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 …

We propose a new family of easy-to-implement realized volatility based forecasting models. The models exploit the …

, forecasting of the full density for long horizons is feasible, which we pursue. We document variability in conditional variances … over time, which stresses the importance of careful modeling and forecasting of volatility. We show that improved model fit …

changes in the dynamics of the series, for specifying models parsimoniously, and may be helpful in forecasting. We propose the …

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. …

price variation and jumps. This paper proposes a tobit multivariate factor model for the jumps coupled with a standard …

The paper investigates the impact of jumps in forecasting co-volatility, accommodating leverage effects. We modify the … the co-jumps of two assets have a significant impact on future co-volatility, but that the impact is negligible for … forecasting weekly and monthly horizons. …

coverage or tone to provide the largest forecasting performance improvements in the prediction of the conditional variance of …