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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 su
by beejiu 12y ago
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.)
- leeber 12y agoCross validation for time series, goes something like this: http://robjhyndman.com/hyndsight/crossvalidation/ 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...