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VAR for VaR: measuring systemic risk using multivariate regression quantiles

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  • White, Halbert
  • Kim, Tae-Hwan
  • Manganelli, Simone

Abstract

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.

Suggested Citation

  • White, Halbert & Kim, Tae-Hwan & Manganelli, Simone, 2010. "VAR for VaR: measuring systemic risk using multivariate regression quantiles," MPRA Paper 35372, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:35372
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    References listed on IDEAS

    as
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    6. 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.
    7. repec:cep:stiecm:/2014/574 is not listed on IDEAS
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    17. White, Halbert, 2006. "Approximate Nonlinear Forecasting Methods," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 9, pages 459-512, Elsevier.
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    Citations

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    Cited by:

    1. Henry, Jérôme & Zimmermann, Maik & Leber, Miha & Kolb, Markus & Grodzicki, Maciej & Amzallag, Adrien & Vouldis, Angelos & Hałaj, Grzegorz & Pancaro, Cosimo & Gross, Marco & Baudino, Patrizia & Sydow, , 2013. "A macro stress testing framework for assessing systemic risks in the banking sector," Occasional Paper Series 152, European Central Bank.
    2. Adams, Zeno & Füss, Roland & Gropp, Reint, 2014. "Spillover Effects among Financial Institutions: A State-Dependent Sensitivity Value-at-Risk Approach," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(3), pages 575-598, June.
    3. Nikolaus Hautsch & Julia Schaumburg & Melanie Schienle, 2015. "Financial Network Systemic Risk Contributions," Review of Finance, European Finance Association, vol. 19(2), pages 685-738.
    4. Wuyi Ye & Kebing Luo & Shaofu Du, 2014. "Measuring Contagion of Subprime Crisis Based on MVMQ-CAViaR Method," Discrete Dynamics in Nature and Society, Hindawi, vol. 2014, pages 1-12, June.
    5. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    6. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2014. "Forecasting systemic impact in financial networks," International Journal of Forecasting, Elsevier, vol. 30(3), pages 781-794.
    7. Castro, Carlos & Ferrari, Stijn, 2014. "Measuring and testing for the systemically important financial institutions," Journal of Empirical Finance, Elsevier, vol. 25(C), pages 1-14.
    8. Grzegorz Hałaj & Christoffer Kok, 2013. "Assessing interbank contagion using simulated networks," Computational Management Science, Springer, vol. 10(2), pages 157-186, June.
    9. Kok, Christoffer & Gross, Marco, 2013. "Measuring contagion potential among sovereigns and banks using a mixed-cross-section GVAR," Working Paper Series 1570, European Central Bank.
    10. Li Wang, 2019. "The Risk Spillover Effects of Securities Companies in China’s Capital Market with the CoVaR Method," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 9(3), pages 1-7.
    11. Giovanni Bonaccolto & Massimiliano Caporin, 2016. "The Determinants of Equity Risk and Their Forecasting Implications: A Quantile Regression Perspective," JRFM, MDPI, vol. 9(3), pages 1-25, July.
    12. Kraft, Holger & Schmidt, Alexander, 2013. "Systemic risk in the financial sector: What can se learn from option markets?," SAFE Working Paper Series 25, Leibniz Institute for Financial Research SAFE.
    13. Raffaella Calabrese & Silvia Osmetti, 2014. "Modelling cross-border systemic risk in the European banking sector: a copula approach," Papers 1411.1348, arXiv.org.

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    More about this item

    Keywords

    Quantile impulse-responses; spillover; codependence; CAViaR;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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