This article studies the sensitivity of Granger causality to the addition of noise, the introduction of subsampling, and the application of causal invertible filters to weakly stationary processes. Using canonical spectral factors and Wold decompositions, we give general conditions under which...

A survey is provided dealing with the formulation of modelling problems for dynamic factor models, and the various algorithm possibilities for solving these modelling problems. Emphasis is placed on understanding requirements for the handling of errors, noting the relevance of the proposed...

Factor Sequences are stochastic double sequences indexed in time and cross-section which have a so called factor structure. The name was coined by Forni and Lippi (2001) who introduced dynamic factor sequences. We show the difference between dynamic factor sequences and static factor sequences...

A data-driven approach for forecasting returns of asset prices is introduced. Special emphasis is given to data-driven specification and to dimension reduction. Specification is performed by a modified AIC, BIC-based An-algorithm. Quasi-static principal component analysis, quasi-static factor...