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Publications
Publications
  • November 2019
  • Article
  • Journal of Financial Economics

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

By: Marco Di Maggio, Francesco Franzoni, Amir Kermani and Carlo Sommavilla
  • Format:Print
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Abstract

This paper shows that the network of relationships between brokers and institutional investors shapes information diffusion in the stock market. We exploit trade-level data to show that central brokers gather information 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 institutional investors execute similar trades through the same broker, allowing them to capture returns that are twice as large as their normal trading performance. Similarly, we show that the clients of the broker employed by activist investors to execute their trades tend to buy the same stocks just before the filing of the 13D. Informed traders find it profitable to concentrate their trades with a leaking broker because the loss due to the information leakage is more than compensated by the gains derived from trading on the information generated by the other clients of the broker.

Keywords

Broker Networks; Institutional Investors; Asset Prices; Business and Shareholder Relations; Institutional Investing; Information; Knowledge Dissemination; Financial Markets; Asset Pricing

Citation

Di Maggio, Marco, Francesco Franzoni, Amir Kermani, and Carlo Sommavilla. "The Relevance of Broker Networks for Information Diffusion in the Stock Market." Journal of Financial Economics 134, no. 2 (November 2019): 419–446.
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About The Author

Marco Di Maggio

Finance
→More Publications

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More from the Authors
  • Ava Labs: Navigating the Next Blockchain By: Marco Di Maggio and Wenyao Sha
  • Cryptocurrency Investing: Stimulus Checks and Inflation Expectations By: Darren Aiello, Scott R. Baker, Tetyana Balyuk, Marco Di Maggio, Mark J. Johnson and Jason Kotter
  • Avoiding Idiosyncratic Volatility: Flow Sensitivity to Individual Stock Returns By: Marco Di Maggio, Francesco Franzoni, Shimon Kogan and Ran Xing
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