IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1610.08414.html
   My bibliography  Save this paper

The Fellowship of LIBOR: A Study of Spurious Interbank Correlations by the Method of Wigner-Ville Function

Author

Listed:
  • Peter B. Lerner

Abstract

The manipulation of LIBOR by a group of banks became one of the major blows to the remaining confidence in financial industry. Yet, despite an enormous amount of popular literature on the subject, rigorous time-series studies are few. In my paper, I discuss the following hypothesis. Namely, if we should assume for a statistical null, the quotes, which were submitted by the member banks were true, the deviations from the LIBOR should have been entirely random because they were determined by idiosyncratic conditions by the member banks. This hypothesis can be statistically verified. Serial correlations of the rates, which cannot be explained by the differences in credit qualities of the member banks or the domicile Governments, were subjected to correlation tests. A new econometric method--the analysis of the Wigner-Ville function borrowed from quantum mechanics and signal processing--is used and explained for the statistical interpretation of regression residuals.

Suggested Citation

  • Peter B. Lerner, 2016. "The Fellowship of LIBOR: A Study of Spurious Interbank Correlations by the Method of Wigner-Ville Function," Papers 1610.08414, arXiv.org, revised Apr 2020.
  • Handle: RePEc:arx:papers:1610.08414
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1610.08414
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Albert S. Kyle & S. Viswanathan, 2008. "How to Define Illegal Price Manipulation," American Economic Review, American Economic Association, vol. 98(2), pages 274-279, May.
    2. Rosa Abrantes-Metz & Sofia Villas-Boas & George Judge, 2011. "Tracking the Libor rate," Applied Economics Letters, Taylor & Francis Journals, vol. 18(10), pages 893-899.
    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. Xihan Xiong & Zhipeng Wang & Tianxiang Cui & William Knottenbelt & Michael Huth, 2023. "Market Misconduct in Decentralized Finance (DeFi): Analysis, Regulatory Challenges and Policy Implications," Papers 2311.17715, arXiv.org, revised Mar 2024.
    2. Yensen Ni & Yirung Cheng & Yulu Liao & Paoyu Huang, 2022. "Does board structure affect stock price overshooting informativeness measured by stochastic oscillator indicators?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2290-2302, April.
    3. Peck, James, 2014. "A battle of informed traders and the market game foundations for rational expectations equilibrium," Games and Economic Behavior, Elsevier, vol. 88(C), pages 153-173.
    4. Luca Gelsomini, 2024. "On the Profitability of Rumors," Working Papers 2024: 06, Department of Economics, University of Venice "Ca' Foscari".
    5. Meoli, Michele & Vismara, Silvio, 2021. "Information manipulation in equity crowdfunding markets," Journal of Corporate Finance, Elsevier, vol. 67(C).
    6. Archishman Chakraborty & Bilge Yilmaz, 2008. "Microstructure Bluffing with Nested Information," American Economic Review, American Economic Association, vol. 98(2), pages 280-284, May.
    7. Oh, Sebeom, 2023. "Market Manipulation in NFT Markets," MPRA Paper 116704, University Library of Munich, Germany.
    8. Takayama, Shino, 2021. "Price manipulation, dynamic informed trading, and the uniqueness of equilibrium in sequential trading," Journal of Economic Dynamics and Control, Elsevier, vol. 125(C).
    9. Li-Xin Wang, 2014. "Dynamical Models of Stock Prices Based on Technical Trading Rules Part I: The Models," Papers 1401.1888, arXiv.org, revised Feb 2016.
    10. Yu Huang & Yao Cheng, 2015. "Stock manipulation and its effects: pump and dump versus stabilization," Review of Quantitative Finance and Accounting, Springer, vol. 44(4), pages 791-815, May.
    11. Massimo La Morgia & Alessandro Mei & Francesco Sassi & Julinda Stefa, 2020. "Pump and Dumps in the Bitcoin Era: Real Time Detection of Cryptocurrency Market Manipulations," Papers 2005.06610, arXiv.org.
    12. ap Gwilym, Rhys & Ebrahim, M. Shahid, 2013. "Can position limits restrain ‘rogue’ trading?," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 824-836.
    13. Rossi, Stefano & Tinn, Katrin, 2021. "Rational quantitative trading in efficient markets," Journal of Economic Theory, Elsevier, vol. 191(C).
    14. Ni, Yensen & Huang, Paoyu & Chen, Yuhsin, 2019. "Board structure, considerable capital, and stock price overreaction informativeness in terms of technical indicators," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 514-528.
    15. Christian Leuz & Steffen Meyer & Maximilian Muhn & Eugene Soltes & Andreas Hackethal, 2017. "Who Falls Prey to the Wolf of Wall Street? Investor Participation in Market Manipulation," NBER Working Papers 24083, National Bureau of Economic Research, Inc.
    16. Carole Comerton-Forde & Tālis J. Putniņš, 2014. "Stock Price Manipulation: Prevalence and Determinants," Review of Finance, European Finance Association, vol. 18(1), pages 23-66.
    17. Pirrong, Craig, 2017. "The economics of commodity market manipulation: A survey," Journal of Commodity Markets, Elsevier, vol. 5(C), pages 1-17.
    18. Shino Takayama, 2018. "Price Manipulation, Dynamic Informed Trading and Tame Equilibria: Theory and Computation," Discussion Papers Series 603, School of Economics, University of Queensland, Australia.
    19. Kun Li, 2018. "Do high-frequency fleeting orders exacerbate market illiquidity?," Electronic Commerce Research, Springer, vol. 18(2), pages 241-255, June.
    20. Liu, Jie & Wu, Chonglin & Yuan, Lin & Liu, Jia, 2022. "Opening price manipulation and its value influences," International Review of Financial Analysis, Elsevier, vol. 83(C).

    More about this item

    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:arx:papers:1610.08414. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.