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Autoregressive gamma processes

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Author Info
Joann Jasiak (York University, Canada)
Christian Gourieroux (CREST, CEPREMAP and University of Toronto, Canada)

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Abstract

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.

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File URL: http://hdl.handle.net/10.1002/for.978
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Publisher Info
Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 25 (2006)
Issue (Month): 2 ()
Pages: 129-152
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Handle: RePEc:jof:jforec:v:25:y:2006:i:2:p:129-152

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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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  1. Nour Meddahi, 2001. "An Eigenfunction Approach for Volatility Modeling," CIRANO Working Papers 2001s-70, CIRANO. [Downloadable!]
  2. Roberto Casarin, 2005. "Stochastic Processes in Credit Risk Modelling," Working Papers ubs0505, University of Brescia, Department of Economics. [Downloadable!]
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This page was last updated on 2008-8-6.

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