First time here so any and all help is welcome :)

1) When trying to use VWAP function in this algo I get the following error: "Runtime Error: NotSupportedException : VolumeWeightedAveragePriceIndicator does not support Update(DateTime, decimal) method overload. Use Update(TradeBar) instead." but can't figure out how to fix it.

2) How would I add a candlestick pattern such as the Doji following the same format as other indicators.


Thanks in advance!!



class MultipleSymbolConsolidationAlgorithm(QCAlgorithm): # Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized. def Initialize(self): #Initial investment and backtest period self.SetStartDate(2019,1,1) self.SetEndDate( - timedelta(1)) self.SetCash(100000) #Brokerage Model self.SetBrokerageModel(BrokerageName.InteractiveBrokersBrokerage) # This is the period of bars we'll be creating BarPeriod = TimeSpan.FromMinutes(20) # This is the period of our rsi indicators RSIPeriod = 30 # This is the period of our vwap indicators VWAPPeriod = 10 # This is the period of our sma indicators SimpleMovingAveragePeriod = 30 # This is the period of our last price SimpleMovingAverageonePeriod = 1 # This is the period of our TEma indicators TripleExponentialMovingAveragePeriod = 5 # This is the period of our ema indicators ExponentialMovingAveragePeriod = 10 # This is the period of our tema indicators TripleExponentialMovingAveragePeriod = 5 # This is the number of consolidated bars we'll hold in symbol data for reference RollingWindowSize = 30 # Holds all of our data keyed by each symbol self.Data = {} # Contains all of our equity symbols EquitySymbols = ["QQQ"] # initialize our equity data for symbol in EquitySymbols: equity = self.AddEquity(symbol) self.Data[symbol] = SymbolData(equity.Symbol, BarPeriod, RollingWindowSize) for symbol in EquitySymbols: if self.Portfolio[symbol].Invested: self.Schedule.On(self.DateRules.EveryDay(symbol), self.TimeRules.BeforeMarketClose(symbol, 15)) self.Liquidate(symbol) # loop through all our symbols and request data subscriptions and initialize indicator for symbol, symbolData in self.Data.items(): # define the indicator symbolData.VWAP = VolumeWeightedAveragePriceIndicator(self.CreateIndicatorName(symbol, "VWAP" + str(VWAPPeriod), Resolution.Minute), VWAPPeriod) # define the indicator symbolData.SMA = SimpleMovingAverage(self.CreateIndicatorName(symbol, "SMA" + str(SimpleMovingAveragePeriod), Resolution.Minute), SimpleMovingAveragePeriod) # define the indicator symbolData.RSI = RelativeStrengthIndex(self.CreateIndicatorName(symbol, "RSI" + str(RSIPeriod), Resolution.Minute), RSIPeriod, MovingAverageType.Simple) # define the indicator symbolData.SMAone = SimpleMovingAverage(self.CreateIndicatorName(symbol, "SMA" + str(SimpleMovingAverageonePeriod), Resolution.Minute), SimpleMovingAverageonePeriod) # define the indicator symbolData.TEMA = TripleExponentialMovingAverage(self.CreateIndicatorName(symbol, "TEMA" + str(TripleExponentialMovingAveragePeriod), Resolution.Minute), TripleExponentialMovingAveragePeriod) # define the indicator symbolData.EMA = ExponentialMovingAverage(self.CreateIndicatorName(symbol, "EMA" + str(ExponentialMovingAveragePeriod), Resolution.Minute), ExponentialMovingAveragePeriod) # define a consolidator to consolidate data for this symbol on the requested period if symbolData.Symbol.SecurityType == SecurityType.Equity: consolidator = TradeBarConsolidator(BarPeriod) elif symbolData.Symbol == symbolData.VWAP: consolidator = TradeBarConsolidator(BarPeriod) else: consolidator = QuoteBarConsolidator(BarPeriod) # write up our consolidator to update the indicator consolidator.DataConsolidated += self.OnDataConsolidated # we need to add this consolidator so it gets auto updates self.SubscriptionManager.AddConsolidator(symbolData.Symbol, consolidator) def OnDataConsolidated(self, sender, bar): self.Data[bar.Symbol.Value].SMA.Update(bar.Time, bar.Close) self.Data[bar.Symbol.Value].SMAone.Update(bar.Time, bar.Close) self.Data[bar.Symbol.Value].RSI.Update(bar.Time, bar.Close) self.Data[bar.Symbol.Value].TEMA.Update(bar.Time, bar.Close) self.Data[bar.Symbol.Value].EMA.Update(bar.Time, bar.Close) self.Data[bar.Symbol.Value].VWAP.Update(bar.Time, bar.Close) self.Data[bar.Symbol.Value].Bars.Add(bar) # OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here. # Argument "data": Slice object, dictionary object with your stock data def OnData(self,data): # loop through each symbol in our structure for symbol in self.Data.keys(): symbolData = self.Data[symbol] stopLossPercent = .98 profitTargetPercent = 1.05 # this check proves that this symbol was JUST updated prior to this OnData function being called if symbolData.IsReady() and symbolData.WasJustUpdated(self.Time): if not self.Portfolio[symbol].Invested: if symbolData.SMAone > symbolData.TEMA: if symbolData.SMAone > symbolData.VWAP: self.Liquidate() openOrders = self.Transactions.GetOpenOrders() if len(openOrders)> 0: for x in openOrders: self.Transactions.CancelOrder(x.Id) posSize = self.CalculateOrderQuantity(symbol, 0.9) self.MarketOrder(symbol, posSize) self.StopLimitOrder(symbol, -posSize, float(symbolData.SMAone.Current.Value) * stopLossPercent, float(symbolData.SMAone.Current.Value) * profitTargetPercent) # End of a trading day event handler. This method is called at the end of the algorithm day (or multiple times if trading multiple assets). # Method is called 10 minutes before closing to allow user to close out position. def OnEndOfDay(self): i = 0 for symbol in sorted(self.Data.keys()): symbolData = self.Data[symbol] # we have too many symbols to plot them all, so plot every other i += 1 if symbolData.IsReady() and i%2 == 0: self.Plot(symbol, symbol, symbolData.SMA.Current.Value) class SymbolData(object): def __init__(self, symbol, barPeriod, windowSize): self.Symbol = symbol # The period used when population the Bars rolling window self.BarPeriod = barPeriod # A rolling window of data, data needs to be pumped into Bars by using Bars.Update( tradeBar ) and can be accessed like: # mySymbolData.Bars[0] - most first recent piece of data # mySymbolData.Bars[5] - the sixth most recent piece of data (zero based indexing) self.Bars = RollingWindow[IBaseDataBar](windowSize) # The simple moving average indicator for our symbol self.SMA = None # Returns true if all the data in this instance is ready (indicators, rolling windows, ect...) def IsReady(self): return self.Bars.IsReady and self.SMA.IsReady # Returns true if the most recent trade bar time matches the current time minus the bar's period, this # indicates that update was just called on this instance def WasJustUpdated(self, current): return self.Bars.Count > 0 and self.Bars[0].Time == current - self.BarPeriod