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