Social media such as SNS, Twitter, and the blogs has been spreading all over the world, and a large number of firms recognize social media as new communication tools for obtaining information on consumer needs and market for developing new goods and services and promoting marketing. In spite of...

Including disaggregate variables or using information extracted from the disaggregate variables into a forecasting model for an eco- nomic aggregate may improve the forecasting accuracy. In this paper we suggest to use boosting as a method to select the disaggregate variables which are most...

Due to their well-known indeterminacies, factor models require identifying assumptions to guarantee unique parameter estimates. For Bayesian estimation, these identifying assumptions are usually implemented by imposing constraints on certain model parameters. This strategy, however, may result...

This paper proposes a latent dynamic factor model for low- as well as high-dimensional realized covariance matrices of stock returns. The approach is based on the matrix logarithm and allows for flexible dynamic dependence patterns by combining common latent factors driven by HAR dynamics and...

We study the forecasting performance of three alternative large scale approaches for German key macroeconomic variables using a dataset that consists of 123 variables in quarterly frequency. These three approaches handle the dimensionality problem evoked by such a large dataset by aggregating...