asset management are predicated on the importance of jumps, or discontinuous movements in asset returns. In light of this, a … number of recent papers have addressed volatility predictability, some from the perspective of the usefulness of jumps in … forecasting volatility. Key papers in this area include Andersen, Bollerslev, Diebold and Labys (2003), Corsi (2004), Andersen …

asset management are predicated on the importance of jumps, or discontinuous movements in asset returns. In light of this, a … number of recent papers have addressed volatility predictability, some from the perspective of the usefulness of jumps in … forecasting volatility. Key papers in this area include Andersen, Bollerslev, Diebold and Labys (2003), Corsi (2004), Andersen …

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 …

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 …

in applications that involve forecasts of latent target variables. Such applications include the forecasting of … application to correlation forecasting is presented. …

Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these … these two family forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the … assumptions of jumps in prices and leverage effects for volatility. Findings suggest that daily-data models are preferred to HF …

Forecasting-volatility models typically rely on either daily or high frequency (HF) data and the choice between these … 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 … these two family forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the … assumptions of jumps in prices and leverage effects for volatility. Findings suggest that daily-data models are preferred to HF …

HAR components in the model improve the point forecasting accuracy while the introduction of asymmetric effects only leads …