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Information Revelation in Decentralized Markets

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  • BJÖRN HAGSTRÖMER
  • ALBERT J. MENKVELD

Abstract

How does information get revealed in decentralized markets? We test several hypotheses inspired by recent dealer‐network theory. To do so, we construct an empirical map of information revelation where two dealers are connected based on the synchronicity of their quote changes. The tests, based on the euro to Swiss franc spot rate (EUR/CHF) quote data including the 2015 crash, largely support theory: strongly connected (i.e., central) dealers are more informed. Connections are weaker when there is less to be learned. The crash serves to identify how a network forms when dealers are transitioned from no‐learning to learning, that is, from a fixed to a floating rate.

Suggested Citation

  • Björn Hagströmer & Albert J. Menkveld, 2019. "Information Revelation in Decentralized Markets," Journal of Finance, American Finance Association, vol. 74(6), pages 2751-2787, December.
    • Handle: RePEc:bla:jfinan:v:74:y:2019:i:6:p:2751-2787
    DOI: 10.1111/jofi.12838
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    Cited by:

    1. Lifang Li & Valentina Galvani, 2021. "Informed Trading and Momentum in the Corporate Bond Market [Asset pricing with liquidity risk]," Review of Finance, European Finance Association, vol. 25(6), pages 1773-1816.
    2. Joel Hasbrouck, 2021. "Price Discovery in High Resolution," Journal of Financial Econometrics, Oxford University Press, vol. 19(3), pages 395-430.
    3. Rainone, Edoardo, 2020. "The network nature of over-the-counter interest rates," Journal of Financial Markets, Elsevier, vol. 47(C).
    4. Péter Kondor & Gábor Pintér, 2022. "Clients' Connections: Measuring the Role of Private Information in Decentralized Markets," Journal of Finance, American Finance Association, vol. 77(1), pages 505-544, February.
    5. Shrestha, Keshab & Philip, Sheena & Peranginangin, Yessy, 2020. "Contributions of Crude Oil Exchange Traded Funds in Price Discovery Process," American Business Review, Pompea College of Business, University of New Haven, vol. 23(2), pages 393-407, November.
    6. de Roure, Calebe & Mönch, Emanuel & Pelizzon, Loriana & Schneider, Michael, 2019. "OTC discount," Discussion Papers 42/2019, Deutsche Bundesbank.
      • de Roure, Calebe & Mönch, Emanuel & Pelizzon, Loriana & Schneider, Michael, 2021. "OTC discount," SAFE Working Paper Series 298, Leibniz Institute for Financial Research SAFE, revised 2021.
    7. Joseph, Andreas & Vasios, Michalis, 2022. "OTC Microstructure in a period of stress: A Multi-layered network approach," Journal of Banking & Finance, Elsevier, vol. 138(C).
    8. Kamate, Vidya & Kumar, Abhishek, 2024. "Dealer networks, client sophistication and pricing in OTC derivatives," Journal of International Money and Finance, Elsevier, vol. 140(C).
    9. 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.
    10. Pintér, Gábor & Wang, Chaojun & Zou, Junyuan, 2022. "Information chasing versus adverse selection," Bank of England working papers 971, Bank of England.
    11. Breedon, Francis & Chen, Louisa & Ranaldo, Angelo & Vause, Nicholas, 2023. "Judgment day: Algorithmic trading around the Swiss franc cap removal," Journal of International Economics, Elsevier, vol. 140(C).
    12. Mark Marner-Hausen, 2022. "Developing a Framework for Real-Time Trading in a Laboratory Financial Market," ECONtribute Discussion Papers Series 172, University of Bonn and University of Cologne, Germany.
    13. Khapko, Mariana & Zoican, Marius, 2021. "Do speed bumps curb low-latency investment? Evidence from a laboratory market," Journal of Financial Markets, Elsevier, vol. 55(C).
    14. Zema, Sebastiano Michele, 2022. "Directed acyclic graph based information shares for price discovery," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
    15. Joseph, Andreas & Vasios, Michalis & Maizels, Olga & Shreyas, Ujwal & Tanner, John, 2019. "OTC microstructure in a period of stress: a multi‑layered network approach," Bank of England working papers 832, Bank of England.
    16. Batten, Jonathan A. & Lončarski, Igor & Szilagyi, Peter G., 2021. "Strategic insider trading in foreign exchange markets," Journal of Corporate Finance, Elsevier, vol. 69(C).
    17. Donald Lien & Pi-Hsia Hung, 2023. "Whose trades contribute more to price discovery? Evidence from the Taiwan stock exchange," Review of Quantitative Finance and Accounting, Springer, vol. 61(1), pages 213-263, July.
    18. Hasbrouck, Joel & Levich, Richard M., 2021. "Network structure and pricing in the FX market," Journal of Financial Economics, Elsevier, vol. 141(2), pages 705-729.

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