Hello,

I am struggling with learning how to warm up an indicator when using universe selection. My test code and the error message it yields are given below. I would just attach the backtest, but apparently I am not able to do that since it results in a runtime error. It seems to dislike the "loc" attribute in line 36 for some reason. Any suggestions would be appreciated because I am at a loss as to how I can fix this.

 

2010-01-01 00:00:00 : Runtime Error: AttributeError : '0, Culture=neutral, PublicKeyToken=null]]' object has no attribute 'loc' AttributeError : '0, Culture=neutral, PublicKeyToken=null]]' object has no attribute 'loc'

 

from Execution.ImmediateExecutionModel import ImmediateExecutionModel
from Portfolio.EqualWeightingPortfolioConstructionModel import EqualWeightingPortfolioConstructionModel
from Risk.MaximumDrawdownPercentPerSecurity import MaximumDrawdownPercentPerSecurity
from Selection.QC500UniverseSelectionModel import QC500UniverseSelectionModel

class SimpleRSITestQC500Universe(QCAlgorithm):

def Initialize(self):
self.SetStartDate(2010, 1, 1) # Set Start Date
self.SetEndDate(2010, 2, 28) # Set End Date
self.SetCash(100000) # Set Strategy Cash
self.SetExecution(ImmediateExecutionModel())
self.SetPortfolioConstruction(EqualWeightingPortfolioConstructionModel())
self.SetRiskManagement(MaximumDrawdownPercentPerSecurity(0.05))
symbols = [ Symbol.Create("SPY", SecurityType.Equity, Market.USA)]#, Symbol.Create("GE", SecurityType.Equity, Market.USA), Symbol.Create("BA", SecurityType.Equity, Market.USA) ]
self.SetUniverseSelection(ManualUniverseSelectionModel(symbols))
self.AddAlpha(RsiAlphaModelTest())

class RsiAlphaModelTest(AlphaModel):

def __init__(self, period = 14, resolution = Resolution.Daily):
self.period = period
self.resolution = resolution
self.insightPeriod = Time.Multiply(Extensions.ToTimeSpan(resolution), period)
self.rsiData ={}
resolutionString = Extensions.GetEnumString(resolution, Resolution)
self.Name = '{}({},{})'.format(self.__class__.__name__, period, resolutionString)

def OnSecuritiesChanged(self, algorithm, changes):
addedSymbols = [X.Symbol for X in changes.AddedSecurities]
[algorithm.Debug(str(X) + ' added to universe at ' + str(algorithm.UtcTime)) for X in addedSymbols]
#warmUpData = algorithm.History([X.Symbol for X in changes.AddedSecurities],self.period, self.resolution)
warmUpData = algorithm.History(self.period, self.resolution)
for symbol in addedSymbols:
self.rsiData[symbol] = algorithm.RSI(symbol, self.period, MovingAverageType.Wilders, self.resolution)
for time, row in warmUpData.loc[symbol].iterrows():
self.rsiData[symbol].Update(time, row["close"])
algorithm.Debug("Debug message OnSecuritiesChanged for:" + str(symbol) + " " + str(self.rsiData[symbol]))
#[algorithm.Debug("Time: " + str(X.Time) + " , Close:" + str(X.Bars["GE"].Close)) for X in WarmUpData]

def Update(self, algorithm, data):
insights = []
prior_rsiData = self.rsiData
for symbol in self.rsiData.keys():
#self.rsiData[symbol] = algorithm.RSI(symbol, self.period, MovingAverageType.Wilders, self.resolution)
#if self.rsiData[symbol] <= 34.0:
algorithm.Debug("Debug message for:" + str(symbol) + " " + str(self.rsiData[symbol]))
#prior_rsiData[symbol] <= 34.0 and self.rsiData[symbol] >= prior_rsiData[symbol] + 1.0:
#insights.append(Insight.Price(symbol, self.insightPeriod, InsightDirection.Up))
# elif prior_rsiData[symbol] >= 70 and self.rsiData[symbol] <= prior_rsiData[symbol] - 1:
# #insights.append(Insight.Price(symbol, self.insightPeriod, InsightDirection.Down))
# algorithm.Debug("Insight down for:" + symbol)
return insights

. Many thanks.