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

  • Robert F. Engle
  • Jeffrey R. Russell

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.

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Article provided by Econometric Society in its journal Econometrica.

Volume (Year): 66 (1998)
Issue (Month): 5 (September)
Pages: 1127-1162

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