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

This paper considers the performance of different long-memory dynamic models when forecasting volatility in the stock … noise. A comparison between a class of HAR- and ARFIMA models is facilitated on the basis of out-of-sample forecasting …

been proposed. A related strand of literature focuses on dynamic models and covariance forecasting for high-frequency data … address, is the relative importance of the quality of the realized measure as an input in a given forecasting model vs. the …

evaluation. An important implication is that forecasting superiority of models using high frequency data is likely to be …