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Fast and slow informed trading

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  • Roşu, Ioanid

Abstract

I develop a model in which traders receive a stream of private signals, and differ in their information processing speed. In equilibrium, the fast traders (FTs) quickly reveal a large fraction of their information. If a FT is averse to holding inventory, his optimal strategy changes considerably as his aversion crosses a threshold. He no longer takes long-term bets on the asset value, gets most of his profits in cash, and generates a “hot potato” effect: after trading on information, the FT quickly unloads part of his inventory to slower traders. The results match evidence about high-frequency traders.

Suggested Citation

  • Roşu, Ioanid, 2019. "Fast and slow informed trading," Journal of Financial Markets, Elsevier, vol. 43(C), pages 1-30.
    • Handle: RePEc:eee:finmar:v:43:y:2019:i:c:p:1-30
    DOI: 10.1016/j.finmar.2019.02.003
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    References listed on IDEAS

    as
    1. 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.
    2. repec:bla:jfinan:v:59:y:2004:i:1:p:339-390 is not listed on IDEAS
    3. Madhavan, Ananth & Smidt, Seymour, 1993. "An Analysis of Changes in Specialist Inventories and Quotations," Journal of Finance, American Finance Association, vol. 48(5), pages 1595-1628, December.
    4. Holden, Craig W & Subrahmanyam, Avanidhar, 1992. "Long-Lived Private Information and Imperfect Competition," Journal of Finance, American Finance Association, vol. 47(1), pages 247-270, March.
    5. Songzi Du & Haoxiang Zhu, 2017. "What is the Optimal Trading Frequency in Financial Markets?," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 84(4), pages 1606-1651.
    6. Albuquerque, Rui & Miao, Jianjun, 2014. "Advance information and asset prices," Journal of Economic Theory, Elsevier, vol. 149(C), pages 236-275.
    7. Biais, Bruno & Foucault, Thierry & Moinas, Sophie, 2015. "Equilibrium fast trading," Journal of Financial Economics, Elsevier, vol. 116(2), pages 292-313.
    8. Baron, Matthew & Brogaard, Jonathan & Hagströmer, Björn & Kirilenko, Andrei, 2019. "Risk and Return in High-Frequency Trading," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 54(3), pages 993-1024, June.
    9. Thierry Foucault & Johan Hombert & Ioanid Roşu, 2016. "News Trading and Speed," Journal of Finance, American Finance Association, vol. 71(1), pages 335-382, February.
    10. Andrei Kirilenko & Albert S. Kyle & Mehrdad Samadi & Tugkan Tuzun, 2017. "The Flash Crash: High-Frequency Trading in an Electronic Market," Journal of Finance, American Finance Association, vol. 72(3), pages 967-998, June.
    11. Ekkehart Boehmer & Dan Li & Gideon Saar, 2018. "The Competitive Landscape of High-Frequency Trading Firms," The Review of Financial Studies, Society for Financial Studies, vol. 31(6), pages 2227-2276.
    12. Back, Kerry & Pedersen, Hal, 1998. "Long-lived information and intraday patterns," Journal of Financial Markets, Elsevier, vol. 1(3-4), pages 385-402, September.
    13. Hasbrouck, Joel & Saar, Gideon, 2013. "Low-latency trading," Journal of Financial Markets, Elsevier, vol. 16(4), pages 646-679.
    14. RenÈ Caldentey & Ennio Stacchetti, 2010. "Insider Trading With a Random Deadline," Econometrica, Econometric Society, vol. 78(1), pages 245-283, January.
    15. Albert J. Menkveld, 2016. "The Economics of High-Frequency Trading: Taking Stock," Annual Review of Financial Economics, Annual Reviews, vol. 8(1), pages 1-24, October.
    16. Alain P. Chaboud & Benjamin Chiquoine & Erik Hjalmarsson & Clara Vega, 2014. "Rise of the Machines: Algorithmic Trading in the Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 69(5), pages 2045-2084, October.
    17. Kerry Back & C. Henry Cao & Gregory A. Willard, 2000. "Imperfect Competition among Informed Traders," Journal of Finance, American Finance Association, vol. 55(5), pages 2117-2155, October.
    18. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    19. 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.
    20. Lyons, Richard K., 1997. "A simultaneous trade model of the foreign exchange hot potato," Journal of International Economics, Elsevier, vol. 42(3-4), pages 275-298, May.
    21. Giovanni Cespa & Thierry Foucault, 2014. "Sale of Price Information by Exchanges: Does It Promote Price Discovery?," Management Science, INFORMS, vol. 60(1), pages 148-165, January.
    22. Vincent Glode & Christian Opp, 2016. "Asymmetric Information and Intermediation Chains," American Economic Review, American Economic Association, vol. 106(9), pages 2699-2721, September.
    23. Menkveld, Albert J., 2013. "High frequency trading and the new market makers," Journal of Financial Markets, Elsevier, vol. 16(4), pages 712-740.
    24. Ho, Thomas & Stoll, Hans R., 1981. "Optimal dealer pricing under transactions and return uncertainty," Journal of Financial Economics, Elsevier, vol. 9(1), pages 47-73, March.
    25. Eric Budish & Peter Cramton & John Shim, 2015. "Editor's Choice The High-Frequency Trading Arms Race: Frequent Batch Auctions as a Market Design Response," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(4), pages 1547-1621.
    26. 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.
    27. Benos, Evangelos & Sagade, Satchit, 2016. "Price discovery and the cross-section of high-frequency trading," Journal of Financial Markets, Elsevier, vol. 30(C), pages 54-77.
    28. Terrence Hendershott & Charles M. Jones & Albert J. Menkveld, 2011. "Does Algorithmic Trading Improve Liquidity?," Journal of Finance, American Finance Association, vol. 66(1), pages 1-33, February.
    29. Easley, David & O’Hara, Maureen & Yang, Liyan, 2016. "Differential Access to Price Information in Financial Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 51(4), pages 1071-1110, August.
    30. Álvaro Cartea & José Penalva, 2012. "Where is the Value in High Frequency Trading?," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 2(03), pages 1-46.
    31. Jonathan Brogaard & Björn Hagströmer & Lars Nordén & Ryan Riordan, 2015. "Trading Fast and Slow: Colocation and Liquidity," The Review of Financial Studies, Society for Financial Studies, vol. 28(12), pages 3407-3443.
    32. Hoffmann, Peter, 2014. "A dynamic limit order market with fast and slow traders," Journal of Financial Economics, Elsevier, vol. 113(1), pages 156-169.
    33. Foster, F Douglas & Viswanathan, S, 1996. "Strategic Trading When Agents Forecast the Forecasts of Others," Journal of Finance, American Finance Association, vol. 51(4), pages 1437-1478, September.
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    More about this item

    Keywords

    Trading volume; Inventory; Volatility; High-frequency trading; Price impact; Mean reversion;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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