heteroskedasticity using a FIGARCH model. The dramatic decrease in the number of significant nonlinear causality lags confirms that …

these series. But from among the conditional heteroscedasticity models, the ARFIMA-FIGARCH model was selected as the best …

appeared. In this paper two models of the conditional heteroskedasticity - fractionally integrated GARCH (FIGARCH) and EWMA are … by Kupiec´s test, TUFF and Christoffersen´s test. These tests demonstrate, that the FIGARCH model is a suitable …

trajectories from FIGARCH model. This paper is presented as follows: Section 1 opens on a definition of the volatility, Section 2 … examines the interdependence of the studied markets; Section 3 provides a FIGARCH model in order to capture the dynamics and …

latter characterizes the case of Integrated and Fractionally Integrated GARCH processes. Finally, we discuss testing for …

class of models (namely, ARFIMA (p,d',q)-GARCH (1,1), IGARCH (1,1), FIGARCH (1,d,0), FIGARCH (1,d,1), EGARCH (1,1) and … paper utilizes the wavelets approach (based on Haar, Daubechies-4, Daubechies-12 and Daubechies-20 wavelets) and the GARCH … support the Taylor effect in the volatility proxies. The results show that ARFIMA (p,d',q)-FIGARCH (1,d,0) model specification …

Conditionally Heteroskedastic (FIGARCH) and the two-state Markov Regime-Switching GARCH (RS-GARCH) models. For most of the DJN 65 … FIGARCH generally outperforms RS-GARCH. … a greater impact on volatility than positive news. Furthermore, the results from the RS-GARCH model indicate that news …

univariate and multivariate conventional VaR methods. The reported results demonstrate that GARCH-t, conditional EVT and FIGARCH … before fitting a copula. Each return series is modeled by AR-(FI) GARCH univariate model. Then, we fit the GPD distribution …

the intraday volatility using a FIGARCH model and the intraday seasonality by the Fourier Flexible Form. We find that …