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 …

The key to achieving successful stock market forecasting is obtaining the best possible
results with the minimum required input data. The central objectivesfor acquiring accurate …

This paper introduces a new long memory volatility process, denoted by adaptive FIGARCH,
or A-FIGARCH, which is designed to account for both long memory and structural change in …

We evaluate the forecasting performance of time series models for realized volatility, which
accommodate long memory, level shifts, leverage effects, day-of-the-week and holiday …

We explore the possibility of structural breaks in the daily realized volatility of the
Deutschemark/Dollar, Yen/Dollar and Yen/Deutschemark spot exchange rates with …

Traditionally, statistics and music are not generally associated with each other. However,...
intelligent... music software, computer digitization, and other advanced techniques and …

This paper proposes a model of the US unemployment rate which accounts for both its
asymmetry and its long memory. Our approach introduces fractional integration and …

Long‐range dependence (LRD) refers to dependence structures that decay slowly with
increasing distance. Mathematically this leads to limit theorems that differ from the short …

Local polynomial smoothing for the trend function and its derivatives in nonparametric
regression with long-memory, short-memory and antipersistent errors is considered. We …

This paper proposes a semiparametric approach by introducing a smooth scale function into
the standard generalized autoregressive conditional heteroskedastic (GARCH) model so …