w = world_from_live( basket, cash=10000, indicators=[Moving_Average(n=200), Moving_Average(n=10), RSI(2)]) # get model from models import Mean_Reversion mr = Mean_Reversion('Mean Reversion', 200, 10, 2) # build investor from investor import Investor i = Investor(models=[mr], world=w, live=False) # set up backtest from backtest import Backtest b = Backtest(name='mean_reversion_backtest_000', investor=i, base_world=w) # show/export results b.do_backtest() b.export_history(path='backtests/') # --- workflow 4 --- # neural ODE model class / some other trainable model # that will allow us to good make use of the backtesting tools # --- workflow 5 --- # exporting, importing model # test many models against each other # export best ones r.logout()