| Overall Statistics |
|
Total Trades 1 Average Win 0% Average Loss 0% Compounding Annual Return -8.321% Drawdown 0.800% Expectancy 0 Net Profit -0.348% Sharpe Ratio -2.402 Probabilistic Sharpe Ratio 15.014% Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha -0.24 Beta 0.135 Annual Standard Deviation 0.034 Annual Variance 0.001 Information Ratio -7.482 Tracking Error 0.168 Treynor Ratio -0.597 Total Fees $1.00 Estimated Strategy Capacity $11000000.00 Lowest Capacity Asset AAPL X22O820Y7OME|AAPL R735QTJ8XC9X |
from QuantConnect.Algorithm import *
from QuantConnect.Securities.Option import OptionPriceModels
class BasicTemplateOptionsFilterUniverseAlgorithm(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2019, 1, 1)
self.SetEndDate(2019, 1, 16)
self.SetCash(100000)
self.option = self.AddOption("AAPL")
self.option.SetFilter(-1, +1, 14, 60)
self.option.PriceModel = OptionPriceModels.BinomialTian()
self.SetWarmUp(30, Resolution.Daily)
self.done = False
def OnData(self,slice):
if self.IsWarmingUp:
return
for chain in slice.OptionChains:
for symbol, chain in slice.OptionChains.items():
if not self.done:
contracts = [c for c in chain if c.Right == OptionRight.Call]
sorted_contracts = sorted(contracts, key = lambda x: x.Expiry, reverse=True)
self.contract = sorted_contracts[0]
self.MarketOrder(self.contract.Symbol, 1)
self.done = True
else:
contract = [c for c in chain if str(c) == str(self.contract)]
if len(contract) == 0:
return
contract = contract[0]
self.Plot("Price", "Theoretical", contract.TheoreticalPrice)
self.Plot("Volatility", "Value", self.Securities[symbol.Underlying].VolatilityModel.Volatility)
self.Plot("Delta", "Value", contract.Greeks.Delta)