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Autor
Karkowska Renata (University of Warsaw, Poland)
Tytuł
Measuring Systemic Risk in the Polish Banking System by Means of the Risk-Based Balance Sheets Method
Źródło
Folia Oeconomica Stetinensia, 2012, vol. 12, nr 2, s. 7-18, ryc., tab., bibliogr. 13 poz.
Słowa kluczowe
Ryzyko systemowe, System bankowy, Kryzys finansowy
Systemic risk, Banking system, Financial crisis
Uwagi
summ.
Abstrakt
The complex connections, spillovers and feedbacks of the global financial crisis remind how important it is to improve the analysis of risk modeling. This article introduces a new framework for mitigating systemic risk by using a risk-adjusted balance sheet approach. In this regard, the analysis of individual banks in Poland shows potential risk which could threaten all the financial system. Traditional banking models do not adequately measure risk position of financial institutions and cannot be used to understand risk within and between balance sheets in the financial sector. A fundamental subject is that accounting balance sheets do not indicate risk exposures, which are forward-looking. The paper concludes new directions for measuring systemic risk by using Merton's model. It shows how risk management tools can be applied in new ways to measure and analyze systemic risk in the Polish banking system. (original abstract)
Dostępne w
Biblioteka Główna Uniwersytetu Ekonomicznego w Katowicach
Biblioteka Główna Uniwersytetu Ekonomicznego we Wrocławiu
Pełny tekst
Pokaż
Bibliografia
Pokaż
  1. Gapen, I. (2009). Evaluating the Implicit Guarantee to Fannie Mae and Freddie Mac Using Contingent Claims. In: Credit, Capital, Currency, and Derivatives: Instruments of Global Financial Stability or Crisis? International Finance Review. Vol. 10. DOI: 10.1108/S1569-3767(2009)0000010014.
  2. Garcia, C., Gray, D., Luna, L. & Restrepo, J. (2010). Incorporating Financial Sector Risk into Monetary Policy Models: Application to Chile. In: Financial Stability, Monetary Policy and Central Banking, R. Alfaro (Ed.). Santiago, Chile: Central Bank of Chile Book.
  3. Gątarek, D., Maksymiuk, M., Krysiak, R. & Witkowski, Ł. (2001). Modern method of financial risk management. Warsaw: WIG-Press.
  4. Gray, D.F. & Malone, S. (2011). Macrofinancial Risk Analysis. Publisher John Wiley & Sons, ISBN: 978-0-470-05831-2.
  5. Gray, D.F. & Jobst, A.A. (2009). Higher Moments and Multivariate Dependence of ImpliedVolatilities from Equity Options as Measures of Systemic Risk. Global Financial Stability Report, Chapter 3, April (Washington: International Monetary Fund).
  6. Gray, D.F., Jobst, A.A. & Malone, S. (2010). Quantifying Systemic Risk and Reconceptualizing the Role of Finance for Economic Growth. Journal of Investment Management, Vol. 8, No. 2.
  7. Hull, J.C. (2003). Options, Futures and Other Derivatives. NJ: Prentice Hall, Upper Saddle River.
  8. Hull, J.C., Nelken, I. & White, A. (2003). Merton's Model, Credit Risk, and Volatility Skews. University of Toronto.
  9. International Monetary Fund. (2009). Global Financial Stability Report: Responding to the Financial Crisis and Measuring Systemic Risks. World Economic and Financial Surveys (International Monetary Fund: Washington, D.C.).
  10. International Monetary Fund. (2008). Global Financial Stability Report: Containing Systemic Risks and Restoring Financial Soundness. World Economic and Financial Surveys (International Monetary Fund: Washington, D.C.).
  11. MKMV. (2003). Modeling Default Risk. Moody's KMV, Moody's Analytics (www.mkmv. com).
  12. Schuermann, T., Pesaran, M.H., Treuler, B.J. & Weiner, S.M. (2006). Macroeconomic Dynamics and Credit Risk: A Global Perspective. Journal of Money, Credit and Banking, Vol. 38, No. 5, 1211-1262.
  13. Wójciak, M. & Wójcicka, A. (2007). Comparison of stock option modification Bystrom modelcredit risk assessment model MKMV. Dynamic econometric models. X Nationwide Seminar, September 4-6, 2007 in Torun.
Cytowane przez
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ISSN
1730-4237
Język
eng
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