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Liquidity: Considerations of a Portfolio Manager

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  • Laurie Simon Hodrick
  • Pamela C. Moulton

Abstract

This paper examines liquidity and how it affects the behavior of portfolio managers, who account for a significant portion of trading in many assets. We define an asset to be perfectly liquid if a portfolio manager can trade the quantity she desires when she desires at a price not worse than the uninformed expected value. A portfolio manager is limited by both what she needs to attain and the ease with which she can attain it, making her sensitive to three dimensions of liquidity: price, timing, and quantity. Deviations from perfect liquidity in any of these dimensions impose shadow costs on the portfolio manager. By focusing on the trade‐off between sacrificing on price and quantity instead of the canonical price‐time trade‐off, the model yields several novel empirical implications. Understanding a portfolio manager's liquidity considerations provides important insights into the liquidity of many assets and asset classes.

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  • Laurie Simon Hodrick & Pamela C. Moulton, 2009. "Liquidity: Considerations of a Portfolio Manager," Financial Management, Financial Management Association International, vol. 38(1), pages 59-74, March.
  • Handle: RePEc:bla:finmgt:v:38:y:2009:i:1:p:59-74
    DOI: 10.1111/j.1755-053X.2009.01028.x
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    Cited by:

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    2. Chen, Tao, 2019. "Trade-size clustering and price efficiency," Japan and the World Economy, Elsevier, vol. 49(C), pages 195-203.
    3. Mishra, Ajay Kumar & Tripathy, Trilochan, 2018. "Price and trade size clustering: Evidence from the national stock exchange of India," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 63-72.
    4. Fernando Palao & Ángel Pardo Tornero, 2012. "When size matters: Clustering in the European Carbon Market," Working Papers. Serie EC 2012-10, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    5. Richard Borghesi, 2017. "Liquidity, overpricing, and the tactics of informed traders," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 41(4), pages 701-713, October.
    6. Palao, Fernando & Pardo, Ángel, 2014. "What makes carbon traders cluster their orders?," Energy Economics, Elsevier, vol. 43(C), pages 158-165.
    7. Giuseppe Buccheri & Davide Pirino & Luca Trapin, 2021. "Managing liquidity with portfolio staleness," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(1), pages 215-239, June.
    8. Meng, Lei & Verousis, Thanos & ap Gwilym, Owain, 2013. "A substitution effect between price clustering and size clustering in credit default swaps," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 24(C), pages 139-152.
    9. Garvey, Ryan & Huang, Tao & Wu, Fei, 2016. "Why do traders choose dark markets?," Journal of Banking & Finance, Elsevier, vol. 68(C), pages 12-28.
    10. Verousis, Thanos & ap Gwilym, Owain, 2013. "Trade size clustering and the cost of trading at the London Stock Exchange," International Review of Financial Analysis, Elsevier, vol. 27(C), pages 91-102.
    11. Li, Wei & Wang, Steven Shuye, 2010. "Daily institutional trades and stock price volatility in a retail investor dominated emerging market," Journal of Financial Markets, Elsevier, vol. 13(4), pages 448-474, November.
    12. Garvey, Ryan & Wu, Fei, 2014. "Clustering of intraday order-sizes by uninformed versus informed traders," Journal of Banking & Finance, Elsevier, vol. 41(C), pages 222-235.
    13. Jon A. Fulkerson & Timothy B. Riley, 2017. "Mutual Fund Liquidity Costs," Financial Management, Financial Management Association International, vol. 46(2), pages 359-375, June.
    14. Tao Chen, 2021. "Round‐number biases on trading time: Evidence from international markets," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 44(3), pages 469-495, September.

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