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 …

memory in stochastic volatility (SV) components in order to develop the General Long Memory SV (GLMSV) model. We examine the …

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 …

forecasting errors in realized volatility are substantive. Even though returns standardized by ex post quadratic variation … degree of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which … distribution of returns. Explicitly modeling this volatility risk is fundamental. We propose a dually asymmetric realized …