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Market Liquidity and Flow-driven Risk

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  • Prachi Deuskar
  • Timothy C. Johnson

Abstract

Using a unique dataset of trades and limit orders for S&P 500 futures, we decompose the aggregate risk into a component driven by the impact of net market orders and a component unrelated to net orders. The first component--flow-driven risk--is large, accounting for approximately 50% of market variance, and it is not transient. This risk represents the joint effect of net trade demand and the price impact of that demand--i.e., illiquidity. We find that flows are largely unpredictable, and lagged flows have no price impact. Flow-driven risk is time varying because price impact is highly variable. Illiquidity rises with market volatility, but not with flow uncertainty. Net selling increases illiquidity, which amplifies downside flow-driven risk. The findings are consistent with flow-driven shocks resulting from fluctuations in aggregate risk-bearing capacity. Under this interpretation, investors with constant risk tolerance should trade against such shocks (i.e., "supply liquidity") to achieve substantial utility gains. Quantitatively accounting for the scale of flow-driven risk poses a major challenge for asset pricing theory. The Author 2011. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com., Oxford University Press.

Suggested Citation

  • Prachi Deuskar & Timothy C. Johnson, 2011. "Market Liquidity and Flow-driven Risk," Review of Financial Studies, Society for Financial Studies, vol. 24(3), pages 721-753.
  • Handle: RePEc:oup:rfinst:v:24:y:2011:i:3:p:721-753
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    File URL: http://hdl.handle.net/10.1093/rfs/hhq132
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    Cited by:

    1. repec:eee:ecolet:v:159:y:2017:i:c:p:65-68 is not listed on IDEAS
    2. Brunetti, Celso & Büyükşahin, Bahattin & Harris, Jeffrey H., 2016. "Speculators, Prices, and Market Volatility," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 51(05), pages 1545-1574, October.
    3. Marshall, Ben R. & Nguyen, Nhut H. & Visaltanachoti, Nuttawat, 2013. "ETF arbitrage: Intraday evidence," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3486-3498.
    4. Opschoor, Anne & Taylor, Nick & van der Wel, Michel & van Dijk, Dick, 2014. "Order flow and volatility: An empirical investigation," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 185-201.
    5. repec:eee:finlet:v:21:y:2017:i:c:p:264-271 is not listed on IDEAS
    6. Algieri, Bernardina, 2012. "Price Volatility, Speculation and Excessive Speculation in Commodity Markets: sheep or shepherd behaviour?," Discussion Papers 124390, University of Bonn, Center for Development Research (ZEF).
    7. repec:eee:finmar:v:38:y:2018:i:c:p:14-38 is not listed on IDEAS
    8. Craig W. Holden & Stacey Jacobsen & Avanidhar Subrahmanyam, 2014. "The Empirical Analysis of Liquidity," Foundations and Trends(R) in Finance, now publishers, vol. 8(4), pages 263-365, December.
    9. Chung, Dennis Y. & Hrazdil, Karel, 2012. "Speed of convergence to market efficiency: The role of ECNs," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 702-720.
    10. Johnson, Timothy C., 2016. "Rethinking reversals," Journal of Financial Economics, Elsevier, vol. 120(2), pages 211-228.

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