Bayesian learning provides a core concept of information processing in financialmarkets. Typically it is assumed that market participants perfectly know the qual-ity of released news. However, in practice, news’ precision is rarely disclosed. Therefore, we extend standard Bayesian learning...

We introduce a multivariate multiplicative error model which is driven by componentspecific observation driven dynamics as well as a common latent autoregressive factor. The model is designed to explicitly account for (information driven) common factor dynamics as well as idiosyncratic effects...