, and, although it outperforms representative GARCH models, it does so with greater complexity and data intensiveness that … may not be worthwhile relative to GARCH's simplicity and flexibility. …

. After showing that the expectation of the sum of the estimates of the autoregressive coefficients of a GARCH(1,1) model is …

univariate ARCH-type models including the GARCH, EGARCH, GJR, APARCH, IGARCH, FIGARCH, FIEGARCH and FIAPARCH specifications of …

, the author applies several generalised autoregressive conditional heteroskedasticity (GARCH) models to account for … asymmetry and long memory effects in conditional volatility. Finally, the author back tests the GARCH models’ forecasts for … GARCH models with skewed Student’s t -distribution is recommended to forecast VaR and ES. Originality/value Up to now, no …

The paper considers the Markov-Switching GARCH(1,1)-model with time-varying transition probabilities. It derives su … observation that estimated GARCH-parameters often sum to almost one. …

It has long been known that the estimated persistence parameter in the GARCH(1,1) - model is biased upwards when the …

In this paper, we focus on three daily exchange rate returns dynamics. Indeed, we have assessed five GARCH-class models …

the GARCH(1,1), GJR(1,1) and EGARCH(1,1) models for Korean tourist arrivals to Taiwan and the Korean Won / New Taiwan …