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 … prices and leverage effects for volatility. Findings suggest that GARJI model provides more accurate VaR measures for the S …

. Results show individual models excel in forecasting VaR at a 0.975 confidence level, while combined methods outperform at 0 …This study contrasts GARCH models with diverse combined forecast techniques for Commodities Value at Risk (VaR … methods such as mean or lowest VaR yield optimal results, highlighting their efficacy. This study contributes by offering a …

these two family forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the …Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these …-data models at 5% and 1% VaR level. Specifically, independently from the data frequency, allowing for jumps in price (or providing …

shown to be specific for commodity and market. A forecasting comparison on the basis of the identified models suggests that …

new model achieves higher forecasting performance compared to a standard DCC model. …

wholesale power markets have only recently been deregulated. We introduce the weather factor into well-known forecasting models …

wholesale power markets have only recently been deregulated. We introduce the weather factor into well-known forecasting models …