This paper explores the relevance of asymmetry and long memory in modeling and forecasting the

We analyze the empirical relationship between announcement effects and return volatilities of four CAC40 companies using intraday financial and event data from SBF-Euronext and Bloomberg, respectively. We estimate the daily component of the intraday volatility using a FIGARCH model and the...

This paper explores the relevance of asymmetry and long memory in modeling and forecasting the conditional volatility and market risk of four major commodities (crude oil, natural gas, gold, and sil- ver). A broad set of the most popular linear and nonlinear GARCH-type models is used to...

This paper explores the relevance of asymmetry and long memory in modeling and forecasting the conditional volatility and market risk of four widely traded commodities (crude oil, natural gas, gold, and silver). A broad set of the most popular linear and

This paper develops methods of investigating the existence and extent of cointegration in fractionally integrated systems. We focus on stationary series, with some discussion of extension to nonstationarity. The setting is semiparametric, so that modelling is effectively confined to a...

We consider the long memory and leverage properties of a model for the conditional variance of an observable stationary sequence, where the conditional variance is the square of an inhomogeneous linear combination of past values of the observable sequence, with square summable weights. This...

Smoothed nonparametric estimates of the spectral density matrix at zero frequency have been widely used in econometric inference, because they can consistently estimate the covariance matrix of a partial sum of a possibly dependent vector process. When elements of the vector process exhibit long...

We show that it is possible to adapt to nonparametric disturbance autocorrelation in time series regression in the presence of long memory in both regressors and disturbances by using a smoothed nonparametric spectrum estimate in frequency-domain generalized least squares. When the collective...