Measuring and testing for the systemically important financial institutions


Autoria(s): Castro, Carlos; Ferrari., Stijn
Data(s)

2011

Resumo

This paper analyzes the measure of systemic importance ∆CoV aR proposed by Adrian and Brunnermeier (2009, 2010) within the context of a similar class of risk measures used in the risk management literature. In addition, we develop a series of testing procedures, based on ∆CoV aR, to identify and rank the systemically important institutions. We stress the importance of statistical testing in interpreting the measure of systemic importance. An empirical application illustrates the testing procedures, using equity data for three European banks.

Formato

application/pdf

Identificador

http://repository.urosario.edu.co/handle/10336/10821

Publicador

Facultad de Economía

Relação

Serie documentos de trabajo. No 101 (Mayo 2011)

https://ideas.repec.org/p/col/000092/008779.html

Direitos

info:eu-repo/semantics/openAccess

Fonte

instname:Universidad del Rosario

reponame:Repositorio Institucional EdocUR

instname:Universidad del Rosario

Abadie, A.: Bootstrap test for distribution treatment effects in instrumental variable models, Journal of the American Statistical Association, Vol. 97(457), pp.284-92, (2002).

Adrian, T., Brunnermeier, M.: CoVaR, working paper, Federal Reserve Bank of New York, (2009).

Anatolyev, S. Kosenok, G.: Another numerical method of finding critical values for the Andrews stability test, Econometric Theory, Forthcoming, (2011).

Andrews, D.P.: Test for Parameter instability and structural change with unknown change point, Econometrica, Vol. 61(4), pp.821-856, (1993).

Andrews, D.P.: Test for Parameter instability and structural change with unknown change point: A corrigendum, Econometrica, Vol. 71(1), pp.395- 397, (2003).

Bank for International Settlements: Basel III: A global regulatory framework for more resilient banks and banking systems, Report, December, (2010).

Basset, G., Koenker, R.: An empirical quantile function for linear model with iid errors, Journal of the American Statistical Association, Vol. 77(378), pp. 407-15, (1982).

Brownlees C., Engle, R.: Volatility, correlation, and tails for systemic risk measurement, working paper, NYU Stern, (2010).

Billio, M., Getmansky, M., Lo, A., Pelizzon, L.: Econometric measures of systemic risk in finance and insurance sectors, working paper, NBER, 16223, (2010).

Cai, Z., Wang, X.: Nonparametric estimation of conditional VaR and expected shortfall, Journal of Econometrics, 147, pp 120-130 (2008).

Castro, C., Ferrari, S.: Measuring the systemic importance of financial institutions using market information, Financial Stability Review, National Bank of Belgium, June , pp 127-141 (2010).

Chan-Lau, J.: Balance sheet network analysis of too-connected-to-fail risk in global and domestic banking systems, IMF Working Papers, April (2010).

Chernozhukov, V.: Conditional Extremes and Near-extremes: Concepts, Estimation and Economic applications, Standfod Ph.D Dissertation (2000).

Chernozhukov, V., Fernandez-Val, I.: Subsampling inference on quantile regression process, The Indian Journal of Statistics, Vol.6 (2), pp 253-276 (2005).

Chernozhukov, V., Hansen, C.: Instrumental quantile regression inference for structural and treatment effect models, Journal of Econometrics, Vol. 132, pp 491-525 (2006).

Chernozhukov, V., Umantzev, L.: Conditional Value-at-Risk: Aspects of modelling and estimation, Empirical Economics, 26, pp 271-292 (2001).

De Jonghe, O.: Back to the Basics of Banking? A Micro-Analysis of Banking System Stability, Journal of Financial Intermediation, forthcomming, working paper, (2008).

Estrella, A.: Critical values and p-values of Bessel process distributions: Computation and application to structural break tests, Econometric Theory, 19, pp. 1128-1143, (2003).

Elsinger, H., Lehar, A., Summer, M.: Using market information for banking system risk assesment, International Journal of Central Banking, 2(1), pp. 137-165, (2006).

Jager-Ambrozewiez, M.: Systemic risk and CoVaR in a Gaussian setting, Working Paper, September, (2010).

Gail, M., Sylvan, G.: A generalization of the one-sided two-sample Kolmogorov-Smirnov statistic for evaluating diagnostic test, Biometrics, 32, pp. 561-70, (1976).

Gail, M., Sylvan, G.: Critical values for the one-sided two-sample Kolmogorov-Smirnov statistic, Journal of the American Statistical Association, Vol. 71(355), pp. 757-60, (1976).

Gautier, C., Lehar, A., Souissi, M.: Macroprudential regulation and systemic capital requirements, Bank of Canada Working Paper, April, (2010).

Geluk, J., De Haan, L., De Vries, C.: Weak and strong financial system fragility, Tinbergen Institute, Discussion Paper, 023/2, (2007).

Girardi, G., Ergun, A.T.: Systemic Risk Measurement: Multivariate GARCH Estimation of CoVaR, Working Paper, April, (2011).

Gilchrist, W.: Statistical modelling with quantile functions, Chapman & Hall/CRC (2000).

Gourieroux, C., Laurent, J., Scaillet, O.: Sensitivity analysis of Value at Risk, Journal of Empirical Finance, 7, 225-245, (2000).

Hartmann, P., Straetmans, S., De Vries, C.: Banking system stability: A cross atlantic perspective, ECB Working Paper, 527, (2005)

Huang, X., Zhou, H., Zhu, H.: Assessing the systemic risk of a heterogeneous portfolio of banks during the recent financial crisis, Federal Reserve Board Finance and Economics Discussion Series, 44, (2009).

International Monetary Fund: Financial Stability Report, April, pp 74-109, (2009).

Koenker, R.: Quantile Regression, Econometric Society Monographs, Cambriedge University Press (2005).

Koenker, R., Xiao, Z.: Inference on the quantile regression process, Econometrica, Vol. 70(4), pp. 1583-1612, (2002).

Koenker, R., Machado, J.: Goodness of fit and related inference process for quantile regression, Journal of the American Statistical Association, Vol. 94(448), pp. 1296-1310, (1999).

Koyluoglu, U., Stoker, J.: Honour your contribution, Risk, April, (2002).

Kurth, A., Tasche, D.: Contributions to credit risk, Risk, March, (2003).

Linton, O., Maasoumi, E., Whang, Y.: Consistent testing for stochastic dominance under general sampling schemes, Review of Economic Studies, 72, pp. 735-765, (2005).

Parzen, E.: Nonparametric statistical data modeling, Journal of the American Statistical Association, Vol. 74(365), pp 105-121, (1979).

Parzen, E.: Quantile probability and statistical data modeling, Statistical Science, Vol. 19(4), pp 652-662, (2004).

Mason, D., Schuenemeyer J.: A modified Kolmogorov-Smirnov test sensitive to tail alternatives, The Annals of Statistics, Vol. 11(3), pp.933- 46 (1983).

McNeil, A., Frey, R., Embrechts, P.: Quantitive Risk Management, Princeton University Press, (2005).

Scaillet, O.: Nonparametric estimation and sensitivity analysis of expected shortfall, Mathemathical Finance, January, No. 1 (2004).

Segoviano, M., Goodhart, C.: Bank Stability Measures, IMF Working paper, No. 4 (2009).

Stoyanov, S., Samorodnitsky, G., Rachev, S., Ortobelli, S.: Computing the portfolio conditional value-at-risk in the α-stable case, Probability and Mathematical Statistics, Vol. 26(1) pp 1-22 (2006).

Tarashev, N., Borio, C., Tsatsaronis K.: The systemic importance of financial institutions, BIS Quartely review, September, (2009).

Tasche, D.: Risk contributions and perfomence measurement, working paper, TU Munchen, (2000).

White, H., Kim, Tae-Hwan, K., Manganelli, S.: VAR for VaR: Measuring systemic risk using multivariate regression quantiles, working paper, UC San Diego,(2010).

Zhou, C.: Are banks too big to fail, DNB working paper, 232,(2009).

Palavras-Chave #Instituciones financieras #Evaluación de riesgos #Crisis financiera #Administración financiera #658.15
Tipo

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