def apply_action(self, state: Union[date, Iterable[date]],
backtest: BackTest):
with HistoricalPricingContext(dates=make_list(state),
csa_term=self.action.csa_term):
backtest.calc_calls += 1
backtest.calculations += len(make_list(state))
f = Portfolio(make_list(
self.action.priceable)).resolve(in_place=False)
for create_date, portfolio in f.result().items():
active_dates = [
s for s in backtest.states
if get_final_date(portfolio.instruments[0], create_date, self.
action.trade_duration) >= s >= create_date
]
if len(active_dates):
for t in portfolio:
t.name = f'{t.name}_{create_date.strftime("%Y-%m-%d")}'
backtest.scaling_portfolios[create_date].append(
ScalingPortfolio(trade=portfolio.instruments[0],
dates=active_dates,
risk=self.action.risk,
csa_term=self.action.csa_term))
return backtest
def apply_action(self,
state: Union[date, Iterable[date]],
backtest: BackTest,
trigger_info: Optional[Union[HedgeActionInfo, Iterable[HedgeActionInfo]]] = None):
with HistoricalPricingContext(dates=make_list(state), csa_term=self.action.csa_term, show_progress=True):
backtest.calc_calls += 1
backtest.calculations += len(make_list(state))
f = Portfolio(make_list(self.action.priceable)).resolve(in_place=False)
for create_date, portfolio in f.result().items():
hedge = portfolio.instruments[0]
hedge.name = f'{hedge.name}_{create_date.strftime("%Y-%m-%d")}'
final_date = get_final_date(hedge, create_date, self.action.trade_duration)
active_dates = [s for s in backtest.states if create_date <= s < final_date]
if len(active_dates):
backtest.scaling_portfolios[create_date].append(
ScalingPortfolio(trade=hedge, dates=active_dates, risk=self.action.risk,
csa_term=self.action.csa_term, scaling_parameter=self.action.scaling_parameter))
# add cashflows on trade entry and unwind
backtest.cash_payments[create_date].append(
CashPayment(trade=hedge, effective_date=create_date, direction=-1))
if final_date <= dt.date.today():
backtest.cash_payments[final_date].append(
CashPayment(trade=hedge, effective_date=final_date, scale_date=create_date))
return backtest
def apply_action(
self,
state: Union[date, Iterable[date]],
backtest: BackTest,
trigger_info: Optional[Union[HedgeActionInfo,
Iterable[HedgeActionInfo]]] = None):
with HistoricalPricingContext(dates=make_list(state),
csa_term=self.action.csa_term):
backtest.calc_calls += 1
backtest.calculations += len(make_list(state))
f = Portfolio(make_list(
self.action.priceable)).resolve(in_place=False)
for create_date, portfolio in f.result().items():
final_date = get_final_date(portfolio.instruments[0], create_date,
self.action.trade_duration)
if self.action.risks_on_final_day:
next_state = list(
filter(lambda x: x > create_date, backtest.states))
final_date = min(
final_date,
next_state[0]) if len(next_state) else final_date
active_dates = [
s for s in backtest.states if create_date <= s < final_date
]
if len(active_dates):
for t in portfolio:
t.name = f'{t.name}_{create_date.strftime("%Y-%m-%d")}'
backtest.scaling_portfolios[create_date].append(
ScalingPortfolio(trade=portfolio.instruments[0],
dates=active_dates,
risk=self.action.risk,
csa_term=self.action.csa_term))
if self.action.risks_on_final_day and final_date <= dt.date.today(
):
backtest.scaling_portfolios[final_date].append(
ScalingPortfolio(trade=portfolio.instruments[0],
dates=[final_date],
risk=self.action.risk,
csa_term=self.action.csa_term,
unwind=True))
return backtest
def apply_action(self, state: Union[datetime.date,
Iterable[datetime.date]],
backtest: BackTest):
with HistoricalPricingContext(dates=make_list(state)):
backtest.calc_calls += 1
backtest.calculations += len(make_list(state)) * len(
self._priceables)
f = Portfolio(self._priceables).resolve(in_place=False)
for s in backtest.states:
pos = []
for create_date, portfolio in f.result().items():
pos += [
inst for inst in portfolio.instruments
if get_final_date(inst, create_date, self.trade_duration)
>= s >= create_date
]
backtest.portfolio_dict[s].append(pos)
return backtest
def apply_action(self, state: Union[datetime.date,
Iterable[datetime.date]],
backtest: BackTest):
with HistoricalPricingContext(dates=make_list(state)):
backtest.calc_calls += 1
backtest.calculations += len(make_list(state))
f = Portfolio(make_list(self._priceable)).resolve(in_place=False)
for create_date, portfolio in f.result().items():
active_dates = [
s for s in backtest.states
if get_final_date(portfolio.instruments[0], create_date,
self.trade_duration) >= s >= create_date
]
backtest.scaling_portfolios[create_date].append(
ScalingPortfolio(trade=portfolio.instruments[0],
dates=active_dates,
risk=self.risk))
return backtest
