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 …

heteroscedasticity (CGARCH (1, 1)) model. Employing the autoregressive distributed lag (ARDL) estimator on data covering 1970 to 2020 …

Although the properties of the ARCH(∞) model are well investigated, the existence of long memory FIGARCH and IARCH … finite variance FIGARCH and IARCH models and, thus, the possibility of long memory in the ARCH setting was doubtful. The … present paper solves this controversy by showing that FIGARCH and IARCH equations have a non-trivial covariance stationary …

fractionally integrated generalized autoregressive conditional heteroskedasticity (FIGARCH) model. Our algorithm is a variation of …

and structural breaks on fractality is investigated through the ARFIMA-FIGARCH and ARFIMA-HYGARCH models. We observe that …