An Examination of the Role of Time in Ultra-High Frequency Data and its Impact on Price Revisions in News Corporation Stock
Edith Cowan University Accounting, Finance and Economics Working Paper
23 Pages Posted: 9 Apr 2004
Date Written: December 2003
We consider a new class of time series models (introduced by Engle and Russell (1998)) used in statistical applications in finance. These models treat the time between events (durations) as a stochastic process and the corresponding durations are modelled using a theory similar to that of autoregressive processes. This new class of time series models is called Autoregressive Conditional Duration (ACD) models. We apply the theory to analyse the behaviour of an Australian Stock: News Corporation, using a high-frequency data set obtained from SIRCA.
Keywords: Autoregressive, Conditional expectation, Intensity, Hazard function
JEL Classification: G12, C22
Suggested Citation: Suggested Citation