ASYMPTOTIC THEORY FOR A VECTOR ARMA-GARCH MODEL
Hong Kong University of Science and Technology · The University of Western Australia
Abstract
This paper investigates the asymptotic theory for a vector autoregressive moving average–generalized autoregressive conditional heteroskedasticity (ARMA-GARCH) model. The conditions for the strict stationarity, the ergodicity, and the higher order moments of the model are established. Consistency of the quasi-maximum-likelihood estimator (QMLE) is proved under only the second-order moment condition. This consistency result is new, even for the univariate autoregressive conditional heteroskedasticity (ARCH) and GARCH models. Moreover, the asymptotic normality of the QMLE for the vector ARCH model is obtained under only the second-order moment of the unconditional errors and the finite fourth-order moment of the…
Citation impact
- FWCI
- 38.91
- Percentile
- 100%
- References
- 36
Authors
2Topics & keywords
- Mathematics
- Autoregressive conditional heteroskedasticity
- Asymptotic distribution
- Estimator
- Autoregressive model
- Strong consistency
- Moment (physics)
- Heteroscedasticity