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Price Discovery without Trading: Evidence from Limit Orders




We analyze the contribution to price discovery of market and limit orders by high‐frequency traders (HFTs) and non‐HFTs. While market orders have a larger individual price impact, limit orders are far more numerous. This results in price discovery occurring predominantly through limit orders. HFTs submit the bulk of limit orders and these limit orders provide most of the price discovery. Submissions of limit orders and their contribution to price discovery fall with volatility due to changes in HFTs’ behavior. Consistent with adverse selection arising from faster reactions to public information, HFTs’ informational advantage is partially explained by public information.

Suggested Citation

  • Jonathan Brogaard & Terrence Hendershott & Ryan Riordan, 2019. "Price Discovery without Trading: Evidence from Limit Orders," Journal of Finance, American Finance Association, vol. 74(4), pages 1621-1658, August.
  • Handle: RePEc:bla:jfinan:v:74:y:2019:i:4:p:1621-1658
    DOI: 10.1111/jofi.12769

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    Cited by:

    1. Nilabhra Bhattacharya & Bidisha Chakrabarty & Xu (Frank) Wang, 0. "High-frequency traders and price informativeness during earnings announcements," Review of Accounting Studies, Springer, vol. 0, pages 1-44.
    2. Bellia, Mario & Christensen, Kim & Kolokolov, Aleksey & Pelizzon, Loriana & Renò, Roberto, 2020. "High-frequency trading during flash crashes: Walk of fame or hall of shame?," SAFE Working Paper Series 270, Leibniz Institute for Financial Research SAFE.
    3. Sudhanshu Pani, 2020. "A Theory of 'Auction as a Search' in speculative markets," Papers 2006.00775,
    4. Patel, Vinay & Putniņš, Tālis J. & Michayluk, David & Foley, Sean, 2020. "Price discovery in stock and options markets," Journal of Financial Markets, Elsevier, vol. 47(C).
    5. Nawn, Samarpan & Banerjee, Ashok, 2019. "Do the limit orders of proprietary and agency algorithmic traders discover or obscure security prices?," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 109-125.
    6. Lien, Donald & Hung, Pi-Hsia & Lin, Zong-Wei, 2020. "Whose trades move stock prices? Evidence from the Taiwan Stock Exchange," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 25-50.
    7. Robert Garrison & Pankaj Jain & Mark Paddrik, 2019. "Cross-Asset Market Order Flow, Liquidity, and Price Discovery," Working Papers 19-04, Office of Financial Research, US Department of the Treasury.
    8. Roberto Riccò & Barbara Rindi & Duane J. Seppi, 2020. "Information, Liquidity, and Dynamic Limit Order Markets," Working Papers 660, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    9. Corey Garriot & Ryan Riordan, 2020. "Trading on Long-term Information," Staff Working Papers 20-20, Bank of Canada.
    10. Aït-Sahalia, Yacine & Brunetti, Celso, 2020. "High frequency traders and the price process," Journal of Econometrics, Elsevier, vol. 217(1), pages 20-45.
    11. Yamamoto, Ryuichi, 2020. "Limit order submission risks, order choice, and tick size," Pacific-Basin Finance Journal, Elsevier, vol. 59(C).
    12. Comerton-Forde, Carole & Grégoire, Vincent & Zhong, Zhuo, 2019. "Inverted fee structures, tick size, and market quality," Journal of Financial Economics, Elsevier, vol. 134(1), pages 141-164.
    13. Philip, R., 2020. "Estimating permanent price impact via machine learning," Journal of Econometrics, Elsevier, vol. 215(2), pages 414-449.
    14. Mynbaev, Kairat, 2020. "Using full limit order book for price jump prediction," MPRA Paper 101684, University Library of Munich, Germany.

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