| Overall Statistics |
|
Total Trades 2 Average Win 0.78% Average Loss 0% Compounding Annual Return 17.026% Drawdown 1.300% Expectancy 0 Net Profit 3.981% Sharpe Ratio 3.626 Probabilistic Sharpe Ratio 85.700% Loss Rate 0% Win Rate 100% Profit-Loss Ratio 0 Alpha -0.038 Beta 0.273 Annual Standard Deviation 0.048 Annual Variance 0.002 Information Ratio -5.841 Tracking Error 0.103 Treynor Ratio 0.635 Total Fees $1.00 Estimated Strategy Capacity $3500000.00 |
from QuantConnect.Algorithm import *
from QuantConnect.Securities.Option import OptionPriceModels
class BasicTemplateOptionsFilterUniverseAlgorithm(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2019, 1, 1)
self.SetEndDate(2019, 4, 1)
self.SetCash(100000)
self.option = self.AddOption("AAPL")
self.option.PriceModel = OptionPriceModels.CrankNicolsonFD()
self.option.SetFilter(-3, +3, 1, 31)
self.SetWarmUp(30, Resolution.Daily)
def OnData(self,slice):
if self.IsWarmingUp or self.Portfolio.Invested:
return
for symbol, chain in slice.OptionChains.items():
contracts = [c for c in chain if c.Right == OptionRight.Put]
if len(contracts) == 0:
self.Log("No put contracts")
return
sorted_contracts = sorted(contracts, key = lambda x: x.Expiry)
# Select contracts with the closest expiry
closest_expiry_contracts = []
for contract in sorted_contracts:
if contract.Expiry == sorted_contracts[0].Expiry:
closest_expiry_contracts.append(contract)
else:
break
# Sort remaining contracts by Delta
sorted_by_delta = sorted(closest_expiry_contracts, key=lambda x: x.Greeks.Delta)
self.Log(f"Delta: {sorted_by_delta[0].Greeks.Delta}")
# Sell put option
self.MarketOrder(sorted_by_delta[0].Symbol, -1)