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Experience in Developing Early Warning System for Financial Crises and the Forecast of Russian Banking Sector Dynamic in 2012

Author Info

  • Solntsev, O.

    (Center for Macroeconomic Analysis and Short-Term Forecasting (CMASF), Moscow, Russia)

  • Mamonov, M.

    (Center for Macroeconomic Analysis and Short-Term Forecasting (CMASF), Moscow, Russia)

  • Pestova, A.

    (Center for Macroeconomic Analysis and Short-Term Forecasting (CMASF), Moscow, Russia)

  • Magomedova, Z.

    (Center for Macroeconomic Analysis and Short-Term Forecasting (CMASF), Moscow, Russia)

Abstract

The article summarizes the key results of researches in the field of early warning systems for financial crises, conducted by the Center for Macroeconomic Analysis and Short-Term Forecasting (CMASF) since 2005. The proposed early warning system consists of three major blocks: the leading indicators of certain types of risks and the composite leading indicator of a systemic banking crisis; the medium-term scenario forecasting of key macroeconomic and financial indicators; stress testing of credit and liquidity risks of banks. On the basis of this early warning system we estimate the risks of financial crisis and some kinds of systemic risks in the different scenarios for the Russian economy in 2012. The analysis, in particular, revealed a sensitivity threshold of the domestic financial sector to changes in the world oil prices. Furthermore, it was found that the greatest destabilizing effect on the Russian financial sector may be caused by systemic credit risk.

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File URL: http://www.econorus.org/repec/journl/2011-12-41-76r.pdf
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Article provided by New Economic Association in its journal Journal of the New Economic Association.

Volume (Year): (2011)
Issue (Month): 12 ()
Pages: 41-76

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Handle: RePEc:nea:journl:y:2011:i:12:p:41-76
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Keywords: systemic financial crises; credit risks; liquidity risks; currency risks; early warning system; leading indicators; stress testing;

Find related papers by JEL classification:

  • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
  • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
  • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
  • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
  • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
  • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
  • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
  • G01 - Financial Economics - - General - - - Financial Crises

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Cited by:

  1. Mamonov, Mikhail, 2012. "The impact of market power of Russian banks on their credit risk tolerance: A panel study," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 28(4), pages 85-112.

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