QuantConnect Community

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