Hm, not really convinced by the "just classify buy/hold/sell based on an n-lookback" strategy -> Maybe read Ernie Chan's book on algo-trading, or use a more traditional method trying to predict volatility instead of movement.
Thanks for the book recc. You are absolutely right that those are important metrics to feed into the system.
Note I'm not really trying to 'convince' anyone of anything. I shared this on HN was to show off a fun problem domain I've been playing with. If you're looking for an end-game, you got me: Maybe I'll pick up a collaborator or two and get to profitability faster that way. Worst case, I get some resume fodder and an anecdote about machine learning to share at my next cocktail party. Best case: Eventually when cryptocurrencies are everywhere, long after this repo mints it's first millionaire, Hollywood will make a movie where I'm played by Johnny Depp. A haxxor can dream, can't I? ;)
The database model already supports the following inputs: price, volume, bid/ask spread. If a potential future contributor to this repo wanted to run a classifier or NN on this data, they could do so with significantly less time, using this repo's code.
I have a database of price, volume, bid/ask spread history for the entire poloniex index, at a minute-by-minute- granularity, for the last 2 months. I will post if there is enough interest. Vote here if interested => https://github.com/owocki/pytrader/issues
