def get_test_object_futures():
"""
Returns some standard test data
"""
data = csvFuturesData("sysdata.tests")
rawdata = FuturesRawData()
config = Config("systems.provided.example.exampleconfig.yaml")
return (rawdata, data, config)
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 = csvFuturesSimData()
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):
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 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 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():
"""
Returns some standard test data
"""
data = csvFuturesSimData(datapath_dict=dict(
config_data="sysdata.tests.configtestdata",
adjusted_prices="sysdata.tests.multiplepricestestdata",
spot_fx_data="sysdata.tests.fxtestdata",
multiple_price_data="sysdata.tests.multiplepricestestdata"))
config = Config("systems.provided.example.exampleconfig.yaml")
rawdata = FuturesRawData()
return (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_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)
import inspect
import sys; sys.path.append('../..')
import numpy as np
from systems.basesystem import System
from systems.forecast_combine import ForecastCombineEstimated
from sysdata.csvdata import csvFuturesData
from systems.futures.rawdata import FuturesRawData
from systems.forecasting import Rules
from sysdata.configdata import Config
from systems.forecast_scale_cap import ForecastScaleCapFixed, ForecastScaleCapEstimated
from systems.account import Account
data = csvFuturesData("sysdata.tests")
rawdata = FuturesRawData()
rules = Rules()
config = Config("examples.test14.yaml")
fcs = ForecastScaleCapEstimated()
accounts=Account()
from systems.portfolio import PortfoliosEstimated
from systems.positionsizing import PositionSizing
system=System([accounts, rawdata, rules, fcs, ForecastCombineEstimated(), PositionSizing(), PortfoliosEstimated()], data, config)
print (system.portfolio.get_instrument_correlation_matrix().corr_list)
#array([[ 1. , 0.87041785],
# [ 0.87041785, 1. ]])
