Overall Statistics Total Trades 566 Average Win 0.24% Average Loss -0.22% Compounding Annual Return -96.265% Drawdown 24.400% Expectancy -0.438 Net Profit -24.162% Sharpe Ratio -4.379 Probabilistic Sharpe Ratio 0% Loss Rate 73% Win Rate 27% Profit-Loss Ratio 1.09 Alpha -0.935 Beta -0.055 Annual Standard Deviation 0.216 Annual Variance 0.046 Information Ratio -4.47 Tracking Error 0.247 Treynor Ratio 17.197 Total Fees \$707.50
from datetime import timedelta

class OptionsAlgorithm(QCAlgorithm):

# Order ticket for our stop order, Datetime when stop order was last hit
stopMarketTicket = None
stopMarketOrderFillTime = datetime.min
highestSPYPrice = 0

def Initialize(self):
self.SetStartDate(2015, 11, 1)
self.SetEndDate(2015, 12, 1)
self.SetCash(20000)
self.syl = "SPY"
self.spy = "SPY"
equity.SetDataNormalizationMode(DataNormalizationMode.Raw)

# create a XX-period exponential moving average; since this is minute, may have to multiply by 2
self.fast = self.EMA("SPY", 26, Resolution.Minute);

# create a XX-period exponential moving average; since this is minute, may have to multiply by 2
self.slow = self.EMA("SPY", 97, Resolution.Minute);

# self.macd = self.MACD(self.syl, 12, 26, 9, MovingAverageType.Exponential, Resolution.Daily)
self.underlyingsymbol = equity.Symbol
# use the underlying equity as the benchmark
self.SetBenchmark(equity.Symbol)

# self.hist = RollingWindow[float](390*22)

def OnData(self,slice):

'''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.'''

# buying puts; needs to be in a loop; will need to initiate options chain here; may need to incorporate slope
# will need to check and see if holding any positions self.Portfolio[self.BuyPut()].Quantity == 0 and
#self.Securities[self.vix].Price > 30 and not self.buy_spy

if (self.Portfolio.Invested == False) and (self.fast.Current.Value < self.slow.Current.Value) and (self.Securities[self.spy].Price >= (self.fast.Current.Value - 0.05)):

#if (self.fast.Current.Value > self.slow.Current.Value):
#    self.Liquidate()

if (self.Securities["SPY"].Close < self.highestSPYPrice) or (self.Securities[self.spy].Price < (self.fast.Current.Value - 0.20)) or (self.Securities[self.spy].Close >= (self.fast.Current.Value + 0.20)):

#2. Save the new high to highestSPYPrice; then update the stop price to 90% of highestSPYPrice
self.highestSPYPrice = self.Securities["SPY"].Close
#updateFields = UpdateOrderFields()
#updateFields.StopPrice = self.highestSPYPrice * 0.9
#self.stopMarketTicket.Update(updateFields)
self.Liquidate()

#if (self.fast.Current.Value > self.slow.Current.Value):

#    if self.Portfolio[self.syl].Quantity == 0 and self.fast.Current.Value > self.slow.Current.Value:

# # <1> if there is a MACD short signal, liquidate the stock
# elif self.Portfolio[self.syl].Quantity > 0 and self.macd.Current.Value < self.macd.Signal.Current.Value:
#     self.Liquidate()

# # <2> if today's close < lowest close of last 30 days, liquidate the stock
# history = self.History([self.syl], 30, Resolution.Daily).loc[self.syl]['close']
# self.Plot('Stock Plot','stop loss frontier', min(history))
# if self.Portfolio[self.syl].Quantity > 0:
#     if self.Securities[self.syl].Price < min(history):
#         self.Liquidate()

# <3> if there is a MACD short signal, trade the options
#    elif self.Portfolio[self.syl].Quantity > 0 and self.macd.Current.Value < self.macd.Signal.Current.Value:
#        try:
#            if self.Portfolio[self.syl].Invested and not self.Portfolio[self.contract].Invested \
#              and self.Time.hour != 0 and self.Time.minute == 1:
#                self.SellCall()
#        except:
#            if self.Portfolio[self.syl].Invested and self.Time.hour != 0 and self.Time.minute == 1:
#                self.SellCall()

contracts = self.OptionChainProvider.GetOptionContractList(self.underlyingsymbol, self.Time.date())
if len(contracts) == 0: return
filtered_contracts = self.InitialFilter(self.underlyingsymbol, contracts, -1, 1, 0, 14)
put = [x for x in filtered_contracts if x.ID.OptionRight == 1]
# sorted the contracts according to their expiration dates and choose the ATM options
contracts = sorted(sorted(put, key = lambda x: abs(self.Securities[self.syl].Price - x.ID.StrikePrice)),
key = lambda x: x.ID.Date, reverse=True)
self.contract = contracts[0]

#    contracts = self.OptionChainProvider.GetOptionContractList(self.underlyingsymbol, self.Time.date())
#    if len(contracts) == 0: return
#    filtered_contracts = self.InitialFilter(self.underlyingsymbol, contracts, -3, 3, 0, 30)
#    call = [x for x in filtered_contracts if x.ID.OptionRight == 1]
# sorted the contracts according to their expiration dates and choose the ATM options
#    contracts = sorted(sorted(call, key = lambda x: abs(self.Securities[self.syl].Price - x.ID.StrikePrice)),
#                                    key = lambda x: x.ID.Date, reverse=True)
#    self.contract = contracts[0]

def SellCall(self):
contracts = self.OptionChainProvider.GetOptionContractList(self.underlyingsymbol, self.Time.date())
if len(contracts) == 0: return
filtered_contracts = self.InitialFilter(self.underlyingsymbol, contracts, -3, 3, 0, 30)
put = [x for x in filtered_contracts if x.ID.OptionRight == 0]
# sorted the contracts according to their expiration dates and choose the ATM options
contracts = sorted(sorted(put, key = lambda x: abs(self.Securities[self.syl].Price - x.ID.StrikePrice)),
key = lambda x: x.ID.Date, reverse=True)
self.contract = contracts[0]
self.Sell(self.contract, 1)

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

''' This method is an initial filter of option contracts
according to the range of strike price and the expiration date '''

if len(symbol_list) == 0 : return
# 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]
max_strike = strike_list[atm_strike_rank + max_strike_rank]
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