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

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  • Nathaniel Frank

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

Abstract

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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    File URL: http://www.nuffield.ox.ac.uk/economics/papers/2009/w4/HF%20Working%20Paper.pdf
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    References listed on IDEAS

    as
    1. King, Mervyn A & Wadhwani, Sushil, 1990. "Transmission of Volatility between Stock Markets," The 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.
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    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. Mr. Heiko Hesse & Nathaniel Frank & Ms. Brenda Gonzalez-Hermosillo, 2008. "Transmission of Liquidity Shocks: Evidence from the 2007 Subprime Crisis," IMF Working Papers 2008/200, International Monetary Fund.
    6. 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.
    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, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
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    Cited by:

    1. Sylvia Gottschalk, 2016. "Entropy and credit risk in highly correlated markets," Papers 1604.07042, arXiv.org.
    2. Seyfi, Seyed Mohammad Sina & Sharifi, Azin & Arian, Hamidreza, 2021. "Portfolio Value-at-Risk and expected-shortfall using an efficient simulation approach based on Gaussian Mixture Model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 190(C), pages 1056-1079.
    3. Seyed Mohammad Sina Seyfi & Azin Sharifi & Hamidreza Arian, 2020. "Portfolio Risk Measurement Using a Mixture Simulation Approach," Papers 2011.07994, arXiv.org.
    4. 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.
    5. Gottschalk, Sylvia, 2017. "Entropy measure of credit risk in highly correlated markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 478(C), pages 11-19.

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    More about this item

    Keywords

    Financial crisis; high frequency data; kernel based estimation;
    All these keywords.

    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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