Journal article
A Note on Non-Negative Arma Processes
Journal of time series analysis, Vol.28(3), pp.350-360
First Version received February 2005
05/2007
DOI: 10.1111/j.1467-9892.2006.00513.x
Abstract
Recently, there has been much research on developing models suitable for analysing the volatility of a discrete-time process. Since the volatility process, like many others, is necessarily non-negative, there is a need to construct models for stationary processes which are non-negative with probability one. Such models can be obtained by driving autoregressive moving average (ARMA) processes with non-negative kernel by non-negative white noise. This raises the problem of finding simple conditions under which an ARMA process with given coefficients has a non-negative kernel. In this article, we derive a necessary and sufficient condition. This condition is in terms of the generating function of the ARMA kernel which has a simple form. Moreover, we derive some readily verifiable necessary and sufficient conditions for some ARMA processes to be non-negative almost surely. © 2006 Blackwell Publishing Ltd.
Details
- Title: Subtitle
- A Note on Non-Negative Arma Processes
- Creators
- Henghsiu Tsai - University of IowaK. S Chan - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Journal of time series analysis, Vol.28(3), pp.350-360
- Edition
- First Version received February 2005
- DOI
- 10.1111/j.1467-9892.2006.00513.x
- ISSN
- 0143-9782
- eISSN
- 1467-9892
- Publisher
- Blackwell Publishing Ltd
- Number of pages
- 11
- Language
- English
- Date published
- 05/2007
- Academic Unit
- Statistics and Actuarial Science; Radiology
- Record Identifier
- 9984257741102771
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