my_system = System([my_rules], data)
my_system.rules.get_raw_forecast("EDOLLAR", "ewmac32").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",
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
from systems.basesystem import System
from sysdata.csvdata import csvFuturesData
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.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 systems.provided.example.rules import ewmac_forecast_with_defaults as ewmac
from sysdata.configdata import Config
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
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"
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
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
