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What factors drive the Russian banks license withdrawal

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  • Peresetsky, A. A.

Abstract

The binary and multinomial logit models are applied for prediction of the Russian banks defaults (license withdrawals) using data from bank balance sheets and macroeconomic indicators. Significantly different models correspond to the two main grounds for license withdrawal: financial insolvency and money laundering. Analysis of data for the period 2005.2–2008.4 for accurate prediction of a bank’s financial insolvency, which is the focus of interest for the Russian Deposit Insurance Agency, demonstrates that the multinomial model doesn’t outperform the binary model.

Suggested Citation

  • Peresetsky, A. A., 2011. "What factors drive the Russian banks license withdrawal," MPRA Paper 41507, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:41507
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    References listed on IDEAS

    as
    1. Cole, Rebel A. & Gunther, Jeffery W., 1995. "Separating the likelihood and timing of bank failure," Journal of Banking & Finance, Elsevier, vol. 19(6), pages 1073-1089, September.
    2. Wiginton, John C., 1980. "A Note on the Comparison of Logit and Discriminant Models of Consumer Credit Behavior," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 15(3), pages 757-770, 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. Izan, H. Y., 1984. "Corporate distress in Australia," Journal of Banking & Finance, Elsevier, vol. 8(2), pages 303-320, June.
    5. Christophe J. Godlewski, 2007. "Are Ratings Consistent with Default Probabilities?: Empirical Evidence on Banks in Emerging Market Economies," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 43(4), pages 5-23, August.
    6. Pamela K. Coats & L. Franklin Fant, 1993. "Recognizing Financial Distress Patterns Using a Neural Network Tool," Financial Management, Financial Management Association, vol. 22(3), Fall.
    7. 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.
    8. 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.
    9. repec:zbw:bofitp:2008_017 is not listed on IDEAS
    10. 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.
    11. Wei, Yingqi & Liu, Bo & Liu, Xiaming, 2005. "Entry modes of foreign direct investment in China: a multinomial logit approach," Journal of Business Research, Elsevier, vol. 58(11), pages 1495-1505, November.
    12. John Krainer & Jose A. Lopez, 2008. "Using Securities Market Information for Bank Supervisory Monitoring," International Journal of Central Banking, International Journal of Central Banking, vol. 4(1), pages 125-164, March.
    13. John Krainer & Jose A. Lopez, 2002. "Off-site monitoring of bank holding companies," FRBSF Economic Letter, Federal Reserve Bank of San Francisco, issue may17.
    14. Arturo Estrella & Sangkyun Park & Stavros Peristiani, 2000. "Capital ratios as predictors of bank failure," Economic Policy Review, Federal Reserve Bank of New York, issue Jul, pages 33-52.
    15. repec:zbw:bofitp:2004_021 is not listed on IDEAS
    16. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
    17. Koetter, M. & Bos, J.W.B. & Heid, F. & Kolari, J.W. & Kool, C.J.M. & Porath, D., 2007. "Accounting for distress in bank mergers," Journal of Banking & Finance, Elsevier, vol. 31(10), pages 3200-3217, October.
    18. Altman, Edward I. & Haldeman, Robert G. & Narayanan, P., 1977. "ZETATM analysis A new model to identify bankruptcy risk of corporations," Journal of Banking & Finance, Elsevier, vol. 1(1), pages 29-54, June.
    19. John Krainer & Jose A. Lopez, 2003. "How might financial market information be used for supervisory purposes?," Economic Review, Federal Reserve Bank of San Francisco, pages 29-45.
    20. Anatoly Peresetsky, Alexander Karminsky, 2011. "Models for Moody’s Bank Ratings," Frontiers in Finance and Economics, SKEMA Business School, vol. 8(1), pages 88-110, April.
    21. R. Alton Gilbert & Andrew P. Meyer & Mark D. Vaughan, 2002. "Could a CAMELS downgrade model improve off-site surveillance?," Review, Federal Reserve Bank of St. Louis, vol. 84(Jan.), pages 47-63.
    22. Westgaard, Sjur & van der Wijst, Nico, 2001. "Default probabilities in a corporate bank portfolio: A logistic model approach," European Journal of Operational Research, Elsevier, vol. 135(2), pages 338-349, December.
    23. Пересецкий А.А., 2007. "Методы Оценки Вероятности Дефолта Банков," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 43(3), июль.
    24. Scott, James, 1981. "The probability of bankruptcy: A comparison of empirical predictions and theoretical models," Journal of Banking & Finance, Elsevier, vol. 5(3), pages 317-344, September.
    25. John Krainer & Jose A. Lopez, 2009. "Do supervisory rating standards change over time?," Economic Review, Federal Reserve Bank of San Francisco, pages 13-24.
    26. Karminsky, Alexandr & Peresetsky, Anatoly, 2007. "Models of Banks Ratings," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 5(1), pages 3-19.
    27. Altman, Edward I. & Marco, Giancarlo & Varetto, Franco, 1994. "Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience)," Journal of Banking & Finance, Elsevier, vol. 18(3), pages 505-529, May.
    28. Poon, Winnie P. H., 2003. "Are unsolicited credit ratings biased downward?," Journal of Banking & Finance, Elsevier, vol. 27(4), pages 593-614, April.
    29. Patrick Roy, 2013. "Is There a Difference Between Solicited and Unsolicited Bank Ratings and, If So, Why?," Journal of Financial Services Research, Springer;Western Finance Association, vol. 44(1), pages 53-86, August.
    30. 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.
    31. Martin, Daniel, 1977. "Early warning of bank failure : A logit regression approach," Journal of Banking & Finance, Elsevier, vol. 1(3), pages 249-276, November.
    32. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    33. Rebel Cole & Jeffery Gunther, 1998. "Predicting Bank Failures: A Comparison of On- and Off-Site Monitoring Systems," Journal of Financial Services Research, Springer;Western Finance Association, vol. 13(2), pages 103-117, April.
    34. Rebel A. Cole & Jeffery W. Gunther, 1995. "FIMS: a new monitoring system for banking institutions," Federal Reserve Bulletin, Board of Governors of the Federal Reserve System (U.S.), issue Jan, pages 1-15.
    35. Krainer, John & Lopez, Jose A, 2004. "Incorporating Equity Market Information into Supervisory Monitoring Models," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 36(6), pages 1043-1067, December.
    36. Espahbodi, Hassan & Espahbodi, Pouran, 2003. "Binary choice models and corporate takeover," Journal of Banking & Finance, Elsevier, vol. 27(4), pages 549-574, April.
    37. Beverly Hirtle & Jose A. Lopez, 1999. "Supervisory information and the frequency of bank examinations," Economic Policy Review, Federal Reserve Bank of New York, vol. 5(Apr), pages 1-20.
    38. Peresetsky, Anatoly, 2009. "Models for the External Support Component of Moody's Bank Ratings," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 14(2), pages 3-23.
    39. van Soest, A.H.O. & Peresetsky, A. & Karminsky, A.M., 2003. "An Analysis of Ratings of Russian Banks," Discussion Paper 2003-85, Tilburg University, Center for Economic Research.
    40. Bussiere, Matthieu & Fratzscher, Marcel, 2006. "Towards a new early warning system of financial crises," Journal of International Money and Finance, Elsevier, vol. 25(6), pages 953-973, October.
    41. Altman, Edward I. & Rijken, Herbert A., 2004. "How rating agencies achieve rating stability," Journal of Banking & Finance, Elsevier, vol. 28(11), pages 2679-2714, November.
    42. Julapa Jagtiani & James Kolari & Catharine Lemieux & G. Hwan Shin, 2003. "Early warning models for bank supervision: Simpler could be better," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 27(Q III), pages 49-60.
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    Cited by:

    1. Alexander Karminsky & Alexander Kostrov & Taras Murzenkov, 2012. "Comparison of default probability models: Russian experience," HSE Working papers WP BRP 06/FE/2012, National Research University Higher School of Economics.

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    More about this item

    Keywords

    Multinomial logit model; binary logit model; probability of default; Russian banks; money laundering; bank supervision;
    All these keywords.

    JEL classification:

    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G20 - Financial Economics - - Financial Institutions and Services - - - General

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