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From Trade-to-Trade in US Treasuries

The aim of this paper is to model the trading intensity of the US Treasury bond market which has a unique expandable limit order book which distinguishes its structure from other asset markets. An analysis of tick data from the eSpeed database suggests that the US bond market displays a greater degree of clustering in trade durations than is evident in other asset markets. Duration is affected by the presence of news particularly in the hour following the release of scheduled news to the markets. Finally, the length of time taken to complete a given transaction, or ‘workup’, has a measurable impact on the trade duration

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File URL: http://eprints.utas.edu.au/10446/1/DP2010-02_Dungey_Henry_McKenzie_May2010.pdf
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Paper provided by University of Tasmania, School of Economics and Finance in its series Working Papers with number 10446.

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Length: 39 pages
Date of creation: 01 May 2010
Date of revision: 01 May 2010
Publication status: Published by the University of Tasmania. Discussion paper 2010-02
Handle: RePEc:tas:wpaper:10446
Contact details of provider: Postal: Private Bag 85, Hobart, Tasmania 7001
Phone: +61 3 6226 7672
Fax: +61 3 6226 7587
Web page: http://www.utas.edu.au/economics-finance/
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  9. Michael J. Fleming & Eli M. Remolona, 1999. "Price Formation and Liquidity in the U.S. Treasury Market: The Response to Public Information," Journal of Finance, American Finance Association, vol. 54(5), pages 1901-1915, October.
  10. Dungey, Mardi & McKenzie, Michael & Smith, L. Vanessa, 2009. "Empirical evidence on jumps in the term structure of the US Treasury Market," Journal of Empirical Finance, Elsevier, vol. 16(3), pages 430-445, June.
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  17. Bauwens, Luc, 2006. "Econometric Analysis of Intra-daily Trading Activity on the Tokyo Stock Exchange," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 24(1), pages 1-23, March.
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  19. BAUWENS, Luc & VEREDAS, David, . "The stochastic conditional duration model: a latent variable model for the analysis of financial durations," CORE Discussion Papers RP -1688, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  20. Boni, Leslie & Leach, Chris, 2004. "Expandable limit order markets," Journal of Financial Markets, Elsevier, vol. 7(2), pages 145-185, February.
  21. Joachim Grammig & Kai-Oliver Maurer, 2000. "Non-monotonic hazard functions and the autoregressive conditional duration model," Econometrics Journal, Royal Economic Society, vol. 3(1), pages 16-38.
  22. Anat R. Admati, Paul Pfleiderer, 1988. "A Theory of Intraday Patterns: Volume and Price Variability," Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 3-40.
  23. Foster, F Douglas & Viswanathan, S, 1990. "A Theory of the Interday Variations in Volume, Variance, and Trading Costs in Securities Markets," Review of Financial Studies, Society for Financial Studies, vol. 3(4), pages 593-624.
  24. Easley, David & O'Hara, Maureen, 1992. " Time and the Process of Security Price Adjustment," Journal of Finance, American Finance Association, vol. 47(2), pages 576-605, June.
  25. Engle, Robert F. & Russell, Jeffrey R., 1997. "Forecasting the frequency of changes in quoted foreign exchange prices with the autoregressive conditional duration model," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 187-212, June.
  26. Goodhart, Charles A. E. & O'Hara, Maureen, 1997. "High frequency data in financial markets: Issues and applications," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 73-114, June.
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