They correctly state that, under the EMH, financial time series are IID, and so algorithmically incompressible. They then say that a series's unpredictability is a manifestation of the fact that it ``carries a large amount of nonredundant information''. True, but only in the sense that the same thing is true of a sequence of coin tosses. It takes a lot of bits to specify an exact sequence of heads and tails, but it takes no bits of memory to generate such sequences statistically. (To model coin-tossing, toss a coin.) So it does not follow that a financial time series contains ``valuable and important economic information''. By the EMH, the series contains no information about future price changes, and the only information it has about future prices is contained in the current price. The structural or statistical complexity is thus negligible. (For more on how to measure complexity, see my review of Badii and Politi's Complexity.)