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
-3.313
Tracking Error
0.163
Treynor Ratio
0
Total Fees
$0.00
 
class MeanReversionResearch(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2020, 10, 1)
        self.SetEndDate(2020, 12, 5)
        self.SetCash(100_000)
        
        self.symbol1 = self.AddEquity('CVX', Resolution.Daily).Symbol
        self.symbol2 = self.AddEquity('XOM', Resolution.Daily).Symbol
        
        lookback = 20
        self.sma = SimpleMovingAverage(lookback)
        self.std = StandardDeviation(lookback)


    def OnData(self, data):
        if data.ContainsKey(self.symbol1) and data.ContainsKey(self.symbol2):
            ratio = data[self.symbol1].Close / data[self.symbol2].Close
            self.sma.Update(self.Time, ratio)
            self.std.Update(self.Time, ratio)
            
            if self.sma.IsReady and self.std.IsReady:
                self.Plot("SMA", "Value", self.sma.Current.Value)
                self.Plot("STD", "Value", self.std.Current.Value)
            
                z_score = (ratio - self.sma.Current.Value) / self.std.Current.Value
                self.Plot("Z Score", "Value", z_score)