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The Relevance of Broker Networks for Information Diffusion in the Stock Market

Author

Listed:
  • Marco Di Maggio

    (Harvard Business School and National Bureau of Economic Research (NBER))

  • Francesco A. Franzoni

    (University of Lugano and Swiss Finance Institute)

  • Amir Kermani

    (University of California and National Bureau of Economic Research (NBER))

  • Carlo Sommavilla

    (University of Lugano and Swiss Finance Institute)

Abstract

This paper shows that the network of relationships between brokers and institutional investors shapes the information diffusion in the stock market. We exploit trade-level data to show that trades channeled through central brokers earn significantly positive abnormal returns. This result is not due to differences in the investors that trade through central brokers or to stocks characteristics, as we control for this heterogeneity; nor is it the result of better trading execution. We find that a key driver of these excess returns is the information that central brokers gather by executing informed trades, which is then leaked to their best clients. We show that after large informed trades, a significantly higher volume of other investors execute similar trades through the same central broker, allowing them to capture higher returns in the first few days after the initial trade. The best clients of the broker executing the informed trade, and the asset managers affiliated with the broker, are among the first to benefit from the information about order flow. This evidence also suggests that an important source of alpha for fund managers is the access to better connections rather than superior skill.

Suggested Citation

  • Marco Di Maggio & Francesco A. Franzoni & Amir Kermani & Carlo Sommavilla, 2017. "The Relevance of Broker Networks for Information Diffusion in the Stock Market," Swiss Finance Institute Research Paper Series 17-08, Swiss Finance Institute.
    • Handle: RePEc:chf:rpseri:rp1708
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    Citations

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    Cited by:

    1. Andrea Barbon & Marco Di Maggio & Francesco Franzoni & Augustin Landier, 2019. "Brokers and Order Flow Leakage: Evidence from Fire Sales," Journal of Finance, American Finance Association, vol. 74(6), pages 2707-2749, December.
    2. Anand, Amber & Irvine, Paul & Liu, Tingting, 2019. "Does institutional trading affect underwriting?," Journal of Corporate Finance, Elsevier, vol. 58(C), pages 1-1.
    3. Azi Ben-Rephael & Ryan D Israelsen, 2018. "Are Some Clients More Equal Than Others? An Analysis of Asset Management Companies’ Execution Costs [An analysis of trade-size clustering and its relation to stealth trading]," Review of Finance, European Finance Association, vol. 22(5), pages 1705-1736.
    4. Agarwal, Sumit & He, Jia & Sing, Tien Foo & Song, Changcheng, 2019. "Do real estate agents have information advantages in housing markets?," Journal of Financial Economics, Elsevier, vol. 134(3), pages 715-735.
    5. Acheson, Graeme G. & Coyle, Christopher & Turner, John D., 2018. "Prices and informed trading: Evidence from an early stock market," QUCEH Working Paper Series 2018-05, Queen's University Belfast, Queen's University Centre for Economic History.
    6. Krishna Dasaratha & Benjamin Golub & Nir Hak, 2018. "Learning from Neighbors about a Changing State," Papers 1801.02042, arXiv.org, revised Nov 2022.

    More about this item

    Keywords

    broker networks; institutional investors; asset prices; information;
    All these keywords.

    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
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage

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