A few weeks ago, I posted an entry about a bad graphical display of financial data; specifically, which asset classes have performed well, or badly, by year. Here’s the graphic:
I pointed out that although this graphic is poor, it’s not easy to display the same information really well, either. For instance, a simple line plot does a far better job than the original graphic of showing the extent to which asset classes do or don’t vary together, and which ones have wilder swings from year to year, but it’s also pretty confusing to read. Here’s what I mean:
I suggested that others might take a shot at this, and a few people did. Kelly O’Day sent
which is good for comparing variability of different classes, but bad for seeing which classes do or don’t vary together in time. Kelly also sent
Hadley Wickham sent this contribution:
(Hadley provides the R code, too, at had.co.nz. I feel that I should note that this R code is both more elegant and more general than what I woulda done.) The lower plot breaks the asset classes into groups based on variance, which is nice. As with my graphic, though, the heavily overlapping lines and sometimes similar colors makes it hard to see exactly what is going on with what asset class.
Richard uses a tabular approach, where colors indicate yearly performance:
I would say that each of these has some good and some bad characteristics (even the original one at the top). It’s very hard to make a single display that lets you see both the relative and absolute performances, for each year and for the whole period. The original graphic gives up on the absolute performances (or at least gives up on graphically displaying them; you can still read off the percent gains), in favor of simply rank-ordering within each year and overall. My contribution, and the uppermost of Hadley’s plots, puts everything on a single line plot; you can see how things vary together, you can see the relative volatility (i.e. variance) of the various asset classes…but this is a lot of lines on a single plot, and is therefore hard to read. (Hadley’s color scheme is harder for me to distinguish than “my” color scheme, which was an attempt to duplicate the one in the original chart). Kelly’s two contributions attempt to resolve the overlapping-lines issue by presenting the data two ways: side-by-side, which allows visually comparing variances but does not help with comparing temporal behavior; and vertically aligned, which allows comparison of temporal variability but makes it harder to compare variances. Richard’s table is easy to follow, but (for me) much of the interpretation comes from reading the numbers rather than taking advantage of our ability to process graphical information.