Hedge fund guy here.
- You need to know something about the domain in order to make sensible predictions. Is the data daily? Is it per second? Is it ticks? You can't build a sensible model if you don't know that, even if you have good predictions. Relative cost will vary a lot between timescales.
- It matters what the features are. Maybe there's some clever reason why it doesn't, but until I hear why I'm going to take the ordinary view that some features are different in nature to others. For instance maybe one feature is volatility, a thing we typically model with GARCH, while another is some fundamental like P/E, which we'd incorporate some other way.
- How are you executing the trades? It matters a lot whether you're click-trading through some broker API, automating via Excel, or running your own network of colo servers. Some things just aren't possible if you're too slow.
- If you make the data encrypted, you'd better know very well what it represents. For instance, you might take all the closing prices of the LSE stocks on a given day as inputs. You can make analyses that are valid with that, and ones that aren't, because the data you've collected do not represent a snapshot of the market at a specific time. It might sound like it does, but it doesn't on deeper inspection (market opens and closes are not simultaneous).
Does anyone know how it's going for them?