Not Available for Download

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

Posted: 21 Apr 1998  

Jeffrey R. Russell

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

Robert F. Engle

New York University - Leonard N. Stern School of Business - Department of Economics; New York University (NYU) - Department of Finance; National Bureau of Economic Research (NBER)

Abstract

This paper proposes a new statistical model for the analysis of data that do 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 events as a stochastic time varying process. We propose a new model for point processes with intertemporal correlation. Because the model focuses on the time interval between events it is called the Autoregressive Conditional Duration (ACD) model. Strong evidence is provided for transaction clustering for the financial transactions dataanalyzed, even after time-of-day effects are removed. Although the model is most naturally applied to the arrival of transactions, we suggest a thinning algorithm to model characteristics associated with the arrival times, allowing the investigator to model processes that are observed in irregular time intervals, not just the arrival times of the data. Models for transaction events, the flow of volume, and the rate of change for prices are estimated.

JEL Classification: C2, C22, G1

Suggested Citation

Russell, Jeffrey R. and Engle, Robert F., Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data. Available at SSRN: https://ssrn.com/abstract=6809

Jeffrey R. Russell (Contact Author)

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

New York University - Leonard N. Stern School of Business - Department of Economics ( email )

269 Mercer Street
New York, NY 10003
United States

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

Paper statistics

Abstract Views
3,156