  We introduce a simple approach for testing the reliability of homogeneous
generators and the Markov property of the stochastic processes underlying
empirical time series of credit ratings. We analyze open access data provided
by Moody's and show that the validity of these assumptions - existence of a
homogeneous generator and Markovianity - is not always guaranteed. Our analysis
is based on a comparison between empirical transition matrices aggregated over
fixed time windows and candidate transition matrices generated from
measurements taken over shorter periods. Ratings are widely used in credit
risk, and are a key element in risk assessment; our results provide a tool for
quantifying confidence in predictions extrapolated from these time series.
