forecasting errors in realized volatility are substantive. Even though returns standardized by ex post quadratic variation …

forecasting, the authors propose a new factor multivariate stochastic volatility (fMSV) model for realized covariance measures … outperform existing dynamic conditional correlation models for forecasting future covariances. Among the new fMSV models, the … Cholesky MSV model with long memory and asymmetry shows stable and better forecasting performance for one-day, five-day and ten …

under the Basel Accord: A Bayesian approach to forecasting value-at-risk of VIX futures, fast clustering of GARCH processes … dynamics of BRICS's country risk ratings and domestic stock markets, U.S. stock market and oil price, forecasting value …

The paper investigates the impact of jumps in forecasting co-volatility, accommodating leverage effects. We modify the … the co-jumps of two assets have a significant impact on future co-volatility, but that the impact is negligible for … forecasting weekly and monthly horizons. …

This discussion paper resulted in a publication in the 'International Journal of Forecasting', 2009, 27, 282-303.<P …

and when parameter-driven time-varying parameter models lead to forecasting gains over observation-driven models. We … alternatives. We also find that GAS models outperform many familiar observation-driven models in terms of forecasting accuracy. The … results point to a class of observation-driven models with comparable forecasting ability to parameter-driven models, but …

This paper develops a novel approach to modeling and forecasting realized volatility (RV) measures based on copula … index futures, we find that the copula-based RV (C-RV) model outperforms conventional forecasting approaches for one …

forecasting errors in realized volatility are substantive. Even though returns standardized by ex post quadratic variation …