The fourth edition follows the general layout of the third edition but includes some
modernization of topics as well as the coverage of additional topics. The preface to the third …

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 …

Nonlinear Trends, Long-Range Dependence, and Climate Noise Properties of Surface
Temperature in: Journal of Climate Volume 25 Issue 12 (2012) Jump to Content Jump to Main …

This paper explores persistence of eight largest cryptocurrency markets using daily data
from 25∕ 08∕ 2015–13∕ 03∕ 2018, across time and trading scale. Employing ARFIMA …

In this paper, we propose a simple bias–reduced log–periodogram regression estimator,^
dr, of the long–memory parameter, d, that eliminates the first–and higher–order biases of the …

Streamflow forecasting is of great importance to water resources management and flood
defense. On the other hand, a better understanding of the streamflow process is …

We argue that the predictive regression between implied volatility (regressor) and realized
volatility over the remaining life of a European option (regressand) is likely to be a fractional …

This study examines the long-range dependency, climate noise characteristics, and
nonlinear temperature trends of eight Antarctic stations from the Reference Antarctic Data for …

Provides a simple exposition of the basic time series material, and insights into underlying
technical aspects and methods of proof Long memory time series are characterized by a …

The local Whittle (or Gaussian semiparametric) estimator of long range dependence,
proposed by Künsch (1987) and analyzed by Robinson (1995a), has a relatively slow rate of …