The paper examines the volatility predictive ability of the CBOE crude oil volatility index (OVX), GARCH and Stochastic … Volatility Models in the crude oil market. Specifically, the dynamics of two major crude oil pricing benchmarks - Brent in Europe … and WTI in America are compared. OVX index is able to provide the optimal forecast for the volatility of Brent's future …

volatility for estimating conditional variances and covariances; (2) alternative currencies; and (3) alternative maturities of … Chang et al. [17], we estimate four multivariate volatility models (namely CCC, VARMA-AGARCH, DCC and BEKK), and calculate …

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. …

Nowadays, modeling and forecasting the volatility of stock markets have become central to the practice of risk … to forecast the volatility of the Moroccan stock-market index MADEX. We use daily returns covering the period between 01 …, as well as leading to a better understanding of the Moroccan stock-exchange volatility dynamics, especially with the lack …

We propose a model that extends the RT-GARCH model by allowing conditional heteroskedasticity in the volatility process …. We show we are able to filter and forecast both volatility and volatility of volatility simultaneously in this simple … setting. The volatility forecast function follows a second-order difference equation as opposed to first-order under GARCH(1 …

decades in the mean and volatility dynamics, including the underlying volatility persistence and volatility spillovers … existence of time varying correlations as well as time varying shock and volatility spillovers between the returns of FTSE and …

Forecasting-volatility models typically rely on either daily or high frequency (HF) data and the choice between these … two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer of many … forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the assumptions of jumping …

Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these … two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer from … these two family forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the …