So in R, for instance, this would be:
my_ts_logged_diffed = diff(log(some_ts_object)) plot(my_ts_logged_diffed)
This seems to be part of every experienced analyst/forecaster analytical workflow--in particular, a visual examination of the plotted data. What are they looking for--i.e., what useful information does this transformation help reveal?
Similarly, I have a pretty good selection of time series textbooks, tutorials, and the like; nearly all of them mention this analytical step, but none of them say why it's done (i am sure there's a good reason, and one that's apparently too obvious to even mention).
(i do indeed routinely rely on this transformation but only for the limited purpose of testing for a normal distribution (i think the test is called Shapiro-Wilk). The application of the test just involves (assuming i am applying it correctly) comparing a couple of parameters (a 'W' parameter and the p-value) against a baseline--the Test doesn't appear to require plotting the data).