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Measuring the Interdependence of Banks in Hong Kong


  • Tom Fong

    (Research Department, Hong Kong Monetary Authority)

  • Laurence Fung

    (Research Department, Hong Kong Monetary Authority)

  • Lillie Lam

    (Research Department, Hong Kong Monetary Authority)

  • Ip-wing Yu

    (Research Department, Hong Kong Monetary Authority)


This paper assesses systemic linkages among banks in Hong Kong using the risk measure "CoVaR" derived from quantile regression. The CoVaR measure captures the co-movements of banks¡¯ default risk by taking into account their nonlinear relationship when the banks are in distress. Based on equity price information, our estimation results show that the default risks of the banks were interdependent during the recent crisis. Although local banks are generally smaller, their systemic importance is found to be similar to their international and Mainland counterparts, which may be due to a higher degree of commonality in the risk profile of local banks. Regarding the impact of external shocks on the banks, international banks are more likely to be affected by the equity price fall in the US market, while local banks are relatively more responsive to funding liquidity risk.

Suggested Citation

  • Tom Fong & Laurence Fung & Lillie Lam & Ip-wing Yu, 2009. "Measuring the Interdependence of Banks in Hong Kong," Working Papers 0919, Hong Kong Monetary Authority.
  • Handle: RePEc:hkg:wpaper:0919

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    References listed on IDEAS

    1. Axel Schimmelpfennig & Selma Mahfouz & Richard Hemming, 2002. "Fiscal Policy and Economic Activity During Recessions in Advanced Economies," IMF Working Papers 02/87, International Monetary Fund.
    2. Douglas Laxton & Michael Kumhof, 2007. "A Party without a Hangover? On the Effects of U.S. Government Deficits," IMF Working Papers 07/202, International Monetary Fund.
    3. Bernanke, Ben & Gertler, Mark & Gilchrist, Simon, 1996. "The Financial Accelerator and the Flight to Quality," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 1-15, February.
    4. Furceri, Davide & Mourougane, Annabelle, 2012. "The effect of financial crises on potential output: New empirical evidence from OECD countries," Journal of Macroeconomics, Elsevier, vol. 34(3), pages 822-832.
    5. Davis, E. Philip & Stone, Mark R., 2004. "Corporate financial structure and financial stability," Journal of Financial Stability, Elsevier, vol. 1(1), pages 65-91, September.
    6. Glenn Rudebusch & Lars E.O. Svensson, 1999. "Policy Rules for Inflation Targeting," NBER Chapters,in: Monetary Policy Rules, pages 203-262 National Bureau of Economic Research, Inc.
    7. Douglas Laxton & Andrew Berg & Philippe D Karam, 2006. "Practical Model-Based Monetary Policy Analysis; A How-To Guide," IMF Working Papers 06/81, International Monetary Fund.
    8. Zhiwei Zhang & Wenlang Zhang & Gaofeng Han, 2009. "How Does the US Credit Crisis Affect the Asia-Pacific Economies? --- Analysis based on a General Equilibrium Model," Working Papers 0912, Hong Kong Monetary Authority.
    9. Sanjeev Gupta & Carlos Mulas-Granados & Emanuele Baldacci, 2009. "How Effective is Fiscal Policy Response in Systemic Banking Crises?," IMF Working Papers 09/160, International Monetary Fund.
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    Cited by:

    1. Wong, Alfred Y-T. & Fong, Tom Pak Wing, 2011. "Analysing interconnectivity among economies," Emerging Markets Review, Elsevier, vol. 12(4), pages 432-442.

    More about this item


    Value-at-Risk; Systemic Risk; Risk Spillovers; Quantile Regression;

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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