def _pandl_for_subsystem_with_cash_costs(
self,
instrument_code,
delayfill=True,
roundpositions=True) -> accountCurve:
if not roundpositions:
self.log.warn(
"Using roundpositions=False with cash costs may lead to inaccurate costs (fixed costs, eg commissions will be overstated!!!"
)
raw_costs = self.get_raw_cost_data(instrument_code)
price = self.get_daily_price(instrument_code)
positions = self.get_subsystem_position(instrument_code)
fx = self.get_fx_rate(instrument_code)
value_of_price_point = self.get_value_of_block_price_move(
instrument_code)
capital = self.get_notional_capital()
pandl_calculator = pandlCalculationWithCashCostsAndFills(
price,
raw_costs=raw_costs,
positions=positions,
capital=capital,
value_per_point=value_of_price_point,
delayfill=delayfill,
fx=fx,
roundpositions=roundpositions)
account_curve = accountCurve(pandl_calculator)
return account_curve
def pandl_for_instrument_forecast(
forecast: pd.Series,
price: pd.Series,
daily_returns_volatility: pd.Series = arg_not_supplied,
target_abs_forecast: float = 10.0,
SR_cost=0.0,
delayfill=True) -> accountCurve:
if daily_returns_volatility is arg_not_supplied:
daily_returns_volatility = robust_daily_vol_given_price(price)
normalised_forecast = _get_normalised_forecast(
forecast, target_abs_forecast=target_abs_forecast)
average_notional_position = -_get_average_notional_position(
daily_returns_volatility)
notional_position = _get_notional_position_for_forecast(
normalised_forecast,
average_notional_position=average_notional_position)
pandl_calculator = pandlCalculationWithSRCosts(
price,
SR_cost=SR_cost,
positions=notional_position,
daily_returns_volatility=daily_returns_volatility,
average_position=average_notional_position,
capital=ARBITRARY_FORECAST_CAPITAL,
value_per_point=ARBITRARY_VALUE_OF_PRICE_POINT,
delayfill=delayfill)
account_curve = accountCurve(pandl_calculator)
return account_curve
def account_curve_for_asset(self,
asset_name: str,
account_curve_group: 'accountCurveGroup' = arg_not_supplied,
freq_str: str = "daily",
curve_type_str = "net",
is_percentage = True
) -> accountCurve:
if account_curve_group is arg_not_supplied:
account_curve_group = self.account_curve_group
frequency = _from_freq_str_to_frequency(freq_str)
curve_type = _from_curve_str_to_curve_type(curve_type_str)
account_curve = accountCurve(account_curve_group.get_pandl_calculator_for_item(asset_name),
curve_type=curve_type,
is_percentage= is_percentage,
frequency=frequency)
return account_curve
def _pandl_for_instrument_with_SR_costs(
self,
instrument_code: str,
delayfill: bool = True,
roundpositions: bool = True) -> accountCurve:
price = self.get_daily_price(instrument_code)
positions = self.get_buffered_position(instrument_code,
roundpositions=roundpositions)
fx = self.get_fx_rate(instrument_code)
value_of_price_point = self.get_value_of_block_price_move(
instrument_code)
daily_returns_volatility = self.get_daily_returns_volatility(
instrument_code)
capital = self.get_notional_capital()
SR_cost_per_trade = self.get_SR_cost_per_trade_for_instrument(
instrument_code)
instrument_turnover = self.instrument_turnover(
instrument_code, roundpositions=roundpositions)
annualised_SR_cost = SR_cost_per_trade * instrument_turnover
average_position = self.get_average_position_for_instrument_at_portfolio_level(
instrument_code)
pandl_calculator = pandlCalculationWithSRCosts(
price,
SR_cost=annualised_SR_cost,
positions=positions,
average_position=average_position,
daily_returns_volatility=daily_returns_volatility,
capital=capital,
value_per_point=value_of_price_point,
delayfill=delayfill,
fx=fx,
roundpositions=roundpositions)
account_curve = accountCurve(pandl_calculator, weighted=True)
return account_curve
def _pandl_for_instrument_with_cash_costs(
self,
instrument_code: str,
positions: pd.Series,
delayfill: bool = True,
roundpositions: bool = True,
) -> accountCurve:
if not roundpositions:
self.log.warn(
"Using roundpositions=False with cash costs may lead to inaccurate costs (fixed costs, eg commissions will be overstated!!!"
)
raw_costs = self.get_raw_cost_data(instrument_code)
price = self.get_daily_price(instrument_code)
fx = self.get_fx_rate(instrument_code)
value_of_price_point = self.get_value_of_block_price_move(
instrument_code)
capital = self.get_notional_capital()
vol_normalise_currency_costs = self.config.vol_normalise_currency_costs
rolls_per_year = self.get_rolls_per_year(instrument_code)
pandl_calculator = pandlCalculationWithCashCostsAndFills(
price,
raw_costs=raw_costs,
positions=positions,
capital=capital,
value_per_point=value_of_price_point,
delayfill=delayfill,
fx=fx,
roundpositions=roundpositions,
vol_normalise_currency_costs=vol_normalise_currency_costs,
rolls_per_year=rolls_per_year,
)
account_curve = accountCurve(pandl_calculator, weighted=True)
return account_curve
def _pandl_for_subsystem_with_SR_costs(
self,
instrument_code,
delayfill=True,
roundpositions=False) -> accountCurve:
price = self.get_daily_price(instrument_code)
positions = self.get_subsystem_position(instrument_code)
fx = self.get_fx_rate(instrument_code)
value_of_price_point = self.get_value_of_block_price_move(
instrument_code)
daily_returns_volatility = self.get_daily_returns_volatility(
instrument_code)
average_position = self.get_volatility_scalar(instrument_code)
SR_cost_per_trade = self.get_SR_cost_per_trade_for_instrument(
instrument_code)
subsystem_turnover = self.subsystem_turnover(instrument_code)
annualised_SR_cost = SR_cost_per_trade * subsystem_turnover
capital = self.get_notional_capital()
pandl_calculator = pandlCalculationWithSRCosts(
price,
SR_cost=annualised_SR_cost,
positions=positions,
average_position=average_position,
daily_returns_volatility=daily_returns_volatility,
capital=capital,
value_per_point=value_of_price_point,
delayfill=delayfill,
fx=fx,
roundpositions=roundpositions)
account_curve = accountCurve(pandl_calculator)
return account_curve
def __getitem__(self, item):
kwargs = self.kwargs
return accountCurve(self.get_pandl_calculator_for_item(item), **kwargs)