Quantile regression is an efficient tool when it comes to estimate popular measures of tail risk such as the conditional quantile Value at Risk. In this paper we exploit the availability of data at mixed frequency to build a volatility model for daily returns with low- (for macro-variables) and...

This paper proposes novel approaches to the modeling of attenuation bias effects in volatility forecasting. Our strategy relies on suitable generalizations of the Realized GARCH model by Hansen et al. (2012) where the impact of lagged realized measures on the current conditional variance is...

This paper investigates the benefits of jointly using several realized measures in predicting daily price volatility, Value-at-Risk, and Expected Shortfall in the Australian electricity markets of New South Wales, Queensland, and Victoria. We propose using Realized GARCH-type models with...