Cross validation too uses training sets and test sets. This sort of time-ordered data will not be independent, so the prequential approach seems to be a more suitable approach to measuring forecast accuracy. (I haven't read the paper.)
http://robjhyndman.com/hyndsight/crossvalidation/
(near bottom of the article)
Anyways, as somebody who has spent GIANT amounts of time experimenting with machine learning using market data (mainly stocks), I can give you TONS algorithms I've created that would show similar, even much higher, gains when you only test on 6 weeks of data. Been there done that. For example 6 weeks you make a 100% return, then in the next 3 weeks you suffer a 50% loss. Reality sets in...