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Market liquidity as dynamic factors

Author

Listed:
  • Marc Hallin
  • Charles Mathias
  • Hugues Pirotte
  • David Veredas

Abstract

We study market liquidity via daily close relative spreads and daily traded volumes in a sample of 426 S&P500 constituents recorded over the years 2004-2006, a period of “normal” liquidity conditions. We use recent results on the Generalized Dynamic Factor Model (GDFM) with block structure to provide a sound definition of unobservable market liquidity and to assess the complementarity of those two liquidity measures. The advantage of defining market liquidity as dynamic factors is that, contrary to other definitions that can be found in the literature, it tackles time dependence and commonness at the same time, without making any restrictive assumptions on the underlying data generating process. Both relative spread and volume in the dataset under study appear to be driven by the same one-dimensional common shocks, which therefore naturally qualify as the unobservable market liquidity shocks.

Suggested Citation

  • Marc Hallin & Charles Mathias & Hugues Pirotte & David Veredas, 2011. "Market liquidity as dynamic factors," Working Papers ECARES 163, 42-50, ULB -- Universite Libre de Bruxelles.
    • Handle: RePEc:eca:wpaper:2013/230740
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    Cited by:

    1. Forni, Mario & Cavicchioli, Maddalena & Lippi, Marco & Zaffaroni, Paolo, 2016. "Eigenvalue Ratio Estimators for the Number of Common Factors," CEPR Discussion Papers 11440, C.E.P.R. Discussion Papers.
    2. Forni, Mario & Hallin, Marc & Lippi, Marco & Zaffaroni, Paolo, 2015. "Dynamic factor models with infinite-dimensional factor spaces: One-sided representations," Journal of Econometrics, Elsevier, vol. 185(2), pages 359-371.
    3. Mario Forni & Marc Hallin & Marco Lippi & Paolo Zaffaroni, 2011. "One-Sided Representations of Generalized Dynamic Factor Models," EIEF Working Papers Series 1106, Einaudi Institute for Economics and Finance (EIEF), revised Mar 2011.
    4. Chang, Ya-Ting & Gau, Yin-Feng & Hsu, Chih-Chiang, 2017. "Liquidity Commonality in Foreign Exchange Markets During the Global Financial Crisis and the Sovereign Debt Crisis: Effects of Macroeconomic and Quantitative Easing Announcements," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 172-192.
    5. Hagströmer, Björn & Anderson, Richard G. & Binner, Jane & Nilsson, Birger, 2009. "Dynamics in Systematic Liquidity," Working Papers 2009:7, Lund University, Department of Economics.
    6. Ergemen, Yunus Emre, 2023. "Parametric estimation of long memory in factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1483-1499.
    7. Anderson, Richard G. & Binner, Jane M. & Hagströmer, Björn & Nilsson, Birger, 2013. "Does Commonality in Illiquidity Matter to Investors?," Working Papers 2013:24, Lund University, Department of Economics.
    8. Ergemen, Yunus Emre & Rodríguez-Caballero, C. Vladimir, 2023. "Estimation of a dynamic multi-level factor model with possible long-range dependence," International Journal of Forecasting, Elsevier, vol. 39(1), pages 405-430.
    9. Yunus Emre Ergemen, 2022. "Parametric Estimation of Long Memory in Factor Models," CREATES Research Papers 2022-10, Department of Economics and Business Economics, Aarhus University.
    10. Priyanka Naik & Y. V. Reddy, 2021. "Stock Market Liquidity: A Literature Review," SAGE Open, , vol. 11(1), pages 21582440209, January.
    11. Hallin, Marc & Liska, Roman, 2011. "Dynamic factors in the presence of blocks," Journal of Econometrics, Elsevier, vol. 163(1), pages 29-41, July.
    12. Barigozzi, Matteo & Hallin, Marc & Luciani, Matteo & Zaffaroni, Paolo, 2024. "Inferential theory for generalized dynamic factor models," Journal of Econometrics, Elsevier, vol. 239(2).
    13. Berger Tino & Hienzsch Sebastian, 2025. "Which Global Cycle? A Stochastic Factor Selection Approach for Global Macro-Financial Cycles," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 29(5), pages 541-559.
    14. Rubia, Antonio & Sanchis-Marco, Lidia, 2013. "On downside risk predictability through liquidity and trading activity: A dynamic quantile approach," International Journal of Forecasting, Elsevier, vol. 29(1), pages 202-219.
    15. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Working Papers ECARES 2023-15, ULB -- Universite Libre de Bruxelles.
    16. Lübbers, Johannes & Posch, Peter N., 2016. "Commodities' common factor: An empirical assessment of the markets' drivers," Journal of Commodity Markets, Elsevier, vol. 4(1), pages 28-40.

    More about this item

    Keywords

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    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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