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Extreme dependence and risk spillovers across north american equity markets

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  • Warshaw, Evan

Abstract

This study analyzes risk spillovers across North American equity markets over 1995–2016. Downside and upside Conditional Value-at-Risk (CoVaR) are estimated after modeling the dynamic dependence structure for each equity market pair using generalized autoregressive score (GAS) copulas. US-CAN and CAN-MX dynamic correlations trend upwards over the sample period while the US-CAN correlation fluctuates around a higher long-run average. Conditional tail dependence is symmetric and significantly higher following the Global Financial Crisis (GFC) in all cases, implying greater co-movement under extreme economic conditions. Downside and upside risk spillovers are significant and asymmetric along two dimensions for each equity market pair, where downside risk spillovers are more severe and the degree of asymmetry by conditioning direction is rank ordered by relative equity market sizes. Aside from the US-CAN pair, downside and upside risk spillovers are significantly larger following the GFC as compared to the pre-crisis period. Observed asymmetric and time-varying behavior is consistent across high/low risk and high/low risk spillover sub-periods.

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  • Warshaw, Evan, 2019. "Extreme dependence and risk spillovers across north american equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 237-251.
  • Handle: RePEc:eee:ecofin:v:47:y:2019:i:c:p:237-251
    DOI: 10.1016/j.najef.2018.12.012
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    as
    1. Andrew Ang & Geert Bekaert, 2002. "International Asset Allocation With Regime Shifts," The Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1137-1187.
    2. Phengpis, Chanwit & Swanson, Peggy E., 2006. "Portfolio diversification effects of trading blocs: The case of NAFTA," Journal of Multinational Financial Management, Elsevier, vol. 16(3), pages 315-331, July.
    3. Yacine Aït-Sahalia & Thomas Robert Hurd, 2016. "Portfolio Choice in Markets with Contagion," Journal of Financial Econometrics, Oxford University Press, vol. 14(1), pages 1-28.
    4. Lorenzo Cappiello & Robert F. Engle & Kevin Sheppard, 2006. "Asymmetric Dynamics in the Correlations of Global Equity and Bond Returns," Journal of Financial Econometrics, Oxford University Press, vol. 4(4), pages 537-572.
    5. Andrew J. Patton, 2006. "Estimation of multivariate models for time series of possibly different lengths," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(2), pages 147-173, March.
    6. Tobias Adrian & Markus K. Brunnermeier, 2016. "CoVaR," American Economic Review, American Economic Association, vol. 106(7), pages 1705-1741, July.
      • Tobias Adrian & Markus K. Brunnermeier, 2008. "CoVaR," Staff Reports 348, Federal Reserve Bank of New York.
      • Tobias Adrian & Markus K. Brunnermeier, 2011. "CoVaR," NBER Working Papers 17454, National Bureau of Economic Research, Inc.
    7. 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.
    8. Girardi, Giulio & Tolga Ergün, A., 2013. "Systemic risk measurement: Multivariate GARCH estimation of CoVaR," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3169-3180.
    9. Dimitris Politis & Halbert White, 2004. "Automatic Block-Length Selection for the Dependent Bootstrap," Econometric Reviews, Taylor & Francis Journals, vol. 23(1), pages 53-70.
    10. Cathy Ning, 2009. "Extreme Dependence in International Stock Markets," Working Papers 008, Ryerson University, Department of Economics.
    11. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    12. Ciner, Cetin, 2006. "A further look at linkages between NAFTA equity markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 46(3), pages 338-352, July.
    13. Andrew J. Patton, 2006. "Modelling Asymmetric Exchange Rate Dependence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 527-556, May.
    14. Mensi, Walid & Hammoudeh, Shawkat & Shahzad, Syed Jawad Hussain & Shahbaz, Muhammad, 2017. "Modeling systemic risk and dependence structure between oil and stock markets using a variational mode decomposition-based copula method," Journal of Banking & Finance, Elsevier, vol. 75(C), pages 258-279.
    15. Hansen, Bruce E, 1994. "Autoregressive Conditional Density Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(3), pages 705-730, August.
    16. Ji, Qiang & Liu, Bing-Yue & Cunado, Juncal & Gupta, Rangan, 2020. "Risk spillover between the US and the remaining G7 stock markets using time-varying copulas with Markov switching: Evidence from over a century of data," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    17. Reboredo, Juan C. & Ugolini, Andrea, 2015. "Systemic risk in European sovereign debt markets: A CoVaR-copula approach," Journal of International Money and Finance, Elsevier, vol. 51(C), pages 214-244.
    18. Joe, Harry, 2005. "Asymptotic efficiency of the two-stage estimation method for copula-based models," Journal of Multivariate Analysis, Elsevier, vol. 94(2), pages 401-419, June.
    19. Jondeau, Eric & Rockinger, Michael, 2006. "The Copula-GARCH model of conditional dependencies: An international stock market application," Journal of International Money and Finance, Elsevier, vol. 25(5), pages 827-853, August.
    20. Hans Manner & Olga Reznikova, 2012. "A Survey on Time-Varying Copulas: Specification, Simulations, and Application," Econometric Reviews, Taylor & Francis Journals, vol. 31(6), pages 654-687, November.
    21. Lahrech, Abdelmounaim & Sylwester, Kevin, 2013. "The impact of NAFTA on North American stock market linkages," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 94-108.
    22. Aggarwal, Raj & Kyaw, NyoNyo A., 2005. "Equity market integration in the NAFTA region: Evidence from unit root and cointegration tests," International Review of Financial Analysis, Elsevier, vol. 14(4), pages 393-406.
    23. Darrat, Ali F. & Zhong, Maosen, 2005. "Equity market linkage and multinational trade accords: The case of NAFTA," Journal of International Money and Finance, Elsevier, vol. 24(5), pages 793-817, September.
    24. Drew Creal & Siem Jan Koopman & André Lucas, 2013. "Generalized Autoregressive Score Models With Applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(5), pages 777-795, August.
    25. Abadie A., 2002. "Bootstrap Tests for Distributional Treatment Effects in Instrumental Variable Models," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 284-292, March.
    26. Reboredo, Juan C. & Rivera-Castro, Miguel A. & Ugolini, Andrea, 2016. "Downside and upside risk spillovers between exchange rates and stock prices," Journal of Banking & Finance, Elsevier, vol. 62(C), pages 76-96.
    27. Francis X. Diebold & Jinyong Hahn & Anthony S. Tay, 1999. "Multivariate Density Forecast Evaluation And Calibration In Financial Risk Management: High-Frequency Returns On Foreign Exchange," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 661-673, November.
    28. Douglas Rivers & Quang Vuong, 2002. "Model selection tests for nonlinear dynamic models," Econometrics Journal, Royal Economic Society, vol. 5(1), pages 1-39, June.
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    4. Caston Sigauke & Rosinah Mukhodobwane & Wilbert Chagwiza & Winston Garira, 2022. "Asymptotic Dependence Modelling of the BRICS Stock Markets," IJFS, MDPI, vol. 10(3), pages 1-32, July.

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    More about this item

    Keywords

    Equity prices; Dynamic copulas; Tail dependence; Value-at-risk; Conditional value-at-risk; Risk spillovers; C58; F30; F36; G15;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • F30 - International Economics - - International Finance - - - General
    • F36 - International Economics - - International Finance - - - Financial Aspects of Economic Integration
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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