Sparse non-Gaussian component analysis (SNGCA) is an unsupervised method of extracting a linear structure from a high dimensional data based on estimating a low-dimensional non-Gaussian data component. In this paper we discuss a new approach to direct estimation of the projector on the target...

This paper develops a broad-based sentiment indicator for Germany and investigates whether investor sentiment can explain stock returns on the German stock market. Based on a principal component analysis, we construct a sentiment indicator that condenses information of several well-known...

Using long time series for sovereign bond markets of fifteen industrialized economies from 1875 to 2009, I find that financial market integration by the end of the 20th century was higher than in earlier periods and exhibited a J-shaped trend with a trough in the 1920s. The main reason for the...

This paper investigates the finite sample properties of the two-step estimators of dynamic factor models when unobservable common factors are estimated by the principal components methods in the first step. Effects of the number of individual series on the estimation of an auto-regressive model...

Using long time series for sovereign bond markets of fifteen industrialized economies from 1875 to 2009, I find that financial market integration by the end of the 20th century was higher than in earlier periods and exhibited a J-shaped trend with a trough in the 1920s. The main reason for the...