| Overall Statistics |
|
Total Trades 173 Average Win 0.02% Average Loss -0.01% Compounding Annual Return 0.335% Drawdown 0.200% Expectancy 0.540 Net Profit 0.337% Sharpe Ratio 0.621 Probabilistic Sharpe Ratio 30.265% Loss Rate 49% Win Rate 51% Profit-Loss Ratio 2.04 Alpha 0.002 Beta 0.003 Annual Standard Deviation 0.005 Annual Variance 0 Information Ratio -1.023 Tracking Error 0.349 Treynor Ratio 0.972 Total Fees $89.00 |
# from datetime import timedelta
# import numpy as np
# from QuantConnect.Securities.Option import OptionPriceModels
class CondorAlgorithm(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2019, 6, 30)
self.SetEndDate(2020, 6, 30)
self.SetCash(1000000)
equity = self.AddEquity("GOOG", Resolution.Minute)
equity.SetDataNormalizationMode(DataNormalizationMode.Raw)
self.SetSecurityInitializer(lambda x: x.SetMarketPrice(self.GetLastKnownPrice(x)))
self.underlyingsymbol = equity.Symbol
self.SetBenchmark(equity.Symbol)
def OnData(self,slice):
# slice.Contains(symbol)
if self.Portfolio[self.underlyingsymbol].Quantity != 0:
self.Liquidate()
if not self.Portfolio.Invested:
contracts = self.OptionChainProvider.GetOptionContractList(self.underlyingsymbol, self.Time.date())
if contracts:
self.TradeOptions(contracts, slice)
def TradeOptions(self,contracts, slice):
filtered_contracts = self.InitialFilter(self.underlyingsymbol, contracts, -50, 50, 0, 7)
# sorted the optionchain by expiration date and choose the furthest date
expiry = sorted(filtered_contracts,key = lambda x: x.ID.Date)[-1].ID.Date
# filter the call and put options from the contracts
call = [i for i in filtered_contracts if i.ID.OptionRight == 0 and i.ID.Date == expiry]
# put = [i for i in filtered_contracts if i.ID.OptionRight == 1 and i.ID.Date == expiry]
# sorted the contracts according to their strike prices
call_contracts = sorted(call,key = lambda x: x.ID.StrikePrice)
# put_contracts = sorted(put,key = lambda x: x.ID.StrikePrice)
# my long condor components
itm_call_lower = call_contracts[-15]
itm_call_upper = call_contracts[-10]
otm_call_lower = call_contracts[-5]
otm_call_upper = call_contracts[-1]
if itm_call_lower == 0:
return
if itm_call_upper == 0:
return
if otm_call_lower == 0:
return
if otm_call_upper == 0:
return
self.trade_contracts = [itm_call_lower,itm_call_upper,otm_call_lower,otm_call_upper]
for contract in self.trade_contracts:
self.AddOptionContract(contract, Resolution.Minute)
#for contract in self.trade_contracts:
# if not slice.ContainsKey(contract):
# return
self.Buy(itm_call_lower, 1) # Buy 1 ITM Call
self.Sell(itm_call_upper, 1) # Sell 1 ITM Call
self.Sell(otm_call_lower, 1) # Sell 1 OTM Call
self.Buy(otm_call_upper, 1) # Buy 1 OTM Call
def InitialFilter(self, underlyingsymbol, symbol_list, min_strike_rank, max_strike_rank, min_expiry, max_expiry):
# fitler 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]
# find the strike price of ATM option
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 + 1]
max_strike = strike_list[atm_strike_rank + max_strike_rank - 1]
except:
min_strike = strike_list[0]
max_strike = strike_list[-1]
filtered_contracts = [i for i in contract_list if i.ID.StrikePrice >= min_strike and i.ID.StrikePrice <= max_strike]
return filtered_contracts