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Stress Testing of the Montenegrin Banking System with Aggregated and Bank-Specific Data

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  • Sanja Vuković

    () (Hipotekarna bank AD Podgorica)

Abstract

There are many different approaches to the process of stress testing and two of them will be investigated in this paper. The first one is a stress test performed on aggregated data i.e. the banking system as a whole. The variable of interest in both exercises is the Loan Loss Provision ratio (hereinafter: the LLP). The main goal of the thesis is to find an answer to the following question: what are the macroeconomic variables that influence LLP the most and how will LLP, as a variable of interest, behave in a situation when all these variables were to experience negative performance at the same time? The resilience of the banking system to such scenario will be tested through the capital adequacy ratio. In order to find out more about the management practices of banks, microlevel data on banks were also used in the analysis. The focus was to see which of the variables are able to explain the LLP ratio for each bank individually and how is this information helpful for possible improvements in the banking sector. The relations between these variables will be able to explain some of the banks’ losses and some of the banks’ practices regarding credit activities. The analysis there will provide for some recommendations for the banks but also for the Central Bank and its way to influence the practices in the banking sector.

Suggested Citation

  • Sanja Vuković, 2014. "Stress Testing of the Montenegrin Banking System with Aggregated and Bank-Specific Data," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 3(2), pages 85-119.
  • Handle: RePEc:cbk:journl:v:3:y:2014:i:2:p:85-119
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    File URL: http://www.cbcg.me/repec/cbk/journl/vol3no2-5.pdf
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    References listed on IDEAS

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    1. Beck, Thorsten & Demirguc-Kunt, Asli & Maksimovic, Vojislav, 2004. "Bank Competition and Access to Finance: International Evidence," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 36(3), pages 627-648, June.
    2. Robert G. King & Ross Levine, 1993. "Finance and Growth: Schumpeter Might Be Right," The Quarterly Journal of Economics, Oxford University Press, vol. 108(3), pages 717-737.
    3. Masten, Arjana Brezigar & Coricelli, Fabrizio & Masten, Igor, 2008. "Non-linear growth effects of financial development: Does financial integration matter?," Journal of International Money and Finance, Elsevier, vol. 27(2), pages 295-313, March.
    4. Merja Festiæ & Jani Bekõ, 2008. "The Banking Sector and Macroeconomic Performance in Central European Economies," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 58(03-04), pages 131-151, May.
    5. Stephen Cecchetti & Enisse Kharroubi, 2012. "Reassessing the impact of finance on growth," BIS Working Papers 381, Bank for International Settlements.
    6. Beck, Thorsten & Levine, Ross & Loayza, Norman, 2000. "Finance and the sources of growth," Journal of Financial Economics, Elsevier, vol. 58(1-2), pages 261-300.
    7. Lucas, Robert Jr., 1988. "On the mechanics of economic development," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 3-42, July.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    stress testing; loan loss provisions; estimation; credit risk;

    JEL classification:

    • E50 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - General
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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