Credit Risk of FX Loans in Poland. Interest and FX Rate Dependence
DOI:
https://doi.org/10.18778/0208-6018.295.04Keywords:
financial stability, credit risk, dependence measures, copulaAbstract
One of important financial stability risks in Poland is relatively high share of bank loans denominated in foreign currency extended to unhedged borrowers. Banks engaged in FX lending are exposed to indirect exchange rate risk (as a component of credit risk) through currency mismatches on their clients' balance sheets. A significant depreciation of Polish zloty would translate into an increase of value of outstanding debt (also in relation to the value of collateral) as well as in the flow of payments to service the debt. As a result, the debt-servicing capacity of unhedged domestic borrowers would deteriorate, leading to a worsening the financial condition of the private sector. The reduction of borrower's ability to service the loan and lower recovery rate affects the loan portfolio quality, increases banks' loan losses. This effect can be mitigated or intensified by foreign interest rates of extended FX loans (i.e. LIBOR). The borrower's ability to service such loan depends strongly on FX rate but also on monetary authorities from abroad. Therefore both risks are linked and should be considered together. This paper presents the statistical analysis of the dependence of foreign interest rates and FX rate of Polish zloty using measures of dependence, amongst others, copula function approach.
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References
Alexander C. (2010), Market Risk Analysis: Practical Financial Econometrics, Wiley.
Google Scholar
Doman M., Doman R. (2010), Copula Based Impulse Response Analysis of Linkages Between Stock Markets, SSRN Working Paper Series, No. 1615108.
Google Scholar
DOI: https://doi.org/10.2139/ssrn.1615108
Financial Stability Report (2012), National Bank of Poland, http://www.nbp.pl/homen.aspx?f=/en/systemfinansowy/stabilnosc.html
Google Scholar
Financial Stability Report (2013), National Bank of Poland, http://www.nbp.pl/homen.aspx?f=en/systemfinansowy/stabilnosc.html
Google Scholar
Giżycki M. (2001), The effect of macroeconomic conditions on banks' risk and profitability, Reserve Bank of Australia Research Discussion Paper, 6.
Google Scholar
Głogowski A. (2008), Macroeconomic determinants of Polish banks' loan losses - results of a panel data study, National Bank of Poland Working Paper, 53.
Google Scholar
DOI: https://doi.org/10.2139/ssrn.1752913
Kearns A. (2004), Loan losses and the macroeconomy: A framework for stress testing credit institutions' financial well-being, Financial Stability Report, Central Bank and Financial Services Authority of Ireland.
Google Scholar
Kelm R. (2010), Model behawioralnego kursu równowagi złotego do euro w okresie styczeń 1996 - czerwiec 2009 r., Bank i Kredyt, 41 (2), 2010, 21-42.
Google Scholar
McNeil A.J., Frey R., Embrechts P. (2005), Quantitative Risk Management: Concepts, Techniques, and Tools, Princeton Series in Finance.
Google Scholar
Patton A.J. (2006), Modelling Asymmetric Exchange Rate Dependence, International Economic Review, Vol. 47, No. 2, pp. 527-556.
Google Scholar
DOI: https://doi.org/10.1111/j.1468-2354.2006.00387.x
Patton A.J. (2012), A review of copula models for economic time series, Journal of Multivariate Analysis, 110, pp. 4-18.
Google Scholar
DOI: https://doi.org/10.1016/j.jmva.2012.02.021
Sklar A. (1959), Fonctions de répartitions â n dimensions et leur marges., Publications de l'Institut de Statistique de l'Université de Paris, vol. 8, pp. 229-231.
Google Scholar
Trivedi P.K., Zimmer M. (2005), Copula Modelling: An Introduction for Practitioners, now Publishers Inc.
Google Scholar
Wanat S. (2011), Modelowanie struktur zależności za pomocą funkcji połączeń w analizie ryzyka ubezpieczyciela, Acta Universitatis Lodziensis, Folia Oeconomica, 254, 89-107.
Google Scholar
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