We provide a methodology to disentangle the long-run relation between variables from their own dynamics. Macroeconomic and aggregate financial series have a high degree of inertia. If this persistence is not properly accounted for, spurious correlations will give rise to paradoxes. Our procedure...

The aim of this paper is to examine the measurement of persistence in a range of time series models nested in the framework of Cramer (1961). This framework is a generalization of the Wold (1938) decomposition for stationary time series which, in addition to accommodating the standard I(0) and...

This paper argues that persistence is not an invariant feature of a time series, but depends on the context in which the series is used: as the parameters of any dynamic model are defined relative to a particular information set, any change in the set of conditioning variables might affect the...

The steady growth in the utilisation of wind power for electricity generation has led to increased interest in methods for synthetically generating wind speeds that are able to more accurately determine the site potential.

The purpose of this paper is to study the self-similar properties of discrete-time long memory processes. We apply our results to specific processes such as GARMA processes and GIGARCH processes, heteroscedastic models and the processes with switches and jumps.

In financial markets, not only prices and returns can be considered as random variables, but also the waiting time between two transactions varies randomly. In the following, we analyse the statistical properties of General Electric stock prices, traded at NYSE, in October 1999. These properties...