White, Halbert and Kim, TaeHwan and Manganelli, Simone (2010): VAR for VaR: measuring systemic risk using multivariate regression quantiles.

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Abstract
This paper proposes methods for estimation and inference in multivariate, multiquantile 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 impulseresponse functions for the quantile processes of a sample of 230 financial institutions around the world and study how financial institutionspecific and systemwide shocks are absorbed by the system.
Item Type:  MPRA Paper 

Original Title:  VAR for VaR: measuring systemic risk using multivariate regression quantiles. 
Language:  English 
Keywords:  Quantile impulseresponses; spillover; codependence; CAViaR 
Subjects:  C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C13  Estimation: General 
Item ID:  35372 
Depositing User:  TaeHwan/T. Kim 
Date Deposited:  13. Dec 2011 03:02 
Last Modified:  23. Apr 2015 12:58 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/35372 