Autoregressive gamma processes
We introduce a class of autoregressive gamma processes with conditional distributions from the family of noncentred gamma (up to a scale factor). The paper provides the stationarity and ergodicity conditions for ARG processes of any autoregressive order p , including long memory, and closed-form expressions of conditional moments. The nonlinear state space representation of an ARG process is used to derive the filtering, smoothing and forecasting algorithms. The paper also presents estimation and inference methods, illustrated by an application to interquote durations data on an infrequently traded stock listed on the Toronto Stock Exchange (TSX). Copyright © 2006 John Wiley & Sons, Ltd.
Volume (Year): 25 (2006)
Issue (Month): 2 ()
|Contact details of provider:|| Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966 |
When requesting a correction, please mention this item's handle: RePEc:jof:jforec:v:25:y:2006:i:2:p:129-152. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing)or (Christopher F. Baum)
If references are entirely missing, you can add them using this form.