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BasicTemplateIntrinioEconomicData.py 3.16 KB
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Martin Molinero 提交于 2018-12-15 02:25 +08:00 . Disabling Intrinio regression tests
# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from clr import AddReference
AddReference("System")
AddReference("QuantConnect.Algorithm")
AddReference("QuantConnect.Common")
AddReference("QuantConnect.Indicators")
from System import *
from QuantConnect import *
from QuantConnect.Algorithm import *
from QuantConnect.Indicators import *
from QuantConnect.Data.Custom import *
from QuantConnect.Data.Custom.Intrinio import *
from numpy import sign
from datetime import timedelta
class BasicTemplateIntrinioEconomicData(QCAlgorithm):
def Initialize(self):
'''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''
self.SetStartDate(2010, 1, 1) #Set Start Date
self.SetEndDate(2013, 12, 31) #Set End Date
self.SetCash(100000) #Set Strategy Cash
# Set your Intrinino user and password.
IntrinioConfig.SetUserAndPassword("intrinio-username", "intrinio-password")
# The Intrinio user and password can be also defined in the config.json file for local backtest.
# Set Intrinio config to make 1 call each minute, default is 1 call each 5 seconds.
#(1 call each minute is the free account limit for historical_data endpoint)
IntrinioConfig.SetTimeIntervalBetweenCalls(timedelta(minutes = 1))
# United States Oil Fund LP
self.uso = self.AddEquity("USO", Resolution.Daily).Symbol
self.Securities[self.uso].SetLeverage(2)
# United States Brent Oil Fund LP
self.bno = self.AddEquity("BNO", Resolution.Daily).Symbol
self.Securities[self.bno].SetLeverage(2)
self.AddData(IntrinioEconomicData, "$DCOILWTICO", Resolution.Daily)
self.AddData(IntrinioEconomicData, "$DCOILBRENTEU", Resolution.Daily)
self.emaWti = self.EMA("$DCOILWTICO", 10)
def OnData(self, slice):
'''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
Arguments:
data: Slice object keyed by symbol containing the stock data
'''
if (slice.ContainsKey("$DCOILBRENTEU") or slice.ContainsKey("$DCOILWTICO")):
spread = slice["$DCOILBRENTEU"].Value - slice["$DCOILWTICO"].Value
else:
return
if ((spread > 0 and not self.Portfolio[self.bno].IsLong) or
(spread < 0 and not self.Portfolio[self.uso].IsShort)):
self.SetHoldings(self.bno, 0.25 * sign(spread))
self.SetHoldings(self.uso, -0.25 * sign(spread))
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