. Anatoly Peresetsky & Alexandr Karminsky & Sergei Golovan, 2011. "Probability of default models of Russian banks," Economic Change and Restructuring, Springer, vol. 44(4), pages 297-334, November.
    6. Peresetsky, A. A., 2011. "What factors drive the Russian banks license withdrawal," MPRA Paper 41507, University Library of Munich, Germany.
    7. Swami, Onkar Shivraj & Vishnu Kumar, N. Arun & Baruah, Palash, 2012. "Determinants of the exit decision of foreign banks in India," MPRA Paper 38722, University Library of Munich, Germany.
    8. fernández, María t. Tascón & gutiérrez, Francisco J. Castaño, 2012. "Variables y Modelos Para La Identificación y Predicción Del Fracaso Empresarial: Revisión de La Investigación Empírica Reciente," Revista de Contabilidad - Spanish Accounting Review, Elsevier, vol. 15(1), pages 7-58.
    9. Karina ALVES & Aquiles KALATZIS & Alberto BORGES MATIAS, 2009. "Survival Analysis of Private Banks in Brazil," EcoMod2009 21500002, EcoMod.
    10. repec:zbw:bofitp:2004_021 is not listed on IDEAS
    11. Anatoly Peresetsky & Alexandr Karminsky & Sergei Golovan, 2011. "Probability of default models of Russian banks," Economic Change and Restructuring, Springer, vol. 44(4), pages 297-334, November.
    12. Пересецкий А.А., 2007. "Методы Оценки Вероятности Дефолта Банков," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 43(3), июль.
    13. Fiordelisi, Franco & Mare, Davide Salvatore, 2013. "Probability of default and efficiency in cooperative banking," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 26(C), pages 30-45.
    14. Cole, Rebel A. & Wu, Qiongbing, 2009. "Is hazard or probit more accurate in predicting financial distress? Evidence from U.S. bank failures," MPRA Paper 24688, University Library of Munich, Germany, revised 01 Aug 2010.
    15. Suzan Hol, 2006. "The influence of the business cycle on bankruptcy probability," Discussion Papers 466, Statistics Norway, Research Department.
    16. Zeineb Affes & Rania Hentati-Kaffel, 2016. "Forecast bankruptcy using a blend of clustering and MARS model - Case of US banks," Post-Print halshs-01314553, HAL.
    17. Daniel Porath, 2006. "Estimating probabilities of default for German savings banks and credit cooperatives," Schmalenbach Business Review (sbr), LMU Munich School of Management, vol. 58(3), pages 214-233, July.
    18. G. Lanine & R. Vander Vennet, 2005. "Failure prediction in the Russian bank sector with logit and trait recognition models," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/329, Ghent University, Faculty of Economics and Business Administration.
    19. Thomas B. King & Daniel A. Nuxoll & Timothy J. Yeager, 2006. "Are the causes of bank distress changing? can researchers keep up?," Review, Federal Reserve Bank of St. Louis, vol. 88(Jan), pages 57-80.
    20. Duffie, Darrell & Saita, Leandro & Wang, Ke, 2007. "Multi-period corporate default prediction with stochastic covariates," Journal of Financial Economics, Elsevier, vol. 83(3), pages 635-665, March.
    21. repec:zbw:bofrdp:2009_035 is not listed on IDEAS
    22. Demyanyk, Yuliya & Hasan, Iftekhar, 2009. "Financial crises and bank failures: a review of prediction methods," Bank of Finland Research Discussion Papers 35/2009, Bank of Finland.

    More about this item

    Keywords

    Modelos estadísticos de alerta temprana; modelos de duración; intensidades de transición.;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G01 - Financial Economics - - General - - - Financial Crises
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

    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:col:000094:005544. 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: Clorith Angelica Bahos Olivera (email available below). General contact details of provider: .

    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.