def test_simple_system_config_import(self, data): my_config = Config("systems.provided.example.simplesystemconfig.yaml") my_config.risk_overlay = arg_not_supplied my_config.exclude_instrument_lists = dict( ignore_instruments=["MILK"], trading_restrictions=["BUTTER"], bad_markets=["CHEESE"], ) print(my_config) my_system = System( [ Account(), Portfolios(), PositionSizing(), ForecastCombine(), ForecastScaleCap(), Rules(), RawData(), ], data, my_config, ) print(my_system.rules.get_raw_forecast("EDOLLAR", "ewmac32").tail(5)) print(my_system.rules.get_raw_forecast("EDOLLAR", "ewmac8").tail(5)) print( my_system.forecastScaleCap.get_capped_forecast("EDOLLAR", "ewmac32").tail(5) ) print(my_system.forecastScaleCap.get_forecast_scalar("EDOLLAR", "ewmac32")) print(my_system.combForecast.get_combined_forecast("EDOLLAR").tail(5)) print(my_system.combForecast.get_forecast_weights("EDOLLAR").tail(5)) print(my_system.positionSize.get_subsystem_position("EDOLLAR").tail(5)) print(my_system.portfolio.get_notional_position("EDOLLAR").tail(5))
def simplesystem(data=None, config=None, log_level="on"): """ Example of how to 'wrap' a complete system """ if config is None: config = Config("systems.provided.example.simplesystemconfig.yaml") if data is None: data = csvFuturesSimData() my_system = System( [ Account(), Portfolios(), PositionSizing(), ForecastCombine(), ForecastScaleCap(), Rules(), ], data, config, ) my_system.set_logging_level(log_level) return my_system
def futures_system(data=None, config=None, trading_rules=None, log_level="on"): """ :param data: data object (defaults to reading from csv files) :type data: sysdata.data.Data, or anything that inherits from it :param config: Configuration object (defaults to futuresconfig.yaml in this directory) :type config: sysdata.configdata.Config :param trading_rules: Set of trading rules to use (defaults to set specified in config object) :type trading_rules: list or dict of TradingRules, or something that can be parsed to that :param log_level: How much logging to do :type log_level: str >>> system=futures_system(log_level="off") >>> system System with stages: accounts, portfolio, positionSize, rawdata, combForecast, forecastScaleCap, rules >>> system.rules.get_raw_forecast("EDOLLAR", "ewmac2_8").dropna().head(2) ewmac2_8 1983-10-10 0.695929 1983-10-11 -0.604704 ewmac2_8 2015-04-21 0.172416 2015-04-22 -0.477559 >>> system.rules.get_raw_forecast("EDOLLAR", "carry").dropna().head(2) carry 1983-10-10 0.952297 1983-10-11 0.854075 carry 2015-04-21 0.350892 2015-04-22 0.350892 """ if data is None: data = csvFuturesData() if config is None: config = Config( "systems.provided.futures_chapter15.futuresconfig.yaml") rules = Rules(trading_rules) system = System([ Account(), PortfoliosFixed(), PositionSizing(), FuturesRawData(), ForecastCombine(), ForecastScaleCap(), rules ], data, config) system.set_logging_level(log_level) return system
def setUp(self): (rules, rawdata, data, config) = get_test_object_futures_with_rules() system = System([rawdata, rules, ForecastScaleCap()], data, config) self.system = system self.config = config self.rules = rules self.rawdata = rawdata self.forecast_scale_cap = ForecastScaleCap self.data = data
def get_test_object_futures_with_rules_and_capping(): """ Returns some standard test data """ data = csvFuturesData("sysdata.tests") rawdata = FuturesRawData() rules = Rules() config = Config("systems.provided.example.exampleconfig.yaml") capobject = ForecastScaleCap() return (capobject, rules, rawdata, data, config)
def get_test_object_futures_with_rules_and_capping_estimate(): """ Returns some standard test data """ data = csvFuturesSimData() rawdata = FuturesRawData() rules = Rules() config = Config("systems.provided.example.estimateexampleconfig.yaml") capobject = ForecastScaleCap() account = Account() return (account, capobject, rules, rawdata, data, config)
def get_test_object_futures_with_comb_forecasts(): """ Returns some standard test data """ data = csvFuturesSimData() rawdata = FuturesRawData() rules = Rules() config = Config("systems.provided.example.exampleconfig.yaml") capobject = ForecastScaleCap() combobject = ForecastCombine() return (combobject, capobject, rules, rawdata, data, config)
def get_test_object_futures_with_pos_sizing(): """ Returns some standard test data """ data = csvFuturesData("sysdata.tests") rawdata = FuturesRawData() rules = Rules() config = Config("systems.provided.example.exampleconfig.yaml") capobject = ForecastScaleCap() combobject = ForecastCombine() posobject = PositionSizing() return (posobject, combobject, capobject, rules, rawdata, data, config)
def get_test_object_futures_with_rules_and_capping(): """ Returns some standard test data """ data = csvFuturesSimData(datapath_dict=dict( config_data="sysdata.tests.configtestdata", adjusted_prices="sysdata.tests.adjtestdata", spot_fx_data="sysdata.tests.fxtestdata", multiple_price_data="sysdata.tests.multiplepricestestdata")) rawdata = FuturesRawData() rules = Rules() config = Config("systems.provided.example.exampleconfig.yaml") capobject = ForecastScaleCap() return (capobject, rules, rawdata, data, config)
def futures_system( data=None, config=None, trading_rules=None, log_level="terse"): """ :param data: data object (defaults to reading from csv files) :type data: sysdata.data.simData, or anything that inherits from it :param config: Configuration object (defaults to futuresconfig.yaml in this directory) :type config: sysdata.configdata.Config :param trading_rules: Set of trading rules to use (defaults to set specified in config object) :param trading_rules: list or dict of TradingRules, or something that can be parsed to that :param log_level: Set of trading rules to use (defaults to set specified in config object) :type log_level: str """ if data is None: data = csvFuturesSimData() if config is None: config = Config( "systems.provided.futures_chapter15.futuresestimateconfig.yaml") rules = Rules(trading_rules) system = System( [ Account(), Portfolios(), PositionSizing(), FuturesRawData(), ForecastCombine(), ForecastScaleCap(), rules, ], data, config, ) system.set_logging_level(log_level) return system
def get_test_object_futures_with_pos_sizing_estimates(): """ Returns some standard test data """ data = csvFuturesSimData(datapath_dict=dict( config_data="sysdata.tests.configtestdata", adjusted_prices="sysdata.tests.adjtestdata", spot_fx_data="sysdata.tests.fxtestdata", multiple_price_data="sysdata.tests.multiplepricestestdata")) rawdata = FuturesRawData() rules = Rules() config = Config("systems.provided.example.estimateexampleconfig.yaml") capobject = ForecastScaleCap() combobject = ForecastCombine() posobject = PositionSizing() account = Account() return (account, posobject, combobject, capobject, rules, rawdata, data, config)
def futures_system(data, config): system = System( [ Risk(), accountForOptimisedStage(), optimisedPositions(), Portfolios(), PositionSizing(), RawData(), ForecastCombine(), ForecastScaleCap(), Rules(), ], data, config, ) system.set_logging_level("on") return system
def test_simple_system_risk_overlay(self, data, ewmac_8, ewmac_32): my_config = Config( dict( trading_rules=dict(ewmac8=ewmac_8, ewmac32=ewmac_32), instrument_weights=dict(US10=0.1, EDOLLAR=0.4, CORN=0.3, SP500=0.2), instrument_div_multiplier=1.5, forecast_scalars=dict(ewmac8=5.3, ewmac32=2.65), forecast_weights=dict(ewmac8=0.5, ewmac32=0.5), forecast_div_multiplier=1.1, percentage_vol_target=25.00, notional_trading_capital=500000, base_currency="GBP", risk_overlay=dict( max_risk_fraction_normal_risk=1.4, max_risk_fraction_stdev_risk=3.6, max_risk_limit_sum_abs_risk=3.4, max_risk_leverage=13.0, ), exclude_instrument_lists=dict( ignore_instruments=["MILK"], trading_restrictions=["BUTTER"], bad_markets=["CHEESE"], ), ) ) print(my_config) my_system = System( [ Account(), Portfolios(), PositionSizing(), ForecastCombine(), ForecastScaleCap(), Rules(), RawData(), ], data, my_config, ) print(my_system.portfolio.get_notional_position("EDOLLAR").tail(5))
def update(self, message): """ Subscriber pattern main method. Will be called each time a registered event occurs. :param message: dict with instrument names as keys and pd.Dataframe as values. """ data = self.get_data(message) # Ib data Object. This is the Object that manage the data from ibAPI. my_data = ib_Data(data) # create a list with the instruments for the config object my_config = Config("private.config.yaml") # create a config object. my_config.instruments = my_data.get_instruments_list() # Setting the rules. my_rules = Rules(dict(ewmac=ewmac)) my_rules.trading_rules() # Initializing the system with all the stages. my_stages = [ Account(), Portfolios(), PositionSizing(), ForecastCombine(), ForecastScaleCap(), my_rules ] my_system = System(stage_list=my_stages, data=my_data, config=my_config) # Forecast for each instrument. for i in message.keys(): print("\n{} forecast:\n".format(i)) position = my_system.portfolio.get_notional_position(i) # Publishing forecast. message = dict(ticker=i, forecast=int(position.iloc[-1])) print(position.tail(5)) self.pub.dispatch(i, message)
from systems.forecasting import TradingRule data = csvFuturesData() my_config = Config() ewmac_8 = TradingRule((ewmac, [], dict(Lfast=8, Lslow=32))) ewmac_16 = TradingRule( dict(function=ewmac, other_args=dict(Lfast=16, Lslow=64))) ewmac_32 = TradingRule( dict(function=ewmac, other_args=dict(Lfast=32, Lslow=128))) my_rules = Rules(dict(ewmac8=ewmac_8, ewmac16=ewmac_16, ewmac32=ewmac_32)) my_config.trading_rules = dict(ewmac8=ewmac_8, ewmac16=ewmac_16, ewmac32=ewmac_32) my_config.instruments = ["SP500"] my_config.forecast_weight_estimate = dict(method="bootstrap") my_config.forecast_weight_estimate['monte_runs'] = 50 my_config.use_forecast_weight_estimates = True my_system = System( [Account(), ForecastScaleCap(), my_rules, ForecastCombine()], data, my_config) print(my_system.combForecast.get_forecast_weights("SP500").tail(5)) # ewmac16 ewmac32 ewmac8 # 2016-07-04 0.199582 0.545313 0.255106 # 2016-07-05 0.199625 0.545273 0.255103 # 2016-07-06 0.199668 0.545233 0.255100 # 2016-07-07 0.199710 0.545193 0.255097 # 2016-07-08 0.199752 0.545154 0.255094
def fcs(): return ForecastScaleCap()
from systems.forecasting import Rules from systems.forecasting import TradingRule data = csvFuturesData() ewmac_8 = TradingRule((ewmac, [], dict(Lfast=8, Lslow=32))) ewmac_32 = TradingRule(dict(function=ewmac, other_args=dict(Lfast=32, Lslow=128))) my_rules = Rules(dict(ewmac8=ewmac_8, ewmac32=ewmac_32)) my_config = Config() my_config my_config.trading_rules = dict(ewmac8=ewmac_8, ewmac32=ewmac_32) ## we can estimate these ourselves #my_config.instruments=[ "US20", "NASDAQ", "SP500"] my_config.instruments=[ "SP500"] #my_config.forecast_weight_estimate=dict(method="one_period") my_config.forecast_weight_estimate=dict(method="bootstrap") my_config.forecast_weight_estimate['monte_runs']=50 my_config.use_forecast_weight_estimates=True my_account = Account() combiner = ForecastCombine() fcs=ForecastScaleCap() my_system = System([my_account, fcs, my_rules, combiner], data, my_config) print(my_system.combForecast.get_forecast_weights("SP500").tail(5)) print('forecast_diversification_multiplier') print(my_system.combForecast.get_forecast_diversification_multiplier("SP500").tail(5))
from sysdata.configdata import Config my_config = Config() my_config empty_rules = Rules() my_config.trading_rules = dict(ewmac8=ewmac_8, ewmac32=ewmac_32) my_system = System([empty_rules], data, my_config) my_system.rules.get_raw_forecast("EDOLLAR", "ewmac32").tail(5) from systems.forecast_scale_cap import ForecastScaleCap # we can estimate these ourselves my_config.instruments = ["US10", "EDOLLAR", "CORN", "SP500"] my_config.use_forecast_scale_estimates = True fcs = ForecastScaleCap() my_system = System([fcs, my_rules], data, my_config) print( my_system.forecastScaleCap.get_forecast_scalar("EDOLLAR", "ewmac32").tail(5)) # or we can use the values from the book my_config.forecast_scalars = dict(ewmac8=5.3, ewmac32=2.65) my_config.use_forecast_scale_estimates = False fcs = ForecastScaleCap() my_system = System([fcs, my_rules], data, my_config) print( my_system.forecastScaleCap.get_capped_forecast("EDOLLAR", "ewmac32").tail(5)) """ combine some rules
subsys_positions = pd.concat(subsys_positions, axis=1).ffill() subsys_positions.columns = instrument_list instrument_weights = fix_weights_vs_pdm(raw_instr_weights, subsys_positions) weighting=system.config.instrument_weight_ewma_span instrument_weights = pd.ewma(instrument_weights, weighting) return instrument_weights if __name__ == "__main__": random.seed(0) np.random.seed(0) data = csvFuturesData() my_config = Config() my_config.instruments=["US20", "SP500"] ewmac_8 = TradingRule((ewmac, [], dict(Lfast=8, Lslow=32))) ewmac_32 = TradingRule(dict(function=ewmac, other_args=dict(Lfast=32, Lslow=128))) my_rules = Rules(dict(ewmac8=ewmac_8, ewmac32=ewmac_32)) my_system = System([Account(), PortfoliosEstimated(), PositionSizing(), ForecastScaleCap(), my_rules, ForecastCombine()], data, my_config) my_system.config.forecast_weight_estimate['method']="equal_weights" my_system.config.instrument_weight_estimate['method']="bootstrap" my_system.config.instrument_weight_estimate["monte_runs"]=1 my_system.config.instrument_weight_estimate["bootstrap_length"]=250 print(my_system.portfolio.get_instrument_diversification_multiplier(my_system)) # 10,250 weights=0.75,0.25 idm=1.26 # 30,250 weights=0.75,0.25
from systems.forecasting import Rules from systems.forecasting import TradingRule from systems.portfolio import PortfoliosEstimated from systems.positionsizing import PositionSizing data = csvFuturesData() my_config = Config() my_config.instruments = ["US20", "SP500"] ewmac_8 = TradingRule((ewmac, [], dict(Lfast=8, Lslow=32))) ewmac_32 = TradingRule( dict(function=ewmac, other_args=dict(Lfast=32, Lslow=128))) my_rules = Rules(dict(ewmac8=ewmac_8, ewmac32=ewmac_32)) my_system = System([ Account(), PortfoliosEstimated(), PositionSizing(), ForecastScaleCap(), my_rules, ForecastCombine() ], data, my_config) my_system.config.forecast_weight_estimate['method'] = "equal_weights" my_system.config.instrument_weight_estimate['method'] = "bootstrap" my_system.config.instrument_weight_estimate["monte_runs"] = 1 my_system.config.instrument_weight_estimate["bootstrap_length"] = 250 print(my_system.portfolio.get_instrument_weights()) print(my_system.portfolio.get_instrument_diversification_multiplier()) # 10,250 weights=0.75,0.25 idm=1.26 # 30,250 weights=0.75,0.25
from systems.account import Account from systems.forecast_combine import ForecastCombine from systems.forecast_scale_cap import ForecastScaleCap from systems.basesystem import System from sysdata.csvdata import csvFuturesData from systems.forecasting import Rules from systems.forecasting import TradingRule data = csvFuturesData() my_config = Config() ewmac_8 = TradingRule((ewmac, [], dict(Lfast=8, Lslow=32))) ewmac_32 = TradingRule(dict(function=ewmac, other_args=dict(Lfast=32, Lslow=128))) my_rules = Rules(dict(ewmac8=ewmac_8, ewmac32=ewmac_32)) my_config.trading_rules = dict(ewmac8=ewmac_8, ewmac32=ewmac_32) #my_config.instruments=[ "US20", "NASDAQ", "SP500"] my_config.instruments=[ "SP500"] my_config.forecast_weight_estimate=dict(method="bootstrap") my_config.forecast_weight_estimate['monte_runs']=50 my_config.use_forecast_weight_estimates=True my_system = System([Account(), ForecastScaleCap(), my_rules, ForecastCombine()], data, my_config) logging.debug(my_system.combForecast.get_forecast_weights("SP500").tail(5)) # DEBUG:root: ewmac32 ewmac8 # 2015-12-07 0.632792 0.367208 # 2015-12-08 0.632930 0.367070 # 2015-12-09 0.633066 0.366934 # 2015-12-10 0.633201 0.366799 # 2015-12-11 0.633335 0.366665
from sysdata.configdata import Config my_config = Config() my_config empty_rules = Rules() my_config.trading_rules = dict(ewmac8=ewmac_8, ewmac32=ewmac_32) my_system = System([empty_rules], data, my_config) my_system.rules.get_raw_forecast("EDOLLAR", "ewmac32").tail(5) from systems.forecast_scale_cap import ForecastScaleCap # we can estimate these ourselves my_config.instruments = ["US10", "EDOLLAR", "CORN", "SP500"] my_config.use_forecast_scale_estimates = True fcs = ForecastScaleCap() my_system = System([fcs, my_rules], data, my_config) my_config.forecast_scalar_estimate["pool_instruments"] = False print( my_system.forecastScaleCap.get_forecast_scalar("EDOLLAR", "ewmac32").tail( 5)) # or we can use the values from the book my_config.forecast_scalars = dict(ewmac8=5.3, ewmac32=2.65) my_config.use_forecast_scale_estimates = False fcs = ForecastScaleCap() my_system = System([fcs, my_rules], data, my_config) print( my_system.forecastScaleCap.get_capped_forecast("EDOLLAR", "ewmac32").tail( 5)) """
def test_simple_system(self): """ This is (mostly) the code from 'examples.introduction.simplesystem', but without graph plotting """ data = csvFuturesSimData() my_rules = Rules(ewmac) print(my_rules.trading_rules()) my_rules = Rules(dict(ewmac=ewmac)) print(my_rules.trading_rules()) my_system = System([my_rules], data) print(my_system) print(my_system.rules.get_raw_forecast("EDOLLAR", "ewmac").tail(5)) ewmac_rule = TradingRule(ewmac) my_rules = Rules(dict(ewmac=ewmac_rule)) print(ewmac_rule) ewmac_8 = TradingRule((ewmac, [], dict(Lfast=8, Lslow=32))) ewmac_32 = TradingRule( dict(function=ewmac, other_args=dict(Lfast=32, Lslow=128))) my_rules = Rules(dict(ewmac8=ewmac_8, ewmac32=ewmac_32)) print(my_rules.trading_rules()["ewmac32"]) my_system = System([my_rules], data) my_system.rules.get_raw_forecast("EDOLLAR", "ewmac32").tail(5) my_config = Config() print(my_config) empty_rules = Rules() my_config.trading_rules = dict(ewmac8=ewmac_8, ewmac32=ewmac_32) my_system = System([empty_rules], data, my_config) my_system.rules.get_raw_forecast("EDOLLAR", "ewmac32").tail(5) # we can estimate these ourselves my_config.instruments = ["US10", "EDOLLAR", "CORN", "SP500"] my_config.use_forecast_scale_estimates = True fcs = ForecastScaleCap() my_system = System([fcs, my_rules], data, my_config) my_config.forecast_scalar_estimate["pool_instruments"] = False print( my_system.forecastScaleCap.get_forecast_scalar( "EDOLLAR", "ewmac32").tail(5)) # or we can use the values from the book my_config.forecast_scalars = dict(ewmac8=5.3, ewmac32=2.65) my_config.use_forecast_scale_estimates = False fcs = ForecastScaleCap() my_system = System([fcs, my_rules], data, my_config) print( my_system.forecastScaleCap.get_capped_forecast( "EDOLLAR", "ewmac32").tail(5)) # defaults combiner = ForecastCombine() my_system = System([fcs, my_rules, combiner], data, my_config) print(my_system.combForecast.get_forecast_weights("EDOLLAR").tail(5)) print( my_system.combForecast.get_forecast_diversification_multiplier( "EDOLLAR").tail(5)) # estimates: my_account = Account() combiner = ForecastCombine() my_config.forecast_weight_estimate = dict(method="one_period") my_config.use_forecast_weight_estimates = True my_config.use_forecast_div_mult_estimates = True my_system = System([my_account, fcs, my_rules, combiner], data, my_config) # this is a bit slow, better to know what's going on my_system.set_logging_level("on") print(my_system.combForecast.get_forecast_weights("US10").tail(5)) print( my_system.combForecast.get_forecast_diversification_multiplier( "US10").tail(5)) # fixed: my_config.forecast_weights = dict(ewmac8=0.5, ewmac32=0.5) my_config.forecast_div_multiplier = 1.1 my_config.use_forecast_weight_estimates = False my_config.use_forecast_div_mult_estimates = False combiner = ForecastCombine() my_system = System( [fcs, empty_rules, combiner], data, my_config) # no need for accounts if no estimation done my_system.combForecast.get_combined_forecast("EDOLLAR").tail(5) # size positions possizer = PositionSizing() my_config.percentage_vol_target = 25 my_config.notional_trading_capital = 500000 my_config.base_currency = "GBP" my_system = System([fcs, my_rules, combiner, possizer], data, my_config) print(my_system.positionSize.get_price_volatility("EDOLLAR").tail(5)) print(my_system.positionSize.get_block_value("EDOLLAR").tail(5)) print(my_system.positionSize.get_underlying_price("EDOLLAR")) print( my_system.positionSize.get_instrument_value_vol("EDOLLAR").tail(5)) print(my_system.positionSize.get_volatility_scalar("EDOLLAR").tail(5)) print(my_system.positionSize.get_vol_target_dict()) print(my_system.positionSize.get_subsystem_position("EDOLLAR").tail(5)) # portfolio - estimated portfolio = Portfolios() my_config.use_instrument_weight_estimates = True my_config.use_instrument_div_mult_estimates = True my_config.instrument_weight_estimate = dict(method="shrinkage", date_method="in_sample") my_system = System( [my_account, fcs, my_rules, combiner, possizer, portfolio], data, my_config) my_system.set_logging_level("on") print(my_system.portfolio.get_instrument_weights().tail(5)) print(my_system.portfolio.get_instrument_diversification_multiplier(). tail(5)) # or fixed portfolio = Portfolios() my_config.use_instrument_weight_estimates = False my_config.use_instrument_div_mult_estimates = False my_config.instrument_weights = dict(US10=0.1, EDOLLAR=0.4, CORN=0.3, SP500=0.2) my_config.instrument_div_multiplier = 1.5 my_system = System([fcs, my_rules, combiner, possizer, portfolio], data, my_config) print(my_system.portfolio.get_notional_position("EDOLLAR").tail(5)) my_system = System( [fcs, my_rules, combiner, possizer, portfolio, my_account], data, my_config) profits = my_system.accounts.portfolio() print(profits.percent().stats()) # have costs data now print(profits.gross.percent().stats()) print(profits.net.percent().stats()) my_config = Config( dict(trading_rules=dict(ewmac8=ewmac_8, ewmac32=ewmac_32), instrument_weights=dict(US10=0.1, EDOLLAR=0.4, CORN=0.3, SP500=0.2), instrument_div_multiplier=1.5, forecast_scalars=dict(ewmac8=5.3, ewmac32=2.65), forecast_weights=dict(ewmac8=0.5, ewmac32=0.5), forecast_div_multiplier=1.1, percentage_vol_target=25.00, notional_trading_capital=500000, base_currency="GBP")) print(my_config) my_system = System( [ Account(), Portfolios(), PositionSizing(), ForecastCombine(), ForecastScaleCap(), Rules() ], data, my_config, ) print(my_system.portfolio.get_notional_position("EDOLLAR").tail(5)) my_config = Config("systems.provided.example.simplesystemconfig.yaml") print(my_config) my_system = System( [ Account(), Portfolios(), PositionSizing(), ForecastCombine(), ForecastScaleCap(), Rules() ], data, my_config, ) print(my_system.rules.get_raw_forecast("EDOLLAR", "ewmac32").tail(5)) print(my_system.rules.get_raw_forecast("EDOLLAR", "ewmac8").tail(5)) print( my_system.forecastScaleCap.get_capped_forecast( "EDOLLAR", "ewmac32").tail(5)) print( my_system.forecastScaleCap.get_forecast_scalar( "EDOLLAR", "ewmac32")) print(my_system.combForecast.get_combined_forecast("EDOLLAR").tail(5)) print(my_system.combForecast.get_forecast_weights("EDOLLAR").tail(5)) print(my_system.positionSize.get_subsystem_position("EDOLLAR").tail(5)) print(my_system.portfolio.get_notional_position("EDOLLAR").tail(5))