IDEAS home Printed from
   My bibliography  Save this paper

Tail Wags Dog? Time-Varying Information Shares in the Bund Market


  • Upper, Christian
  • Werner, Thomas


The flow of information between futures and spot prices may vary over time, in particular during periods of stress. This article analyses the information content of the Bund Future and German government bonds during 1998 and test whether it is constant over time. The use of high-frequency data permits us to capture possible imperfections in the information flows between the two markets. We measure the contributions of trading on the spot and futures markets to price discovery using the information shares approach by Hasbrouck (1995) as well as a recently proposed approach based on the Gonzalo-Granger decomposition. A state-space approach is used to estimate the underlying VECM in the presence of missing values. We test for structural breaks in the pricing relationship between the spot and futures markets and estimate break dates. Although most information is incorporated into prices in the futures market, this does not mean that the spot market is irrelevant for prices discovery. Under normal market conditions, the underlying bonds contribute to 19 to 33 % of the variation in the efficient price. The informational role of the spot market vanishes during episodes of stress. For example, during the two weeks after the recapitalization of LTCM (September 24th to October 8th, 1998), the information share of the spot market dropped to virtually zero and futures prices did not respond to movements in bond prices. All adjustment towards equilibrium took place in the spot market.

Suggested Citation

  • Upper, Christian & Werner, Thomas, 2002. "Tail Wags Dog? Time-Varying Information Shares in the Bund Market," Discussion Paper Series 1: Economic Studies 2002,24, Deutsche Bundesbank.
  • Handle: RePEc:zbw:bubdp1:4189

    Download full text from publisher

    File URL:
    Download Restriction: no


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

    Cited by:

    1. Frank De Jong & Peter C. Schotman, 2010. "Price Discovery in Fragmented Markets," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 8(1), pages 1-28, Winter.
    2. Ranaldo, Angelo & Rossi, Enzo, 2010. "The reaction of asset markets to Swiss National Bank communication," Journal of International Money and Finance, Elsevier, vol. 29(3), pages 486-503, April.
    3. Bruce Mizrach & Christopher J. Neely, 2007. "The microstructure of the U.S. treasury market," Working Papers 2007-052, Federal Reserve Bank of St. Louis.
    4. Marc Simpson & Jose Moreno & Teofilo Ozuna, 2012. "The makings of an information leader: the intraday price discovery process for individual stocks in the DJIA," Review of Quantitative Finance and Accounting, Springer, vol. 38(3), pages 347-365, April.
    5. Alexander Schulz & Jelena Stapf, 2011. "Price discovery on traded inflation expectations: does the financial crisis matter?," IFC Bulletins chapters,in: Bank for International Settlements (ed.), Proceedings of the IFC Conference on "Initiatives to address data gaps revealed by the financial crisis", Basel, 25-26 August 2010, volume 34, pages 202-231 Bank for International Settlements.
    6. repec:eee:pacfin:v:48:y:2018:i:c:p:35-55 is not listed on IDEAS
    7. Mizrach, Bruce & Neely, Christopher J., 2008. "Information shares in the US Treasury market," Journal of Banking & Finance, Elsevier, vol. 32(7), pages 1221-1233, July.
    8. Alessandro Girardi, 2008. "The Informational Content of Trades on the EuroMTS Platform," ISAE Working Papers 97, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).

    More about this item


    high-frequency data; market microstructure; future markets; information shares; kalman filter;

    JEL classification:

    • 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
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates


    Access and download statistics


    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:bubdp1:4189. 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: .

    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.