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.SetEndDate( - timedelta(1))

#Brokerage Model

# 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))

# 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)

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)


# 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:


openOrders = self.Transactions.GetOpenOrders()
if len(openOrders)> 0:
for x in openOrders:

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