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
-0.9
Tracking Error
0.115
Treynor Ratio
0
Total Fees
$0.00
Estimated Strategy Capacity
$0
Lowest Capacity Asset
 
# sma_ratio_spread

# ---------------
MA = 21; SMA = 5;
# ---------------

class SmaRatioSpread(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2021, 1, 1)  
        self.SetEndDate(2022, 2, 22)
        self.SetCash(1000000)  
        self.pep = self.AddEquity("PEP", Resolution.Daily).Symbol 
        self.coke = self.AddEquity("COKE", Resolution.Daily).Symbol 
        price_pep = self.SMA(self.pep, 1, Resolution.Daily)
        price_coke = self.SMA(self.coke, 1, Resolution.Daily)
        sma_pep = self.SMA(self.pep, MA, Resolution.Daily)
        sma_coke = self.SMA(self.coke, MA, Resolution.Daily)
        ratio_pep = IndicatorExtensions.Over(price_pep, sma_pep)
        ratio_coke = IndicatorExtensions.Over(price_coke, sma_coke)
        self.ratio_spread = IndicatorExtensions.Minus(ratio_pep, ratio_coke) 
        self.sma_ratio_spread = IndicatorExtensions.SMA(self.ratio_spread, SMA) 
        self.SetWarmUp(MA + SMA, Resolution.Daily)


    def OnData(self, data):
        if self.IsWarmingUp: return
        if not self.ratio_spread.IsReady: return
        if not self.sma_ratio_spread.IsReady: return
      
        self.Plot("Spread","ratio_spread", self.ratio_spread.Current.Value)
        self.Plot("Spread","sma_ratio_spread", self.sma_ratio_spread.Current.Value)