We propose an automatic machine-learning system to forecast realized volatility for S&P 100 stocks using 118 features … extraordinary performance across forecast horizons, and the improvement in out-of-sample R2's translates into nontrivial economic …

proposed forecast and a benchmark. Considering stock return forecasting as an example, we show that the resulting robust … monitoring forecast improves the average performance of the proposed forecast by 15% (in terms of mean-squared-error) and reduces …

interesting extension, but can it forecast better than existing models.' Indeed, the forecast evaluation literature continues to … widely used in the forecasting literature. We begin by reviewing several tests for comparing the relative forecast accuracy …, such as mean squared forecast error or mean absolute forecast error. Most tests, including those discussed here, are …