variancefunctions. In a genuine out-of-sample forecasting experiment theperformance of the best fitted asMA-asQGARCH model is compared … topure asMA and no-change forecasts. This is done both in terms ofconditional mean forecasting as well as in terms of risk … forecasting. …

For forecasting volatility of futures returns, the paper proposes an indirect method based on the relationship between … futures and the underlying asset for the returns and time-varying volatility. For volatility forecasting, the paper considers … that the new method based on stochastic volatility models with the asymmetry and long memory outperforms the forecasting …

or demographics. We show the good forecasting performance of the model relative to popular alternatives, including … about the unconditional mean and along with the time variation improves the long-run forecasting performance of the VAR …

We present a model for hourly electricity load forecasting based on stochastically time-varying processes that are … implementation of our forecasting procedure relies on the multivariate linear Gaussian state space framework and is applied to … national French hourly electricity load. The analysis focuses on two hours, 9 AM and 12 AM, but forecasting results are …