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The Night and Day of Amihud’s (2002) Liquidity Measure

Author

Listed:
  • Barardehi, Yashar H.

    (Argyros School of Business & Economics, Chapman University)

  • Bernhardt, Dan

    (University of Illinois & University of Warwick)

  • Ruchti, Thomas G.

    (Tepper School of Business, Carnegie Mellon University)

  • Weidenmier, Marc

    (Argyros School of Business & Economics, Chapman University and NBER.)

Abstract

Amihud’s (2002) stock (il)liquidity measure averages the daily ratio of absolute closeto-close return to dollar volume, including overnight returns, while trading volumes come from regular trading hours. Our modified measure addresses this mis-match by using open-to-close returns. It better explains cross-sections of returns, doubling estimated liquidity premia over 1964–2017. Using non-synchronous trading near close as an instrument reveals that overnight returns are primarily information-driven and orthogonal to price impacts of trading. Thus, including them in liquidity proxies magnifies measurement error, understating liquidity premia. Our modification especially matters when applications in finance and accounting render use of intraday data infeasible/undesirable.

Suggested Citation

  • Barardehi, Yashar H. & Bernhardt, Dan & Ruchti, Thomas G. & Weidenmier, Marc, 2019. "The Night and Day of Amihud’s (2002) Liquidity Measure," The Warwick Economics Research Paper Series (TWERPS) 1211, University of Warwick, Department of Economics.
  • Handle: RePEc:wrk:warwec:1211
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    Cited by:

    1. Zeynep Cobandag Guloglu & Cumhur Ekinci, 2022. "Liquidity measurement: A comparative review of the literature with a focus on high frequency," Journal of Economic Surveys, Wiley Blackwell, vol. 36(1), pages 41-74, February.
    2. Ee, Mong Shan & Hasan, Iftekhar & Huang, He, 2022. "Stock liquidity and corporate labor investment," Journal of Corporate Finance, Elsevier, vol. 72(C).
    3. Kim, Jinyong & Kim, Yongsik, 2023. "Which stock price component drives the Amihud illiquidity premium?," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    4. Teplova, Tamara & Sokolova, Tatiana & Kissa, David, 2023. "Revealing stock liquidity determinants by means of explainable AI: The role of ESG before and during the COVID-19 pandemic," Resources Policy, Elsevier, vol. 86(PB).
    5. Sifat, Imtiaz & Zarei, Alireza & Hosseini, Seyedmehdi & Bouri, Elie, 2022. "Interbank liquidity risk transmission to large emerging markets in crisis periods," International Review of Financial Analysis, Elsevier, vol. 82(C).

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    More about this item

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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