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From Stress to Costress

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Author Info

  • Rodolfo Maino
  • Kalin Tintchev

Abstract

This paper presents an integrated framework for assessing systemic risk. The framework models banks’ capital asset ratios as a function of future losses and credit growth using a generalized method of moments to calibrate shocks to credit quality and credit growth. The analysis is complemented by a simple measure of systemic risk, which captures tail risk comovement among banks in the system. The main contribution of this paper is to advance a simple framework to integrate systemic risk scenarios that assess the impact of aggregate and idiosyncratic factors. The analysis is based on CreditRisk+, which uses analytical techniques—similar to those applied in the insurance industry - to estimate banks’ credit portfolio loss distributions, making no assumptions about the cause of default.

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Bibliographic Info

Paper provided by International Monetary Fund in its series IMF Working Papers with number 12/53.

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Length: 34
Date of creation: 01 Feb 2012
Date of revision:
Handle: RePEc:imf:imfwpa:12/53

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Keywords: Stress testing; Credit risk; Banking systems; Credit expansion; Economic models; External shocks; Risk management; banking; probabilities; probability; banking system; sensitivity analysis; capital adequacy; generating function; equations; stata; capital adequacy ratio; minimization; equation; bank of england; credit risk management; empirical model; outliers; probability of default; poisson distribution; interbank market; covariance; samples; estimation procedure; econometrics; banking stability; banks ? assets; bank distress; central banking; prediction; survey; instrumental variables; random variable; generating functions; statistical methods; correlations; tier 1 capital; bootstrap; logarithms; regression analysis; optimization; independent variables; banking sector; bank research; standard deviations; correlation; estimation period; probability distribution; vector autoregression; recapitalization; banks ? solvency; bank liquidity; bank managers; normal distribution; scatter plot; foreign exchange; orthogonality; bank credit; standard deviation; sovereign risk; poisson process; finite sample; nonlinear relationship; functional form; sample size; least squares regression; statistical theory;

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References

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  1. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731, April.
  2. Richard Blundell & Steve Bond, 1999. "GMM estimation with persistent panel data: an application to production functions," IFS Working Papers W99/04, Institute for Fiscal Studies.
  3. Steve Bond, 2002. "Dynamic panel data models: a guide to microdata methods and practice," CeMMAP working papers CWP09/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  4. David Aikman & Piergiorgio Alessandri & Bruno Eklund & Prasanna Gai & Sujit Kapadia & Elizabeth Martin & Nada Mora & Gabriel Sterne & Matthew Willison, 2009. "Funding Liquidity Risk in a Quantitative Model of Systemic Stability," Working Papers Central Bank of Chile 555, Central Bank of Chile.
  5. M Arellano & O Bover, 1990. "Another Look at the Instrumental Variable Estimation of Error-Components Models," CEP Discussion Papers dp0007, Centre for Economic Performance, LSE.
  6. Lelyveld, Iman van & Liedorp, Franka, 2006. "Interbank Contagion in the Dutch Banking Sector: A Sensitivity Analysis," MPRA Paper 806, University Library of Munich, Germany.
  7. Zsófia Arvai & Karl Driessen & Ínci Ötker-Robe, 2009. "Regional Financial Interlinkages and Financial Contagion within Europe," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 59(6), pages 522-540, December.
  8. 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 449-70, May.
  9. Richard Blundell & Steve Bond, 1995. "Initial conditions and moment restrictions in dynamic panel data models," IFS Working Papers W95/17, Institute for Fiscal Studies.
  10. Michael Boss & Gerald Krenn & Claus Puhr & Martin Summer, 2006. "Systemic Risk Monitor: A Model for Systemic Risk Analysis and Stress Testing of Banking Systems," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 11, pages 83-95.
  11. Jorge A. Chan-Lau, 2010. "The Global Financial Crisis and its Impacton the Chilean Banking System," IMF Working Papers 10/108, International Monetary Fund.
  12. Raphael A. Espinoza & Ananthakrishnan Prasad, 2010. "Nonperforming Loans in the GCC Banking System and their Macroeconomic Effects," IMF Working Papers 10/224, International Monetary Fund.
  13. Borio, Claudio & Drehmann, Mathias & Tsatsaronis, Kostas, 2014. "Stress-testing macro stress testing: Does it live up to expectations?," Journal of Financial Stability, Elsevier, vol. 12(C), pages 3-15.
  14. Liliana Schumacher & Theodore M. Barnhill, 2011. "Modeling Correlated Systemic Liquidity and Solvency Risks in a Financial Environment with Incomplete Information," IMF Working Papers 11/263, International Monetary Fund.
  15. Charles Goodhart & Miguel Segoviano, 2009. "Banking Stability Measures," FMG Discussion Papers dp627, Financial Markets Group.
  16. Jorge A. Chan-Lau, 2006. "Fundamentals-Based Estimation of Default Probabilities: A Survey," IMF Working Papers 06/149, International Monetary Fund.
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