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Distribution of credit-risk concentration in particular sectors of the economy, and economic capital before and during the COVID-19 pandemic

Author

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  • Natalia Nehrebecka

    (University of Warsaw
    National Bank of Poland)

Abstract

The aim of the work underpinning this paper has been to track the evolution of tail risk in banks’ NPL portfolios present under normal and worst conditions (before and during the pandemic of COVID-19), and to estimate the impact of sector concentration risk on amounts of economic capital. Results further allowed for analysis of different sectors with a view to determining which is riskiest. The study makes use of a multi-factor structural model, given that each sector is affected by a different systematic risk factor, with the assets of borrowers from the same sector thus correlated markedly, even as correlations between sectors are low. The research has in fact sought the further development of methodology proposed by Düllmann and Masschelein in 2006—in the direction of improved accuracy of economic-capital estimates, thanks to alternate means of mapping out the sectoral factor correlation matrix. The empirical analysis was based on individual data from Prudential Reporting under the National Bank of Poland, as well as market data. Results reveal an increase in tail risk through the 2015–2017 period, as followed by the onset of a decline. Where the paper’s second aim is concerned, there is found to be support for the idea that economic capital may be increased where sector concentration in the portfolio of a bank is accounted for. Tail risk is found to be concentrated in the sectors of construction and real estate, with accommodation and food services becoming more volatile during the pandemic. A channel for risk transfer between the financial and corporate sectors is thus found to exist. Thanks to the work done we have a better understanding of the impact of sectoral concentration of individual banks’ lending activities on level of risk, with the possibility of this gaining application as stress tests are conducted, and as supervisory recommendations from Poland’s Financial Supervision Authority are formulated.

Suggested Citation

  • Natalia Nehrebecka, 2023. "Distribution of credit-risk concentration in particular sectors of the economy, and economic capital before and during the COVID-19 pandemic," Economic Change and Restructuring, Springer, vol. 56(1), pages 129-158, February.
  • Handle: RePEc:kap:ecopln:v:56:y:2023:i:1:d:10.1007_s10644-022-09412-5
    DOI: 10.1007/s10644-022-09412-5
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    References listed on IDEAS

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    1. Puzanova, Natalia & Düllmann, Klaus, 2013. "Systemic risk contributions: A credit portfolio approach," Journal of Banking & Finance, Elsevier, vol. 37(4), pages 1243-1257.
    2. repec:zbw:bofrdp:2004_018 is not listed on IDEAS
    3. Francesco Vallascas & Jens Hagendorff, 2013. "The Risk Sensitivity of Capital Requirements: Evidence from an International Sample of Large Banks," Review of Finance, European Finance Association, vol. 17(6), pages 1947-1988.
    4. Libor Holub & Michal Nyklicek & Pavel Sedlar, 2015. "Credit Portfolio Sector Concentration and Its Implications for Capital Requirements," Occasional Publications - Chapters in Edited Volumes, in: CNB Financial Stability Report 2014/2015, chapter 0, pages 131-138, Czech National Bank.
    5. Dirk Tasche, 2005. "Measuring sectoral diversification in an asymptotic multi-factor framework," Papers physics/0505142, arXiv.org, revised Jul 2006.
    6. Klaus Düllmann & Nancy Masschelein, 2007. "A Tractable Model to Measure Sector Concentration Risk in Credit Portfolios," Journal of Financial Services Research, Springer;Western Finance Association, vol. 32(1), pages 55-79, October.
    7. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-470, May.
    8. Gordy, Michael B., 2003. "A risk-factor model foundation for ratings-based bank capital rules," Journal of Financial Intermediation, Elsevier, vol. 12(3), pages 199-232, July.
    9. Klaus Düllmann & Nancy Masschelein, 2006. "Sector Concentration in Loan Portfolios and Economic Capital," Working Paper Research 105, National Bank of Belgium.
    10. Virolainen, Kimmo, 2004. "Macro stress testing with a macroeconomic credit risk model for Finland," Bank of Finland Research Discussion Papers 18/2004, Bank of Finland.
    11. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    12. Natalia Nehrebecka, 2018. "Sectoral risk assessment with particular emphasis on export enterprises in Poland," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 36(2), pages 677-700.
    13. Matteo Accornero & Giuseppe Cascarino & Roberto Felici & Fabio Parlapiano & Alberto Maria Sorrentino, 2018. "Credit risk in banks’ exposures to non‐financial firms," European Financial Management, European Financial Management Association, vol. 24(5), pages 775-791, November.
    14. Hasan, Iftekhar & Politsidis, Panagiotis N. & Sharma, Zenu, 2021. "Global syndicated lending during the COVID-19 pandemic," Journal of Banking & Finance, Elsevier, vol. 133(C).
    15. Iulia Andreea Bucur & Simona Elena Dragomirescu, 2014. "The Influence Of Macroeconomic Conditions On Credit Risk: Case Of Romanian Banking System," Studies and Scientific Researches. Economics Edition, "Vasile Alecsandri" University of Bacau, Faculty of Economic Sciences, issue 19.
    16. Rösch, Daniel, 2003. "Correlations and Business Cycles of Credit Risk: Evidence from Bankruptcies in Germany," University of Regensburg Working Papers in Business, Economics and Management Information Systems 380, University of Regensburg, Department of Economics.
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    1. Oktay Ozkan & Salah Abosedra & Arshian Sharif & Andrew Adewale Alola, 2024. "Dynamic volatility among fossil energy, clean energy and major assets: evidence from the novel DCC-GARCH," Economic Change and Restructuring, Springer, vol. 57(3), pages 1-19, June.

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    More about this item

    Keywords

    Sector concertation risk; Economic capital; Multi-factor structural model; Monte Carlo methods;
    All these keywords.

    JEL classification:

    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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