This paper deals with statistics�and econometrics�properties of fractionally integra- ted GARCH (FIGARCH). We compare these characteristics with those of traditional models. We insist on the GARCH exponential/IGARCH in�nite decrease of volatility impact. Then, we apply it on three Tunisian...

The variance profile is defined as the power mean of the spectral density function of a stationary stochastic process. It is a continuous and non-decreasing function of the power parameter, p, which returns the minimum of the spectrum (p → −∞), the interpolation error variance (harmonic...

In this paper the specification of long memory has been studied using monthly data in total oil supply in Iran from 1994 to 2009. Because monthly oil supply series in Iran are showing nonstationary and periodic behavior we fit the data with SARIMA and SARFIMA models, and estimate the parameters...

We develop a generalized impulse response function for the fractionally integrated vector autoregressive (FIVAR) model using the Pesaran and Shin (1998) approach. Our method is different from the methodology shown in Chung (2001) since it does not require us to orthogonalize the error vector...

The present study aimed at investigating the existence of long memory properties in ten developed stock markets across the globe. When return series exhibit long memory, the series realizations are not independent over time and past returns can help predict future returns, thus violating the...

We show that the (Baillie and Chung, 2001) minimum distance estimates of the GARCH (1,1) model induce spurious persistence in the volatility when there are structural changes in the mean of the process.

The properties of an iterative procedure for the estimation of the parameters of an ARFIMA process are investigated in a Monte Carlo study. The estimation procedure is applied to stock returns data for 15 countries.

The present study aimed at investigating the existence of long memory properties in ten developed stock markets across the globe. When return series exhibit long memory, the series realizations are not independent over time and past returns can help predict future returns, thus violating the...

In the context of long memory, the finite-sample distortion of statistic distributions is so large, that bootstrap confidence intervals (percentile and percentile-t) for the long memory parameter do not perform better than the corresponding asymptotic confidence interval. In this paper, we...