Overall Statistics Total Trades 10 Average Win 0.00% Average Loss 0.00% Compounding Annual Return 2.669% Drawdown 0.000% Expectancy -0.327 Net Profit 0.288% Sharpe Ratio 6.548 Loss Rate 50% Win Rate 50% Profit-Loss Ratio 0.35 Alpha 0.002 Beta 0.026 Annual Standard Deviation 0.004 Annual Variance 0 Information Ratio -6.172 Tracking Error 0.137 Treynor Ratio 0.943 Total Fees \$5.00
```from datetime import timedelta

class ProtectiveCollarAlgorithm(QCAlgorithm):

def Initialize(self):
self.SetStartDate(2017, 4, 1)
self.SetEndDate(2017, 5, 10)
self.SetCash(10000000)
self.underlyingsymbol = equity.Symbol

# set our strike/expiry filter for this option chain
option.SetFilter(-10, +10, timedelta(0), timedelta(30))
# use the underlying equity as the benchmark
self.SetBenchmark(self.underlyingsymbol)

def OnData(self,slice):

if not self.Portfolio[self.underlyingsymbol].Invested:

options_invested = [x.Key for x in self.Portfolio if x.Value.Invested and x.Value.Type==SecurityType.Option]
if len(options_invested) == 0:
optionchain = slice.OptionChains
for i in slice.OptionChains:
chain = i.Value
contract_list = [x for x in chain]
if (slice.OptionChains.Count == 0) or (len(contract_list) == 0):
return

# choose the furthest expiration date within 30 days from now on
expiry = sorted(chain, key = lambda x: x.Expiry)[-1].Expiry
# filter the call options contracts
call = [x for x in chain if x.Right == 0 and x.Expiry == expiry]
# filter the put options contracts
put = [x for x in chain if x.Right == 1 and x.Expiry == expiry]
# sorted the call options by strike price and choose the deep OTM one in the list
self.otm_call = sorted(call, key = lambda x: x.Strike)[-1]
self.otm_put = sorted(put, key = lambda x: x.Strike)
if (self.otm_call is None) or (self.otm_put is None): return

self.Sell(self.otm_call.Symbol, 1) # sell the OTM call