Hi everyone, so the basic premise of what this strategy is supposed to be doing is this:

On days SPY is down, buy stocks that are up at 9:45am, and sell everything at 3:45pm. But for some reason QuantConnect buys and sells stock at exact same price? The quote is the same. My code is attached below, I'm hoping someone can provide insight on what I'm doing wrong. Thank you.

"""
Buy 20 stocks showing strength vs SPY. Buy them. Liquidate at EOD

"""
class JumpingLightBrownScorpion(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2018, 1, 1)  # Set Start Date
        self.SetCash(100000) # Set Cash
        
        self.stocks = ["AAPL", "MSFT"] # stocks I'm interested in
            
        # Dictionary to hold Symbol Data
        self.symbolData = {}

        for stock in self.stocks:
            # Add equity data
            symbol = self.AddEquity(stock, Resolution.Daily).Symbol
            # Create symbol data for respective symbol
            self.symbolData[symbol] = SymbolData(self, symbol)
        
        self.spy = self.AddEquity("SPY", Resolution.Minute).Symbol # intialize SPY
        self.SetWarmUp(200, Resolution.Daily) # warm up indicators
        self.yest_close = self.SMA(self.spy, 1, Resolution.Daily, Field.Close) # set SMA with close price as field
        
        

    def OnData(self, data):
        if self.IsWarmingUp or not self.yest_close.IsReady or not len(data.Bars) > 0: # if indicators warming up, not ready, or no data bars then stop
            return
        
        # Make sure indicators and rolling windows are ready
        for symbol in self.symbolData.values():
            if not symbol.IsReady:
                return
        
        
        if self.Time.hour == 9 and self.Time.minute == 45: # if it's 9:45am eastern
            price = self.Securities[self.spy].Price        # set price to SPYs price
            yest_close = self.yest_close.Current.Value     # set yesterday's closing price to variable
            
            if price < yest_close:# If SPY fell from yesterday,
                selected = []
                for symbol, value in self.symbolData.items():
                    # If the SMA today is higher than SMA yesterday
                    sma_value = str(value.smaWindow[1])
                    sma_value = float((sma_value.split("-")[3]).strip())
                    if self.Securities[symbol].Price > sma_value:
                        selected.append(symbol)
                for stock in selected:
                    self.SetHoldings(stock,1/len(selected))
                
                        
        if self.Time.hour == 15 and self.Time.minute == 45: # if it's 3:45pm eastern, liquidate portfolio
            self.Liquidate()
            
class SymbolData:
    
    def __init__(self, algorithm, symbol):
        self.algorithm = algorithm
        self.symbol = symbol
        # Define our indicator
        self.sma = algorithm.SMA(symbol, 1, Resolution.Daily, Field.Close)
        # Define our rolling window to hold indicator points
        self.smaWindow = RollingWindow[IndicatorDataPoint](2)
        # Set our event handler
        self.sma.Updated += self.OnSMAUpdated
        
    def OnSMAUpdated(self, sender, updated):
        # Add updated indicator data to rolling window
        self.smaWindow.Add(updated)
        
    @property
    def IsReady(self):
        return self.sma.IsReady and self.smaWindow.IsReady

 

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