fractionally integrated GARCH (FIGARCH) model. Monte Carlo methods are used to characterize the finite sample distributions of … these statistics when data are generated from GARCH(1,1), component GARCH and FIGARCH models. For several daily financial …This paper investigates if component GARCH models introduced by Engle and Lee(1999) and Ding and Granger(1996) can …

fractionally integrated GARCH (FIGARCH) model. Monte Carlo methods are used to characterize the finite sample distributions of … these statistics when data are generated from GARCH(1,1), component GARCH and FIGARCH models. For several daily financial …This paper investigates if component GARCH models introduced by Engle and Lee(1999) and Ding and Granger(1996) can …

price volatility, and compares their forecasting performance to the standard GARCH, fractionally integrated GARCH (FIGARCH …) and the two-state Markov-switching GARCH (MS-GARCH) models via three loss functions (the mean squared error, the mean … criteria and forecast horizons, while MS-GARCH mostly comes out as the least successful model. Applying various VaR backtesting …

financial time series and use it to improve the short-term forecasts from GARCH models. We study different generalizations of … GARCH that allow for several time scales. On our holding sample, none of the considered models can fully exploit the …

fractionally-integrated GARCH for the conditional variance. The interaction between the funds is modelled as the Dynamic …