Overall Statistics
Total Trades
0
Average Win
0%
Average Loss
0%
Compounding Annual Return
0%
Drawdown
0%
Expectancy
0
Net Profit
0%
Sharpe Ratio
0
Probabilistic Sharpe Ratio
0%
Loss Rate
0%
Win Rate
0%
Profit-Loss Ratio
0
Alpha
0
Beta
0
Annual Standard Deviation
0
Annual Variance
0
Information Ratio
1.954
Tracking Error
0.184
Treynor Ratio
0
Total Fees
$0.00
Estimated Strategy Capacity
$0
 
class EnergeticOrangeBat(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2021, 1, 20) # Set Start Date
        self.SetEndDate(2021, 2, 1)
        self.SetCash(100000)  # Set Strategy Cash
        
        self.symbol = self.AddEquity("SPY", Resolution.Daily).Symbol
        self.EnableAutomaticIndicatorWarmUp = True
        self.ema = self.EMA(self.symbol, 50, Resolution.Daily)
        
        self.ema_2 = self.EMA(self.symbol, 50, Resolution.Daily)
        # Warm up
        history = self.History(self.symbol, 50, Resolution.Daily)
        for time, row in history.loc[self.symbol].iterrows():
            self.ema_2.Update(time, row.close)
        
        self.Log(f"Starting values: {self.ema.Current.Value} {self.ema_2.Current.Value}")


    def OnData(self, data):
        if not (data.ContainsKey(self.symbol) and data[self.symbol] is not None):
            return

        self.Plot("SPY", "EMA", self.ema.Current.Value)
        self.Plot("SPY", "EMA2", self.ema_2.Current.Value)
        self.Plot("SPY", "Price", data[self.symbol].Price)