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Intrinsic Liquidity in Conditional Volatility Models


  • Serge Darolles
  • Gaëlle Le Fol
  • Christian Francq
  • Jean-Michel Zakoïan


Until recently the liquidity of financial assets has typically been viewed as a second-order consideration. Liquidity was frequently associated with simple transaction costs that impose ? temporary if any ? effect on asset prices, and whose shocks could be easily diversified away. Yet the evidence ? especially the recent liquidity crisis ? suggests that liquidity is now a primary concern. This paper aims at disentangling market risk and liquidity risk in the context of conditional volatility models. Our approach allows the isolation of the intrisic liquidity of any asset, and thus makes it possible to deduce a liquidity risk even when volumes are not observed.

Suggested Citation

  • Serge Darolles & Gaëlle Le Fol & Christian Francq & Jean-Michel Zakoïan, 2016. "Intrinsic Liquidity in Conditional Volatility Models," Annals of Economics and Statistics, GENES, issue 123-124, pages 225-245.
  • Handle: RePEc:adr:anecst:y:2016:i:123-124:p:225-245 DOI: 10.15609/annaeconstat2009.123-124.0225

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    References listed on IDEAS

    1. Golosnoy, Vasyl & Gribisch, Bastian & Liesenfeld, Roman, 2012. "The conditional autoregressive Wishart model for multivariate stock market volatility," Journal of Econometrics, Elsevier, vol. 167(1), pages 211-223.
    2. Luc Bauwens & Christian M. Hafner & Diane Pierret, 2013. "Multivariate Volatility Modeling Of Electricity Futures," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(5), pages 743-761, August.
    3. Colacito, Riccardo & Engle, Robert F. & Ghysels, Eric, 2011. "A component model for dynamic correlations," Journal of Econometrics, Elsevier, vol. 164(1), pages 45-59, September.
    4. Laurent, Sébastien & Rombouts, Jeroen V.K. & Violante, Francesco, 2013. "On loss functions and ranking forecasting performances of multivariate volatility models," Journal of Econometrics, Elsevier, vol. 173(1), pages 1-10.
    5. BAUWENS, Luc & STORTI, Giuseppe & VIOLANTE, Francesco, 2012. "Dynamic conditional correlation models for realized covariance matrices," CORE Discussion Papers 2012060, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2012. "Multivariate high‐frequency‐based volatility (HEAVY) models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(6), pages 907-933, September.
    7. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
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    More about this item


    GARCH; Liquidity; Quasi-Maximum Likelihood; Risk measures; Value-at-Risk;

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions


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