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()
