This paper proposes a very general time series framework to capture the long-run behaviour of financial series. The suggested model includes linear and non-linear time trends, and stationary and nonstationary processes based on integer and/or fractional degrees of differentiation. Moreover, the...

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...

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 examines the degree of persistence in the volatility of financial time series using a Long Memory Stochastic Volatility (LMSV) model. Specifically, it employs a Gaussian semiparametric (or local Whittle) estimator of the memory parameter, based on the frequency domain, proposed by...

This paper focuses on nominal exchange rates, specifically the US dollar rate vis-à-vis the Euro and the Japanese Yen at a daily frequency. We model both absolute values of returns and squared returns using long-memory techniques, being particularly interested in volatility modelling and...

This paper investigates the empirical relevance of different unemployment theories in three major economies, namely the UK, the US and Japan, by estimating the degree of dependence in the unemployment series. Both univariate and multivariate long memory methods are used. The results vary...

This paper analyses monthly hours worked in the US over the sample period 1939m1–2011m10 using a cyclical long memory model. This model, which is based on Gegenbauer processes, is characterised by autocorrelations decaying to zero cyclically and hyperbolically, with a spectral density that is...

This note examines the stochastic properties of US term spreads with parametric and semi-parametric fractional integration techniques. Since the observed data (rather than the estimated residuals from a cointegrating regression) are used for the analysis, standard methods can be applied. The...

This paper examines several US monthly financial time series data using fractional integration and cointegration techniques. The univariate analysis based on fractional integration aims to determine whether the series are I(1) (in which case markets might be efficient) or alternatively I(d) with...

This paper examines the degree of persistence in the volatility of financial time series using a Long Memory Stochastic Volatility (LMSV) model. Specifically, it employs a Gaussian semiparametric (or local Whittle) estimator of the memory parameter, based on the frequency domain, proposed by...