Banks in trouble? A Early Warning System for the Prevention of Banking Crisis
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Published
18-09-2018
Ana Fernández Sainz
Felipe Llaugel
Abstract
The regulatory and supervisory financial authorities have tried various methods to find an effective procedure in developing an early warning system of banking crises. Logistic regression models have been used but have shown some weaknesses, so we need new and better methods. The banking crisis occurred in the Dominican Republic between 2002 and 2004 has been used to compare the effectiveness of the logistic regression method over the use of Support Vector Machines (SVM) for the detection of banking crisis. In the analysis 30 financial indicators are used to determine which ones are most appropriate to build a model able to classify banks. In this context, the SVM method produced better results than logistic regression, in detecting problem banks and contradict the findings of other studies that ask about the ineffectiveness of the financial indicators to identify banking crises in emerging economies.
How to Cite
Fernández Sainz, A., & Llaugel, F. (2018). Banks in trouble? A Early Warning System for the Prevention of Banking Crisis. Cuadernos De Gestión, 11(2), 149–168. https://doi.org/10.5295/cdg.100239af
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Keywords
banking crisis, logistic regression, support vector machines
References
ABE, S. (2005): Support Vector Machines for Pattern Classification. Springer-Verlag London Limited.
AHUMADA, A. y BUDNEVICH, C. (2001): “Some Measures of Financial Fragility in the Chilean Banking System: an Early Warning Indicator Application”. Banco Central de Chile, Working Paper # 117.
ALTMAN, E.I. (1968): “Financial ratios, discriminant analysis and the prediction of corporate failure”. Journal of Finance.
ATLE B.S., y HEXEBERG, B. (1994): “Early Warning Indicators for Norwegian Banks: A Logit Analysis of the Experiences from the Banking Crisis”. Oslo, Norway: Norges Bank Research Department.
BELL, J. y PAIN, D. (2000): “Leading Indicator Models of Banking Crises: a Critical Review”. Financial Stability Review, Bank of England.
BERG, A. y PATTILLO, C. (1999): “Predicting Currency Crises: The Indicators Approach and an Alternative”. Journal of International Money and Finance.
BUSSIERE, M. y FRATZSCHER, M. (2002): “Toward a new Early Warning System of Financial Crises”. European Central Bank. Working Paper No. 145.
COLE, R. A. (1995): “FIMS: A New Monitoring System for Banking Institutions”. Federal Reserve Bulletin.
CRISTIANINI, N. y SHAWE-TAYLOR, J. (2000): “An Introduction to Support Vector Machines and other Kernel-based Learning Methods”. Cambridge University Press. Cambridge. UK.
DEMIRGÜC-KUNT, A. (1989). “Deposit-Institution Failures: A Review of Empirical Literature.” Federal Reserve Bank of Cleveland, Economic Review.
DEMIRGÜC-KUNT, A., y DETRAGIACHE, E. (1998): “The Determinants of Banking Crises in Developing and Developed Countries”. International Monetary Fund Staff Paper.
FONDO MONETARIO INTERNACIONAL (2006): Indicadores de solidez financiera. Guía de Compilación.
GAYTÁN, A. y JOHNSON, C.A. (2002): “A Review of the Literature on Early Warning Systems for Banking Crises”. Working Paper 183, Central Bank of Chile.
GONZÁLEZ-HERMOSILLO, B.; PAZARBASIOGLU, C. y BILLINGS, R. (1996): “Banking System Fragility: Likelihood versus Timing of Failure: An Application to the Mexican Financial Crisis”. IMF Working Paper. Washington: International Monetary Fund
HARDY, D. y PAZARBASIOGLU, C. (1999): “Determinant and Leading Indicators of Banking Crisis: Further Evidence”. International Monetary Fund Staff Papers.
JONES, D. S. y KUESTER-KING, K. (1995): “The Implementation of Prompt Corrective Action: An Assessment”. Journal of Banking and Finance.
KAMIN, S. y BABSON, O. (1999): “The Contribution of Domestic and External Factors to Latin American Devaluation Crises: An Early Warning Systems Approach”, Board of Governors of the Federal Reserve System, International Finance Discussion Papers.
KAMIN, S.; SCHINDLER, J. y SAMUEL, S. (2001): “The Contribution of Domestic and External Factors to Emerging Market Devaluation Crises: An Early Warning Systems Approach”, International Finance Working Paper, Board of Governors of the Federal Reserve System.
KAMINSKY, G. (1999): “Currency and Banking Crises: The Early Warning of Distress”. IMF Working Paper.
KAMINSKY, G. y REINHART, C.M. (1998): “Financial Crises in Asia and Latin America: Then and Now”. American Economic Review, Papers and Proceedings.
KAMINSKY, G. y REINHART, C.M. (1999): “The Twin Crises: the Causes of Banking and Balance-of-payments Problems”. American Economic Review.
KING, T.; NUXOLL, D. y YEAGER, T. (2005): “Are the Causes of Banking Distress Changing? Can Researchers Keep Up?”. FDIC Center for Financial Research Working Paper.
LLAUGEL, F. 2008. “Improving Logit Models using Bootstrapping: A Banking Crisis Prevention Application”. Mimeo.
MANGASARIAN, O. L. y MUSICANT, D. R. (2001): “Lagrangian Support Vector Machines”. Journal of Machine Learning Research.
MARTIN, D. (1977): “Early Warning of Bank Failure: A Logit Regression Approach”. Journal of Banking and Finance.
MIN, J. y LEE, Y. (2005): “Bankruptcy Prediction using Support Vector Machine with optimal choice of kernel function parameters”. Expert Systems and Applications.
MONTAS, J.T. (2009): La Crisis Bancaria del 2003, Como y por qué. Editora Alfa y Omega CxA. Santo Domingo.
ROJAS-SUAREZ, L. (2001): “Rating Banks in Emerging Markets: What Credit Rating Agencies Should Learn from Financial Indicators”. Working Paper, Peterson Institute for International Economics.
SAHAJWALA, R. y VAN DEN BERGH, P. (2000): “Supervisory Risk Assessment and Early Warning System”. Basel Committee on Banking Supervision Working Papers.
SCHNATZ, B. (1998): “Macroeconomic Determinants of currency turbulences in emerging markets”. Discussion paper, Economic Research Group of the Deutsche Bundesbank.
SCHNATZ, B. (1999): “The Sudden Freeze of the Asian Miracle: The Role of Macroeconomic Fundamentals”. Asia Pacific Journal of Finance.
SHU-XIA, L. y WANG, X. (2004): “A Comparison among four SVM Classification methods: LSVM, NLSVM, SSVM and NSVM”. Proceeding of the Third International Conference on Machine Learning on Cybernetics.
TODOROV, V.K, NEYKOV, N.M., and NEYTCHEV, R.V. (1999). Robust Selection of Variables in the Discriminant Analysis based on MVE and MCD estimators. Proceedings of International Computational Statistics 9th Symp. 193-198.
VAPNIK, N.V. (1998): Statistical Learning Theory. John Wiley and Sons, Inc. New York.
WHALEN, G. y THOMPSON, J.B. (1989): “Using Financial Data to Identify Changes in Bank Condition”. Federal Reserve Bank of Cleveland Economic Review.
WONG, J.; WONG, E. y LEUNG, P. (2007): “A Leading Indicator Model of Banking Distress an Early Warning System for Hong Kong and other EMEAP economies”. Hong Kong Monetary Authority, Working Paper.
YI, P. L.; QIU, D. F. y BAO, P. (2007): “A Study of Financial Distress Prediction of Listed Corporations with Support Vector Machines Model”. Proceedings of 2007 IEEE International Conference on Grey Systems and Intelligent Services.
AHUMADA, A. y BUDNEVICH, C. (2001): “Some Measures of Financial Fragility in the Chilean Banking System: an Early Warning Indicator Application”. Banco Central de Chile, Working Paper # 117.
ALTMAN, E.I. (1968): “Financial ratios, discriminant analysis and the prediction of corporate failure”. Journal of Finance.
ATLE B.S., y HEXEBERG, B. (1994): “Early Warning Indicators for Norwegian Banks: A Logit Analysis of the Experiences from the Banking Crisis”. Oslo, Norway: Norges Bank Research Department.
BELL, J. y PAIN, D. (2000): “Leading Indicator Models of Banking Crises: a Critical Review”. Financial Stability Review, Bank of England.
BERG, A. y PATTILLO, C. (1999): “Predicting Currency Crises: The Indicators Approach and an Alternative”. Journal of International Money and Finance.
BUSSIERE, M. y FRATZSCHER, M. (2002): “Toward a new Early Warning System of Financial Crises”. European Central Bank. Working Paper No. 145.
COLE, R. A. (1995): “FIMS: A New Monitoring System for Banking Institutions”. Federal Reserve Bulletin.
CRISTIANINI, N. y SHAWE-TAYLOR, J. (2000): “An Introduction to Support Vector Machines and other Kernel-based Learning Methods”. Cambridge University Press. Cambridge. UK.
DEMIRGÜC-KUNT, A. (1989). “Deposit-Institution Failures: A Review of Empirical Literature.” Federal Reserve Bank of Cleveland, Economic Review.
DEMIRGÜC-KUNT, A., y DETRAGIACHE, E. (1998): “The Determinants of Banking Crises in Developing and Developed Countries”. International Monetary Fund Staff Paper.
FONDO MONETARIO INTERNACIONAL (2006): Indicadores de solidez financiera. Guía de Compilación.
GAYTÁN, A. y JOHNSON, C.A. (2002): “A Review of the Literature on Early Warning Systems for Banking Crises”. Working Paper 183, Central Bank of Chile.
GONZÁLEZ-HERMOSILLO, B.; PAZARBASIOGLU, C. y BILLINGS, R. (1996): “Banking System Fragility: Likelihood versus Timing of Failure: An Application to the Mexican Financial Crisis”. IMF Working Paper. Washington: International Monetary Fund
HARDY, D. y PAZARBASIOGLU, C. (1999): “Determinant and Leading Indicators of Banking Crisis: Further Evidence”. International Monetary Fund Staff Papers.
JONES, D. S. y KUESTER-KING, K. (1995): “The Implementation of Prompt Corrective Action: An Assessment”. Journal of Banking and Finance.
KAMIN, S. y BABSON, O. (1999): “The Contribution of Domestic and External Factors to Latin American Devaluation Crises: An Early Warning Systems Approach”, Board of Governors of the Federal Reserve System, International Finance Discussion Papers.
KAMIN, S.; SCHINDLER, J. y SAMUEL, S. (2001): “The Contribution of Domestic and External Factors to Emerging Market Devaluation Crises: An Early Warning Systems Approach”, International Finance Working Paper, Board of Governors of the Federal Reserve System.
KAMINSKY, G. (1999): “Currency and Banking Crises: The Early Warning of Distress”. IMF Working Paper.
KAMINSKY, G. y REINHART, C.M. (1998): “Financial Crises in Asia and Latin America: Then and Now”. American Economic Review, Papers and Proceedings.
KAMINSKY, G. y REINHART, C.M. (1999): “The Twin Crises: the Causes of Banking and Balance-of-payments Problems”. American Economic Review.
KING, T.; NUXOLL, D. y YEAGER, T. (2005): “Are the Causes of Banking Distress Changing? Can Researchers Keep Up?”. FDIC Center for Financial Research Working Paper.
LLAUGEL, F. 2008. “Improving Logit Models using Bootstrapping: A Banking Crisis Prevention Application”. Mimeo.
MANGASARIAN, O. L. y MUSICANT, D. R. (2001): “Lagrangian Support Vector Machines”. Journal of Machine Learning Research.
MARTIN, D. (1977): “Early Warning of Bank Failure: A Logit Regression Approach”. Journal of Banking and Finance.
MIN, J. y LEE, Y. (2005): “Bankruptcy Prediction using Support Vector Machine with optimal choice of kernel function parameters”. Expert Systems and Applications.
MONTAS, J.T. (2009): La Crisis Bancaria del 2003, Como y por qué. Editora Alfa y Omega CxA. Santo Domingo.
ROJAS-SUAREZ, L. (2001): “Rating Banks in Emerging Markets: What Credit Rating Agencies Should Learn from Financial Indicators”. Working Paper, Peterson Institute for International Economics.
SAHAJWALA, R. y VAN DEN BERGH, P. (2000): “Supervisory Risk Assessment and Early Warning System”. Basel Committee on Banking Supervision Working Papers.
SCHNATZ, B. (1998): “Macroeconomic Determinants of currency turbulences in emerging markets”. Discussion paper, Economic Research Group of the Deutsche Bundesbank.
SCHNATZ, B. (1999): “The Sudden Freeze of the Asian Miracle: The Role of Macroeconomic Fundamentals”. Asia Pacific Journal of Finance.
SHU-XIA, L. y WANG, X. (2004): “A Comparison among four SVM Classification methods: LSVM, NLSVM, SSVM and NSVM”. Proceeding of the Third International Conference on Machine Learning on Cybernetics.
TODOROV, V.K, NEYKOV, N.M., and NEYTCHEV, R.V. (1999). Robust Selection of Variables in the Discriminant Analysis based on MVE and MCD estimators. Proceedings of International Computational Statistics 9th Symp. 193-198.
VAPNIK, N.V. (1998): Statistical Learning Theory. John Wiley and Sons, Inc. New York.
WHALEN, G. y THOMPSON, J.B. (1989): “Using Financial Data to Identify Changes in Bank Condition”. Federal Reserve Bank of Cleveland Economic Review.
WONG, J.; WONG, E. y LEUNG, P. (2007): “A Leading Indicator Model of Banking Distress an Early Warning System for Hong Kong and other EMEAP economies”. Hong Kong Monetary Authority, Working Paper.
YI, P. L.; QIU, D. F. y BAO, P. (2007): “A Study of Financial Distress Prediction of Listed Corporations with Support Vector Machines Model”. Proceedings of 2007 IEEE International Conference on Grey Systems and Intelligent Services.
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