IDEAS home Printed from https://ideas.repec.org/p/cnb/wpaper/2019-9.html
   My bibliography  Save this paper

How to Improve the Model Selection Procedure in a Stress-testing Framework

Author

Listed:
  • Jiri Panos
  • Petr Polak

Abstract

This paper aims to introduce a contemporary, computing-power-driven approach to econometric modeling in a stress-testing framework. The presented approach explicitly takes into account model uncertainty of satellite models used for projecting forward paths of financial variables employing the constrained Bayesian model averaging (BMA) technique. The constrained BMA technique allows for selecting models with reasonably severe but plausible trajectories conditional on given macro-financial scenarios. It also ensures that the modeling is conducted in a sufficiently robust and prudential manner despite the limited time-series length for the explained and/or explanatory variables.

Suggested Citation

  • Jiri Panos & Petr Polak, 2019. "How to Improve the Model Selection Procedure in a Stress-testing Framework," Working Papers 2019/9, Czech National Bank.
    • Handle: RePEc:cnb:wpaper:2019/9
    as

    Download full text from publisher

    File URL: https://www.cnb.cz/export/sites/cnb/en/economic-research/.galleries/research_publications/cnb_wp/cnbwp_2019_09.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Louzis, Dimitrios P. & Vouldis, Angelos T. & Metaxas, Vasilios L., 2012. "Macroeconomic and bank-specific determinants of non-performing loans in Greece: A comparative study of mortgage, business and consumer loan portfolios," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 1012-1027.
    2. Adam Gersl & Petr Jakubik & Tomas Konecny & Jakub Seidler, 2012. "Dynamic Stress Testing: The Framework for Testing Banking Sector Resilience Used by the Czech National Bank," Working Papers 2012/11, Czech National Bank.
    3. Adam Kucera & Milan Szabo, 2019. "Estimating the neutral Czech government bond yield curve," Occasional Publications - Chapters in Edited Volumes,, Czech National Bank.
    4. Antonella Foglia, 2009. "Stress Testing Credit Risk: A Survey of Authorities' Aproaches," International Journal of Central Banking, International Journal of Central Banking, vol. 5(3), pages 9-45, September.
    5. Pavel Kapinos & Oscar A. Mitnik, 2016. "A Top-down Approach to Stress-testing Banks," Journal of Financial Services Research, Springer;Western Finance Association, vol. 49(2), pages 229-264, June.
    6. Siemsen, Thomas & Vilsmeier, Johannes, 2017. "A stress test framework for the German residential mortgage market: Methodology and application," Discussion Papers 37/2017, Deutsche Bundesbank.
    7. Hirtle, Beverly & Kovner, Anna & Vickery, James & Bhanot, Meru, 2016. "Assessing financial stability: The Capital and Loss Assessment under Stress Scenarios (CLASS) model," Journal of Banking & Finance, Elsevier, vol. 69(S1), pages 35-55.
    8. Thomas Breuer & Martin Jandacka & Klaus Rheinberger & Martin Summer, 2009. "How to Find Plausible, Severe and Useful Stress Scenarios," International Journal of Central Banking, International Journal of Central Banking, vol. 5(3), pages 205-224, September.
    9. Mr. Dale F Gray, 2013. "Modeling Banking, Sovereign, and Macro Risk in a CCA Global VAR," IMF Working Papers 2013/218, International Monetary Fund.
    10. 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.
    11. Sorge, Marco & Virolainen, Kimmo, 2006. "A comparative analysis of macro stress-testing methodologies with application to Finland," Journal of Financial Stability, Elsevier, vol. 2(2), pages 113-151, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. David Mazáček & Jiří Panoš, 2022. "Key determinants of new residential real estate prices in Prague," FFA Working Papers 5.002, Prague University of Economics and Business, revised 11 Apr 2023.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Marco Gross & Javier Población, 2019. "Implications of Model Uncertainty for Bank Stress Testing," Journal of Financial Services Research, Springer;Western Finance Association, vol. 55(1), pages 31-58, February.
    2. Vazquez, Francisco & Tabak, Benjamin M. & Souto, Marcos, 2012. "A macro stress test model of credit risk for the Brazilian banking sector," Journal of Financial Stability, Elsevier, vol. 8(2), pages 69-83.
    3. di Mauro, Filippo & Dées, Stéphane & Al-Haschimi, Alexander & Jančoková, Martina, 2014. "Linking distress of financial institutions to macrofinancial shocks," Working Paper Series 1749, European Central Bank.
    4. Busch, Ramona & Koziol, Philipp & Mitrovic, Marc, 2018. "Many a little makes a mickle: Stress testing small and medium-sized German banks," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 237-253.
    5. Kolari, James W. & López-Iturriaga, Félix J. & Sanz, Ivan Pastor, 2019. "Predicting European bank stress tests: Survival of the fittest," Global Finance Journal, Elsevier, vol. 39(C), pages 44-57.
    6. Ferrari, Stijn & Van Roy, Patrick & Vespro, Cristina, 2021. "Sensitivity of credit risk stress test results: Modelling issues with an application to Belgium," Journal of Financial Stability, Elsevier, vol. 52(C).
    7. Paul Glasserman & Mike Li, 2022. "Should Bank Stress Tests Be Fair?," Papers 2207.13319, arXiv.org, revised May 2023.
    8. Dua, Pami & Kapur, Hema, 2018. "Macro stress testing and resilience assessment of Indian banking," Journal of Policy Modeling, Elsevier, vol. 40(2), pages 452-475.
    9. Gross, Marco & Población García, Francisco Javier, 2015. "A false sense of security in applying handpicked equations for stress test purposes," Working Paper Series 1845, European Central Bank.
    10. Patrick Van Roy & Stijn Ferrari & Cristina Vespro, 2018. "Sensitivity of credit risk stress test results: Modelling issues with an application to Belgium," Working Paper Research 338, National Bank of Belgium.
    11. Kanas, Angelos & Molyneux, Philip, 2018. "Macro stress testing the U.S. banking system," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 54(C), pages 204-227.
    12. Schechtman, Ricardo & Gaglianone, Wagner Piazza, 2012. "Macro stress testing of credit risk focused on the tails," Journal of Financial Stability, Elsevier, vol. 8(3), pages 174-192.
    13. Darne, O. & Levy-Rueff, O. & Pop, A., 2013. "Calibrating Initial Shocks in Bank Stress Test Scenarios: An Outlier Detection Based Approach," Working papers 426, Banque de France.
    14. Siemsen, Thomas & Vilsmeier, Johannes, 2018. "On a quest for robustness: About model risk, randomness and discretion in credit risk stress tests," Discussion Papers 31/2018, Deutsche Bundesbank.
    15. Chau H. A. Le, 2016. "Macro-financial linkages and bank behaviour: evidence from the second-round effects of the global financial crisis on East Asia," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 6(3), pages 365-387, December.
    16. Stijn Ferrari & Patrick Van Roy & Cristina Vespro, 2011. "Stress testing credit risk: modelling issues," Financial Stability Review, National Bank of Belgium, vol. 9(1), pages 105-120, June.
    17. Busch, Ramona & Koziol, Philipp & Mitrovic, Marc, 2015. "Many a little makes a mickle: Macro portfolio stress test for small and medium-sized German banks," Discussion Papers 23/2015, Deutsche Bundesbank.
    18. Alexander Chudik & M. Hashem Pesaran, 2016. "Theory And Practice Of Gvar Modelling," Journal of Economic Surveys, Wiley Blackwell, vol. 30(1), pages 165-197, February.
    19. Michael W. McCracken & Joseph T. McGillicuddy, 2019. "An empirical investigation of direct and iterated multistep conditional forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(2), pages 181-204, March.
    20. 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.

    More about this item

    Keywords

    Bayesian model averaging; model selection; model uncertainty; probability of default; stress testing;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cnb:wpaper:2019/9. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Jan Babecky (email available below). General contact details of provider: https://edirc.repec.org/data/cnbgvcz.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.