It is shown that the EGARCH model is the degenerate case of Danielsson's [Journal of Econometrics (1994) Vol. 61, pp. 375-400] stochastic volatility model where the disturbance of the transition equation of conditional volatility has zero variance. The Lagrange multiplier test statistic is...

Although the t-ratio variant of the Dickey-Fuller test is the most commonly applied unit-root test in practical applications, it has been known for some time that readily implementable, more powerful modifications are available. We explore the large-sample properties of five of these modified...

Tsai and Chan (2003) has recently introduced the Continuous-time Auto-Regressive Fractionally Integrated Moving-Average (CARFIMA) models useful for studying long-memory data. We consider the estimation of the CARFIMA models with discrete-time data by maximizing the Whittle likelihood. We show...

In this paper we attempt to establish unified sufficient conditions for geometric ergodicity of autoregressive models. It is shown that there is a close relationship between geometric ergodicity and mixing properties. The case of nonstationary time series is incorporated into the investigations....

The extension of stationary process autocorrelation coefficient sequence is a classical problem in the field of spectral estimation. In this note, we treat this extension problem for the periodically correlated processes by using the partial autocorrelation function. We show that the theory of...

We propose simple parametric and nonparametric bootstrap methods for estimating the prediction mean square error (PMSE) of state vector predictors that use estimated model parameters. As is well known, substituting the model parameters by their estimates in the theoretical PMSE expression that...

The problem of identifying the time location and estimating the amplitude of outliers in nonlinear time series is addressed. A model-based method is proposed for detecting the presence of additive or innovational outliers when the series is generated by a general nonlinear model. We use this...

We propose a non-parametric local likelihood estimator for the log-transformed autoregressive conditional heteroscedastic (ARCH) (1) model. Our non-parametric estimator is constructed within the likelihood framework for non-Gaussian observations: it is different from standard kernel regression...

The aim of this paper is to examine the application of measures of persistence in a range of time-series models nested in the framework of Cramer (1961). This framework is a generalization of the Wold (1938) decomposition for stationary time-series which, in addition to accommodating the...

Exact and asymptotic distributions of the maximum likelihood estimator of the autoregressive parameter in a first-order bifurcating autoregressive process with exponential innovations are derived. The limit distributions for the stationary, critical and explosive cases are unified via a single...