For forecasting volatility of futures returns, the paper proposes an indirect method based on the relationship between … futures and the underlying asset for the returns and time-varying volatility. For volatility forecasting, the paper considers … that the new method based on stochastic volatility models with the asymmetry and long memory outperforms the forecasting …

of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which forecasting …

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. …

We study whether and when parameter-driven time-varying parameter models lead to forecasting gains over observation … 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 …