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Ideas for evaluating / backtesting trading models.
From https://github.com/owocki/pytrader/issues/5#issuecomment-204250257 :
> A quick way would be create a theoretical control group: (if you bought 1 BTC/ETH and held it for the same two months) and compare the profits.
> A second much more rigorous method (what I would do before even investing 1 real BTC) would be to get a collection of data from different markets and simulate PyTrader at random segments on them. This would be a true experiment and give a good idea of the actual profitability of the algorithm in the general market. But, I imagine this would take quite a bit of computation power. Do you have a general estimate of how long it would take a $900 PC running 24/7 to simulate 2 months of trading? (assuming all the code is modified somehow for this to happen)
Thanks @jeff-hykin for these ideas. Lets discuss these and other ideas below.