VAR for VaR: measuring systemic risk using multivariate regression quantiles
This paper proposes methods for estimation and inference in multivariate, multi-quantile models. The theory can simultaneously accommodate models with multiple random variables, multiple confidence levels, and multiple lags of the associated quantiles. The proposed framework can be conveniently thought of as a vector autoregressive (VAR) extension to quantile models. We estimate a simple version of the model using market returns data to analyse spillovers in the values at risk (VaR) of different financial institutions. We construct impulse-response functions for the quantile processes of a sample of 230 financial institutions around the world and study how financial institution-specific and system-wide shocks are absorbed by the system.
|Date of creation:||17 Oct 2010|
|Date of revision:|
|Contact details of provider:|| Postal: |
Web page: https://mpra.ub.uni-muenchen.de
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001.
"Modeling and Forecasting Realized Volatility,"
Center for Financial Institutions Working Papers
01-01, Wharton School Center for Financial Institutions, University of Pennsylvania.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001. "Modeling and Forecasting Realized Volatility," NBER Working Papers 8160, National Bureau of Economic Research, Inc.
- Anderson, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Labys, Paul, 2002. "Modeling and Forecasting Realized Volatility," Working Papers 02-12, Duke University, Department of Economics.
- Stinchcombe, Maxwell B. & White, Halbert, 1998. "Consistent Specification Testing With Nuisance Parameters Present Only Under The Alternative," Econometric Theory, Cambridge University Press, vol. 14(03), pages 295-325, June.
- repec:cep:stiecm:/2014/574 is not listed on IDEAS
- Engle, Robert F & Manganelli, Simone, 1999.
"CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles,"
University of California at San Diego, Economics Working Paper Series
qt06m3d6nv, Department of Economics, UC San Diego.
- Robert F. Engle & Simone Manganelli, 2004. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 367-381, October.
- Robert Engle & Simone Manganelli, 2000. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Econometric Society World Congress 2000 Contributed Papers 0841, Econometric Society.
- Karun Adusumilli & Taisuke Otsu, 2014.
"Empirical Likelihood for Random Sets,"
STICERD - Econometrics Paper Series
574, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- repec:cup:cbooks:9780521574464 is not listed on IDEAS
- Viral V. Acharya & Lasse H. Pedersen & Thomas Philippon & Matthew Richardson, 2010.
"Measuring systemic risk,"
1002, Federal Reserve Bank of Cleveland.
- White, Halbert & Kim, Tae-Hwan & Manganelli, Simone, 2008. "Modeling autoregressive conditional skewness and kurtosis with multi-quantile CAViaR," Working Paper Series 0957, European Central Bank.
- Andrews, Donald W. K., 1987.
"Laws of Large Numbers for Dependent Non-Identically Distributed Random Variables,"
645, California Institute of Technology, Division of the Humanities and Social Sciences.
- Andrews, Donald W.K., 1988. "Laws of Large Numbers for Dependent Non-Identically Distributed Random Variables," Econometric Theory, Cambridge University Press, vol. 4(03), pages 458-467, December.
- Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
- repec:cup:cbooks:9780521252805 is not listed on IDEAS
- Komunjer, Ivana & Vuong, Quang, 2010. "Efficient estimation in dynamic conditional quantile models," Journal of Econometrics, Elsevier, vol. 157(2), pages 272-285, August.
- Komunjer, Ivana, 2005.
"Quasi-maximum likelihood estimation for conditional quantiles,"
Journal of Econometrics,
Elsevier, vol. 128(1), pages 137-164, September.
- Komunjer, Ivana, 2002. "Quasi-Maximum Likelihood Estimation for Conditional Quantiles," Working Papers 1139, California Institute of Technology, Division of the Humanities and Social Sciences.
- Powell, James L., 1984. "Least absolute deviations estimation for the censored regression model," Journal of Econometrics, Elsevier, vol. 25(3), pages 303-325, July.
- Newey, Whitney K. & Powell, James L., 1990. "Efficient Estimation of Linear and Type I Censored Regression Models Under Conditional Quantile Restrictions," Econometric Theory, Cambridge University Press, vol. 6(03), pages 295-317, September.
- Weiss, Andrew A., 1991. "Estimating Nonlinear Dynamic Models Using Least Absolute Error Estimation," Econometric Theory, Cambridge University Press, vol. 7(01), pages 46-68, March.
When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:35372. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Ekkehart Schlicht)
If references are entirely missing, you can add them using this form.