def _create_rebalance_event_times(self):
"""
Creates the list of rebalance timestamps used to determine when
to execute the quant trading strategy throughout the backtest.
Returns
-------
`List[pd.Timestamp]`
The list of rebalance timestamps.
"""
if self.rebalance == 'buy_and_hold':
rebalancer = BuyAndHoldRebalance(self.start_dt)
elif self.rebalance == 'daily':
rebalancer = DailyRebalance(
self.start_dt, self.end_dt
)
elif self.rebalance == 'weekly':
rebalancer = WeeklyRebalance(
self.start_dt, self.end_dt, self.rebalance_weekday
)
elif self.rebalance == 'end_of_month':
rebalancer = EndOfMonthRebalance(self.start_dt, self.end_dt)
else:
raise ValueError(
'Unknown rebalance frequency "%s" provided.' % self.rebalance
)
return rebalancer.rebalances
def test_monthly_rebalance(
start_date, end_date, pre_market, expected_dates, expected_time
):
"""
Checks that the end of month (business day) rebalance provides
the correct datetimes for the provided range.
"""
sd = pd.Timestamp(start_date, tz=pytz.UTC)
ed = pd.Timestamp(end_date, tz=pytz.UTC)
reb = EndOfMonthRebalance(
start_dt=sd, end_dt=ed, pre_market=pre_market
)
actual_datetimes = reb._generate_rebalances()
expected_datetimes = [
pd.Timestamp('%s %s' % (expected_date, expected_time), tz=pytz.UTC)
for expected_date in expected_dates
]
assert actual_datetimes == expected_datetimes