Overall Statistics 
Total Trades
11
Average Win
5.27%
Average Loss
2.77%
Compounding Annual Return
14.401%
Drawdown
7.300%
Expectancy
1.322
Net Profit
30.907%
Sharpe Ratio
1.392
Loss Rate
20%
Win Rate
80%
ProfitLoss Ratio
1.90
Alpha
0.015
Beta
0.702
Annual Standard Deviation
0.1
Annual Variance
0.01
Information Ratio
1.233
Tracking Error
0.065
Treynor Ratio
0.198
Total Fees
$44.17

# 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/LICENSE2.0 # # 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 startend 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))