Resumen de Análisis de factores comunes dinámicos en presencia de procesos de ruido autocorrelacionados

Stevenson Bolívar

• This thesis presents a procedure to build a dynamic factor model in the presence of orthogonal stationary noise-processes. The procedure is based on the Peña-Box model (Peña & Box, 1987), in which the number of observed time series is fixed, and in the extension proposed by Peña & Poncela (2006) to non-stationary common factors, in which the common factors may be integrated processes. As a first result, an alternative for detecting the number of common factors is proposed by extending the statistical test of Peña & Poncela (2006), proposed for the Peña-Box model with a white noise process. Furthermore, in the same context, a statistical test is proposed to identify the number of non-stationary common factors. These proposals are illustrated by simulation and an application with real data, in which some empirical findings related to seasonal factors are also presented. The model is estimated by maximum likelihood, via a state-space model.