Realized Volatility and the Variance Risk Premium. The approach is innovative along two different dimensions, namely: (1) we …-type models and (2) we price equity volatility risk using factors which go beyond the equity class. These are volatility factors …

We examine the relationship between MIDAS regressions and the estimation of state space models applied to mixed … called for. The approach is appealing when we consider state space models which feature stochastic volatility, or other non … stochastic volatility feature is particularly relevant when considering high frequency financial series. In addition, we propose …

"We consider various MIDAS (Mixed Data Sampling) regression models to predict volatility. The models differ in the … specification of regressors (squared returns, absolute returns, realized volatility, realized power, and return ranges), in the use … data, we find that daily realized power (involving 5-minute absolute returns) is the best predictor of future volatility …

We consider various MIDAS (Mixed Data Sampling) regression models to predict volatility. The models differ in the … specification of regressors (squared returns, absolute returns, realized volatility, realized power, and return ranges), in the use … data, we find that daily realized power (involving 5-minute absolute returns) is the best predictor of future volatility …

We consider various MIDAS (Mixed Data Sampling) regression models to predict volatility. The models differ in the … specification of regressors (squared returns, absolute returns, realized volatility, realized power, and return ranges), in the use … data, we find that daily realized power (involving 5-minute absolute returns) is the best predictor of future volatility …