Long-memory, or more generally fractal, processes are known to play an important role in
many scientific disciplines and applied fields such as physics, geophysics, hydrology …

Econometric modelling of financial data received a broad interest in the last 20 years and
the literature on ARCH and related models is vast. Starting with the path breaking works by …

In this paper we propose a flexible model to describe nonlinearities and long-range
dependence in time series dynamics. The new model is a multiple regime smooth transition …

In transportation analyses, autoregressive integrated moving average (ARIMA) and
generalized autoregressive conditional heteroskedasticity (GARCH) models have been …

We develop a framework to assess how successfully standard time series models explain
low‐frequency variability of a data series. The low‐frequency information is extracted by …

The paper proposes a novel model for time series displaying persistent stationary cycles, the
fractional sinusoidal waveform process. The underlying idea is to allow the parameters that …

The presence of long memory in realized volatility (RV) is a widespread stylized fact. The
origins of long memory in RV have been attributed to jumps, structural breaks …

It is commonly argued that observed long memory in time series variables can result from
cross-sectional aggregation of dynamic heterogeneous micro units. In this paper we …

The so-called type I and type II fractional Brownian motions are limit distributions associated
with the fractional integration model in which pre-sample shocks are either included in the …

Age coherence describes the property that forecast mortality rates across ages will not
diverge in the long run. Although intuitively and biologically reasonable, this property is lost …