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Predicting Bank CAMELS and S&P Ratings: The Case of the Czech Republic

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  • Alexis Derviz
  • Jiri Podpiera

Abstract

In this paper we investigate the determinants of the movements in the long-term Standard & Poors and CAMELS bank ratings in the Czech Republic during the period when the three biggest banks, representing approximately 60% of the Czech banking sector's total assets, were privatized (i.e., the time span 1998-2001). The same list of explanatory variables corresponding to the CAMELS rating inputs employed by the Czech National Bank's banking sector regulators was examined for both ratings in order to select significant predictors among them. We employed an ordered response logit model to analyze the monthly long-run S&P rating and a panel data framework for the analysis of the quarterly CAMELS rating. The predictors for which we found significant explanatory power are: Capital Adequacy, Credit Spread, the ratio of Total Loans to Total Assets, and the Total Asset Value at Risk. Models based on these predictors exhibited a predictive accuracy of 70%. Additionally, we found that the verified variables satisfactorily predict the S&P rating one month ahead.

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Bibliographic Info

Paper provided by Czech National Bank, Research Department in its series Working Papers with number 2004/01.

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Date of creation: Jan 2004
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Handle: RePEc:cnb:wpaper:2004/01

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Keywords: Bank rating; CAMELS; ordered logit model; panel data analysis.;

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Cited by:
  1. Jan Babecky & Sofia Bauducco & Ales Bulir & Martin Cihak & Petr Jakubik & Lubos Komarek & Zlata Komarkova & Jiri Podpiera & Christian Schmieder & Laurent Weill, 2009. "CNB Economic Research Bulletin: Financial and Global Stability Issues," Occasional Publications - Edited Volumes, Czech National Bank, Research Department, edition 2, volume 7, number rb07/2 edited by Jan Babecky & Jan Frait.
  2. Evzen Kocenda & Martin Vojtek, 2011. "Default Predictors in Retail Credit Scoring: Evidence from Czech Banking Data," William Davidson Institute Working Papers Series wp1015, William Davidson Institute at the University of Michigan.
  3. Radu Muntean, 2009. "Early Warning Models for Banking Supervision in Romania," Advances in Economic and Financial Research - DOFIN Working Paper Series 39, Bucharest University of Economics, Center for Advanced Research in Finance and Banking - CARFIB.
  4. Anca Podpiera & Jiri Podpiera, 2005. "Deteriorating Cost Efficiency in Commercial Banks Signals an Increasing Risk of Failure," Working Papers 2005/06, Czech National Bank, Research Department.
  5. Alena Bicakova & Kamil Dybczak & Ales Krejdl & Jiri Slacalek & Michal Slavik, 2007. "CNB Economic Research Bulletin: Fiscal Policy and its Sustainability," Occasional Publications - Edited Volumes, Czech National Bank, Research Department, edition 2, volume 5, number rb05/2 edited by Ian Babetskii & Vladimir Bezdek.
  6. Fuad Aleskerov & V. Belousova & M. Serdyuk & V. Solodkov, 2008. "Dynamic Analysis of the Behavioural Patterns of the Largest Commercial Banks in the Russian Federation," ICER Working Papers - Applied Mathematics Series 12-2008, ICER - International Centre for Economic Research.
  7. Juraj Antal & Frantisek Brazdik & Jan Bruha & Martin Fukac & Adrian Pagan & Jiri Podpiera & Stanislav Polak & Yuliya Rychalovska, 2008. "CNB Economic Research Bulletin: Inflation Targeting and DSGE Models," Occasional Publications - Edited Volumes, Czech National Bank, Research Department, edition 2, volume 6, number rb06/2 edited by Juraj Antal & Jan Babecky.

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