of point and density forecasting. The relative accuracy is higher when the full distribution is predicted. We also …

account of them in estimating and forecasting IV. This paper investigates through Monte Carlo simulations the effects of RV … errors on estimating and forecasting IV with RV data. It is found that: (i) neglecting RV errors can lead to serious bias in …

– 2010 I exhaustively evaluate the forecasting properties of Bayesian shrinkage in regressions with many predictors. Results …

This paper compares the forecasting performance of different models which have been proposed for forecasting in the … forecasting in the vast majority of cases. However, we find no single forecasting model consistently works best in the presence of …

We propose a nouvel methodology for forecasting chaotic systems which uses information on local Lyapunov exponents … focal value of zero, which traditionally distinguishes order from chaos, plays no role whatsoever when forecasting …

This paper applies LINEX loss functions to forecasting nonlinear functions of variance. We derive the optimal one …. Our results suggest that the LINEX loss function is particularly well-suited to many of these forecasting problems and can …

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 …

…ndings provide an easy-to-use method for conducting mixed data-sampling analysis as well as for forecasting world commodity price …

-- 2010 I exhaustively evaluate the forecasting properties of Bayesian shrinkage in regressions with many predictors. Results …