Elegant method for saving opening price for multiple equities?

The code didn't attach, here is the current state I was referring to above. 

class MeasuredTanTermite(QCAlgorithm):

    stopMarketTicket = None
    stopMarketFillTime = datetime.min

    def Initialize(self):
        self.SetStartDate(2022, 7, 20)
        #self.SetEndDate(2022, 8, 25) 
        self.SetCash(1000000)
        self.rebalanceTime = datetime.min
        self.AddUniverse(self.CoarseSelectionFilter, self.FineSelectionFilter)
        self.UniverseSettings.Resolution = Resolution.Minute #resolution of the securities in the universe, default is minute
        self.AddEquity("SPY")
        self.Data = {}
        self.AddRiskManagement(TrailingStopRiskManagementModel(0.03))
        
    def OnData(self, data):
        for symbol in self.Data.keys():
            symbolData = self.Data[symbol]

            if not symbolData.IsReady: 
                continue

        
            if self.Time.hour == 9 and self.Time.minute == 31:
                self.openingBar = self.Securities[symbol].Open
                #self.Debug("Market Open " + str(openingBar))
                   
            orderTicket = self.MarketOrder(symbol, 100)
                    
      def CoarseSelectionFilter(self, coarse):
		#stuff
		pass

    def FineSelectionFilter(self, fine):
		#stuff
		pass

    def OnSecuritiesChanged(self, changes):
        for security in changes.AddedSecurities:
            symbol = security.Symbol
            if symbol not in self.Data:
                self.Data[symbol] = SymbolData(self, symbol)
        
        for security in changes.RemovedSecurities:
            symbol = security.Symbol
            if symbol in self.Data:
                symbolData = self.Data.pop(symbol, None)
                self.SubscriptionManager.RemoveConsolidator(symbol, symbolData.consolidator) # Remove subcription for symbols removed from universe

class SymbolData:
    def __init__(self, algorithm, symbol):
        self.algorithm = algorithm
        self.symbol = symbol
        self.Bars = RollingWindow[TradeBar](10) # Rolling window for data bars
        self.consolidator = TradeBarConsolidator(timedelta(days=1))
        self.consolidator.DataConsolidated += self.OnDataConsolidated
        algorithm.SubscriptionManager.AddConsolidator(symbol, self.consolidator)
        self.openingBar = None
    
    def OnDataConsolidated(self, sender, bar):
        self.Bars.Add(bar)
    
    @property
    def IsReady(self):
        return self.Bars.IsReady

Hi Justin

We suggest using an auto-updating Identity indicator with Field.Open selector:

self.open_prices = {}

def OnSecuritiesChanged(self, changes):
    for security in changes.AddedSecurities:
        symbol = security.Symbol
        self.open_prices[symbol] = self.Identity(symbol, Resolution.Daily, Field.Open)	# say we want daily open price
        
    for security in changes.RemovedSecurities:
        open_price_indicator = self.open_prices.pop(symbol, None)
        if open_price_indicator:
            open_price_indicator.Reset()    # free memory
            
def OnData(self, slice):
    for symbol, open_price_indicator in self.open_prices.items():
        self.Log(f"Today's opening price for {symbol} :: {open_price_indicator.Current.Value}")

Best
Louis

Hi, Louis Szeto but with Daily resolution the indicator will get current day's bar only at Midnight, isn't it? That's quite a delay to get the opening price. In general I think the Justin's approach is good enough, if it works. It may not work for non-liquid stocks if they didn't have any trades before 9:31 though. 

Thanks Louis, I tried your suggestion and implemented it as follows with backtest below. 

A few oddities upon doing a quality check: I see the opening prices are different compared to Etrade data. Below are some checks against a few tickers in the backtest. The Etrade opening price is from daily historical data. How large is the slice (in terms of time) does QC use for opening price (tick, minute, etc.)?

7/20/22, XPEV: $26.59 Etrade, QC backtest $28.00

7/22/22, TWLO: $91.72 Etrade data, QC backtest $92.41

7/29/22, TTD: $43.39 Etrade data, QC backtest $45.93

Another question is why my algorithm sells so fast, my trailing stop isn't being hit but it repeatedly buys and sells the same ticker each minute. A max of 1 buy order per day per ticker, otherwise, it should wait until the next day. 

For background, the algo strategy is a placeholder/dummy strategy designed to watch for higher daily highs and then buy the ticker, just once per day. 

Hi Justin

The auto-update of the bar is done after OnData. Hence, there is discrepancy at the point of your debug message. You might move the whole trading and debug logic on a indicator update event handler:

self.indicator.Updated = self.OnUpdate

def OnUpdate(self, sender, updated):
    # trade and debug here

Best
Louis

Ok interesting, that would explain it. I instead chose to simply include a check for opening price in a scheduled event occurring one minute after open. I'll keep the above methods in mind for the future. Thanks Louis.