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
-2.224
Tracking Error
0.114
Treynor Ratio
0
Total Fees
$0.00
Estimated Strategy Capacity
$0
Lowest Capacity Asset
Portfolio Turnover
0%
 
from AlgorithmImports import *

class ETFConstituentsDataAlgorithm(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2023, 1, 1)
        self.SetEndDate(2023, 8, 1)
        self.SetCash(100000)
        
        self.UniverseSettings.Resolution = Resolution.Minute
        
        # Requesting data
        self.qqq = self.AddEquity("QQQ").Symbol
        self.AddUniverse(self.Universe.ETF(self.qqq, self.UniverseSettings, self.ETFConstituentsFilter))
       # self.Schedule.On(
        #    self.DateRules.MonthStart(self.qqq, 0),
        #    self.TimeRules.AfterMarketOpen(self.qqq, 1)
        #    self.ETFConstituentsFilter(self, constituents))

    def ETFConstituentsFilter(self, constituents: List[ETFConstituentData]) -> List[Symbol]:
        for c in constituents:
            self.Debug(f'{c.LastUpdate} :: {c.Symbol} :: {c.Weight}')
            return [x.Symbol for x in constituents]