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Research toward the Practical Application of Liquidity Risk Evaluation Methods

Author

Listed:
  • Hisata, Yoshifumi

    (Institute for Monetary & Econ Studies, Bank of Japan)

  • Yamai, Yasuhiro

    (Institute for Monetary & Econ Studies, Bank of Japan)

Abstract

This paper proposes a practical framework for the quantification of Liquidity-adjusted Value at Risk ("L-VaR") incorporating the market liquidity of financial products. This framework incorporates the mechanism of the market impact caused by the investor's own dealings through adjusting Value-at-Risk according to the level of market liquidity and the scale of the investor's position. Specifically, the optimal execution strategy for liquidating the investor's entire position is first calculated taking the market impact into account. Then the maximum loss that may be incurred by price fluctuations under optimal execution strategy is calculated as L-VaR. This paper presents a specific model providing a closed-form solution for calculating L-VaR, and examines whether this framework can be applied to the practices of financial risk management by calculating numerical examples. It also demonstrates that this L-VaR calculation framework may be applied under more general conditions, such as (1) when the market impact is uncertain, (2) when the investor's portfolio consists of multiple financial assets, and (3) when there is a non-linear relationship between the market impact and the trading volume.

Suggested Citation

  • Hisata, Yoshifumi & Yamai, Yasuhiro, 2000. "Research toward the Practical Application of Liquidity Risk Evaluation Methods," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 18(2), pages 83-127, December.
  • Handle: RePEc:ime:imemes:v:18:y:2000:i:2:p:83-127
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    File URL: http://www.imes.boj.or.jp/research/papers/english/me18-2-4.pdf
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    References listed on IDEAS

    as
    1. Holthausen, Robert W. & Leftwich, Richard W. & Mayers, David, 1987. "The effect of large block transactions on security prices: A cross-sectional analysis," Journal of Financial Economics, Elsevier, vol. 19(2), pages 237-267, December.
    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-.
    3. Bertsimas, Dimitris & Lo, Andrew W., 1998. "Optimal control of execution costs," Journal of Financial Markets, Elsevier, vol. 1(1), pages 1-50, April.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Stange, Sebastian & Kaserer, Christoph, 2008. "Why and how to integrate liquidity risk into a VaR-framework," CEFS Working Paper Series 2008-10, Technische Universit√§t M√ľnchen (TUM), Center for Entrepreneurial and Financial Studies (CEFS).
    2. repec:rss:jnljfm:v2i1p1 is not listed on IDEAS
    3. Ourir, Awatef & Snoussi, Wafa, 2012. "Markets liquidity risk under extremal dependence: Analysis with VaRs methods," Economic Modelling, Elsevier, vol. 29(5), pages 1830-1836.
    4. Mazin A.M. Al Janabi, 2011. "Modeling coherent trading risk parameters under illiquid market perspective," Studies in Economics and Finance, Emerald Group Publishing, vol. 28(4), pages 301-320, October.

    More about this item

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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