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Cash Flow at Risk Assessment for the Banking Sector of Georgia


  • Tamar Mdivnishvili

    (Macroeconomic Research Division, National Bank of Georgia)

  • Shalva Mkhatrishvili

    (Macroeconomic Research Division, National Bank of Georgia)

  • Davit Tutberidze

    (Macroeconomic Research Division, National Bank of Georgia)


The aim of our study is to estimate the distribution of the profitability of the Georgian banking sector, in order to determine liquidity risk, for which we use Cash Flow at Risk (CFaR). In our estimation, we took into account possible nonlinear impact of monetary policy on banks' profit, which allows us also to estimate the neutral interest rate. According to our results, the relationship between bank profits on the one hand and short- and long-term interest rates on another is nonlinear indeed. In addition to median estimates, we also use quantile regression, which allows us to estimate tail risks. According to the results in a "normal" (median) situation, when interest rates are below neutral rate, decreasing policy rate reduces banks' profits, while if banks suffer from low liquidity (on a lower percentile), reduction of policy rate increases banks' profits. According to the quantile regression output, the relationship between bank profitability and yield curve is asymmetric. The results also show the dependence of bank liquidity risk on other macro variables. Estimates are made for the entire banking sector as well as for the two largest banks in Georgia.

Suggested Citation

  • Tamar Mdivnishvili & Shalva Mkhatrishvili & Davit Tutberidze, 2020. "Cash Flow at Risk Assessment for the Banking Sector of Georgia," NBG Working Papers 03/2020, National Bank of Georgia.
  • Handle: RePEc:aez:wpaper:03/2020

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    References listed on IDEAS

    1. Leonardo Gambacorta, 2009. "Monetary policy and the risk-taking channel," BIS Quarterly Review, Bank for International Settlements, December.
    2. Emanuel Kohlscheen & Andrés Murcia Pabón & Juan Contreras, 2018. "Determinants of bank profitability in emerging markets," BIS Working Papers 686, Bank for International Settlements.
    3. Ms. TengTeng Xu & Kun Hu & Mr. Udaibir S Das, 2019. "Bank Profitability and Financial Stability," IMF Working Papers 2019/005, International Monetary Fund.
    4. Klumpes, Paul & Welch, Peter & Reibel, Andres, 2009. "Bank cash flows – a source of new insight?," Journal of Financial Transformation, Capco Institute, vol. 26, pages 69-78.
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    More about this item


    Quantile regression; Forecasting; Monetary policy; Bank profitability; CFaR;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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