Forecasting Transaction Rates: The Autoregressive Conditional Duration Model

47 Pages Posted: 30 Aug 2000 Last revised: 30 Jul 2010

See all articles by Jeffrey R. Russell

Jeffrey R. Russell

University of Chicago - Booth School of Business - Econometrics and Statistics

Robert F. Engle

New York University (NYU) - Department of Finance; National Bureau of Economic Research (NBER); New York University (NYU) - Volatility and Risk Institute

Date Written: December 1994

Abstract

This paper will propose a new statistical model for the analysis of data that does not arrive in equal time intervals such as financial transactions data, telephone calls, or sales data on commodities that are tracked electronically. In contrast to fixed interval analysis, the model treats the time between observation arrivals as a stochastic time varying process and therefore is in the spirit of the models of time deformation initially proposed by Tauchen and Pitts (1983), Clark (1973) and more recently discussed by Stock (1988), Lamoureux and Lastrapes (1992), Muller et al. (1990) and Ghysels and Jasiak (1994) but does not require auxiliary data or assumptions on the causes of time flow. Strong evidence is provided for duration clustering beyond a deterministic component for the financial transactions data analyzed. We will show that a very simple version of the model can successfully account for the significant autocorrelations in the observed durations between trades of IBM stock on the consolidated market. A simple transformation of the duration data allows us to include volume in the model.

Suggested Citation

Russell, Jeffrey R. and Engle, Robert F., Forecasting Transaction Rates: The Autoregressive Conditional Duration Model (December 1994). NBER Working Paper No. w4966, Available at SSRN: https://ssrn.com/abstract=226565

Jeffrey R. Russell

University of Chicago - Booth School of Business - Econometrics and Statistics ( email )

Chicago, IL 60637
United States
773-834-0720 (Phone)
773-702-0458 (Fax)

Robert F. Engle (Contact Author)

New York University (NYU) - Department of Finance

Stern School of Business
44 West 4th Street
New York, NY 10012-1126
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

New York University (NYU) - Volatility and Risk Institute ( email )

44 West 4th Street
New York, NY 10012
United States

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