text: ﻿# 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.Algorithm import *
  from QuantConnect.Indicators import *
  from datetime import datetime
  
  class MACDTrendAlgorithm(QCAlgorithm):
      '''MACD Example Algorithm'''
          
      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(2004, 01, 01)  #Set Start Date
          self.SetEndDate(2015, 01, 01)    #Set End Date
          self.SetCash(100000)             #Set Strategy Cash
          # Find more symbols here: http://quantconnect.com/data
          equity = self.AddEquity("SPY", Resolution.Daily)
          self.spy = equity.Symbol
  
          # define our daily macd(12,26) with a 9 day signal
          self.__macd = self.MACD(self.spy, 9, 26, 9, MovingAverageType.Exponential, Resolution.Daily)
          self.__previous = datetime.min
          self.PlotIndicator("MACD", True, self.__macd, self.__macd.Signal)
          self.PlotIndicator(str(self.spy), self.__macd.Fast, self.__macd.Slow)
  
  
      def OnData(self, data):
          '''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.'''
          # wait for our macd to fully initialize
          if not self.__macd.IsReady: return    
      
          # only once per day
          if self.__previous.date() == self.Time.date(): return
  
          # define a small tolerance on our checks to avoid bouncing
          tolerance = 0.0025;
          
          holdings = self.Portfolio[self.spy].Quantity
  
          signalDeltaPercent = (self.__macd.Current.Value - self.__macd.Signal.Current.Value)/self.__macd.Fast.Current.Value
  
          # if our macd is greater than our signal, then let's go long
          if holdings <= 0 and signalDeltaPercent > tolerance:  # 0.01%
              # longterm says buy as well
              self.SetHoldings(self.spy, 1.0)
  
          # of our macd is less than our signal, then let's go short
          elif holdings >= 0 and signalDeltaPercent < -tolerance:
              self.Liquidate(self.spy)  
  
          
          self.__previous = self.Time