In this paper we give the theoretical basis of a possible explanation for two stylized facts observed in long log-return series: the long range dependence (LRD) in volatility and the integrated GARCH (IGARCH). Both these effects can be theoretically explained if one assumes that the data is...

Our study supports the hypothesis of global non-stationarity of the return time series. We bring forth both theoretical and empirical evidence that the long range dependence (LRD) type behavior of the sample ACF and the periodogram of absolute return series and the IGARCH effect documented in...

In this paper we propose a goodness of fit test that checks the resemblance of the spectral density of a GARCH process to that of the log-returns. The asymptotic behavior of the test statistics are given by a functional central limit theorem for the integrated periodogram of the data. A...

The paper outlines a methodology for analyzing daily stock returns that relinquishes the assumption of global stationarity. Giving up this common working hypothesis reflects our belief that fundamental features of the financial markets are continuously and significantly changing. Our approach...

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 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 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 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 analyses the long-memory properties of high frequency financial time series. It focuses on temporal aggregation and the influence that this might have on the degree of dependence of the series. Fractional integration or I(d) models are estimated with a variety of specifications for...

This paper analyses two well-known features of interest rates, namely their time dependence and their cyclical structure. Specifically, it focuses on the monthly Euribor rate, using monthly data from January 1994 to May 2011. Models based on fractional integration at the long run or zero...