volatility (RV) of ten global stock market indices in the period from January 2000 to December 2021. We train models using a …

In this paper, we estimate, model and forecast Realized Range Volatility, a new realized measure and estimator of the …-known stylized effects present in financial data. We consider an HAR model with asymmetric effects with respect to the volatility and …

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 …

allowing the conditional variance of a particular market to depend on past volatility shocks in other markets. The inter …. Extending the model to incorporate leverage effects leads to further improvement in the volatility fit. We compare weight …

Alternative strategies for predicting stock market volatility are examined. In out-of-sample forecasting experiments … implied-volatility information, derived from contemporaneously observed option prices or history-based volatility predictors …, such as GARCH models, are investigated, to determine if they are more appropriate for predicting future return volatility …

framework. However, little is known about the ranking of multivariate volatility models in terms of their forecasting ability …. The ranking of multivariate volatility models is inherently problematic because it requires the use of a proxy for the … unobservable volatility matrix and this substitution may severely affect the ranking. We address this issue by investigating the …