def test_run():
class TestStrategy(Strategy):
@overrides
def run(self, dt: date, prices_df: pd.DataFrame,
fees_df: pd.DataFrame) -> List[str]:
if dt == date(2001, 1, 1): # 1st BDAY
return ["isin1", "isin2"]
if dt == date(2001, 1, 4): # 4th BDAY
return ["isin1"]
if dt == date(2001, 1, 9): # 7th BDAY
return []
if dt == date(2001, 1, 10): # 8th BDAY
return ["isin2"]
raise ValueError()
@overrides
def on_data_ready(self, data: Simulator.Data) -> None:
pass
simulator = Simulator(strategy=TestStrategy(),
tie_breaker=NoOpTieBreaker(),
num_portfolio=2,
hold_interval=2 * BDAY,
buy_sell_gap=BDAY)
[result] = simulator.run(start_date=date(2001, 1, 1),
end_date=date(2001, 1, 12))
# Does not factor in platform fees, check_less_precise later
expected_account = pd.DataFrame(data=[
[100, [], []],
[
100 * (0.5 * (14 / 12) + 0.5 * (24 / 22)), ["isin1", "isin2"],
["Fund 1", "Fund 2"]
],
[
100 * (0.5 * (14 / 12) + 0.5 * (24 / 22)) * (17 / 15), ["isin1"],
["Fund 1"]
], [100 * (0.5 * (14 / 12) + 0.5 * (24 / 22)) * (17 / 15), [], []],
[
100 * (0.5 * (14 / 12) + 0.5 * (24 / 22)) * (17 / 15) * (30 / 29),
["isin2"], ["Fund 2"]
]
],
index=[
date(2001, 1, 1),
date(2001, 1, 4),
date(2001, 1, 9),
date(2001, 1, 11),
date(2001, 1, 12)
],
columns=["value", "isins", "names"])
assert_frame_equal(result.account, expected_account, rtol=1e-4)
assert result.returns == 0.32330550475798586
assert result.annual_returns == 10955.427133719217
assert result.max_drawdown == -1.3864736012392243e-05
assert result.sharpe_ratio == 12.37846848338121
assert result.start_date == date(2001, 1, 1)
assert result.end_date == date(2001, 1, 12)
)
@overrides
def on_data_ready(self, data: Simulator.Data) -> None:
for strategy in self.strategies:
strategy.on_data_ready(data)
if __name__ == "__main__":
simulator = Simulator(
strategy=AndStrategy(
BollingerReturns(),
TargetReturns()
),
isins=[
"GB00B1XFGM25",
"GB00B4TZHH95",
"GB00B8JYLC77",
# "GB00B39RMM81",
"GB00B80QG615",
"GB00B99C0657",
# "GB00BH57C751",
"GB0006061963",
# "IE00B4WL8048",
"IE00B90P3080",
"LU0827884411",
]
)
results = simulator.run()
Simulator.describe_and_plot(results)
from datetime import date
from typing import List
import pandas as pd
from lib.simulate.simulator import Simulator
from lib.simulate.strategy.strategy import SelectAll
from lib.simulate.tiebreaker.tie_breaker import TieBreaker
class RandomTieBreaker(TieBreaker):
def run(self, allowed_isins: List[str], num_portfolio: int, dt: date,
prices_df: pd.DataFrame, fees_df: pd.DataFrame) -> List[str]:
return prices_df.loc[dt].dropna().sample(num_portfolio).index.tolist()
def on_data_ready(self, data: Simulator.Data) -> None:
pass
if __name__ == "__main__":
num_runs = 10
simulator = Simulator(strategy=SelectAll(), tie_breaker=RandomTieBreaker())
results = [res for res in simulator.run() for i in range(num_runs)]
Simulator.describe_and_plot(results)
def _build_simulator(cls, params: SimulateRoutes.SimulateParam) -> Simulator:
return Simulator(
strategy=params.strategy,
isins=params.isins,
num_portfolio=params.num_portfolio)
import pandas as pd
from overrides import overrides
from lib.fund.fund_utils import calc_returns
from lib.simulate.simulator import Simulator
from lib.simulate.strategy.strategy import Strategy
from lib.simulate.tiebreaker.no_op_tie_breaker import NoOpTieBreaker
class MaxReturns(Strategy):
@overrides
def run(self, dt: date, prices_df: pd.DataFrame,
fees_df: pd.DataFrame) -> List[str]:
next_dt = dt + self._hold_interval
next_returns = calc_returns(prices_df, next_dt, self._hold_interval,
fees_df)
isin = next_returns.idxmax()
return [isin]
@overrides
def on_data_ready(self, data: Simulator.Data) -> None:
self._hold_interval = data.hold_interval
if __name__ == "__main__":
simulator = Simulator(strategy=MaxReturns(),
tie_breaker=NoOpTieBreaker(),
num_portfolio=1)
results = simulator.run()
Simulator.describe_and_plot(results)
from lib.simulate.simulator import Simulator
from lib.simulate.strategy.strategy import SelectAll
from lib.simulate.tiebreaker.no_op_tie_breaker import NoOpTieBreaker
from lib.util.dates import BDAY
if __name__ == "__main__":
simulator = Simulator(
strategy=SelectAll(),
tie_breaker=NoOpTieBreaker(),
buy_sell_gap=0 * BDAY,
isins=[
"GB00B1XFGM25",
"GB00B4TZHH95",
"GB00B8JYLC77",
"GB00B39RMM81",
"GB00B80QG615",
"GB00B99C0657",
# "GB00BH57C751",
"GB0006061963",
# "IE00B4WL8048",
"IE00B90P3080",
"LU0827884411",
])
results = simulator.run()
Simulator.describe_and_plot(results)