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
-1.298
Tracking Error
0.122
Treynor Ratio
0
Total Fees
$0.00
Estimated Strategy Capacity
$0
Lowest Capacity Asset
 
# Three ways to get a normalized ATR 


class MuscularGreenAlbatross(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2020, 9, 1)  
        self.SetEndDate(2021, 10, 7) 
        self.stock = self.AddEquity("SPY", Resolution.Daily).Symbol
        self.SetWarmUp(15, Resolution.Daily)
        self.atr = self.ATR(self.stock, 14, MovingAverageType.Simple, Resolution.Daily)
        self.yest_close = self.Identity(self.stock, Resolution.Daily, Field.Close)
        self.atr_norm_2 = IndicatorExtensions.Over(self.atr, self.yest_close)
        
        
    def OnData(self, data):
        if self.IsWarmingUp or not self.atr.IsReady or not self.atr_norm_2.IsReady: return

        atr_norm_1 = float(self.atr.Current.Value / self.yest_close.Current.Value)
        atr_norm_2 = float(self.atr_norm_2.Current.Value)
        # atr_norm_3 = 

        self.Plot("ATR", "atr_norm_1", atr_norm_1)
        self.Plot("ATR", "atr_norm_2", atr_norm_2)
        # self.Plot("ATR", "atr_norm_3", atr_norm_3)
        
        
class symbolData:
    
    def __init__(self, algo, ticker):
        self.symbol = algo.AddEquity(ticker, Resolution.Daily).Symbol
        
        self.atr = algo.ATR(self.symbol, 14, MovingAverageType.Simple, Resolution.Daily)
        self.id = algo.Identity(self.symbol, Resolution.Daily, Field.Close)
        self.atrOverPrice = IndicatorExtensions.Over(self.atr, self.id)
        
        # Warm up ATR
        history = algo.History(self.symbol, 15, Resolution.Daily)
        for bar in history.itertuples():
            tradeBar = TradeBar(bar.Index[1], bar.Index[0], bar.open, bar.high, 
                                bar.low, bar.close, bar.volume)
            self.atr.Update(tradeBar)
            
        # Warm up Identity, since it should be using 2-day-prior close price
        history = algo.History(self.symbol, 2, Resolution.Daily).iloc[0]
        self.id.Update(pd.to_datetime(history.name[1]), history.close)