def pandl_for_all_trading_rules_unweighted(self, delayfill=True):
"""
Get the p&l for all trading rules; unweighted
Each trading rule has capital in isolation
:param delayfill: Lag fills by one day
:type delayfill: bool
:returns: accountCurveGroup
"""
self.log.terse("Calculating pandl for all trading rules unweighted")
variations = self.get_entire_trading_rule_list()
# already weighted, don't need to do again
pandl_by_trading_rule_unweighted = [
self.pandl_for_trading_rule(rulename, delayfill)
for rulename in variations
]
# this is a group of groups... will it work?
pandl_all_rules = accountCurveGroup(pandl_by_trading_rule_unweighted,
variations,
capital=ARBITRARY_FORECAST_CAPITAL,
weighted_flag=False)
return pandl_all_rules
def portfolio_with_multiplier(self, delayfill=True, roundpositions=True):
"""
Get the p&l for entire portfolio using multiplied "actual" capital
:param delayfill: Lag fills by one day
:type delayfill: bool
:param roundpositions: Round positions to whole contracts
:type roundpositions: bool
:returns: accountCurve
"""
self.log.terse("Calculating pandl for portfolio")
capital = self.get_actual_capital(delayfill, roundpositions)
instruments = self.get_instrument_list()
port_pandl = [
self.pandl_for_instrument_with_multiplier(
instrument_code,
delayfill=delayfill,
roundpositions=roundpositions)
for instrument_code in instruments
]
port_pandl = accountCurveGroup(port_pandl,
instruments,
capital=capital,
weighted_flag=True)
return port_pandl
def pandl_for_instrument_rules(self, instrument_code, delayfill=True):
"""
Get the p&l for one instrument over multiple forecasts; as % of arbitrary capital
P&L are weighted by forecast weights and FDM
KEY OUTPUT
:param instrument_code: instrument to get values for
:type instrument_code: str
:param delayfill: Lag fills by one day
:type delayfill: bool
:returns: accountCurve
>>> from pysystemtrade.systems.basesystem import System
>>> from pysystemtrade.systems.tests.testdata import get_test_object_futures_with_portfolios
>>> (portfolio, posobject, combobject, capobject, rules, rawdata, data, config)=get_test_object_futures_with_portfolios()
>>> system=System([portfolio, posobject, combobject, capobject, rules, rawdata, Account()], data, config)
>>>
>>> system.accounts.pandl_for_instrument_rules_weighted("EDOLLAR").get_stats("sharpe")
{'ewmac16': 0.6799720823590352, 'ewmac8': 0.69594671177102}
"""
self.log.terse("Calculating pandl for instrument rules for %s" %
instrument_code,
instrument_code=instrument_code)
forecast_rules = self.get_trading_rule_list(instrument_code)
pandl_rules_unweighted = [
self.pandl_for_instrument_forecast(instrument_code,
rule_variation_name,
delayfill=delayfill)
for rule_variation_name in forecast_rules
]
pandl_rules = [
weighted(pandl_this_rule,
weighting=self.get_forecast_scaling_factor(
instrument_code, rule_variation_name))
for (pandl_this_rule, rule_variation_name
) in zip(pandl_rules_unweighted, forecast_rules)
]
pandl_rules = accountCurveGroup(pandl_rules,
forecast_rules,
capital=ARBITRARY_FORECAST_CAPITAL,
weighted_flag=True)
return pandl_rules
def pandl_for_instrument_rules_unweighted(self,
instrument_code,
rule_list=None,
delayfill=True):
"""
Get the p&l for one instrument over multiple forecasts; as % of arbitrary capital
All forecasting rules will have same expected std dev of returns; these aren't weighted
KEY OUTPUT
:param instrument_code: instrument to get values for
:type instrument_code: str
:param delayfill: Lag fills by one day
:type delayfill: bool
:returns: accountCurveGroup
>>> from pysystemtrade.systems.basesystem import System
>>> from pysystemtrade.systems.tests.testdata import get_test_object_futures_with_portfolios
>>> (portfolio, posobject, combobject, capobject, rules, rawdata, data, config)=get_test_object_futures_with_portfolios()
>>> system=System([portfolio, posobject, combobject, capobject, rules, rawdata, Account()], data, config)
>>>
>>> system.accounts.pandl_for_instrument_rules_unweighted("EDOLLAR").get_stats("sharpe")
{'ewmac16': 0.6799720823590352, 'ewmac8': 0.69594671177102}
"""
self.log.terse("Calculating pandl for instrument rules for %s" %
instrument_code,
instrument_code=instrument_code)
if rule_list is None:
rule_list = self.get_trading_rule_list(instrument_code)
pandl_rules = [
self.pandl_for_instrument_forecast(instrument_code,
rule_variation_name,
delayfill=delayfill)
for rule_variation_name in rule_list
]
pandl_rules = accountCurveGroup(pandl_rules,
rule_list,
capital=ARBITRARY_FORECAST_CAPITAL,
weighted_flag=False)
return pandl_rules
def pandl_across_subsystems(self, delayfill=True, roundpositions=False):
"""
Get the p&l across subsystems (unweighted)
:param delayfill: Lag fills by one day
:type delayfill: bool
:param roundpositions: Round positions to whole contracts
:type roundpositions: bool
:returns: accountCurve
>>> from pysystemtrade.systems.basesystem import System
>>> from pysystemtrade.systems.tests.testdata import get_test_object_futures_with_portfolios
>>> (portfolio, posobject, combobject, capobject, rules, rawdata, data, config)=get_test_object_futures_with_portfolios()
>>> system=System([portfolio, posobject, combobject, capobject, rules, rawdata, Account()], data, config)
>>>
>>> system.accounts.pandl_across_subsystems().to_frame().tail(5)
EDOLLAR US10
2015-12-07 0.001191 -0.005012
2015-12-08 0.000448 -0.002395
2015-12-09 0.000311 -0.002797
2015-12-10 -0.002384 0.003957
2015-12-11 0.004835 -0.007594
"""
# Subsystems use entire capital
capital = self.get_notional_capital()
instruments = self.get_instrument_list()
pandl_across_subsys = [
self.pandl_for_subsystem(instrument_code,
delayfill=delayfill,
roundpositions=roundpositions)
for instrument_code in instruments
]
pandl = accountCurveGroup(pandl_across_subsys,
instruments,
capital=capital,
weighted_flag=False)
return pandl
def pandl_for_trading_rule_weighted(self,
rule_variation_name,
delayfill=True):
"""
Get the p&l for one trading rule over multiple instruments; as % of total capital
Within the trading rule the instrument returns are weighted by risk contribution
:param rule_variation_name: rule to get values for
:type rule_variation_name: str
:param delayfill: Lag fills by one day
:type delayfill: bool
:returns: accountCurveGroup
"""
self.log.terse("Calculating pandl for trading rule %s" %
rule_variation_name)
instrument_list = self.parent.get_instrument_list()
instrument_list = [
instr_code for instr_code in instrument_list
if rule_variation_name in self.get_trading_rule_list(instr_code)
]
# already weighted, don't need to do again
pandl_by_instrument_weighted = [
self.pandl_for_instrument_forecast_weighted(
instr_code, rule_variation_name, delayfill)
for instr_code in instrument_list
]
pandl_rule = accountCurveGroup(pandl_by_instrument_weighted,
instrument_list,
capital=ARBITRARY_FORECAST_CAPITAL,
weighted_flag=True)
return pandl_rule
def pandl_for_trading_rule_unweighted(self,
rule_variation_name,
delayfill=True):
"""
Get the p&l for one trading rule over multiple instruments; as % of arbitrary capital
Within the trading rule the instrument returns are NOT weighted by instrument weight
:param rule_variation_name: rule to get values for
:type rule_variation_name: str
:param delayfill: Lag fills by one day
:type delayfill: bool
:returns: accountCurve
"""
self.log.terse("Calculating pandl for trading rule (unweighted) %s" %
rule_variation_name)
instrument_list = self.parent.get_instrument_list()
instrument_list = [
instr_code for instr_code in instrument_list
if rule_variation_name in self.get_trading_rule_list(instr_code)
]
pandl_by_instrument = [
self.pandl_for_instrument_forecast(instr_code, rule_variation_name,
delayfill)
for instr_code in instrument_list
]
pandl_rule = accountCurveGroup(pandl_by_instrument,
instrument_list,
capital=ARBITRARY_FORECAST_CAPITAL,
weighted_flag=False)
return pandl_rule
def portfolio(self, delayfill=True, roundpositions=True):
"""
Get the p&l for entire portfolio
:param delayfill: Lag fills by one day
:type delayfill: bool
:param roundpositions: Round positions to whole contracts
:type roundpositions: bool
:returns: accountCurve
>>> from pysystemtrade.systems.basesystem import System
>>> from pysystemtrade.systems.tests.testdata import get_test_object_futures_with_portfolios
>>> (portfolio, posobject, combobject, capobject, rules, rawdata, data, config)=get_test_object_futures_with_portfolios()
>>> system=System([portfolio, posobject, combobject, capobject, rules, rawdata, Account()], data, config)
>>>
>>> system.accounts.portfolio().ann_std()
0.2638225179274214
"""
self.log.terse("Calculating pandl for portfolio")
capital = self.get_notional_capital()
instruments = self.get_instrument_list()
port_pandl = [
self.pandl_for_instrument(instrument_code,
delayfill=delayfill,
roundpositions=roundpositions)
for instrument_code in instruments
]
port_pandl = accountCurveGroup(port_pandl,
instruments,
capital=capital,
weighted_flag=True)
return port_pandl
def pandl_for_trading_rule(self, rule_variation_name, delayfill=True):
"""
Get the p&l for one trading rule over multiple instruments; as % of its risk contribution
Within the trading rule the instrument returns are weighted by instrument weight
:param rule_variation_name: rule to get values for
:type rule_variation_name: str
:param delayfill: Lag fills by one day
:type delayfill: bool
:returns: accountCurve
"""
self.log.terse("Calculating pandl for trading rule %s" %
rule_variation_name)
instrument_list = self.parent.get_instrument_list()
instrument_list = [
instr_code for instr_code in instrument_list
if rule_variation_name in self.get_trading_rule_list(instr_code)
]
# already weighted
# capital on these will be the default
pandl_by_instrument_weighted = [
self.pandl_for_instrument_forecast_weighted(
instr_code, rule_variation_name, delayfill)
for instr_code in instrument_list
]
# now we weight so total capital is correct
capital_this_rule = self.get_capital_in_rule(rule_variation_name)
def _cleanweightelement(capelement):
if np.isnan(capelement):
return 0.0
if capelement == 0.0:
return 0.0
else:
return 1.0 / capelement
weight = [
_cleanweightelement(capelement)
for capelement in list(capital_this_rule.values)
]
weight = pd.Series(weight, index=capital_this_rule.index)
pandl_by_instrument_reweighted = [
weighted(pandl_for_instrument, weight, allow_reweighting=True)
for pandl_for_instrument in pandl_by_instrument_weighted
]
pandl_rule = accountCurveGroup(pandl_by_instrument_reweighted,
instrument_list,
capital=ARBITRARY_FORECAST_CAPITAL,
weighted_flag=True)
return pandl_rule