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Linkages between asset classes during the financial crisis, accounting for market microstructure noise and non-synchronous trading


  • Nathaniel Frank

    () (Oxford-Man Institute and Department of Economics, University of Oxford)


In this paper we analyse market co-movements during the global financial crisis. Using high frequency data and accounting for market microstructure noise and non-synchronous trading, interdependencies between differing as-set classes such as equity, FX, fixed income, commodity and energy securities are quantified. To this end multivariate realised kernels and GARCH models are employed. We find that during the current period of market dislocations and times of increased risk aversion, assets have become more correlated when applying these intra-day measures. FX pairs seemingly lead the other variables, but commodities remain entirely unaffected.

Suggested Citation

  • Nathaniel Frank, 2009. "Linkages between asset classes during the financial crisis, accounting for market microstructure noise and non-synchronous trading," Economics Papers 2009-W04, Economics Group, Nuffield College, University of Oxford.
  • Handle: RePEc:nuf:econwp:0904

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    References listed on IDEAS

    1. King, Mervyn A & Wadhwani, Sushil, 1990. "Transmission of Volatility between Stock Markets," Review of Financial Studies, Society for Financial Studies, vol. 3(1), pages 5-33.
    2. Guglielmo Caporale & Nikitas Pittis & Nicola Spagnolo, 2006. "Volatility transmission and financial crises," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 30(3), pages 376-390, September.
    3. Engle, Robert F. & Gallo, Giampiero M., 2006. "A multiple indicators model for volatility using intra-daily data," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 3-27.
    4. Marcello Pericoli & Massimo Sbracia, 2003. "A Primer on Financial Contagion," Journal of Economic Surveys, Wiley Blackwell, vol. 17(4), pages 571-608, September.
    5. Mardi Dungey & Renee Fry & Brenda Gonzalez-Hermosillo & Vance Martin, 2005. "Empirical modelling of contagion: a review of methodologies," Quantitative Finance, Taylor & Francis Journals, vol. 5(1), pages 9-24.
    6. 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.
    7. repec:oxf:wpaper:264 is not listed on IDEAS
    8. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 33(1), pages 125-132.
    9. Heiko Hesse & Nathaniel Frank & Brenda Gonzalez-Hermosillo, 2008. "Transmission of Liquidity Shocks; Evidence from the 2007 Subprime Crisis," IMF Working Papers 08/200, International Monetary Fund.
    10. King, Mervyn & Sentana, Enrique & Wadhwani, Sushil, 1994. "Volatility and Links between National Stock Markets," Econometrica, Econometric Society, vol. 62(4), pages 901-933, July.
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    Cited by:

    1. Magdalena Osinska & Andrzej Dobrzynski & Yochanan Shachmurove, 2016. "Performance Of American And Russian Joint Stock Companies On Financial Market. A Microstructure Perspective," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 11(4), pages 819-851, December.
    2. Sylvia Gottschalk, 2016. "Entropy and credit risk in highly correlated markets," Papers 1604.07042,

    More about this item


    Financial crisis; high frequency data; kernel based estimation;

    JEL classification:

    • 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
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G01 - Financial Economics - - General - - - Financial Crises

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