forecasts gain from conditioning on volatility. Empirical results support the view that the relationship of interest might be …

Das in Finanzmarktdaten zu beobachtende volatility-clustering impliziert, daß große Renditeschocks bei der Preisbildung …The volatility clustering observed in financial market data implies that large net yield shocks increase the … probability of a higher future volatility during the price formation. Starting from the ARCH models which were suggested by Engle …

(2000) is applied but generalised to account for weekly periodicities and time-varying volatility. Eventually we find a …

Estimation of the volatility of time series has taken off since the introduction of the GARCH and stochastic volatility … models. While variants of the GARCH model are applied in scores of articles, use of the stochastic volatility model is less … unobserved stochastic volatility, and the varying approaches that have been taken for such estimation. In order to simplify the …

We examine the performance of volatility models that incorporate features such as long (short) memory, regime …-t). Second, we perform a comprehensive panel forecasting analysis of the MSM models as well as other competing volatility models … over the alternative volatility models in terms of mean absolute forecast errors and that (iii) forecast combinations …

characterized by volatility clustering and asymmetry. Also revealed as a stylized fact is Long memory or long range dependence in … market volatility, with significant impact on pricing and forecasting of market volatility. The implication is that models … that accomodate long memory hold the promise of improved long-run volatility forecast as well as accurate pricing of long …