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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 datetime import datetime, timedelta
import clr
clr.AddReference("System")
clr.AddReference("QuantConnect.Algorithm")
clr.AddReference("QuantConnect.Indicators")
clr.AddReference("QuantConnect.Common")
from System import *
from QuantConnect import *
from QuantConnect.Algorithm import *
from QuantConnect.Indicators import *
from QuantConnect.Data.Market import *
class RegressionAlgorithm(QCAlgorithm):
'''Algorithm used for regression tests purposes'''
def __init__(self):
self.__lastTradeTicks = None
self.__lastTradeTradeBars = None
self.__tradeEvery = timedelta(minutes=1)
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(10000000) #Set Strategy Cash
# Find more symbols here: http://quantconnect.com/data
self.AddSecurity(SecurityType.Equity, "SPY", Resolution.Tick);
self.AddSecurity(SecurityType.Equity, "BAC", Resolution.Minute);
self.AddSecurity(SecurityType.Equity, "AIG", Resolution.Hour);
self.AddSecurity(SecurityType.Equity, "IBM", Resolution.Daily);
self.__lastTradeTicks = datetime(2013,10,07)
self.__lastTradeTradeBars = datetime(2013,10,07)
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: Tradebars object keyed by symbol containing the stock data
'''
pyTime = datetime(self.Time)
if pyTime - self.__lastTradeTradeBars < self.__tradeEvery:
return
self.__lastTradeTradeBars = pyTime
for symbol in data.Bars.Keys:
period = data.Bars[symbol].Period.TotalSeconds
if self.roundTime(pyTime, period) != pyTime:
pass
holdings = self.Portfolio[symbol]
if not holdings.Invested:
self.MarketOrder(symbol, 10)
else:
self.MarketOrder(symbol, -holdings.Quantity)
def roundTime(self, dt=None, roundTo=60):
"""Round a datetime object to any time laps in seconds
dt : datetime object, default now.
roundTo : Closest number of seconds to round to, default 1 minute.
"""
if dt == None : dt = datetime.now()
seconds = (dt - dt.min).seconds
# // is a floor division, not a comment on following line:
rounding = (seconds+roundTo/2) // roundTo * roundTo
return dt + timedelta(0,rounding-seconds,-dt.microsecond)