Estimation of GARCH models can be simplified by augmenting quasi-maximum likelihood (QML) estimation with variance … volatility equation and corresponding value-at-risk predictions. We find that most GARCH coefficients and associated predictions …

for conditional heteroskedasticity; a favored model is Dynamic Conditional Correlation (DCC), derived from the ARCH/GARCH …

for conditional heteroskedasticity; a favored model is Dynamic Conditional Correlation (DCC), derived from the ARCH/GARCH …

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 …

This paper examines exchange-rate volatility with GARCH models using monthly exchange-rate return series from 1985:1 to … compare estimates of variants of GARCH models with break in respect of the US dollar rates with exogenously determined break … estimation of volatility models with breaks as against those of GARCH models without volatility breaks and that the introduction …

When the ARMA-GARCH model errors lack a finite fourth moment, the asymptotic distribution of the quasi …, simulations show that the conventional bootstrap, despite its inconsistency, provides accurate confidence intervals for ARMA-GARCH … intervals for ARMA-GARCH VaR. According to theory, this `omnibus' method produces confidence intervals with asymptotically …

-correction method can improve the n-GARCH and n-EGARCH VaR forecasts so much that the acquired VaR predictions are different from the … distribution instead of GARCH improves the performance of the bias-correction method in forecasting the VaR for almost all …