We forecast realized volatilities by developing a time-varying heterogeneous autoregressive (HAR) latent factor model with dynamic model average (DMA) and dynamic model selection (DMS) approaches. The number of latent factors is determined using Chan and Grant's (2016) deviation information...

In this paper, we review studies of oil volatility prediction from a new perspective: that of investors who require economic evaluations of forecasting performance. Our results indicate that no single volatility model outperforms all of the competing models, of which GARCH and realized...