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A combined statistical framework for forecasting default rates of Greek Financial Institutions' credit portfolios

Author

Listed:
  • Anastasios Petropoulos

    (Bank of Greece)

  • Vasilis Siakoulis

    (Bank of Greece)

  • Dionysios Mylonas

    (Bank of Greece)

  • Aristotelis Klamargias

    (Bank of Greece)

Abstract
Credit risk modeling remains an important research topic both for financial institutions and the academic community due to its significant contribution to the issue of a bank’s capital adequacy. In this paper we build macro models for the default rates of Greek bank’s loan portfolios. Modeling is performed at two levels: First we use common techniques: regime switching regression, Bayesian regression averaging and linear regression; subsequently we combine the forecasts of the three statistical techniques. This results in increasing performance accuracy and minimizing model risk. Our main goal is twofold: First we attempt to investigate the determinants and the sensitivities of default rates in the Greek banking system where Non Performing Loans (NPLs) have risen sharply due to the sovereign debt crisis which led to a decrease in GDP from 2007 to 2016 of 25%. Secondly, the suggested statistical models can serve as the basis of projecting Greek portfolio dynamics under various macro scenarios. We find that dynamic forecasting combinations exhibit higher predictive accuracy than individual methods. This may provide practitioners with significant insight and policy tools for the banking supervision division in order to enhance monitoring efficiency and support informed decision making.

Suggested Citation

  • Anastasios Petropoulos & Vasilis Siakoulis & Dionysios Mylonas & Aristotelis Klamargias, 2018. "A combined statistical framework for forecasting default rates of Greek Financial Institutions' credit portfolios," Working Papers 243, Bank of Greece.
    • Handle: RePEc:bog:wpaper:243
    as

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    References listed on IDEAS

    as
    1. Stefan Kerbl & Michael Sigmund, 2011. "What Drives Aggregate Credit Risk?," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 22, pages 72-87.
    2. Jacob A. Mincer & Victor Zarnowitz, 1969. "The Evaluation of Economic Forecasts," NBER Chapters, in: Economic Forecasts and Expectations: Analysis of Forecasting Behavior and Performance, pages 3-46, National Bureau of Economic Research, Inc.
    3. Fernandez, Carmen & Ley, Eduardo & Steel, Mark F. J., 2001. "Benchmark priors for Bayesian model averaging," Journal of Econometrics, Elsevier, vol. 100(2), pages 381-427, February.
    4. Castro, Vítor, 2013. "Macroeconomic determinants of the credit risk in the banking system: The case of the GIPSI," Economic Modelling, Elsevier, vol. 31(C), pages 672-683.
    5. Vasilis Siakoulis, 2017. "Fiscal policy effects on non-performing loan formation," Working Papers 224, Bank of Greece.
    6. repec:onb:oenbwp:y::i:79:b:1 is not listed on IDEAS
    7. D Rösch & H Scheule, 2014. "Forecasting probabilities of default and loss rates given default in the presence of selection," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(3), pages 393-407, March.
    8. Helmut Elsinger & Alfred Lehar & Martin Summer, 2006. "Risk Assessment for Banking Systems," Management Science, INFORMS, vol. 52(9), pages 1301-1314, September.
    9. Ley, Eduardo & Steel, Mark F. J., 2007. "On the effect of prior assumptions in Bayesian model averaging with applications to growth regression," Policy Research Working Paper Series 4238, The World Bank.
    10. Konrad Banachewicz & André Lucas & Aad van der Vaart, 2008. "Modelling Portfolio Defaults Using Hidden Markov Models with Covariates," Econometrics Journal, Royal Economic Society, vol. 11(1), pages 155-171, March.
    11. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    12. Claus Puhr & Reinhardt Seliger & Michael Sigmund, 2012. "Contagiousness and Vulnerability in the Austrian Interbank Market," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 24, pages 62-78.
    13. Castrén, Olli & Dées, Stéphane & Zaher, Fadi, 2010. "Stress-testing euro area corporate default probabilities using a global macroeconomic model," Journal of Financial Stability, Elsevier, vol. 6(2), pages 64-78, June.
    14. Mr. Christian Schmieder & Maher Hasan & Mr. Claus Puhr, 2011. "Next Generation Balance Sheet Stress Testing," IMF Working Papers 2011/083, International Monetary Fund.
    15. Bellotti, Tony & Crook, Jonathan, 2013. "Forecasting and stress testing credit card default using dynamic models," International Journal of Forecasting, Elsevier, vol. 29(4), pages 563-574.
    16. Tony Bellotti & Jonathan Crook, 2014. "Retail credit stress testing using a discrete hazard model with macroeconomic factors," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(3), pages 340-350, March.
    17. Martin Feldkircher & Gerhard Fenz & Robert Ferstl & Gerald Krenn & Benjamin Neudorfer & Claus Puhr & Thomas Reininger & Stefan W. Schmitz & Martin Schneider & Christoph Siebenbrunner & Michael Sigmund, 2013. "ARNIE in Action: The 2013 FSAP Stress Tests for the Austrian Banking System," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 26, pages 100-118.
    18. Gibson, Heather D. & Palivos, Theodore & Tavlas, George S., 2014. "The Crisis in the Euro Area: An Analytic Overview," Journal of Macroeconomics, Elsevier, vol. 39(PB), pages 233-239.
    19. Muller, Ulrich K., 2005. "Size and power of tests of stationarity in highly autocorrelated time series," Journal of Econometrics, Elsevier, vol. 128(2), pages 195-213, October.
    20. Dendramis, Y. & Tzavalis, E. & Adraktas, G., 2018. "Credit risk modelling under recessionary and financially distressed conditions," Journal of Banking & Finance, Elsevier, vol. 91(C), pages 160-175.
    21. Mark W. Watson & James H. Stock, 2004. "Combination forecasts of output growth in a seven-country data set," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(6), pages 405-430.
    22. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    23. Henry, Jérôme & Zimmermann, Maik & Leber, Miha & Kolb, Markus & Grodzicki, Maciej & Amzallag, Adrien & Vouldis, Angelos & Hałaj, Grzegorz & Pancaro, Cosimo & Gross, Marco & Baudino, Patrizia & Sydow, , 2013. "A macro stress testing framework for assessing systemic risks in the banking sector," Occasional Paper Series 152, European Central Bank.
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    Citations

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    Cited by:

    1. Pinelopi Zioutou & Dimitris Sideris, 2018. "The energy sector: developments and prospects," Economic Bulletin, Bank of Greece, issue 47, pages 57-73, July.
    2. Zacharias Bragoudakis, 2018. "Are the price adjustments asymmetric in basic food categories? The case of the Greek food market," Economic Bulletin, Bank of Greece, issue 47, pages 75-91, July.
    3. Melina Vasardani & Dimitra Dimitropoulou, 2018. "The utilisation of EU structural funds in Greece," Economic Bulletin, Bank of Greece, issue 47, pages 31-55, July.
    4. Hiona Balfoussia & Dimitris Papageorgiou, 2018. "Real and financial cycles in the Greek economy," Economic Bulletin, Bank of Greece, issue 47, pages 7-30, July.
    5. Wang, Zheqi & Crook, Jonathan & Andreeva, Galina, 2020. "Reducing estimation risk using a Bayesian posterior distribution approach: Application to stress testing mortgage loan default," European Journal of Operational Research, Elsevier, vol. 287(2), pages 725-738.
    6. Panagiotis Lazaris & Anastasios Petropoulos & Vasileios Siakoulis & Evangelos Stavroulakis & Nikolaos Vlachogiannakis, 2021. "Interest rate pass through in the deposit and loan products provided by Greek banks," Working Papers 287, Bank of Greece.

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    More about this item

    Keywords

    Forecasting Default Rates; Forecast Combination; Stress Testing;
    All these keywords.

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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