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False News, Informational Efficiency, and Price Reversals

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  • J. Dugast
  • T. Foucault

Abstract

Speculators can discover whether a signal is true or false by processing it but this takes time. Hence they face a trade-off between trading fast on a signal (i.e., before processing it), at the risk of trading on a false news, or trading after processing the signal, at the risk that prices already reflect their information. The number of speculators who choose to trade fast increases with news reliability and decreases with the cost of fast trading technologies. We derive testable implications for the effects of these variables on (i) the value of information, (ii) patterns in returns and trades, (iii) the frequency of price reversals in a stock, and (iv) informational efficiency. Cheaper fast trading technologies simultaneously raise informational efficiency and the frequency of ``mini-flash crashes": large price movements that revert quickly.

Suggested Citation

  • J. Dugast & T. Foucault, 2014. "False News, Informational Efficiency, and Price Reversals," Working papers 513, Banque de France.
    • Handle: RePEc:bfr:banfra:513
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    References listed on IDEAS

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    1. Froot, Kenneth A & Scharftstein, David S & Stein, Jeremy C, 1992. "Herd on the Street: Informational Inefficiencies in a Market with Short-Term Speculation," Journal of Finance, American Finance Association, vol. 47(4), pages 1461-1484, September.
    2. Biais, Bruno & Foucault, Thierry & Moinas, Sophie, 2015. "Equilibrium fast trading," Journal of Financial Economics, Elsevier, vol. 116(2), pages 292-313.
    3. Back, Kerry & Pedersen, Hal, 1998. "Long-lived information and intraday patterns," Journal of Financial Markets, Elsevier, vol. 1(3-4), pages 385-402, September.
    4. Glosten, Lawrence R. & Milgrom, Paul R., 1985. "Bid, ask and transaction prices in a specialist market with heterogeneously informed traders," Journal of Financial Economics, Elsevier, vol. 14(1), pages 71-100, March.
    5. repec:bla:jfinan:v:53:y:1998:i:6:p:1839-1885 is not listed on IDEAS
    6. Minh Chau & Dimitri Vayanos, 2008. "Strong-Form Efficiency with Monopolistic Insiders," The Review of Financial Studies, Society for Financial Studies, vol. 21(5), pages 2275-2306, September.
    7. Hirshleifer, David & Subrahmanyam, Avanidhar & Titman, Sheridan, 1994. "Security Analysis and Trading Patterns When Some Investors Receive Information before Others," Journal of Finance, American Finance Association, vol. 49(5), pages 1665-1698, December.
    8. Jonathan Brogaard & Terrence Hendershott & Ryan Riordan, 2014. "High-Frequency Trading and Price Discovery," The Review of Financial Studies, Society for Financial Studies, vol. 27(8), pages 2267-2306.
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    Citations

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    Cited by:

    1. Bizzozero, Paolo & Flepp, Raphael & Franck, Egon, 2018. "The effect of fast trading on price discovery and efficiency: Evidence from a betting exchange," Journal of Economic Behavior & Organization, Elsevier, vol. 156(C), pages 126-143.
    2. Albert S. Kyle & Anna Obizhaeva & Yajun Wang, 2016. "Smooth Trading with Overconfidence and Market Power," Working Papers w0226, New Economic School (NES).
    3. Alexandru-Ioan Stan, 2018. "Computational speed and high-frequency trading profitability: an ecological perspective," Electronic Markets, Springer;IIM University of St. Gallen, vol. 28(3), pages 381-395, August.
    4. Michael J. Aitken & Angelo Aspris & Sean Foley & Frederick H. de B. Harris, 2018. "Market Fairness: The Poor Country Cousin of Market Efficiency," Journal of Business Ethics, Springer, vol. 147(1), pages 5-23, January.
    5. Massa, Massimo & von Beschwitz, Bastian & Keim, Donald B, 2015. "First to ?Read? the News: News Analytics and Institutional Trading," CEPR Discussion Papers 10534, C.E.P.R. Discussion Papers.
    6. Jun Aoyagi, 2019. "Strategic Speed Choice by High-Frequency Traders under Speed Bumps," ISER Discussion Paper 1050, Institute of Social and Economic Research, The University of Osaka.
    7. Zachary S Levine & Scott A Hale & Luciano Floridi, 2017. "The October 2014 United States Treasury bond flash crash and the contributory effect of mini flash crashes," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-14, November.
    8. Albert S Kyle & Anna A Obizhaeva & Yajun Wang, 2018. "Smooth Trading with Overconfidence and Market Power," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 85(1), pages 611-662.
    9. Md Miran Hossain & Babak Mammadov & Hamid Vakilzadeh, 2022. "Wisdom of the crowd and stock price crash risk: evidence from social media," Review of Quantitative Finance and Accounting, Springer, vol. 58(2), pages 709-742, February.
    10. Jean-Edouard Colliard, 2017. "Catching Falling Knives: Speculating on Liquidity Shocks," Management Science, INFORMS, vol. 63(8), pages 2573-2591, August.
    11. Steffen, Viktoria, 2023. "A literature review on extreme price movements with reversal," Journal of Behavioral and Experimental Finance, Elsevier, vol. 38(C).

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    More about this item

    Keywords

    news; high-frequency trading; price reversals; informational efficiency; mini-flash crashes.;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • 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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