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 …

We present an estimation and forecasting method, based on a differential evolution MCMC method, for inference in GARCH … nearly all series. Finally, we carry out a forecasting exercise to evaluate the usefulness of structural break models. …

large number of forecasting models have been designed to forecast crude oil prices' volatility, so far the relative … performance evaluation of competing forecasting models remains an exercise that is unidimensional in nature. To be more specific …

literature on GARCH models favors some rather complex volatility specifications whose relative performance is usually assessed … through their likelihood based on a time series of asset returns. This paper compares a range of GARCH models along a …

to evaluate the out-of-sample forecasting ability of both the GARCH models and the Kalman method. Measures of forecast …This paper investigates the forecasting ability of three different Generalised Autoregressive Conditional … Heteroscedasticity (GARCH) models and the Kalman filter method. The three GARCH models applied are: bivariate GARCH, BEKK GARCH, and …

Practical aspects of likelihood-based inference and forecasting of series with long memory are considered, based on the …

Practical aspects of likelihood-based inference and forecasting of series with long memory are considered, based on the …