Thanks June. After doing some research I hopefully got it right now: Basically I have a number of 215 corporate bonds and for some of those bonds the author estimated excess returns after the event of a Credit Rating Downgrade. The distribution of those estimated returns are slightly skewed and may not follow a normal distribution. However, the t-test does only assumes that the sample mean is normally distributed and because of the Central limit theorem I can assume that this is the case, given a big enough sample size of 215 observations. Therefore, the Binomial test is basically neglectable when interpreting the results.

If I want to interpret the Z-score I would say: Given the sample size "All", in 40.4% of the cases there are excess notable returns. The binomial test is testing, whether the observed 40.4% differ from 50% (Is there an explanation why the authors choose 50% in this case?). If they do differ significantly, one would conclude that the 40.4% excess returns are not there by chance but are significant. Therefore this would be "additional significance" to the t test results. However, the Z score does not tell me whether the excess returns are positiv or negative.

Did I get it right or are there some mistakes in my understanding?