| Overall Statistics |
|
Total Orders 27 Average Win 0.33% Average Loss -0.51% Compounding Annual Return -3.524% Drawdown 20.900% Expectancy -0.415 Start Equity 100000 End Equity 83575.12 Net Profit -16.425% Sharpe Ratio -1.431 Sortino Ratio -1.439 Probabilistic Sharpe Ratio 0.001% Loss Rate 65% Win Rate 35% Profit-Loss Ratio 0.66 Alpha -0.034 Beta -0.163 Annual Standard Deviation 0.043 Annual Variance 0.002 Information Ratio -0.994 Tracking Error 0.229 Treynor Ratio 0.374 Total Fees $17.00 Estimated Strategy Capacity $1700000.00 Lowest Capacity Asset IBM R735QTJ8XC9X Portfolio Turnover 0.08% Drawdown Recovery 305 |
# region imports
from AlgorithmImports import *
# endregion
from datetime import timedelta
class OptionsAlgorithm(QCAlgorithm):
def Initialize(self):
self.SetStartDate(self.end_date - timedelta(5*365))
self.SetCash(100_000)
self.syl = 'IBM'
self.settings.seed_initial_prices = True
equity = self.AddEquity(self.syl, Resolution.Minute)
equity.SetDataNormalizationMode(DataNormalizationMode.Raw)
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)
def OnData(self,slice):
if self.macd.IsReady:
if self.Portfolio[self.syl].Quantity == 0 and self.macd.Current.Value > self.macd.Signal.Current.Value:
self.Buy(self.syl,100)
# # <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()
def BuyPut(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 == 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]
self.AddOptionContract(self.contract, Resolution.Minute)
self.Buy(self.contract, 1)
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.AddOptionContract(self.contract, Resolution.Minute)
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