IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/55801.html
   My bibliography  Save this paper

Systemic Risk of Commercial Banks: A Markov-Switching Quantile Autoregression Approach

Author

Listed:
  • Liu, Xiaochun

Abstract

This paper extends the Conditional Value-at-Risk approach of Adrian and Brunnermeier (2011) by allowing systemic risk structures subject to economic regime shifts, which are governed by a discrete, latent Markov process. This proposed Markov-Switching Conditional Value-at-Risk is more suitable to Supervisory Stress Scenario required by FederalReserve Bank in conducting Comprehensive Capital Analysis and Review, since it is ca-pable of identifying the risk states in which the estimated risk levels are characterized. Applying MSCoVaR to stress-testing the U.S. largest commercial banks, this paper finds that the CoVaR approach underestimates systemic risk contributions of individual banks by around 131 basis points of asset loss on average. In addition, this paper constructs Banking Systemic Risk Index by value-weighted individual risk contributions for specifically monitoring the systemic risk of the banking system as a whole.

Suggested Citation

  • Liu, Xiaochun, 2013. "Systemic Risk of Commercial Banks: A Markov-Switching Quantile Autoregression Approach," MPRA Paper 55801, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:55801
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/55801/1/MPRA_paper_55801.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Koenker, Roger & Xiao, Zhijie, 2006. "Quantile Autoregression," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 980-990, September.
    2. Dimitrios Bisias & Mark Flood & Andrew W. Lo & Stavros Valavanis, 2012. "A Survey of Systemic Risk Analytics," Annual Review of Financial Economics, Annual Reviews, vol. 4(1), pages 255-296, October.
    3. López-Espinosa, Germán & Moreno, Antonio & Rubia, Antonio & Valderrama, Laura, 2012. "Short-term wholesale funding and systemic risk: A global CoVaR approach," Journal of Banking & Finance, Elsevier, vol. 36(12), pages 3150-3162.
    4. 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.
    5. Maarten van Oordt & Chen Zhou, 2011. "Systematic risk under extremely adverse market condition," DNB Working Papers 281, Netherlands Central Bank, Research Department.
    6. Wong, Alfred Y-T. & Fong, Tom Pak Wing, 2011. "Analysing interconnectivity among economies," Emerging Markets Review, Elsevier, vol. 12(4), pages 432-442.
    7. Mauricio Arias & Juan Carlos Mendoza & David Perez-Reyna, 2011. "Applying CoVaR to measure systemic market risk: the Colombian case," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Proceedings of the IFC Conference on "Initiatives to address data gaps revealed by the financial crisis", Basel, 25-26 August 2010, volume 34, pages 351-364, Bank for International Settlements.
    8. Rodríguez-Moreno, María & Peña, Juan Ignacio, 2013. "Systemic risk measures: The simpler the better?," Journal of Banking & Finance, Elsevier, vol. 37(6), pages 1817-1831.
    9. Rungporn Roengpitya & Phurichai Rungcharoenkitkul, 2010. "Measuring Systemic Risk And Financial Linkages In The Thai Banking System," Working Papers 2010-02, Monetary Policy Group, Bank of Thailand.
    10. International Monetary Fund, 2012. "Short-Term Wholesale Funding and Systemic Risk: A Global Covar Approach," IMF Working Papers 2012/046, International Monetary Fund.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Varotto, Simone & Zhao, Lei, 2018. "Systemic risk and bank size," Journal of International Money and Finance, Elsevier, vol. 82(C), pages 45-70.
    2. Liu, Xiaochun, 2017. "Measuring systemic risk with regime switching in tails," Economic Modelling, Elsevier, vol. 67(C), pages 55-72.
    3. Maarten van Oordt & Chen Zhou, 2019. "Systemic risk and bank business models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(3), pages 365-384, April.
    4. Bernal, Oscar & Gnabo, Jean-Yves & Guilmin, Grégory, 2014. "Assessing the contribution of banks, insurance and other financial services to systemic risk," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 270-287.
    5. Sylvain Benoît & Gilbert Colletaz & Christophe Hurlin & Christophe Pérignon, 2013. "A Theoretical and Empirical Comparison of Systemic Risk Measures," Working Papers halshs-00746272, HAL.
    6. 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.
    7. Grupp, Marcel, 2015. "On the impact of leveraged buyouts on bank systemic risk," SAFE Working Paper Series 101, Leibniz Institute for Financial Research SAFE.
    8. Fenghua Wen & Kaiyan Weng & Wei-Xing Zhou, 2020. "Measuring the contribution of Chinese financial institutions to systemic risk: an extended asymmetric CoVaR approach," Risk Management, Palgrave Macmillan, vol. 22(4), pages 310-337, December.
    9. López-Espinosa, Germán & Moreno, Antonio & Rubia, Antonio & Valderrama, Laura, 2012. "Short-term wholesale funding and systemic risk: A global CoVaR approach," Journal of Banking & Finance, Elsevier, vol. 36(12), pages 3150-3162.
    10. Hossein Dastkhan, 2021. "Network‐based early warning system to predict financial crisis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 594-616, January.
    11. Jon Danielsson & Kevin R. James & Marcela Valenzuela & Ilknur Zer, 2016. "Can We Prove a Bank Guilty of Creating Systemic Risk? A Minority Report," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(4), pages 795-812, June.
    12. Rivera-Castro, Miguel A. & Ugolini, Andrea & Arismendi Zambrano, Juan, 2018. "Tail systemic risk and contagion: Evidence from the Brazilian and Latin America banking network," Emerging Markets Review, Elsevier, vol. 35(C), pages 164-189.
    13. Peter Grundke, 2019. "Ranking consistency of systemic risk measures: a simulation-based analysis in a banking network model," Review of Quantitative Finance and Accounting, Springer, vol. 52(4), pages 953-990, May.
    14. repec:zbw:bofitp:2012_012 is not listed on IDEAS
    15. Jokivuolle, Esa & Tunaru, Radu & Vioto, Davide, 2018. "Testing the systemic risk differences in banks," Research Discussion Papers 13/2018, Bank of Finland.
    16. Drakos, Anastassios A. & Kouretas, Georgios P., 2015. "Bank ownership, financial segments and the measurement of systemic risk: An application of CoVaR," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 127-140.
    17. Agur, Itai, 2014. "Bank risk within and across equilibria," Journal of Banking & Finance, Elsevier, vol. 48(C), pages 322-333.
    18. Antonio Rubia Serrano & Lidia Sanchis-Marco, 2015. "Measuring Tail-Risk Cross-Country Exposures in the Banking Industry," Working Papers. Serie AD 2015-01, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    19. Rubia, Antonio & Sanchis-Marco, Lidia, 2013. "On downside risk predictability through liquidity and trading activity: A dynamic quantile approach," International Journal of Forecasting, Elsevier, vol. 29(1), pages 202-219.
    20. Morelli, David & Vioto, Davide, 2020. "Assessing the contribution of China’s financial sectors to systemic risk," Journal of Financial Stability, Elsevier, vol. 50(C).
    21. Maarten van Oordt & Chen Zhou, 2015. "Systemic risk of European banks: Regulators and markets," DNB Working Papers 478, Netherlands Central Bank, Research Department.

    More about this item

    Keywords

    Markov-Switching Conditional Value-at-Risk; Conditional Expected Shortfall; Bayesian Quantile Inference; Stress-testing; Value-at-Risk; Commercial Banks; Banking Systemic Risk Index;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:55801. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.