prediction model specification methods, and that using “hybrid” combination factor/shrinkage methods often yields superior …-spread variables in nonlinear prediction model specification. …

squared return prediction errors gives an adequate approximation of the unobserved realised conditional variance for both the …

and compare state-of-the-art statistical learning techniques for the prediction of shrimp harvest (in pounds) for a little … allowed, Linear Regression with best subset variable selection and SVM with linear Kernel gave the lowest prediction error …

squared return prediction errors gives an adequate approximation of the unobserved realised conditional variance for both the …