Overall Statistics
Total Trades
206
Average Win
6.28%
Average Loss
-1.42%
Compounding Annual Return
17.724%
Drawdown
31.800%
Expectancy
1.650
Net Profit
126.373%
Sharpe Ratio
0.823
Probabilistic Sharpe Ratio
27.845%
Loss Rate
51%
Win Rate
49%
Profit-Loss Ratio
4.43
Alpha
0.168
Beta
-0.007
Annual Standard Deviation
0.204
Annual Variance
0.042
Information Ratio
0.422
Tracking Error
0.313
Treynor Ratio
-23.923
Total Fees
$206.00
 
from math import floor
class MomentumBasedTacticalAllocation(QCAlgorithm):
    
    def Initialize(self):
        
        self.SetStartDate(2007, 8, 1) 
        self.SetEndDate(2012, 8, 1)  
        self.SetCash(3000)  
        
        self.spy = self.AddEquity("SPY", Resolution.Daily)  
        self.bnd = self.AddEquity("BND", Resolution.Daily)  
      
        self.spyMomentum = self.MOMP("SPY", 50, Resolution.Daily) 
        self.bondMomentum = self.MOMP("BND", 50, Resolution.Daily) 
       
        self.SetBenchmark(self.spy.Symbol)  
        self.SetWarmUp(50) 
  
    def OnData(self, data):
        
        if self.IsWarmingUp:
            return
        
        #1. Limit trading to happen once per week
        if self.Time.weekday() != 1:
            return
        
        if self.spyMomentum.Current.Value > self.bondMomentum.Current.Value:
            if self.Securities["SPY"].Close == 0: return
            self.Liquidate(self.bnd.Symbol)
            self.MarketOrder(self.spy.Symbol, floor(self.Portfolio.MarginRemaining/self.Securities["SPY"].Close))
            #2. Otherwise we liquidate our holdings in SPY and allocate 100% to BND
        else:
            if self.Securities["BND"].Close == 0: return
            self.Liquidate(self.spy.Symbol)
            self.MarketOrder(self.bnd.Symbol, floor(self.Portfolio.MarginRemaining/self.Securities["BND"].Close))