Hello everyone,

I am struggling to build a backtesting model that take in custom data to go Long/Short Straddle. So far it does the following steps :

  • Grabs Equity Tickers from a CSV (Done.) 
  • Adds them to the Universe depending on the Timestamp (Done.)
  • Calls OnSecuritiesChanged to call another function that is looking for Weekly ATM Calls and Puts and trades them (Done.)
So everything should be fine but unfortunately I get "Runtime Error: Collection was modified; enumeration operation may not execute." No Trades.. Just failure of the algorithm. My understanding is that when looking at Options it adds them to the universe and therefore OnSecuritiesChanged is called again and we end up in an infinite loop... How to avoid that since we HAVE TO add the equities and options in order to get prices and trade them ? Here is the backtesting, your help or some guidelines would be highly appreciated. Thank you in advance,Terence. import decimal as d
import numpy as np
import pandas as pd
import math
import datetime
import json

class DropboxBaseDataUniverseSelectionAlgorithm(QCAlgorithm):

def Initialize(self):

self.UniverseSettings.Resolution = Resolution.Minute;

self.SetStartDate(2019,1,8)
self.SetEndDate(2019,1,30)
self.SetCash(100000)

spy = self.AddEquity("SPY", Resolution.Minute)
spy.SetDataNormalizationMode(DataNormalizationMode.Raw)


self.AddUniverse(StockDataSource, "my-stock-data-source", self.stockDataSource)
self.Schedule.On(self.DateRules.EveryDay("SPY"), self.TimeRules.BeforeMarketClose("SPY", 10), self.EveryDayBeforeMarketClose)


self.UniverseSettings.DataNormalizationMode = DataNormalizationMode.Raw

def stockDataSource(self, data): # This will grab for each date and hour the different tickers in the csv and add them to the universe
list = []
for item in data:
for symbol in item["Symbols"]:
list.append(symbol)
#self.Debug(str(self.Time))
#self.Debug(str(list))
return list


def TradeOptions(self,contracts, ticker):
# run CoarseSelection method and get a list of contracts expire within 5 days from now on
# and the strike price between rank -1 to rank 1, rank being the step of the contract

filtered_contracts = self.CoarseSelection(ticker, contracts, -1, 1, 0, 15)

if len(filtered_contracts) >0:

expiry = sorted(filtered_contracts,key = lambda x: x.ID.Date, reverse=False)[0].ID.Date # Take the closest expiry

# filter the call options from the contracts expire on that date
call = [i for i in filtered_contracts if i.ID.Date == expiry and i.ID.OptionRight == 0]
# sorted the contracts according to their strike prices
call_contracts = sorted(call,key = lambda x: x.ID.StrikePrice)
self.call = call_contracts[0]

for i in filtered_contracts:
if i.ID.Date == expiry and i.ID.OptionRight == 1 and i.ID.StrikePrice ==call_contracts[0].ID.StrikePrice:
self.put = i

''' Before trading the specific contract, you need to add this option contract
AddOptionContract starts a subscription for the requested contract symbol '''


# self.call is the symbol of a contract
self.AddOptionContract(self.call, Resolution.Minute)
self.AddOptionContract(self.put, Resolution.Minute)

if not self.Portfolio.Invested:
self.SetHoldings(self.call.Value, 0.1)
self.SetHoldings(self.put.Value ,0.1)

# Some Logging
#self.Debug("Strike Price : "+str(self.call.ID.StrikePrice))
#self.Debug("Expiry : "+str(self.call.ID.Date))
#self.Debug("Call Mid-Point : "+str(self.Securities[self.call].Price))

#self.Debug("IV : "+str(self.call.ImpliedVolatility))


else:
pass

def OnSecuritiesChanged(self, changes):
self._changes = changes

for security in changes.AddedSecurities:

self.Debug(security)
self.Debug(security.Symbol.SecurityType)

if security.Symbol.SecurityType == 1:
#self.SetHoldings(security.Symbol, 0.1)
stk = self.AddEquity(security.Symbol.Value, Resolution.Minute)
stk.SetDataNormalizationMode(DataNormalizationMode.Raw)

contracts = self.OptionChainProvider.GetOptionContractList(security.Symbol, self.Time.date()) # Get list of strikes and expiries
self.TradeOptions(contracts, security.Symbol.Value) # Select the right strikes/expiries and trade



def EveryDayBeforeMarketClose(self):
#self.Debug("############## Closing Position " + str(self.Time.date()) + " " + str(self.Time) + "############## ")
self.Liquidate()
self.Debug("Positions closed")

def CoarseSelection(self, underlyingsymbol, symbol_list, min_strike_rank, max_strike_rank, min_expiry, max_expiry):

''' This method implements the coarse selection of option contracts
according to the range of strike price and the expiration date,
this function will help you better choose the options of different moneyness '''


# filter the contracts based on the expiry range
contract_list = [i for i in symbol_list if min_expiry <= (i.ID.Date.date() - self.Time.date()).days < max_expiry]
self.Debug("Ticker Und : " + str(underlyingsymbol))
self.Debug("Nb of contract found : " + str(len(contract_list)))
self.Debug("Underlying price : "+str(self.Securities[underlyingsymbol].Price))

# find the strike price of ATM option
# It seems like sometimes OptionChainProvider.GetOptionContractList is bugging and returns nothing, so let's try/except
try :
atm_strike = sorted(contract_list,
key = lambda x: abs(x.ID.StrikePrice - self.Securities[underlyingsymbol].Price))[0].ID.StrikePrice
strike_list = sorted(set([i.ID.StrikePrice for i in contract_list]))

# find the index of ATM strike in the sorted strike list
atm_strike_rank = strike_list.index(atm_strike)
try:
min_strike = strike_list[atm_strike_rank + min_strike_rank]
max_strike = strike_list[atm_strike_rank + max_strike_rank]
except:
min_strike = strike_list[0]
max_strike = strike_list[-1]
# filter the contracts based on the range of the strike price rank
filtered_contracts = [i for i in contract_list if i.ID.StrikePrice >= min_strike and i.ID.StrikePrice <= max_strike]

except:
self.Debug("NO CONTRACT RETURNED -------")
filtered_contracts = None


return filtered_contracts

class StockDataSource(PythonData):

def GetSource(self, config, date, isLiveMode):
url = "https://www.dropbox.com/s/2az14r5xbx4w5j6/daily-stock-picker-live.csv?dl=1" if isLiveMode else \
"https://www.dropbox.com/s/ofzgxsp2b27pkri/quantconnect_triggers.csv?dl=1"

return SubscriptionDataSource(url, SubscriptionTransportMedium.RemoteFile)

def Reader(self, config, line, date, isLiveMode):
#if not (line.strip() and line[0].isdigit()): return None

stocks = StockDataSource()
stocks.Symbol = config.Symbol

csv = line.rstrip(',').split(',') # rstrip is essential because quantconnect throws an empty element error (extra commas at the end of the csv)
if isLiveMode:
stocks.Time = date
stocks["Symbols"] = csv
else:
stocks.Time = datetime.datetime.combine(datetime.datetime.strptime(csv[0], "%Y%m%d"),
datetime.time(9, 31))
stocks["Symbols"] = csv[1:]
return stocks