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Measuring market liquidity risk - which model works best?

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Abstract

Market liquidity risk, the difficulty or cost of trading assets in crises, has been recognized as an important factor in risk management. The literature has already proposed several models to include liquidity risk in the standard Value-at-Risk framework. While theoretical comparisons between those models have been conducted, their empirical performance has yet to be benchmarked. This paper performs comparative back-testings of daily risk forecasts for a large selection of liquidity risk models. In a comprehensive 5.5-year stock sample we show which model provides the most accurate results and provide detailed recommendations about which model is most suitable in a specific situation.

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  • Ernst, Cornelia & Stange, Sebastian & Kaserer, Christoph, 2012. "Measuring market liquidity risk - which model works best?," Journal of Financial Transformation, Capco Institute, vol. 35, pages 133-146.
    • Handle: RePEc:ris:jofitr:1534
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    1. Bervas, A., 2006. "Market liquidity and its incorporation into risk management," Financial Stability Review, Banque de France, issue 8, pages 63-79, May.
    2. Anil Bangia & Francis X. Diebold & Til Schuermann & John D. Stroughair, 1998. "Modeling Liquidity Risk With Implications for Traditional Market Risk Measurement and Management," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-062, New York University, Leonard N. Stern School of Business-.
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    4. Pierre Giot & Joachim Grammig, 2006. "How large is liquidity risk in an automated auction market?," Empirical Economics, Springer, vol. 30(4), pages 867-887, January.
    5. Timotheos Angelidis & Alexandros Benos, 2006. "Liquidity adjusted value-at-risk based on the components of the bid-ask spread," Applied Financial Economics, Taylor & Francis Journals, vol. 16(11), pages 835-851.
    6. Pierre Giot & Joachim Grammig, 2008. "How large is liquidity risk in an automated auction market?," Studies in Empirical Economics, in: Luc Bauwens & Winfried Pohlmeier & David Veredas (ed.), High Frequency Financial Econometrics, pages 111-131, Springer.
    7. Robert Almgren, 2003. "Optimal execution with nonlinear impact functions and trading-enhanced risk," Applied Mathematical Finance, Taylor & Francis Journals, vol. 10(1), pages 1-18.
    8. Luca Erzegovesi, 2002. "VaR and Liquidity Risk.Impact on Market Behaviour and Measurement Issues," Alea Tech Reports 014, Department of Computer and Management Sciences, University of Trento, Italy, revised 14 Jun 2008.
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    Cited by:

    1. Becchetti, L. & Ferrari, M. & Trenta, U., 2014. "The impact of the French Tobin tax," Journal of Financial Stability, Elsevier, vol. 15(C), pages 127-148.
    2. Kylie-Anne Richards & Gareth W. Peters & William Dunsmuir, 2015. "Heavy-tailed features and dependence in limit order book volume profiles in futures markets," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 2(03), pages 1-56.
    3. Holmberg, Ulf, 2012. "Essays on Credit Markets and Banking," Umeå Economic Studies 840, Umeå University, Department of Economics.
    4. Strašek Sebastjan & Bricelj Bor, 2016. "Spread and Liquidity Issues: A markets comparison," Naše gospodarstvo/Our economy, Sciendo, vol. 62(1), pages 3-11, March.

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    More about this item

    Keywords

    market liquidity; market liquidity risk; risk management; liquidity risk; Value-at-Risk; liquidity risk model;
    All these keywords.

    JEL classification:

    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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