@support Thanks for the detailed answer, that seems to be it, here is the final code:
import xarray as xr
import qnt.stats as qns
import qnt.output as qnout
import qnt.data as qndata
# single-stock trading
data = qndata.futures.load_data(min_date="2005-01-01", assets=["F_ES"])
# attempting an optimal (unrealistic) long-only strategy
# by looking at future prices, and investing only if there will be profit
next_price_open = data.sel(field="open").shift(time=-1)
next2_price_open = data.sel(field="open").shift(time=-2)
weights = xr.where(next_price_open < next2_price_open, 1.0, 0.0)
# sell short when optimal:
# weights = xr.where(next_price_open > next2_price_open, -1.0, weights)
weights = qnout.clean(weights, data)
qnout.check(weights, data)
qnout.write(weights)
stats = qns.calc_stat(
data, weights,
# ignoring slippage for simplicity
slippage_factor=0, roll_slippage_factor=0)
stats.loc[:, "equity"].plot.step();
