def testRules(self):
# config=Config(dict(trading_rules=dict(ewmac=dict(function="systems.provided.example.rules.ewmac_forecast_with_defaults"))))
NOTUSEDrawdata, data, NOTUSEDconfig = get_test_object()
rules = Rules(
dict(
function=
"systems.provided.example.rules.ewmac_forecast_with_defaults"))
system = System([rules], data)
ans = system.rules.get_raw_forecast("EDOLLAR", "rule0")
self.assertAlmostEqual(ans.tail(1).values[0], -3.280028, 5)
config = Config(
dict(trading_rules=dict(ewmac=dict(
function=
"systems.provided.example.rules.ewmac_forecast_with_defaults"))
))
rules = Rules()
system = System([rules], data, config)
ans = system.rules.get_raw_forecast("EDOLLAR", "ewmac")
self.assertAlmostEqual(ans.tail(1).values[0], -3.28002839, 5)
config = Config("systems.provided.example.exampleconfig.yaml")
rawdata = RawData()
rules = Rules()
system = System([rules, rawdata], data, config)
ans = system.rules.get_raw_forecast("EDOLLAR", "ewmac8")
self.assertAlmostEqual(ans.tail(1).values[0], -2.158634, 5)
def testRules(self):
# config=Config(dict(trading_rules=dict(ewmac=dict(function="systems.provided.example.rules.ewmac_forecast_with_defaults"))))
data = csvFuturesData("sysdata.tests")
rules = Rules(
dict(
function=
"systems.provided.example.rules.ewmac_forecast_with_defaults"))
system = System([rules], data)
ans = system.rules.get_raw_forecast("EDOLLAR", "rule0")
self.assertAlmostEqual(ans.tail(1).values[0], 2.1384223788141838, 5)
config = Config(
dict(trading_rules=dict(ewmac=dict(
function=
"systems.provided.example.rules.ewmac_forecast_with_defaults"))
))
rules = Rules()
system = System([rules], data, config)
ans = system.rules.get_raw_forecast("EDOLLAR", "ewmac")
self.assertAlmostEqual(ans.tail(1).values[0], 2.1384223788141838, 5)
config = Config("systems.provided.example.exampleconfig.yaml")
rawdata = RawData()
rules = Rules()
system = System([rules, rawdata], data, config)
ans = system.rules.get_raw_forecast("EDOLLAR", "ewmac8")
self.assertAlmostEqual(ans.tail(1).values[0], 0.16438313875, 5)
def test_simple_system_trading_rule(self, data, raw_data, ewmac_8, ewmac_32):
ewmac_rule = TradingRule(ewmac)
print(ewmac_rule)
my_rules = Rules(dict(ewmac8=ewmac_8, ewmac32=ewmac_32))
print(my_rules.trading_rules()["ewmac32"])
my_system = System([my_rules, raw_data], data)
my_system.rules.get_raw_forecast("EDOLLAR", "ewmac32").tail(5)
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 futures_system(sim_data=arg_not_supplied,
config_filename="systems.provided.rob_system.config.yaml"):
if sim_data is arg_not_supplied:
sim_data = dbFuturesSimData()
config = Config(config_filename)
system = System(
[
Risk(),
accountForOptimisedStage(),
optimisedPositions(),
Portfolios(),
PositionSizing(),
myFuturesRawData(),
ForecastCombine(),
volAttenForecastScaleCap(),
Rules(),
],
sim_data,
config,
)
system.set_logging_level("on")
return system
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 testCallingTradingRule(self):
# config=Config(dict(trading_rules=dict(ewmac=dict(function="systems.provided.example.rules.ewmac_forecast_with_defaults"))))
data = csvFuturesData("sysdata.tests")
rawdata = RawData()
rules = Rules()
system = System([rawdata, rules], data)
# Call with default data and config
rule = TradingRule(ewmac_forecast_with_defaults)
ans = rule.call(system, "EDOLLAR")
self.assertAlmostEqual(ans.tail(1).values[0], 2.1384223788141838, 5)
# Change the data source
rule = TradingRule((
"systems.provided.example.rules.ewmac_forecast_with_defaults_no_vol",
["rawdata.get_daily_prices",
"rawdata.daily_returns_volatility"], dict()))
ans = rule.call(system, "EDOLLAR")
self.assertAlmostEqual(ans.tail(1).values[0], 0.029376, 5)
rule = TradingRule(
dict(
function=
"systems.provided.example.rules.ewmac_forecast_with_defaults_no_vol",
data=[
"rawdata.get_daily_prices",
"rawdata.daily_returns_volatility"
],
other_args=dict(Lfast=50, Lslow=200)))
ans = rule.call(system, "EDOLLAR")
self.assertAlmostEqual(ans.tail(1).values[0], 3.84426755)
def testCallingTradingRule(self):
# config=Config(dict(trading_rules=dict(ewmac=dict(function="systems.provided.example.rules.ewmac_forecast_with_defaults"))))
NOTUSEDrawdata, data, NOTUSEDconfig = get_test_object()
rawdata = RawData()
rules = Rules()
system = System([rawdata, rules], data)
# Call with default data and config
rule = TradingRule(ewmac_forecast_with_defaults)
ans = rule.call(system, "EDOLLAR")
self.assertAlmostEqual(ans.tail(1).values[0], -3.280028, 5)
# Change the data source
rule = TradingRule((
"systems.provided.example.rules.ewmac_forecast_with_defaults_no_vol",
["rawdata.get_daily_prices",
"rawdata.daily_returns_volatility"], dict()))
ans = rule.call(system, "EDOLLAR")
self.assertAlmostEqual(ans.tail(1).values[0], -1.24349, 5)
rule = TradingRule(
dict(
function=
"systems.provided.example.rules.ewmac_forecast_with_defaults_no_vol",
data=[
"rawdata.get_daily_prices",
"rawdata.daily_returns_volatility"
],
other_args=dict(Lfast=50, Lslow=200)))
ans = rule.call(system, "EDOLLAR")
self.assertAlmostEqual(ans.tail(1).values[0], -3.025001057146)
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 get_test_object_futures_with_rules():
"""
Returns some standard test data
"""
data = csvFuturesData("sysdata.tests")
rawdata = FuturesRawData()
rules = Rules()
config = Config("systems.provided.example.exampleconfig.yaml")
return (rules, rawdata, data, config)
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 testCarryRule(self):
data = csvFuturesData("sysdata.tests")
rawdata = FuturesRawData()
rules = Rules()
system = System([rawdata, rules], data)
rule = TradingRule(carry, [
"rawdata.daily_annualised_roll", "rawdata.daily_returns_volatility"
], dict(smooth_days=90))
ans = rule.call(system, "EDOLLAR")
self.assertAlmostEqual(ans.iloc[-1][0], 0.411686026, 5)
def testCarryRule(self):
NOTUSEDrawdata, data, NOTUSEDconfig = get_test_object()
rawdata = FuturesRawData()
rules = Rules()
system = System([rawdata, rules], data)
rule = TradingRule(carry2, [
"rawdata.daily_annualised_roll",
], dict(smooth_days=90))
ans = rule.call(system, "EDOLLAR")
self.assertAlmostEqual(ans.tail(1).values[0], 0.138302, 5)
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_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_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 testCarryRule(self):
data = csvFuturesData("sysdata.tests")
rawdata = FuturesRawData()
rules = Rules()
system = System([rawdata, rules], data)
rule = TradingRule(
carry2, [
"rawdata.daily_annualised_roll",
],
dict(smooth_days=90))
ans = rule.call(system, "EDOLLAR")
self.assertAlmostEqual(ans.tail(1).values[0], 0.37666175, 5)
def get_test_object_futures_with_rules():
"""
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")
return (rules, rawdata, data, config)
def test_simple_system_trading_rules_estimated(
self, data, raw_data, ewmac_8, ewmac_32, fcs
):
my_rules = Rules(dict(ewmac8=ewmac_8, ewmac32=ewmac_32))
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, raw_data], 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
my_system = System([fcs, my_rules, raw_data], data, my_config)
my_config.forecast_scalar_estimate["pool_instruments"] = False
print(
my_system.forecastScaleCap.get_forecast_scalar("EDOLLAR", "ewmac32").tail(5)
)
def test_simple_system_combining_fixed(self, data, raw_data, my_config, fcs):
# 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
empty_rules = Rules()
combiner = ForecastCombine()
my_system = System(
[fcs, empty_rules, combiner, raw_data], data, my_config
) # no need for accounts if no estimation done
my_system.combForecast.get_combined_forecast("EDOLLAR").tail(5)
def get_test_object_futures_with_rules_and_capping_estimate():
"""
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()
account = Account()
return (account, capobject, rules, rawdata, data, config)
def get_test_object_futures_with_pos_sizing():
"""
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()
combobject = ForecastCombine()
posobject = PositionSizing()
return (posobject, combobject, 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 test_simple_system_rules(self, data, raw_data):
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, raw_data], data)
print(my_system)
print(my_system.rules.get_raw_forecast("EDOLLAR", "ewmac").tail(5))
def create_rules_for_random_system():
## create a series of regression trading rules different lookbacks
rules_dict=dict()
for timewindow in WINDOWS_TO_USE:
rule_name="regression%d" % timewindow
min_periods = max(2, int(np.ceil(timewindow / 4.0)))
new_rule = TradingRule((regression_rule, ["rawdata.get_daily_prices", "rawdata.daily_returns_volatility"],
dict(timewindow=timewindow, min_periods=min_periods)))
rules_dict[rule_name]=new_rule
my_rules = Rules(rules_dict)
return my_rules
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))
For this we need to build a system
A system is made up of SystemStages - essentially stages in the process, and it
needs data, and perhaps a configuration
The minimum stage you would have would be Rules - which is where you put
trading rules
"""
from systems.forecasting import Rules
"""
We can create rules in a number of different ways
Note that to make our rule work it needs to have
"""
my_rules = Rules(ewmac)
print(my_rules.trading_rules())
my_rules = Rules(dict(ewmac=ewmac))
print(my_rules.trading_rules())
from systems.basesystem import System
my_system = System([my_rules], data)
print(my_system)
print(my_system.rules.get_raw_forecast("EDOLLAR", "ewmac").tail(5))
"""
Define a TradingRule
"""
from systems.forecasting import TradingRule
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
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())
A system is made up of SystemStages - essentially stages in the process, and it needs data, and perhaps a configuration
The minimum stage you would have would be Rules - which is where you put trading rules
"""
from systems.forecasting import Rules
"""
We can create rules in a number of different ways
Note that to make our rule work it needs to have
"""
my_rules = Rules(ewmac)
print(my_rules.trading_rules())
my_rules = Rules(dict(ewmac=ewmac))
print(my_rules.trading_rules())
from systems.basesystem import System
my_system = System([my_rules], data)
print(my_system)
print(my_system.rules.get_raw_forecast("EDOLLAR", "ewmac").tail(5))
"""
Define a TradingRule
For this we need to build a system
A system is made up of SystemStages - essentially stages in the process, and it
needs data, and perhaps a configuration
The minimum stage you would have would be Rules - which is where you put
trading rules
"""
from systems.forecasting import Rules
"""
We can create rules in a number of different ways
Note that to make our rule work it needs to have
"""
my_rules = Rules(ewmac)
print(my_rules.trading_rules())
my_rules = Rules(dict(ewmac=ewmac))
print(my_rules.trading_rules())
from systems.basesystem import System
my_system = System([my_rules], data)
print(my_system)
print(my_system.rules.get_raw_forecast("EDOLLAR", "ewmac").tail(5))
"""
Define a TradingRule
"""
from systems.forecasting import TradingRule
