heteroscedasticity (GARCH)-type models to forecast oil price volatility over the time periods from January 02, 1875 to December 31, 1895 … indicate that none of our volatility models can uniformly outperform other models across all six different loss functions …

This study investigates the role of oil futures price information on forecasting the US stock market volatility using … futures realized volatility. In particular, the multivariate HAR model outperforms the univariate model. Accordingly …, considering the contemporaneous connection is useful to predict the US stock market volatility. Furthermore, these findings are …

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

prices. We empirically assess efficiency gains in volatility estimation when using range-based estimators as opposed to … simple daily ranges and explore the use of these more efficient volatility measures as predictors of daily ranges. The array … forecasts are produced by a realized range based HAR model with a GARCH volatility-of-volatility component. …