Time-Varying Mixing Weights in Mixture Autoregressive Conditional Duration Models
Universita' di Firenze Working Paper No. 2005-11
29 Pages Posted: 29 Mar 2006
Date Written: October 25, 2005
Abstract
Financial market price formation and exchange activity can be investigated by means of ultra-high frequency data. In this paper we investigate an extension of the Autoregressive Conditional Duration (ACD) model of Engle and Russell (1998) by adopting a mixture of distribution approach with time varying weights. Empirical estimation of the Mixture ACD model shows that the limitations of the standard base model and its inadequacy of modelling the behavior in the tail of the distribution are suitably solved by our model.
When the weights are made dependent on some market activity data, the model lends itself to some structural interpretation related to price formation and information diffusion in the market.
Keywords: Market microstructure, ACD models, Exponential mixtures, Price durations
JEL Classification: C14, c23, c42
Suggested Citation: Suggested Citation
Here is the Coronavirus
related research on SSRN
Recommended Papers
-
By Luc Bauwens and J. V. K. Rombouts
-
Time-Varying Arrival Rates of Informed and Uninformed Trades
By David Easley, Liuren Wu, ...
-
A Model for the Federal Funds Rate Target
By James D. Hamilton and Oscar Jorda
-
A Model for the Federal Funds Rate Target
By James D. Hamilton and Oscar Jorda
-
The Logarithmic Acd Model: An Application to the Bid-Ask Quote Process of Three NYSE Stocks
By Luc Bauwens and Pierre Giot
-
By Luc Bauwens and David Veredas
-
Identifying Bull and Bear Markets in Stock Returns
By John M. Maheu and Thomas H. Mccurdy
