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Modelling the Time Between Trades in the After-Hours Electronic Equity Futures Market

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Abstract

This paper models the time between trades of the after-hours electronically traded equity futures market, a market which is previously unstudied in this regard. Using a relatively long 2 year data set, trades in the NASDAQ and S&P500 equity futures are shown to require different forms of autoregressive conditional duration models, including longer lag lengths than previous spot data applications. Volume provides an informative mark in both cases. The S&P500 necessitates a threshold model where the majority of trades display the typical low autocorrelation and strong clustering evident in other assets, but with large durations more autocorrelated with low clustering.

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File URL: http://eprints.utas.edu.au/10451/1/DP2010-07_Dungey_Sree_Li_May_2010.pdf
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Bibliographic Info

Paper provided by University of Tasmania, School of Economics and Finance in its series Working Papers with number 10451.

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Length: 22 pages
Date of creation: 30 May 2010
Date of revision: 30 May 2012
Publication status: Published by the University of Tasmania. Discussion paper 2010-07
Handle: RePEc:tas:wpaper:10451

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Related research

Keywords: duration; high frequency data; electronic futures markets;

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  1. 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.
  2. Nikolaus Hautsch, 2002. "Modelling Intraday Trading Activity Using Box-Cox-ACD Models," CoFE Discussion Paper 02-05, Center of Finance and Econometrics, University of Konstanz.
  3. Eric Ghysels & Christian Gourieroux & Joanna Jasiak, 1997. "Stochastic Volatility Duration Models," Working Papers 97-46, Centre de Recherche en Economie et Statistique.
  4. 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.
  5. 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).
  6. Russell, Jeffrey R. & Engle, Robert F., 2005. "A Discrete-State Continuous-Time Model of Financial Transactions Prices and Times: The Autoregressive Conditional Multinomial-Autoregressive Conditional Duration Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 166-180, April.
  7. Joel Hasbrouck, 2003. "Intraday Price Formation in U.S. Equity Index Markets," Journal of Finance, American Finance Association, vol. 58(6), pages 2375-2400, December.
  8. 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.
  9. De Luca Giovanni & Gallo Giampiero M., 2004. "Mixture Processes for Financial Intradaily Durations," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(2), pages 1-20, May.
  10. Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, vol. 66(5), pages 1127-1162, September.
  11. Hujer, Reinhard & Vuletic, Sandra, 2007. "Econometric analysis of financial trade processes by discrete mixture duration models," Journal of Economic Dynamics and Control, Elsevier, vol. 31(2), pages 635-667, February.
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