We establish consistency and asymptotic normality for a weighted least squares estimate (2SWLSE) of a threshold power ARCH process in both stationary and nonstationary environments. For models with heavy tail innovations, the 2SWLSE is more efficient than the quasi-maximum likelihood estimate.

For an ARCH model, we propose a multistage weighted least squares (WLS) estimate which consists of repeated WLS procedures until the corresponding asymptotic variance equals that of the quasi-maximum likelihood estimate (QMLE). At every stage, the current estimate is of a WLS type weighted by...

This paper deals with some probabilistic properties of the class of periodic autoregressions (PAR) with periodic ARCH innovations (PAR-PARCH). Under some suitable assumptions an equivalent random coefficient periodic autoregression formulation of the periodic ARCH equation is proposed, leading...

In this paper we mainly study the existence of higher-order moments of periodic GARCH models (P-GARCH) introduced by [Bollerslev, T., Ghysels, E., 1996. Periodic autoregressive conditional heteroskedasticity. Journal of Business and Economic Statistics 14, 139-152]. We provide an explicit...

This paper studies periodic stationarity of a random coefficient periodic autoregression (RCPAR) which generalizes the standard random coefficient autoregressive (RCAR) model to the case where the deterministic parameters and the disturbance variances are periodically time-varying. Sufficient...

This article establishes the strong consistency and asymptotic normality (CAN) of the quasi-maximum likelihood estimator (QMLE) for generalized autoregressive conditionally heteroscedastic (GARCH) and autoregressive moving-average (ARMA)-GARCH processes with periodically time-varying parameters....

A class of nonlinear time-series models in which the underlying process follows a finite mixture of bilinear representations is proposed. The mixture feature appears in the conditional distribution of the process which is given as a finite mixture of distributions evaluated at the normed...

This paper proposes two estimation methods based on a weighted least squares criterion for non-(strictly) stationary power ARCH models. The weights are the squared volatilities evaluated at a known value in the parameter space. The first method is adapted for fixed sample size data while the...