Browsing by Subject "hyperparameter choice"

In this thesis, a conditional BVARX forecasting model for short and medium term economic forecasting is developed. The model is especially designed for small-open economies and its performance on forecasting several Finnish economic variables is assessed. Particular attention is directed to the hyperparameter choice of the model. A novel algorithm for hyperparameter choice is proposed and it is shown to outperform the marginal likelihood based approach often encountered in the literature. Other prominent features of the model include conditioning on predictive densities and exogeneity of the global economic variables. The model is shown to outperform univariate benchmark models in terms of forecasting accuracy for forecasting horizons up to eight quarters ahead.