Hi I'm going through the bootcamp 10. Below is the script

# region imports
from AlgorithmImports import *
from datetime import timedelta, datetime
# endregion

class T10PairTradingwithSMA05WarmingOurPairSpread(QCAlgorithm):
   def Initialize(self):
       self.SetStartDate(2018, 7, 1)
       self.SetEndDate(2019, 3, 31)
       self.SetCash (100000)
       symbols = [Symbol.Create("PEP", SecurityType.Equity, Market.USA), Symbol.Create("KO", SecurityType.Equity, Market.USA)]
       self.AddUniverseSelection(ManualUniverseSelectionModel(symbols))
       self.UniverseSettings.Resolution = Resolution.Hour
       self.UniverseSettings.DataNormalizationMode = DataNormalizationMode.Raw
       self.AddAlpha(PairsTradingAlphaModel())
       self.SetPortfolioConstruction(EqualWeightingPortfolioConstructionModel())
       self.SetExecution(ImmediateExecutionModel())
       
   def OnEndOfDay(self, symbol):
       self.Log("Taking-a position of " + str(self.Portfolio[symbol].Quantity)+ " units of symbol " + str(symbol))

class PairsTradingAlphaModel(AlphaModel):
   def __init__(self):
       self.pair = [ ]
       self.spreadMean = SimpleMovingAverage(500)
       self.spreadStd = StandardDeviation(500)
       #1. Set self.period to a 2 hour timedelta
       self.period = timedelta (hours=2)        
       
   def Update(self, algorithm, data):
       spread = self.pair[1].Price - self.pair[0].Price
       self.spreadMean.Update(algorithm.Time, spread)
       self.spreadStd.Update(algorithm.Time, spread)

       upperthreshold = self.spreadMean.Current.Value + self.spreadStd.Current.Value
       lowerthreshold = self.spreadMean.Current.Value - self.spreadStd.Current.Value

       if spread > upperthreshold:
           return Insight.Group(
               [
                   Insight.Price(self.pair[0].Symbol, self.period, InsightDirection.Up), Insight.Price(self.pair[1].Symbol, self.period, InsightDirection.Down)
               ])
       if spread < lowerthreshold:
           return Insight.Group(
               [
                   Insight.Price(self.pair[0].Symbol, self.period, InsightDirection.Down), Insight.Price(self.pair[1].Symbol, self.period, InsightDirection.Up)
               ])
       
       return []


   def OnSecuritiesChanged(self, algorithm, changes):
       
       self.pair = [x for x in changes.AddedSecurities]

       #1. Call for 500 hours of history data for each symbol in the pair and save to the variable history
       history=algorithm.History([x.Symbol for x in self.pair], 500)
       #2. Unstack the Pandas data frame to reduce it to the history close price
       history=history.close.unstack(level=0)
       #3. Iterate through the history tuple and update the mean and standard deviation with historical data
       for tuple in history.itertuples():
           self.spreadMean.Update(tuple[0], tuple[2]-tuple[1])
           self.spreadStd.Update(tuple[0], tuple[2]-tuple[1])

In the constructor (__init__) of the “PairsTradingAlphaModel(AlphaModel)” class, it is doing simple moving average. What quantity is moving averaged? the constructor doesn't have a parameter other than “self".