volatility specifications, in terms of point forecasting to some degree and density forecasting to a greater degree. …

Small or medium-scale VARs are commonly used in applied macroeconomics for forecasting and evaluating the shock … instability in a forecasting context. While none of the methods clearly emerges as best, some techniques turn out to be useful to … improve the forecasting performance. …

This paper conducts an extensive forecasting study on 13,118 time series measuring Swiss goods exports, grouped …

forecasting experiment is based on a novel big macroeconomic dataset (FRED-QD) comprising over 200 quarterly indicators for almost …

The Chicago Fed dynamic stochastic general equilibrium (DSGE) model is used for policy analysis and forecasting at the …

forecasting techniques, e.g. correlation forecasts based on historical values and on a dynamic conditional correlation (DCC) model … varied. We find that the applied volatility forecasting models have a strong influence on the expected net present value … distribution and on the probability of default. In contrast, correlation forecasting models play a minor role. Time resolution and …

This paper uses a panel VAR (PVAR) approach to estimating, analysing and forecasting price dynamics in four different …

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