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
On a threshold autoregression with conditional heteroscedastic variances
β Scribed by J. Liu; W.K. Li; C.W. Li
- Publisher
- Elsevier Science
- Year
- 1997
- Tongue
- English
- Weight
- 1001 KB
- Volume
- 62
- Category
- Article
- ISSN
- 0378-3758
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β¦ Synopsis
This paper considers a time series model with a piecewise linear conditional mean and a piece-wise linear conditional variance which is a natural extension of Tong's threshold autoregressiw~ model. The model has potential applications in modelling asymmetric behaviour in volatility ia the financial market. Conditions for stationarity and ergodicity are derived. Asymptotic properties of the maximum likelihood estimator and two model diagnostic checking statistics are also presented. An illustrative example based on the Hong Kong Hang Seng index is also reported.
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For a stationary ergodic self-exciting threshold autoregressive model with single threshold parameter, Chan (1993) obtained the consistency and limiting distribution of the least-squares estimator for the underlying true parameters. In this paper, we derive the similar results for the maximum likeli
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