A class of semiparametric fractional autoregressive GARCH models (SEMIFAR-GARCH), which includes deterministic trends, difference stationarity and stationarity with short-and long-range dependence, and heteroskedastic model errors, is very powerful for modelling financial time series. This paper...

The problem of predicting 0-1-events is considered under general conditions, including stationary processes with short and long memory as well as processes with changing distribution patterns. Nonparametric estimates of the probability function and prediction intervals are obtained.

Diese Arbeit stellt eine semiparametrische Erweiterung des ACD-Modells von Engle und Russell (1998) vor. Der Vorschlag des Semi-ACD-Modells basiert auf der Zerlegung der Daten in einen deterministischen und einen stochastischen Teil, wobei der Erste als zeitvariabel angenommen wird. Um dies...

SEMIFAR models introduced in Beran (1999) provide a semiparametric modelling framework that enables the data analyst to separate deterministic and stochastic trends as well as short- and long-memory components in an observed time series. A correct distinction between these components, and in...