Overall Statistics
Total Orders
0
Average Win
0%
Average Loss
0%
Compounding Annual Return
0%
Drawdown
0%
Expectancy
0
Start Equity
100000
End Equity
100000
Net Profit
0%
Sharpe Ratio
0
Sortino 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
Tracking Error
0
Treynor Ratio
0
Total Fees
$0.00
Estimated Strategy Capacity
$0
Lowest Capacity Asset
Portfolio Turnover
0%
Drawdown Recovery
0
 
# region imports
from AlgorithmImports import *
# endregion
class MeasuredFluorescentYellowChimpanzee(QCAlgorithm):
    def initialize(self):
        self.set_start_date(self.end_date)
        self.xly1_list = [self.add_equity(x).symbol for x in 
            [ 'MCD', 'YUM', 'CAVA', 'EAT', 'HRB', 'CCK', 'BALL', 'EBAY', 'CART', 'CPNG', 
              'BIRK', 'TPR', 'URBN', 'TJX', 'BOOT', 'BURL', 'RL', 'PVH', 'WSM', 'DKS', 'FIVE',
              'CAKE', 'SBUX', 'CMG', 'SHAK', 'SCI', 'IP', 'SEE', 'W', 'SE', 'CHWY',  
              'NKE', 'ETSY', 'ROST', 'CROX', 'LULU', 'UAA', 'VFC', 'GAP', 'BBY', 'RH', 'BBWI']]

    def on_warmup_finished(self):
        self.CheckDataAvailability(self.xly1_list)

    def CheckDataAvailability(self, symbols):
        dt = datetime.now()

        def check_missing(period, resolution):
            missing = symbols.copy()
            history = self.history[TradeBar](symbols, period, resolution)
            for bars in history:
                for symbol, bar in bars.items():
                    if symbol in missing:
                        missing.remove(symbol)
            return missing

        missing_daily = check_missing(2, Resolution.DAILY)
        if missing_daily:
            self.log(f'{missing_daily}=')
        
        missing_minute = check_missing(50, Resolution.MINUTE)
        if missing_minute:
            self.log(f'{missing_minute}=')
            
        self.quit(f'{datetime.now()-dt}')