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))
