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Testing for Extreme Volatility Transmission with Realized Volatility Measures

Author

Listed:
  • Christophe Boucher
  • Gilles de Truchis
  • Elena Dumitrescu
  • Sessi Tokpavi

Abstract

This paper proposes a simple and parsimonious semi-parametric testing procedure for variance transmission. Our test focuses on conditional extreme values of the unobserved process of integrated variance since they are of utmost concern for policy makers due to their sudden and destabilizing effects. The test statistic is based on realized measures of variance and has a convenient asymptotic chi-square distribution under the null hypothesis of no Granger causality, which is free of estimation risk. Extensive Monte Carlo simulations show that the test has good small sample size and power properties. An extension to the case of spillovers in quadratic variation is also developed. An empirical application on extreme variance transmission from US to EU equity markets is further proposed. We find that the test performs very well in identifying periods of significant causality in extreme variance, that are subsequently found to be correlated with changes in US monetary policy.

Suggested Citation

  • Christophe Boucher & Gilles de Truchis & Elena Dumitrescu & Sessi Tokpavi, 2017. "Testing for Extreme Volatility Transmission with Realized Volatility Measures," EconomiX Working Papers 2017-20, University of Paris Nanterre, EconomiX.
    • Handle: RePEc:drm:wpaper:2017-20
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    File URL: http://economix.fr/pdf/dt/2017/WP_EcoX_2017-20.pdf
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    References listed on IDEAS

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    1. Cheung, Yin-Wong & Ng, Lilian K., 1996. "A causality-in-variance test and its application to financial market prices," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 33-48.
    2. Aït-Sahalia, Yacine & Mancini, Loriano, 2008. "Out of sample forecasts of quadratic variation," Journal of Econometrics, Elsevier, vol. 147(1), pages 17-33, November.
    3. Christian M. Hafner & Helmut Herwartz, 2008. "Testing for Causality in Variance Usinf Multivariate GARCH Models," Annals of Economics and Statistics, GENES, issue 89, pages 215-241.
    4. McAleer, Michael & Medeiros, Marcelo C., 2008. "A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries," Journal of Econometrics, Elsevier, vol. 147(1), pages 104-119, November.
    5. Andersen, Torben G. & Dobrev, Dobrislav & Schaumburg, Ernst, 2012. "Jump-robust volatility estimation using nearest neighbor truncation," Journal of Econometrics, Elsevier, vol. 169(1), pages 75-93.
    6. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    7. Michael McAleer & Marcelo Medeiros, 2008. "Realized Volatility: A Review," Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 10-45.
    8. 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.
    9. Christensen, Kim & Oomen, Roel & Podolskij, Mark, 2010. "Realised quantile-based estimation of the integrated variance," Journal of Econometrics, Elsevier, vol. 159(1), pages 74-98, November.
    10. Ole E. Barndorff-Nielsen, 2004. "Power and Bipower Variation with Stochastic Volatility and Jumps," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 1-37.
    11. Engle, Robert F & Ito, Takatoshi & Lin, Wen-Ling, 1990. "Meteor Showers or Heat Waves? Heteroskedastic Intra-daily Volatility in the Foreign Exchange Market," Econometrica, Econometric Society, vol. 58(3), pages 525-542, May.
    12. Baele, Lieven, 2005. "Volatility Spillover Effects in European Equity Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 40(2), pages 373-401, June.
    13. Filip Žikeš & Jozef Baruník, 2016. "Semi-parametric Conditional Quantile Models for Financial Returns and Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 14(1), pages 185-226.
    14. Sun, Yixiao, 2004. "A CONVERGENT t-STATISTIC IN SPURIOUS REGRESSIONS," Econometric Theory, Cambridge University Press, vol. 20(5), pages 943-962, October.
    15. repec:hal:journl:peer-00732538 is not listed on IDEAS
    16. Bibinger, Markus & Winkelmann, Lars, 2015. "Econometrics of co-jumps in high-frequency data with noise," Journal of Econometrics, Elsevier, vol. 184(2), pages 361-378.
    17. Lorenzo Cappiello & Bruno Gérard & Arjan Kadareja & Simone Manganelli, 2014. "Measuring Comovements by Regression Quantiles," Journal of Financial Econometrics, Oxford University Press, vol. 12(4), pages 645-678.
    18. Charlotte Christiansen & Maik Schmeling & Andreas Schrimpf, 2012. "A comprehensive look at financial volatility prediction by economic variables," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(6), pages 956-977, September.
    19. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2008. "Designing Realized Kernels to Measure the ex post Variation of Equity Prices in the Presence of Noise," Econometrica, Econometric Society, vol. 76(6), pages 1481-1536, November.
    20. Tim Bollerslev & Julia Litvinova & George Tauchen, 2006. "Leverage and Volatility Feedback Effects in High-Frequency Data," Journal of Financial Econometrics, Oxford University Press, vol. 4(3), pages 353-384.
    21. Chan, Wing H & Maheu, John M, 2002. "Conditional Jump Dynamics in Stock Market Returns," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 377-389, July.
    22. Viktor Todorov & George Tauchen, 2011. "Volatility Jumps," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(3), pages 356-371, July.
    23. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
    24. Souček, Michael & Todorova, Neda, 2014. "Realized volatility transmission: The role of jumps and leverage effects," Economics Letters, Elsevier, vol. 122(2), pages 111-115.
    25. Jeong, Kiho & Härdle, Wolfgang K. & Song, Song, 2012. "A Consistent Nonparametric Test For Causality In Quantile," Econometric Theory, Cambridge University Press, vol. 28(4), pages 861-887, August.
    26. Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-862, November.
    27. Hong, Yongmiao, 2001. "A test for volatility spillover with application to exchange rates," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 183-224, July.
    28. Hansen, Peter R. & Lunde, Asger, 2006. "Realized Variance and Market Microstructure Noise," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 127-161, April.
    29. Gnabo, Jean-Yves & Hvozdyk, Lyudmyla & Lahaye, Jérôme, 2014. "System-wide tail comovements: A bootstrap test for cojump identification on the S&P 500, US bonds and currencies," Journal of International Money and Finance, Elsevier, vol. 48(PA), pages 147-174.
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    Cited by:

    1. repec:uts:finphd:39 is not listed on IDEAS
    2. Fei Su, 2018. "Essays on Price Discovery and Volatility Dynamics in the Foreign Exchange Market," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 2-2018, January-A.
    3. repec:uts:finphd:38 is not listed on IDEAS

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    More about this item

    Keywords

    Extreme volatility transmission; Granger causality; Integrated variance; Realized variance; Semi-parametric test; Financial contagion.;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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