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Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data

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  • Robert F. Engle
  • Jeffrey R. Russell

Abstract

This paper proposes a new statistical model for the analysis of data which arrives at irregular intervals. The model treats the time between events as a stochastic process and proposes a new class of point processes with dependent arrival rates. The conditional intensity is developed and compared with other self-exciting processes. The model is applied to the arrival times of financial transactions and therefore is a model of transaction volume, and also to the arrival of other events such as price changes. Models for the volatility of prices are estimated, and examined from a market microstructure point of view.

Suggested Citation

  • 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.
  • Handle: RePEc:ecm:emetrp:v:66:y:1998:i:5:p:1127-1162
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