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
-7.771
Tracking Error
0.05
Treynor Ratio
0
Total Fees
$0.00
 
class ModulatedOptimizedCompensator(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2019, 11, 5)  # Set Start Date
        self.SetEndDate(2019, 11, 30)
        self.SetCash(100000)  # Set Strategy Cash
        self.AddEquity("SPY", Resolution.Minute)
        
        self.sma = self.SMA("SPY", 5, Resolution.Daily)
        self.sma.Updated += self.OnSMA
        
        self.SetWarmUp(timedelta(days=5))

    def OnData(self, data):
        '''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
            Arguments:
                data: Slice object keyed by symbol containing the stock data
        '''

        # if not self.Portfolio.Invested:
        #    self.SetHoldings("SPY", 1)
        
    def OnSMA(self, sender, updated):
        if self.sma.IsReady:
            self.Debug(f"SMA Updated on {self.Time} with value: {self.sma.Current.Value}")