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Granger causality in risk and detection of extreme risk spillover between financial markets

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  • Hong, Yongmiao
  • Liu, Yanhui
  • Wang, Shouyang
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    Abstract

    Controlling and monitoring extreme downside market risk are important for financial risk management and portfolio/investment diversification. In this paper, we introduce a new concept of Granger causality in risk and propose a class of kernel-based tests to detect extreme downside risk spillover between financial markets, where risk is measured by the left tail of the distribution or equivalently by the Value at Risk (VaR). The proposed tests have a convenient asymptotic standard normal distribution under the null hypothesis of no Granger causality in risk. They check a large number of lags and thus can detect risk spillover that occurs with a time lag or that has weak spillover at each lag but carries over a very long distributional lag. Usually, tests using a large number of lags may have low power against alternatives of practical importance, due to the loss of a large number of degrees of freedom. Such power loss is fortunately alleviated for our tests because our kernel approach naturally discounts higher order lags, which is consistent with the stylized fact that today's financial markets are often more influenced by the recent events than the remote past events. A simulation study shows that the proposed tests have reasonable size and power against a variety of empirically plausible alternatives in finite samples, including the spillover from the dynamics in mean, variance, skewness and kurtosis respectively. In particular, nonuniform weighting delivers better power than uniform weighting and a Granger-type regression procedure. The proposed tests are useful in investigating large comovements between financial markets such as financial contagions. An application to the Eurodollar and Japanese Yen highlights the merits of our approach.

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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Econometrics.

    Volume (Year): 150 (2009)
    Issue (Month): 2 (June)
    Pages: 271-287

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    Handle: RePEc:eee:econom:v:150:y:2009:i:2:p:271-287

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    Web page: http://www.elsevier.com/locate/jeconom

    Related research

    Keywords: Cross-spectrum Extreme downside risk Financial contagion Granger causality in risk Nonlinear time series Risk management Value at Risk;

    References

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    Cited by:
    1. Magdalena Osinska, 2011. "On the Interpretation of Causality in Granger’s Sense," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 11, pages 129-140.
    2. de Araújo, André da Silva & Garcia, Maria Teresa Medeiros, 2013. "Risk contagion in the north-western and southern European stock markets," Journal of Economics and Business, Elsevier, vol. 69(C), pages 1-34.
    3. Bauer, Dietmar & Maynard, Alex, 2012. "Persistence-robust surplus-lag Granger causality testing," Journal of Econometrics, Elsevier, vol. 169(2), pages 293-300.
    4. Bertrand Candelon & Sessi Tokpavi, 2014. "A Nonparametric Test for Grangercausality in Distribution with Application to Financial Contagion," Working Papers 2014-162, Department of Research, Ipag Business School.
    5. Marc Joëts, 2013. "Energy price transmissions during extreme movements," Working Papers 2013-028, Department of Research, Ipag Business School.
    6. Bertrand Candelon & Marc Joëts & Sessi Tokpavi, 2012. "Testing for crude oil markets globalization during extreme price movements," EconomiX Working Papers 2012-28, University of Paris West - Nanterre la Défense, EconomiX.
    7. Dietmar Bauer & Alex Maynard, 2010. "Persistence-robust Granger causality testing," Working Papers 1011, University of Guelph, Department of Economics and Finance.
    8. Jian Zhou, 2013. "Extreme risk spillover among international REIT markets," Applied Financial Economics, Taylor & Francis Journals, vol. 23(2), pages 91-103, January.
    9. Yu, Jing-Rung & Lee, Wen-Yi, 2011. "Portfolio rebalancing model using multiple criteria," European Journal of Operational Research, Elsevier, vol. 209(2), pages 166-175, March.
    10. repec:ipg:wpaper:28 is not listed on IDEAS
    11. Candelon, Bertrand & Joëts, Marc & Tokpavi, Sessi, 2013. "Testing for Granger causality in distribution tails: An application to oil markets integration," Economic Modelling, Elsevier, vol. 31(C), pages 276-285.

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