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Trading, Profits, and Volatility in a Dynamic Information Network Model

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  • Johan Walden

Abstract

We introduce a dynamic noisy rational expectations model in which information diffuses through a general network of agents. In equilibrium, agents who are more closely connected have more similar period-by-period trades, and an agent’s profitability is determined by a centrality measure that is related to Katz centrality. Volatility after an information shock is more persistent in less central networks, and volatility and trading volume are also influenced by the network’s asymmetry and irregularity. Using account-level data of all portfolio holdings and trades on the Helsinki Stock Exchange between 1997 and 2003, we find support for the aggregate predictions, altogether suggesting that the market’s network structure is important for these dynamics.

Suggested Citation

  • Johan Walden, 2019. "Trading, Profits, and Volatility in a Dynamic Information Network Model," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 86(5), pages 2248-2283.
    • Handle: RePEc:oup:restud:v:86:y:2019:i:5:p:2248-2283.
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    File URL: http://hdl.handle.net/10.1093/restud/rdy058
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    Citations

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    Cited by:

    1. Erol Akçay & David Hirshleifer, 2021. "Social finance as cultural evolution, transmission bias, and market dynamics," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 118(26), pages 2015568118-, June.
    2. Lou, Youcheng & Yang, Yaqing, 2023. "Information linkages in a financial market with imperfect competition," Journal of Economic Dynamics and Control, Elsevier, vol. 150(C).
    3. Guang Liu & Hong Yi & Chih-Ping Yu, 2023. "Shareholding Network of Institutional Investors and the Information Efficiency of Capital Market: Evidence From China," SAGE Open, , vol. 13(4), pages 21582440231, November.
    4. Tinic, Murat & Sensoy, Ahmet & Demir, Muge & Nguyen, Duc Khuong, 2020. "Broker Network Connectivity and the Cross-Section of Expected Stock Returns," MPRA Paper 104719, University Library of Munich, Germany.
    5. Tsang, Kwok Ping & Yang, Zichao, 2022. "Do connections pay off in the bitcoin market?," Journal of Empirical Finance, Elsevier, vol. 67(C), pages 1-18.
    6. Wang, Wentao & Zhao, Shangmei & Zhang, Junhuan, 2022. "Multi-asset pricing modeling using holding-based networks in energy markets," Finance Research Letters, Elsevier, vol. 46(PB).
    7. Lou, Youcheng & Parsa, Sahar & Ray, Debraj & Li, Duan & Wang, Shouyang, 2019. "Information aggregation in a financial market with general signal structure," Journal of Economic Theory, Elsevier, vol. 183(C), pages 594-624.
    8. Baltakienė, Margarita & Kanniainen, Juho & Baltakys, Kęstutis, 2021. "Identification of information networks in stock markets," Journal of Economic Dynamics and Control, Elsevier, vol. 131(C).
    9. Luo, Ronghua & Zhao, Senyang & Zhou, Jing, 2023. "Information network, public disclosure and asset prices," Pacific-Basin Finance Journal, Elsevier, vol. 77(C).
    10. Gong, Qingbin & Diao, Xundi, 2023. "The impacts of investor network and herd behavior on market stability: Social learning, network structure, and heterogeneity," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1388-1398.
    11. Pedersen, Lasse Heje, 2022. "Game on: Social networks and markets," Journal of Financial Economics, Elsevier, vol. 146(3), pages 1097-1119.
    12. Sun, Rui & Guo, Junfei & Yu, Wensong, 2023. "Sponsor, institutional investor, and quotation behavior: Theory and evidence from China," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 411-428.
    13. Lou, Youcheng & Wang, Shouyang, 2021. "The equivalence of two rational expectations equilibrium economies with different approaches to processing neighbors’ information," Mathematical Social Sciences, Elsevier, vol. 109(C), pages 93-105.

    More about this item

    Keywords

    Information networks; Trading networks; Heterogeneous investors; Portfolio choice; Asset pricing;
    All these keywords.

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • 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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