Forecasts of crude oil prices' volatility are important inputs to many decision making processes in application areas … large number of forecasting models have been designed to forecast crude oil prices' volatility, so far the relative …

This study attempts to introduce an appropri¬¬ate model for modeling and forecasting Iran’s crude oil price volatility … these series. But from among the conditional heteroscedasticity models, the ARFIMA-FIGARCH model was selected as the best …

conditional volatility of oil spot and futures prices using three GARCH-type models, i.e., linear GARCH, GARCH with structural … GARCH-based conditional volatility processes for energy prices. Second, long memory is effectively present in all the series … considered and a FIGARCH model seems to better fit the data, but the degree of volatility persistence diminishes significantly …

This article examines the volatility forecasting abilities of three approaches: GARCH-type model that uses carbon … document that GARCH-type models perform better than an implied volatility and the k-nearest neighbor model. This result … futures prices, an implied volatility from carbon options prices, and the k-nearest neighbor model. Based on the results, we …

Monte Carlo (MCMC) estimation method to account for the different features observed in an empirical time series of wind …-Switching Autoregressive (MSAR) models with Generalized AutoRegressive Conditional Heteroscedastic (GARCH) errors in each regime to cope with … including a GARCH specification for density forecasts. …