Quantopian Series: Theory to Practice-Simple Moving Averages

Hmm, I don't know enough to give you a confident answer yet. The knowledge sources provided do not contain the specific code that 'Benjamin' is referring to. However, I can guide you on how to implement a simple moving average strategy in Python on QuantConnect.

Here is a basic example of how you might implement a simple moving average (SMA) crossover strategy:

class MyAlgo(QCAlgorithm):
    def Initialize(self):
        self.SetStartDate(2013,10,7)  # Set Start Date
        self.SetEndDate(2013,10,11)    # Set End Date
        self.SetCash(100000)           # Set Strategy Cash
        self.AddEquity("SPY", Resolution.Minute)
        self.sma = self.SMA("SPY", 14, Resolution.Minute)

    def OnData(self, data):
        if not self.sma.IsReady:
            return

        if not self.Portfolio.Invested:
            self.SetHoldings("SPY", 1)
        elif data["SPY"].Close < self.sma.Current.Value:
            self.Liquidate("SPY")

This code creates a 14-minute simple moving average (SMA) on the SPY. When the price of the SPY is above the SMA, it goes long. When the price drops below the SMA, it closes the position.

You can backtest this strategy by clicking the "Backtest" button in the QuantConnect IDE. If you encounter any issues, you can ask for help on the QuantConnect forum or Discord.

For more information on implementing strategies in QuantConnect, you can refer to the QuantConnect documentation.