Some statistical results on autoregressive conditionally heteroscedastic models
✍ Scribed by Esmeralda Gonçalves; NazaréMendes Lopes
- Publisher
- Elsevier Science
- Year
- 1998
- Tongue
- English
- Weight
- 633 KB
- Volume
- 68
- Category
- Article
- ISSN
- 0378-3758
No coin nor oath required. For personal study only.
✦ Synopsis
The aim of this paper is to present some statistical aspects of an order 1 autoregressive model with errors following a stationary and ergodic generalized threshold ARCH process. So, to analyse the precision of forecasts obtained with these models a probabilistic study will be done. Moreover, a consistent test for a general AR( 1) model with errors following an ergodic white noise of null conditional median will be developed and adapted to our stochastic process.
📜 SIMILAR VOLUMES
For the pth-order linear ARCH model, St = gt~/O{O q-~lXt2\_l q-0~2 X.2\_2 +-.-q-o~pXtLp, where c~0 > 0, c~i~>0, i = 1, 2, ..., p, {et} is an i.i.d, normal white noise with E~, = 0, Ee~ = 1, and et is independent of {X~, s < t}, Engle (1982) obtained the necessary and sufficient condition for the sec
The purpose of this paper is to extend the class of \(A R(1)\) models introduced by Aly and Bouzar (1994) to more general \(A R M A\) models. As an application some new Poisson geometric, negative binomial, and Poisson logarithmic ARMA models are derived. 1994 Academic Press, Inc.