We propose a parametric state space model with accompanying estimation and forecasting framework that combines long … process, the model consistently belongs to the 10% Model Confidence Set when considering out-of-sample forecasting performance … as the only one among four competing dynamic models for all forecasting horizons when applied to high frequency stock …

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 …