This paper examines different multivariate models to evaluate what are the main determinants when doing VaR forecasts … and the time sample used for VaR backtesting. The calculated VaR values are then compared using three different testing …

We explore whether forecasting an aggregate variable using information on its disaggregate components can improve the … prediction mean squared error over forecasting the disaggregates and aggregating those forecasts, or using only aggregate … information in forecasting the aggregate. An implication of a general theory of prediction is that the first should outperform the …

This paper presents a rigurous framework for evaluating alternative forecasting methods for Chilean industrial … production and sales. While nonlinear features appear to be important for forecasting the very short term, simple univariate … linear models perform about as well for almost every forecasting horizon …

distribution for a vector autoregression, following the approach in Del Negro and Schorfheide (2003). This DSGE-VAR is fitted to …. We document the fit of the DSGE-VAR …

VAR modelling is a frequent technique in econometrics for assumed linear processes. VAR modelling offers some desirable … structure, it cannot be equivalently represented by any finite-order VAR model. On the other hand, a finite-order state space … provide better forecasts than VAR models when working with VARMA data generating processes. In a simulation study we generate …

-term relationship. We finally conclude by comparing the forecasting ability of these two approaches with classical models such as Random …