We test for fractional dynamics in U.S. monetary series, their various formulations and components, and velocity series. Using the spectral regression method, we find evidence of a fractional exponent in the differencing process of the monetary series (both simple-sum and Divisia indices), in...

The paper derives a Multivariate Asymmetric Long Memory conditional volatility model with Exogenous Variables (X), or the MALMX model, with dynamic conditional correlations, appropriate regularity conditions, and associated asymptotic theory. This enables checking of internal consistency and...

The research used a long memory or Autoregressive Fractionally Integrated Moving Average model to study and forecast crude oil prices using weekly West Texas Intermediate and Brent series for the period 15/5/1987 to 20/12/2013. Fractional differencing Methods such as Local Whittle Estimator and...

We develop methods to obtain optimal forecast under long memory in the presence of a discrete structural break based on different weighting schemes for the observations. We observe significant changes in the forecasts when long-range dependence is taken into account. Using Monte Carlo...

The research used a long memory or Autoregressive Fractionally Integrated Moving Average model to study and forecast crude oil prices using weekly West Texas Intermediate and Brent series for the period 15/5/1987 to 20/12/2013. Fractional differencing Methods such as Local Whittle Estimator and...

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, non-linearities, or pure long memory. An important development has been the Heterogeneous Autoregressive (HAR) model and its...

This paper examines long memory volatility in international stock markets. We show that long memory volatility is widespread in eighty-two countries and that the degree of memory can be related to macroeconomic variables such as inflation, unemployment rates, interest rates or stability of a...

Over the last years there has been considerable interest in the application of long memory time series models in economics using ARFIMA models. Nowadays, the most popular estimator of the difference parameter in economic applications is that proposed by Geweke and Porter-Hudak (GPH) although has...

In short-term evolution analysis, the economic time series are contamined by different types of noises which need to be erased in order to extract a trend signal. In the last years there has been increasingly developed some methods to estimate unobserved components based on the assumption that...

We develop methods to obtain optimal forecast under long memory in the presence of a discrete structural break based on different weighting schemes for the observations. We observe significant changes in the forecasts when long-range dependence is taken into account. Using Monte Carlo...