def calculate_total_commission_for_broker_order(self, broker_order: brokerOrder) -> brokerOrder:
"""
This turns a broker_order with non-standard commission field (list of tuples) into a single figure
in base currency
:return: broker_order
"""
if broker_order is missing_order:
return broker_order
if broker_order.commission is None:
return broker_order
currency_data = dataCurrency(self.data)
if isinstance(broker_order.commission, float):
base_values = [broker_order.commission]
else:
base_values = [
currency_data.currency_value_in_base(ccy_value)
for ccy_value in broker_order.commission
]
commission = sum(base_values)
broker_order.commission = commission
return broker_order
def fx_prices(data):
fx_code = get_valid_fx_code_from_user(data)
diag_prices = dataCurrency(data)
prices = diag_prices.get_fx_prices(fx_code)
print(prices)
return None
def run_backtest(self):
strategy_name = self.strategy_name
data = self.data
capital_data = dataCapital(data)
notional_trading_capital = capital_data.get_capital_for_strategy(strategy_name)
if notional_trading_capital is missing_data:
# critical log will send email
error_msg = (
"Capital data is missing for %s: can't run backtest" %
strategy_name)
data.log.critical(error_msg)
raise Exception(error_msg)
currency_data = dataCurrency(data)
base_currency = currency_data.get_base_currency()
system = self.system_method(
notional_trading_capital=notional_trading_capital, base_currency=base_currency
)
updated_buffered_positions(data, strategy_name, system)
store_backtest_state(data, system, strategy_name=strategy_name)
return success
def get_fx_series_for_instrument(data, instrument_code):
diag_instruments = diagInstruments(data)
currency = diag_instruments.get_currency(instrument_code)
currency_data = dataCurrency(data)
fx_series = currency_data.get_fx_prices_to_base(currency)
return fx_series
def last_currency_fx(data: dataBlob, instrument_code: str) -> float:
data_currency = dataCurrency(data)
diag_instruments = diagInstruments(data)
currency = diag_instruments.get_currency(instrument_code)
fx_rate = data_currency.get_last_fx_rate_to_base(currency)
return fx_rate
def get_last_fx_price_update_for_code(data, fx_code):
data_fx = dataCurrency(data)
px = data_fx.get_fx_prices(fx_code)
last_timestamp = px.index[-1]
update = genericUpdate(fx_code, last_timestamp)
return update
def get_point_size_base_currency(self, instrument_code: str) -> float:
point_size_instrument_currency = self.get_point_size(instrument_code)
instrument_currency = self.get_currency(instrument_code)
currency_data = dataCurrency(self.data)
point_size_currency_value = currencyValue(
instrument_currency, point_size_instrument_currency)
value = currency_data.currency_value_in_base(point_size_currency_value)
return value
def get_total_capital_value_in_base_currency(self) -> float:
currency_data = dataCurrency(self.data)
values_across_accounts = self.data.broker_capital.get_account_value_across_currency_across_accounts(
)
# This assumes that each account only reports either in one currency or
# for each currency, i.e. no double counting
total_account_value_in_base_currency = (
currency_data.total_of_list_of_currency_values_in_base(
values_across_accounts))
return total_account_value_in_base_currency
def update_fx_prices_for_code(fx_code: str, data: dataBlob):
broker_fx_data = dataBroker(data)
db_fx_data = dataCurrency(data)
new_fx_prices = broker_fx_data.get_fx_prices(fx_code) # returns fxPrices object
rows_added = db_fx_data.update_fx_prices_and_return_rows_added(
fx_code, new_fx_prices, check_for_spike=True
)
if rows_added is spike_in_data:
report_fx_data_spike(data, fx_code)
return failure
return success
def get_total_excess_liquidity_in_base_currency(self) -> float:
currency_data = dataCurrency(self.data)
account_id = self.get_broker_account()
values_across_accounts = (
self.broker_capital_data.
get_excess_liquidity_value_across_currency(account_id))
# This assumes that each account only reports either in one currency or
# for each currency, i.e. no double counting
total_account_value_in_base_currency = (
currency_data.total_of_list_of_currency_values_in_base(
values_across_accounts))
return total_account_value_in_base_currency
def update_fx_prices_for_code(fx_code: str, data: dataBlob):
broker_fx_source = dataBroker(data)
db_fx_data = dataCurrency(data)
new_fx_prices = broker_fx_source.get_fx_prices(
fx_code) # returns fxPrices object
rows_added = db_fx_data.update_fx_prices(
fx_code, new_fx_prices, check_for_spike=True
)
if rows_added is data_error:
report_fx_data_spike(data, fx_code)
return success
def _get_currency_and_capital(self):
data = self.data
strategy_name = self.strategy_name
capital_data = dataCapital(data)
notional_trading_capital = capital_data.get_capital_for_strategy(
strategy_name)
if notional_trading_capital is missing_data:
# critical log will send email
error_msg = ("Capital data is missing for %s: can't run backtest" %
strategy_name)
data.log.critical(error_msg)
raise Exception(error_msg)
currency_data = dataCurrency(data)
base_currency = currency_data.get_base_currency()
return base_currency, notional_trading_capital
def update_manual_check_fx_prices_for_code(fx_code: str, data: dataBlob):
db_currency_data = dataCurrency(data)
data_broker = dataBroker(data)
new_fx_prices = data_broker.get_fx_prices(
fx_code) # returns fxPrices object
if len(new_fx_prices) == 0:
data.log.warn("No FX prices found for %s" % fx_code)
old_fx_prices = db_currency_data.get_fx_prices(fx_code)
# Will break manual price checking code if not equal
old_fx_prices.name = new_fx_prices.name = ""
print("\n\n Manually checking prices for %s \n\n" % fx_code)
new_prices_checked = manual_price_checker(
old_fx_prices, new_fx_prices, type_new_data=fxPrices.from_data_frame)
db_currency_data.update_fx_prices_and_return_rows_added(
fx_code, new_prices_checked, check_for_spike=False)
return success
