IDEAS home Printed from https://ideas.repec.org/p/gla/glaewp/2023_02.html
   My bibliography  Save this paper

Signal-jamming in the Frequency Domain

Author

Listed:
  • Bart Taub

Abstract

I examine strategic behaviour for a duopoly in a noisy environment. Firms attempt to learn the value of the rival’s privately observed demand shocks via a noisy signal of price, and at the same time firms attempt to obfuscate that signal by producing excess output on the publicly observable signals, that is, they signal jam. In a dynamic setting firms also distort the intertemporal structure of output keyed to the publicly observable demand shock process in order to disguise their private shocks. The net outcome is to radically increase the persistence of output over its full-information value.

Suggested Citation

  • Bart Taub, 2023. "Signal-jamming in the Frequency Domain," Working Papers 2023_02, Business School - Economics, University of Glasgow.
    • Handle: RePEc:gla:glaewp:2023_02
    as

    Download full text from publisher

    File URL: https://www.gla.ac.uk/media/Media_910031_smxx.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Caminal, Ramon, 1990. "A Dynamic Duopoly Model with Asymmetric Information," Journal of Industrial Economics, Wiley Blackwell, vol. 38(3), pages 315-333, March.
    2. Foster, F Douglas & Viswanathan, S, 1996. "Strategic Trading When Agents Forecast the Forecasts of Others," Journal of Finance, American Finance Association, vol. 51(4), pages 1437-1478, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dan Bernhardt & Bart Taub, 2015. "Learning about common and private values in oligopoly," RAND Journal of Economics, RAND Corporation, vol. 46(1), pages 66-85, March.
    2. Curatola, Giuliano, 2022. "Price impact, strategic interaction and portfolio choice," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    3. Liu, Hong & Qi, Lina & Li, Zaili, 2019. "Insider trading, representativeness heuristic insider, and market regulation," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 48-64.
    4. Menkhoff, Lukas & Schmeling, Maik, 2010. "Trader see, trader do: How do (small) FX traders react to large counterparties' trades?," Journal of International Money and Finance, Elsevier, vol. 29(7), pages 1283-1302, November.
    5. Nicholas Taylor, 2011. "Time-varying price discovery in fragmented markets," Applied Financial Economics, Taylor & Francis Journals, vol. 21(10), pages 717-734.
    6. Lof, Matthijs & van Bommel, Jos, 2023. "Asymmetric information and the distribution of trading volume," Journal of Corporate Finance, Elsevier, vol. 82(C).
    7. Malinova, Katya & Park, Andreas, 2014. "The impact of competition and information on intraday trading," Journal of Banking & Finance, Elsevier, vol. 44(C), pages 55-71.
    8. Antonio Scalia & Valerio Vacca, 2001. "Does market transparency matter? A case study," BIS Papers chapters, in: Bank for International Settlements (ed.), Market liquidity: proceedings of a workshop held at the BIS, volume 2, pages 113-144, Bank for International Settlements.
    9. Chiu, Yen-Chen, 2020. "Macroeconomic uncertainty, information competition, and liquidity," Finance Research Letters, Elsevier, vol. 34(C).
    10. Jiang, Ying & Liu, Hong & Yang, Qingshan, 2024. "Asymmetric information correlation in financial markets," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    11. Daniel Neuhann & Michael Sockin, 2019. "Risk-Sharing and Investment in Concentrated Markets," 2019 Meeting Papers 118, Society for Economic Dynamics.
    12. Nicolas S. Lambert & Michael Ostrovsky & Mikhail Panov, 2018. "Strategic Trading in Informationally Complex Environments," Econometrica, Econometric Society, vol. 86(4), pages 1119-1157, July.
    13. Paolo Pasquariello & Clara Vega, 2007. "Informed and Strategic Order Flow in the Bond Markets," The Review of Financial Studies, Society for Financial Studies, vol. 20(6), pages 1975-2019, November.
    14. Jason Shachat & Anand Srinivasan, 2022. "Informational Price Cascades and Non-Aggregation of Asymmetric Information in Experimental Asset Markets," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 23(4), pages 388-407, November.
    15. Rui Cao & Yongli Zhang, 2021. "Disclosure and Exchange of Inside Information," International Review of Finance, International Review of Finance Ltd., vol. 21(1), pages 183-207, March.
    16. Walker, Todd B., 2007. "How equilibrium prices reveal information in a time series model with disparately informed, competitive traders," Journal of Economic Theory, Elsevier, vol. 137(1), pages 512-537, November.
    17. Minh Chau & Dimitri Vayanos, 2008. "Strong-Form Efficiency with Monopolistic Insiders," The Review of Financial Studies, Society for Financial Studies, vol. 21(5), pages 2275-2306, September.
    18. Aliakbari, Elmira & McKitrick, Ross, 2018. "Information aggregation in a prediction market for climate outcomes," Energy Economics, Elsevier, vol. 74(C), pages 97-106.
    19. Umut Çetin, 2018. "Financial equilibrium with asymmetric information and random horizon," Finance and Stochastics, Springer, vol. 22(1), pages 97-126, January.
    20. Qin Lei & Xuewu Wang, 2014. "Time†Varying Liquidity Trading, Private Information and Insider Trading," European Financial Management, European Financial Management Association, vol. 20(2), pages 321-351, March.

    More about this item

    Keywords

    Dynamic games; signal jamming; strategic information; frequency-domain methods.;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gla:glaewp:2023_02. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Business School Research Team (email available below). General contact details of provider: https://edirc.repec.org/data/dpglauk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.