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# 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.Indicators")
AddReference("QuantConnect.Common")
from System import *
from QuantConnect import *
from QuantConnect.Data import *
from QuantConnect.Algorithm import *
from QuantConnect.Indicators import *
class WarmupHistoryAlgorithm(QCAlgorithm):
'''This algorithm demonstrates using the history provider to
retrieve data to warm up indicators before data is received'''
def __init__(self):
self.__fast = None
self.__slow = None
self.__fastPeriod = 60
self.__slowPeriod = 3600
self.__symbol = Symbol.Create("EURUSD", SecurityType.Forex, "FXCM")
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(2013,10,07) #Set Start Date
self.SetEndDate(2013,10,11) #Set End Date
self.SetCash(100000) #Set Strategy Cash
# Find more symbols here: http://quantconnect.com/data
self.AddSecurity(SecurityType.Forex, self.__symbol.Value, Resolution.Second)
self.__fast = self.EMA(self.__symbol, self.__fastPeriod)
self.__slow = self.EMA(self.__symbol, self.__slowPeriod)
# "self.__slowPeriod + 1" because rolling window waits for one to fall off the back to be considered ready
history = self.History(self.__symbol, self.__slowPeriod + 1)
for bar in history:
datapoint = IndicatorDataPoint(bar.EndTime, bar.Close)
self.__fast.Update(datapoint)
self.__slow.Update(datapoint)
self.Log("FAST IS {0} READY. Samples: {1}".format("" if self.__fast.IsReady else "NOT", self.__fast.Samples))
self.Log("SLOW IS {0} READY. Samples: {1}".format("" if self.__slow.IsReady else "NOT", self.__slow.Samples))
def OnData(self, data):
'''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 self.__fast.Current.Value > self.__slow.Current.Value:
self.SetHoldings(self.__symbol, 1)
else:
self.SetHoldings(self.__symbol, -1)