| Overall Statistics |
|
Total Orders 4 Average Win 0.77% Average Loss 0% Compounding Annual Return -52.972% Drawdown 7.500% Expectancy -0.5 Start Equity 100000 End Equity 94442 Net Profit -5.558% Sharpe Ratio -3.576 Sortino Ratio -2.468 Probabilistic Sharpe Ratio 0.053% Loss Rate 50% Win Rate 50% Profit-Loss Ratio 0 Alpha -0.391 Beta -0.397 Annual Standard Deviation 0.119 Annual Variance 0.014 Information Ratio -3.491 Tracking Error 0.146 Treynor Ratio 1.071 Total Fees $2.00 Estimated Strategy Capacity $250000.00 Lowest Capacity Asset GOOCV WJVVXYW5VKH2|GOOCV VP83T1ZUHROL Portfolio Turnover 3.02% |
# region imports
from AlgorithmImports import *
# endregion
class ShortStrangleAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self.set_start_date(2017, 4, 1)
self.set_end_date(2017, 4, 30)
self.set_cash(100000)
option = self.add_option("GOOG")
self.symbol = option.symbol
option.set_filter(-5, 5, 0, 30)
def on_data(self, slice: Slice) -> None:
if self.portfolio.invested:
return
# Get the OptionChain
chain = slice.option_chains.get(self.symbol)
if not chain:
return
# Find options with the nearest expiry
expiry = max([x.expiry for x in chain])
contracts = [contract for contract in chain if contract.expiry == expiry]
# Order the OTM calls by strike to find the nearest to ATM
call_contracts = sorted([contract for contract in contracts
if contract.right == OptionRight.CALL and
contract.strike > chain.underlying.price],
key=lambda x: x.strike)
if not call_contracts:
return
# Order the OTM puts by strike to find the nearest to ATM
put_contracts = sorted([contract for contract in contracts
if contract.right == OptionRight.PUT and
contract.strike < chain.underlying.price],
key=lambda x: x.strike, reverse=True)
if not put_contracts:
return
call_strike = call_contracts[0].strike
put_strike = put_contracts[0].strike
short_strangle = OptionStrategies.short_strangle(self.symbol, call_strike, put_strike, expiry)
self.buy(short_strangle, 1)