Many current seasonally adjusted level data are based on Census-X-11-type moving average filters applied to past and forecasted log-transformed observations, which is usually called the Census-X-11 ARIMA method. The forecasts are often generated from seasonal ARIMA models for the log-transformed...

In this paper we propose to consider a measure of the persistence of shocks in linear combinations of nonlinear processes, in order to investigate the possible presence of common long-run properties. We argue that such common persistence for nonlinear time series corresponds to the concept of...

In this paper we test for (Generalized) AutoRegressive Conditional Heteroskedasticity [(G) ARCH] in daily and weekly data on 22 exchange rates and 13 stock market indices using the standard Lagrange Multiplier [LM] test for GARCH and a new LM test that is resistant to additive outliers. The data...

In this paper we propose a sequential testing procedure to determine the order of differencing in seasonally observed time series processes, which builds existing approaches developed for nonseasonal series. We allow for the possible presence of multiple unit roots at both zero and seasonal...

In this paper the issue of detecting and handling outliers in the GARCH(1,1) model is addressed. Simulation evidence shows that neglecting even a single outlier has a dramatic on parameter estimates. To detect and correct for outliers, we propose an adaptation of the iterative in Chen and Liu...

This paper is concerned with forecasting univariate seasonal time series data using periodic autoregressive models. We show how one should account for unit roots and deterministic terms when generating out-of-sample forecasts. We illustrate the models for various quarterly UK consumption series.

In addition to clear-cut seasonality in mean and variance, weekly Dutch temperature data appear to have a strong asymmetry in the impact of unexpectedly high or low temperatures on conditional volatility. Furthermore, this asymmetry also shows fairly pronounced seasonal variation. To describe...

In this paper, we make use of state space models to investigate the presence of stochastic trends in economic time series. A model is specified where such a trend can enter either in the autoregressive representation or in a separate state equation. Tests based on the former are analogous to...