This paper analyses the long-memory properties of a high-frequency financial time series dataset. It focuses on temporal aggregation and other features of the data, and how they might affect the degree of dependence of the series. Fractional integration or I(d) models are estimated with a...

In this paper we specify a multi-factor long-memory process that enables us to estimate the fractional differencing parameters at each frequency separately, and adopt this framework to model quarterly prices in three European countries (France, Italy and the UK). The empirical results suggest...

This paper analyses the long memory properties of quarterly real output per capita in the US (1948Q1 – 2008Q3) using non-parametric, semi-parametric and parametric techniques. The results vary substantially depending on the methodology employed. Evidence of mean reversion is obtained in a...

This paper examines the long-run dynamics and the cyclical structure of various series related to the US stock market using fractional integration. We implement a procedure which enables one to consider unit roots with possibly fractional orders of integration both at the zero (long-run) and the...

The paper considers the Markov-Switching GARCH(1,1)-model with time-varying transition probabilities. It derives sufficient conditions for the square of the process to display long memory and provides some additional intuition for the empirical observation that estimated GARCH-parameters often...

This paper considers the problem of aggregation in the case of large linear dynamic panels, where each micro unit is potentially related to all other micro units, and where micro innovations are allowed to be cross sectionally dependent. Following Pesaran (2003), an optimal aggregate function is...