def test_simple_trading_rule(self): """ This is (mostly) the code from 'examples.introduction.asimpletradingrule', but without graph plotting """ # Get some data data = csvFuturesSimData() print(data) print(data.get_instrument_list()) print(data.get_raw_price("EDOLLAR").tail(5)) print(data["VIX"]) print(data.keys()) print(data.get_instrument_raw_carry_data("EDOLLAR").tail(6)) instrument_code = "VIX" price = data.daily_prices(instrument_code) ewmac = self.calc_ewmac_forecast(price, 32, 128) ewmac2 = self.calc_ewmac_forecast(price, 16, 64) ewmac.columns = ["forecast"] print(ewmac.tail(5)) account = accountCurve(price, forecast=ewmac) account2 = accountCurve(price, forecast=ewmac2) account.curve() account2.curve() print(account.percent().stats()) print(account2.percent().stats())
def generate_roll_calendars_from_provided_multiple_csv_prices( output_datapath=arg_not_supplied, ): if output_datapath is arg_not_supplied: print( "USING DEFAULT DATAPATH WILL OVERWRITE PROVIDED DATA in /data/futures/" ) else: print("Writing to %s" % output_datapath) input( "This will overwrite any existing roll calendars to %s: CRTL-C if you aren't sure!" % str(output_datapath)) csv_roll_calendars = csvRollCalendarData(datapath=output_datapath) sim_futures_data = csvFuturesSimData() instrument_list = sim_futures_data.get_instrument_list() for instrument_code in instrument_list: print(instrument_code) multiple_prices = sim_futures_data.get_multiple_prices(instrument_code) roll_calendar = rollCalendar.back_out_from_multiple_prices( multiple_prices) print("Calendar:") print(roll_calendar) # We ignore duplicates since this is run regularly csv_roll_calendars.add_roll_calendar(instrument_code, roll_calendar, ignore_duplication=True)
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 get_test_object_futures(): """ Returns some standard test data """ data = csvFuturesSimData() rawdata = FuturesRawData() config = Config("systems.provided.example.exampleconfig.yaml") return (rawdata, data, config)
def test_prebaked_from_confg(self): """ This is the config system from 'examples.introduction.prebakedsimplesystems' """ my_config = Config("systems.provided.example.simplesystemconfig.yaml") my_data = csvFuturesSimData() my_system = simplesystem(config=my_config, data=my_data) print(my_system.portfolio.get_notional_position("EDOLLAR").tail(5))
def get_test_object_futures_with_rules_and_capping(): """ Returns some standard test data """ data = csvFuturesSimData() 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_pos_sizing(): """ Returns some standard test data """ data = csvFuturesSimData() 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(): """ 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() config = Config("systems.provided.example.exampleconfig.yaml") return (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 generate_roll_calendars_from_provided_multiple_csv_prices(output_datapath): input( "This will overwrite the roll calendars in %s : CRTL-C if you aren't sure!" % output_datapath) csv_roll_calendars = csvRollCalendarData(datapath=output_datapath) sim_futures_data = csvFuturesSimData() instrument_list = sim_futures_data.get_instrument_list() for instrument_code in instrument_list: print(instrument_code) multiple_prices = sim_futures_data.get_multiple_prices(instrument_code) roll_calendar = rollCalendar.back_out_from_multiple_prices( multiple_prices) print("Calendar:") print(roll_calendar) # We ignore duplicates since this is run regularly csv_roll_calendars.add_roll_calendar(instrument_code, roll_calendar, ignore_duplication=True)
def data(): data = csvFuturesSimData() return data
Work up a minimum example of a trend following system """ # Get some data from sysdata.sim.csv_futures_sim_data import csvFuturesSimData """" Let's get some data We can get data from various places; however for now we're going to use prepackaged 'legacy' data stored in csv files """ data = csvFuturesSimData() print(data) """ We get stuff out of data with methods """ print(data.get_instrument_list()) print(data.get_raw_price("EDOLLAR").tail(5)) """ data can also behave in a dict like manner (though it's not a dict) """ print(data["VIX"]) print(data.keys()) """
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.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) :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 = csvFuturesSimData() if config is None: config = Config( "systems.provided.futures_chapter15.futuresconfig.yaml") rules = Rules(trading_rules) system = System( [ Account(), Portfolios(), PositionSizing(), FuturesRawData(), ForecastCombine(), ForecastScaleCap(), rules, ], data, config, ) system.set_logging_level(log_level) return system
from sysdata.sim.csv_futures_sim_data import csvFuturesSimData from sysobjects.roll_calendars import rollCalendar from sysdata.csv.csv_roll_calendars import csvRollCalendarData from sysdata.mongodb.mongo_roll_data import mongoRollParametersData """ Generate the roll calendars from existing data """ if __name__ == "__main__": csv_roll_calendars = csvRollCalendarData() sim_futures_data = csvFuturesSimData() mongo_rollparameters = mongoRollParametersData() instrument_list = sim_futures_data.get_instrument_list() for instrument_code in instrument_list: print(instrument_code) multiple_prices = sim_futures_data.get_all_multiple_prices( instrument_code) roll_parameters = mongo_rollparameters.get_roll_parameters( instrument_code) roll_calendar = rollCalendar.back_out_from_multiple_prices( multiple_prices) print("Calendar:") print(roll_calendar) # We ignore duplicates since this is run regularly csv_roll_calendars.add_roll_calendar(instrument_code, roll_calendar, ignore_duplication=True)
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))