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Trading networks

Author

Listed:
  • Lada Adamic
  • Celso Brunetti
  • Jeffrey H. Harris
  • Andrei Kirilenko

Abstract

In this paper, we analyse the time series of 12,000+ networks of traders in the E‐mini S&P 500 stock index futures contract and we empirically link network variables with financial variables more commonly used to describe market conditions. We show that network variables lead trading volume, intertrade duration, effective spreads, trade imbalances and other market liquidity measures. Network variables reflect information, information asymmetry and market liquidity and significantly presage future market conditions prior to volume or liquidity measures. We also find two‐way Granger‐causality between network variables and both returns and volatility, highlighting strong feedback between market conditions and trading behaviour.

Suggested Citation

  • Lada Adamic & Celso Brunetti & Jeffrey H. Harris & Andrei Kirilenko, 2017. "Trading networks," Econometrics Journal, Royal Economic Society, vol. 20(3), pages 126-149, October.
  • Handle: RePEc:wly:emjrnl:v:20:y:2017:i:3:p:s126-s149
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    File URL: http://hdl.handle.net/10.1111/ectj.12090
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    Cited by:

    1. Li, Ming-Xia & Jiang, Zhi-Qiang & Xie, Wen-Jie & Xiong, Xiong & Zhang, Wei & Zhou, Wei-Xing, 2015. "Unveiling correlations between financial variables and topological metrics of trading networks: Evidence from a stock and its warrant," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 575-584.
    2. Bertrand Candelon & Laurent Ferrara & Marc Joëts, 2021. "Global financial interconnectedness: a non-linear assessment of the uncertainty channel," Applied Economics, Taylor & Francis Journals, vol. 53(25), pages 2865-2887, May.
    3. Diebold, Francis X. & Yilmaz, Kamil, 2015. "Financial and Macroeconomic Connectedness: A Network Approach to Measurement and Monitoring," OUP Catalogue, Oxford University Press, number 9780199338306.
    4. Wen-Jie Xie & Ming-Xia Li & Hai-Chuan Xu & Wei Chen & Wei-Xing Zhou & H. E. Stanley, 2016. "Quantifying immediate price impact of trades based on the $k$-shell decomposition of stock trading networks," Papers 1611.06666, arXiv.org, revised Dec 2016.
    5. Franco Peracchi & Claudio Rossetti, 2013. "The heterogeneous thresholds ordered response model: identification and inference," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(3), pages 703-722, June.
    6. Sam Langfield & Kimmo Soramäki, 2016. "Interbank Exposure Networks," Computational Economics, Springer;Society for Computational Economics, vol. 47(1), pages 3-17, January.
    7. Ethan Cohen-Cole & Andrei Kirilenko & Eleonora Patacchini, 2010. "Are Networks Priced? Network Topology and Order Trading Strategies in High Liquidity Markets," EIEF Working Papers Series 1011, Einaudi Institute for Economics and Finance (EIEF), revised Apr 2010.
    8. David Garcia & Frank Schweitzer, 2015. "Social signals and algorithmic trading of Bitcoin," Papers 1506.01513, arXiv.org, revised Sep 2015.

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