such as Generalized Autoregressive Conditional Heteroskedastic (GARCH), Generalized Autoregressive Score (GAS), and … relevant financial/macroeconomic news into asset price movements. For inference and prediction, we employ an innovative … inclusion of exogenous variables is beneficial for GARCH-type models while offering only a marginal improvement for GAS and SV …

Accurate prediction of risk measures such as Value at Risk (VaR) and Expected Shortfall (ES) requires precise … posterior and traditional Bayesian Model Averaging techniques in applications of Value-at-Risk prediction in GARCH models. …

autoregressive score (GAS) models have similar predictive accuracy to correctly specified parameter-driven models. In most cases … alternatives. We also find that GAS models outperform many familiar observation-driven models in terms of forecasting accuracy. The …

Ding, Granger and Engle (1993) and Ding and Granger (1996). Our prediction experiments use high frequency price returns … variations help less in the prediction of future realized volatility, than past "small" jump power variations. Additionally, we …, are strongly correlated with future volatility, and that past downside jump variations matter in prediction. Finally …

Accurate prediction of risk measures such as Value at Risk (VaR) and Expected Shortfall (ES) requires precise … techniques in applications of Value-at-Risk prediction in GARCH models …