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

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  • Upper, Christian
  • Werner, Thomas

Abstract

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
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    high-frequency data; market microstructure; future markets; information shares; kalman filter;
    All these keywords.

    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

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