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Interconnectedness of Global Systemically-Important Banks and Insurers

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  • Sheheryar Malik
  • TengTeng Xu

Abstract

Interconnectedness among global systemically important banks (GSIBs) and global systemically important insurers (GSIIs) has important financial stability implications. This paper examines connectedness among United States, European and Asian GSIBs and GSIIs, using publicly-available daily equity returns and intra-day volatility data from October 2007 to August 2016. Results reveal strong regional clusters of return and volatility connectedness amongst GSIBs and GSIIs. Compared to Asia, selected GSIBs and GSIIs headquartered in the United States and Europe appear to be main sources of market-based connectedness. Total system connectedness—i.e., among all GSIBs and GSIIs—tends to rise during financial stress, which is corroborated by a balance sheet oriented systemic risk measure. Lastly, the paper demonstrates significant influence of economic policy uncertainty and U.S. long-term interest rates on total connectedness among systemically important institutions, and the important role of bank profitability and asset quality in driving bank-specific return connectedness.

Suggested Citation

  • Sheheryar Malik & TengTeng Xu, 2017. "Interconnectedness of Global Systemically-Important Banks and Insurers," IMF Working Papers 17/210, International Monetary Fund.
  • Handle: RePEc:imf:imfwpa:17/210
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    1. FrancisX. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    2. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    3. repec:oup:jfinec:v:14:y:2016:i:1:p:81-127. is not listed on IDEAS
    4. Mert Demirer & Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2015. "Estimating Global Bank Network Connectedness," Koç University-TUSIAD Economic Research Forum Working Papers 1512, Koc University-TUSIAD Economic Research Forum.
    5. Ravi Bansal & Amir Yaron, 2004. "Risks for the Long Run: A Potential Resolution of Asset Pricing Puzzles," Journal of Finance, American Finance Association, vol. 59(4), pages 1481-1509, August.
    6. Bekaert, Geert & Hoerova, Marie, 2016. "What do asset prices have to say about risk appetite and uncertainty?," Journal of Banking & Finance, Elsevier, vol. 67(C), pages 103-118.
    7. Ang, Andrew & Piazzesi, Monika & Wei, Min, 2006. "What does the yield curve tell us about GDP growth?," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 359-403.
    8. John Y. Campbell & John Cochrane, 1999. "Force of Habit: A Consumption-Based Explanation of Aggregate Stock Market Behavior," Journal of Political Economy, University of Chicago Press, vol. 107(2), pages 205-251, April.
    9. John Y. Campbell & John H. Cochrane, 1994. "By Force of Habit: A Consumption-Based Explanation of Aggregate Stock Market Behavior," CRSP working papers 412, Center for Research in Security Prices, Graduate School of Business, University of Chicago.
    10. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, Oxford University Press, vol. 131(4), pages 1593-1636.
    11. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    12. Viral Acharya & Robert Engle & Matthew Richardson, 2012. "Capital Shortfall: A New Approach to Ranking and Regulating Systemic Risks," American Economic Review, American Economic Association, vol. 102(3), pages 59-64, May.
    13. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    14. Arturo Estrella & Frederic S. Mishkin, 1996. "The yield curve as a predictor of U.S. recessions," Current Issues in Economics and Finance, Federal Reserve Bank of New York, vol. 2(Jun).
    15. Roberto Guimarães-Filho & Gee Hee Hong, 2016. "Dynamic Connectedness of Asian Equity Markets," IMF Working Papers 16/57, International Monetary Fund.
    16. Kristin J. Forbes & Roberto Rigobon, 2002. "No Contagion, Only Interdependence: Measuring Stock Market Comovements," Journal of Finance, American Finance Association, vol. 57(5), pages 2223-2261, October.
    17. Nathan Porter & TengTeng Xu, 2016. "Money-Market Rates and Retail Interest Regulation in China: The Disconnect between Interbank and Retail Credit Conditions," International Journal of Central Banking, International Journal of Central Banking, vol. 12(1), pages 143-198, March.
    18. Pesaran, M. Hashem & Shin, Yongcheol, 1996. "Cointegration and speed of convergence to equilibrium," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 117-143.
    19. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters,in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409 National Bureau of Economic Research, Inc.
    20. Franziska L Ohnsorge & Marcin Wolski & Yuanyan S Zhang, 2014. "Safe Havens, Feedback Loops, and Shock Propagation in Global Asset Prices," IMF Working Papers 14/81, International Monetary Fund.
    21. Sims, Christopher A, 2002. "Solving Linear Rational Expectations Models," Computational Economics, Springer;Society for Computational Economics, vol. 20(1-2), pages 1-20, October.
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