The first three factors resulting from a principal components analysis of term structure data are in the literature …

. Key words: principal components, principal covariates, regression model, factor model, economic forecasting 1 Introduction … information is first summarized by a (small) number of principal components, which are then used as prediction factors in a low … estimated by means of principal components. That is, the p factors are obtained by minimizing the squared Frobenius norm jjX …

factors by cross section averages of the observed variables as suggested by Pesaran (2004), and the other uses principal … components following the work of Stock and Watson (2002). The paper develops the principal component method and provides small …

(VAR) models. In advance, a principal components analysis (PCA) is adopted to reduce the dimensionality of the term …

dynamic principal components obtained using frequency domain methods. The third model is based on subspace algorithm for state …

factors by cross section averages of the observed variables as suggested by Pesaran (2004) , and the other uses principal … components following the work of Stock and Watson (2002) . The paper develops the principal component method and provides small …

(VAR) models. In advance, a principal components analysis (PCA) is adopted to reduce the dimensionality of the term …