def make_optimizer(monkeypatch):
monkeypatch.setattr(config, "ML_PARAMS", ML_PARAMS)
monkeypatch.setattr(config, "TURNOVER_CUT_OFF", 0.0016)
date = pd.Timestamp("2018-12-17")
positions = dict(
KZOS=800, MGNT=0, PIKK=800, MSTT=0, MTLRP=0, GMKN=21, CBOM=0, SNGSP=13000
)
port = portfolio.Portfolio(date, 1000, positions)
return optimizer.Optimizer(port, months=11)
def make_opt():
cash = 176
positions = dict(CHEP=0, KZOS=5080 * 2, MTSS=3300 * 2, RTKMP=29400 * 2, TRCN=68 * 2)
date = "2020-05-13"
port = Portfolio(date, cash, positions)
saved_metrics = optimizer.metrics.MetricsResample
optimizer.metrics.MetricsResample = FakeMetricsResample
yield optimizer.Optimizer(port)
optimizer.metrics.MetricsResample = saved_metrics