Overall Statistics
Total Trades
362
Average Win
2.30%
Average Loss
-1.04%
Compounding Annual Return
6.397%
Drawdown
18.100%
Expectancy
0.462
Net Profit
124.370%
Sharpe Ratio
0.541
Probabilistic Sharpe Ratio
3.038%
Loss Rate
55%
Win Rate
45%
Profit-Loss Ratio
2.22
Alpha
0.062
Beta
-0.03
Annual Standard Deviation
0.108
Annual Variance
0.012
Information Ratio
-0.218
Tracking Error
0.22
Treynor Ratio
-1.944
Total Fees
$1244.34
Estimated Strategy Capacity
$580000000.00
 
# MACD, EMA(MACD), MACD.Signal

MA_FAST =  12; MA_SLOW = 26; MA_SIGNAL = 9;

class MACD_SignalCrossover(QCAlgorithm):

        def Initialize(self):
            self.SetStartDate(2008, 1, 19)  
            self.SetEndDate(2021, 1, 26)
            self.SetCash(100000)  
            self.AddEquity("SPY", Resolution.Daily).Symbol               
        
            self.macd = self.MACD("SPY", MA_FAST, MA_SLOW, MA_SIGNAL, MovingAverageType.Exponential, Resolution.Daily )
            self.macd_ema = IndicatorExtensions.EMA(self.macd, MA_SIGNAL)
            self.SetWarmUp(MA_SLOW*5)

            
        def OnData(self, data):
        
            if not self.macd_ema.IsReady: return   
            
            macd = self.macd.Current.Value
            macd_signal = self.macd.Signal.Current.Value 
            macd_signal_2 = self.macd_ema.Current.Value
            
            self.Plot("MACD", "macd_signal", self.macd.Signal.Current.Value)
            self.Plot("MACD", "macd_ema", self.macd_ema.Current.Value)
            self.Plot("MACD", "Zero", 0)            
            
               
            if  macd > macd_signal:
                self.SetHoldings("SPY", 1)
            else:
                self.Liquidate("SPY")