selecting the best forecasting model class in finite samples of practical relevance. Flanking such a horse race by predictive …

forecasting volatility. Key papers in this area include Andersen, Bollerslev, Diebold and Labys (2003), Corsi (2004), Andersen …

regression used in Bai and Ng (2008), called the elastic net (Zou and Hastie, 2005). We illustrate our approach by forecasting …

using these models in an out-of-sample forecasting exercise compared with the forecasts obtained based on the usual linear …

able to provide more accurate forecasting results than linear models. Therefore, simple autoregressive processes are … observations and autoregression residuals. The proposed forecasting models are applied to a large set of macroeconomic and … autoregression residuals, are somewhat able to provide better forecasting results than simple linear models. Thus, it may be …

variancefunctions. In a genuine out-of-sample forecasting experiment theperformance of the best fitted asMA-asQGARCH model is compared … topure asMA and no-change forecasts. This is done both in terms ofconditional mean forecasting as well as in terms of risk … forecasting. …