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 the case of AIC, the appropriate adjustment to the penalty function has a simple form.
|Date of creation:||1999|
|Publication status:||Published in Economics Letters, 2004, vol. 83, issue 2, pp. 269-275|
|Contact details of provider:|| Postal: Adelaide SA 5005|
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