IDEAS home Printed from https://ideas.repec.org/p/zbw/cfrwps/1006.html
   My bibliography  Save this paper

Tell-tale tails: A data driven approach to estimate unique market information shares

Author

Listed:
  • Grammig, Joachim G.
  • Peter, Franziska J.

Abstract

The trading of securities on multiple markets raises the question of each market's share in the discovery of the informationally efficient price. We exploit salient distributional features of multivariate financial price processes to uniquely determine these contributions. Thereby we resolve the main drawback of the widely used Hasbrouck (1995) methodology which merely delivers upper and lower bounds of a market's information share. When these bounds diverge, as is the case in many applications, informational leadership becomes blurred. We show how fat tails and tail dependence of price changes, which emerge as a result of differences in market design and liquidity, can be exploited to estimate unique information shares. The empirical application of the new methodology emphasizes the leading role of the credit derivatives market compared to the corporate bond market in pricing credit risk during the pre-crisis period.

Suggested Citation

  • Grammig, Joachim G. & Peter, Franziska J., 2010. "Tell-tale tails: A data driven approach to estimate unique market information shares," CFR Working Papers 10-06, University of Cologne, Centre for Financial Research (CFR).
  • Handle: RePEc:zbw:cfrwps:1006
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/41385/1/637040171.pdf
    Download Restriction: no

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. repec:sbe:breart:v:35:y:2015:i:1:a:46423 is not listed on IDEAS
    2. Santos, Francisco Luna & Garcia, Márcio Gomes Pinto & Medeiros, Marcelo Cunha, 2015. "Price Discovery in Brazilian FX Markets," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 35(1), October.

    More about this item

    Keywords

    price discovery; information share; fat tails; tail dependence; liquidity; credit risk;

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

    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:zbw:cfrwps:1006. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (ZBW - German National Library of Economics). General contact details of provider: http://edirc.repec.org/data/cfkoede.html .

    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.

    We have no references for this item. You can help adding them by using 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.