Selecting the order of an ARCH model

Since the parameters of an autoregressive conditional heteroskedasticity (ARCH) process must be non-negative, inference on ARCH parameters can be improved by using inequality constrained estimation. In this paper, we extend this principle to the problem of ARCH lag order selection. We show that in t...

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Bibliographic Details
Published in:Economics letters 2004-05, Vol.83 (2), p.269-275
Main Authors: Hughes, Anthony W, King, Maxwell L, Kwek, Kian Teng
Format: Article
Language:English
Subjects:
Economic models
Economics
Estimation
Inequality
Inequality constrained maximum likelihood
Model selection
Model testing
One-sided AIC
Probability
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Summary:Since the parameters of an autoregressive conditional heteroskedasticity (ARCH) process must be non-negative, inference on ARCH parameters can be improved by using inequality constrained estimation. In this paper, we extend this principle to the problem of ARCH lag order selection. We show that in the case of AIC, the appropriate adjustment to the penalty function has a simple form.
ISSN:0165-1765
1873-7374
DOI:10.1016/j.econlet.2003.05.003