Forecasting linear dynamical systems using subspace methods

Authors


Alfredo García-Hiernaux, Departamento de Economía Cuantitativa, Universidad Complutense de Madrid, Campus de Somosaguas, Madrid 28223, Spain.

Abstract

This article presents a novel approach to predict with subspace methods. It consists in combining multiple forecasts obtained from setting a range of values for a specific parameter that is typically fixed by the user in this literature. Two procedures are proposed. The first one combines all the forecast in a particular range. The second one predicts with a restricted number of combinations previously optimized. Both methods are evaluated using Monte Carlo experiments and by forecasting the German gross domestic product.

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