estimator. The OLS regression with the HAC covariance matrix estimation and the GARCH-type models are employed toexplore the …

: Germany, United Kingdom, China, Russia, and Turkey. MARMA, GARCH, GARCH-in-mean, and exponential GARCH (EGARCH) methodologies …

We apply the GARCH-MIDAS framework to forecast the daily, weekly, and monthly volatility of five highly capitalized …

markets. We use filtered historical simulations, GARCH models, and stochastic volatility models. The out-of-sample performance … models, we obtain better Value-at-Risk forecasts compared to GARCH. The quality varies over forecasting horizons and across …

(GARCH), asymmetric power ARCH (APARCH), exponential generalized autoregressive conditional heteroscedstic (EGARCH …-of-sample volatility forecasting, AR(2)–GARCH(1, 1) is considered the best. …

Linear GARCH(1,1) and threshold GARCH(1,1) processes are established as regularly varying, meaning their heavy tails … considered a stylized fact for many financial returns assumed to follow GARCH-type processes. The result in this note aids in … establishing the asymptotic properties of certain GARCH estimators proposed in the literature …

such as Generalized Autoregressive Conditional Heteroskedastic (GARCH), Generalized Autoregressive Score (GAS), and … inclusion of exogenous variables is beneficial for GARCH-type models while offering only a marginal improvement for GAS and SV …

traditional GARCH-type models (GARCH and GJR-GARCH) the two-regime Markov Switching GARCHtype models (MS-GARCH and MS-GJR-GARCH … persistence of individual markets which substantially differed across the both regimes. Furthermore, the GJR-GARCH and MS-GJR-GARCH … models clearly confirmed the presence of the leverage effect. Consideration of the MS-GARCH-type models enabled to capture …