GARCH for Irregularly Spaced Financial Data: The ACD-GARCH Model

By Ghysels Eric and Jasiak Joanna
Studies in Nonlinear Dynamics and Econometrics (1998)

  • Christophe Hurlin

    University of Orléans


  • Georgiana Denisa Banulescu

    University of Orléans and Maastricht University



October 9, 2013

Last update

October 10, 2013










These codes compute the estimation results of the exponential autoregressive conditional duration (EACD) model of Engle and Russell (1998) and the ACD-GARCH model proposed by Ghysels and Jasiak (1998) (two-step procedure). We display the parameter estimates of these two models as well as the log likelihood values. To obtain these results run the file appel_ACD_GARCH.m. The parameters that can be changed manually are: the dataset used (data), the price change threshold (C), the nominal level of risk (alpha_VaR), the end of the in-sample period (insample_end) and the order of the EACD model (p,q). Note that for these codes the database should contain the following variables: the date, the mid-quote price, the price, the time of the transaction (number of seconds after the midnight), the lagged time of the transaction, the duration, the name of the day, the index of the day, the lagged index of the day, the price variation, the return, the hour. One can define a less complex database; for this the first part of the file ACD_ESTIMATION.m should also be adapted. A demo database is provided.

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