Overall Statistics |
Total Orders 4 Average Win 0% Average Loss -0.92% Compounding Annual Return 96.758% Drawdown 1.300% Expectancy -1 Start Equity 100000 End Equity 105264 Net Profit 5.264% Sharpe Ratio 5.254 Sortino Ratio 30.643 Probabilistic Sharpe Ratio 96.479% Loss Rate 100% Win Rate 0% Profit-Loss Ratio 0 Alpha 0.574 Beta 0.426 Annual Standard Deviation 0.116 Annual Variance 0.013 Information Ratio 4.437 Tracking Error 0.118 Treynor Ratio 1.43 Total Fees $2.00 Estimated Strategy Capacity $150000.00 Lowest Capacity Asset GOOCV WJVVXYW5VKH2|GOOCV VP83T1ZUHROL Portfolio Turnover 3.08% |
# region imports from AlgorithmImports import * # endregion class LongStrangleAlgorithm(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 long_strangle = OptionStrategies.strangle(self.symbol, call_strike, put_strike, expiry) self.buy(long_strangle, 1)