Overall Statistics
# 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.

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 *
import decimal as d 


class MovingAverageCrossAlgorithm(QCAlgorithm):
    '''In this example we look at the canonical 15/30 day moving average cross. This algorithm
    will go long when the 15 crosses above the 30 and will liquidate when the 15 crosses
    back below the 30.'''
    
    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(2012, 01, 01)  #Set Start Date
        self.SetEndDate(2014, 01, 1)    #Set End Date
        self.SetCash(100000)             #Set Strategy Cash
        # Find more symbols here: http://quantconnect.com/data
        self.AddEquity("SPY")
        
        # create a 15 day exponential moving average
        self.fast = self.EMA("SPY", 15, Resolution.Daily);

        # create a 30 day exponential moving average
        self.slow = self.EMA("SPY", 30, Resolution.Daily);

        self.previous = None

    
    
        
    def OnData(self, data):
        '''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.'''
        # a couple things to notice in this method:
        #  1. We never need to 'update' our indicators with the data, the engine takes care of this for us
        #  2. We can use indicators directly in math expressions
        #  3. We can easily plot many indicators at the same time    

        # wait for our slow ema to fully initialize
        if not self.slow.IsReady:
            return    

        # only once per day
        if self.previous is not None and self.previous.date() == self.Time.date():
            return

        # define a small tolerance on our checks to avoid bouncing
        tolerance = 0.00015;
        
        holdings = self.Portfolio["SPY"].Quantity

        # we only want to go long if we're currently short or flat
        if holdings <= 0:
            # if the fast is greater than the slow, we'll go long
            if self.fast.Current.Value > self.slow.Current.Value * d.Decimal(1 + tolerance):
                self.Log("BUY  >> {0}".format(self.Securities["SPY"].Price))
                self.SetHoldings("SPY", 1.0)
             
        # we only want to liquidate if we're currently long
        # if the fast is less than the slow we'll liquidate our long
        if holdings > 0 and self.fast.Current.Value < self.slow.Current.Value:
            self.Log("SELL >> {0}".format(self.Securities["SPY"].Price))
            self.Liquidate("SPY")  
            
            # Rich, call OnEndAlgo.. code myself
            #self.Log("here")
            #self.OnEndOfAlgorithm()  # Try to call myself as not firing itself..
          

        self.previous = self.Time
        
       
        
        
        def OnEndOfAlgorithm(self):
            self.Log("****** End of algo code reached")
            
            for trade in self.TradeBuilder.ClosedTrades:
			    self.Log("Symbol: {0} Quantity: {1} EntryTime: {2} EntryPrice: {3} ExitTime: {4} ExitPrice: {5}, ProfitLoss: {6}, TotalFees: {7}, MAE: {8}, MFE: {9}, Duration: {10}, EndTradeDrawdown: {11}"
			        .format(
			            trade.Symbol, 
			            trade.Quantity, 
			            trade.EntryTime, 
			            trade.EntryPrice, 
			            trade.ExitTime, trade.ExitPrice, 
			            trade.ProfitLoss, 
			            trade.TotalFees, 
			            trade.MAE,
			            trade.MFE,
			            trade.Duration,
			            trade.EndTradeDrawdown))