| Overall Statistics |
|
Total Orders 4998 Average Win 0.00% Average Loss 0.00% Compounding Annual Return -65.022% Drawdown 13.700% Expectancy -0.235 Start Equity 2000000 End Equity 1904505.61 Net Profit -4.775% Sharpe Ratio -0.272 Sortino Ratio -0.461 Probabilistic Sharpe Ratio 37.625% Loss Rate 51% Win Rate 49% Profit-Loss Ratio 0.55 Alpha -1.765 Beta 3.323 Annual Standard Deviation 0.666 Annual Variance 0.444 Information Ratio -1.206 Tracking Error 0.545 Treynor Ratio -0.054 Total Fees $6834.40 Estimated Strategy Capacity $36000.00 Lowest Capacity Asset QQQ 31TIRIE31K486|QQQ RIWIV7K5Z9LX Portfolio Turnover 1015.12% |
from AlgorithmImports import * import pandas as pd import numpy as np class FormalAsparagusFrog(QCAlgorithm): def Initialize(self): self.SetStartDate(2021, 12, 1) self.SetEndDate(2021, 12, 17) self.SetCash(2000000) equity = self.AddEquity('QQQ', Resolution.Minute) option = self.AddOption('QQQ', Resolution.Minute) self.symbol = option.Symbol self.stock = equity.Symbol option.SetFilter(-30, 30, 0, 500) self.trade = True self.contract = None self.size = 203 self.sign = -1 self.highest_pnl = 0 # Track the highest PnL def OnData(self, slice: Slice) -> None: if self.trade: chain = slice.OptionChains.get(self.symbol) if chain: # Change to target put options (Right == 1 for puts) contract_list = [x for x in chain if x.Expiry == DateTime(2021, 12, 17) and x.Right == 1 and x.Strike <= x.UnderlyingLastPrice] self.highest_put = sorted(contract_list, key=lambda x: x.Strike, reverse=True)[0].Strike self.contract = [contract for contract in contract_list if contract.Strike == self.highest_put][0] # Calculate historical volatility based on the last 25 trading days daily_returns = self.History(self.stock, 25, Resolution.Daily)['close'].pct_change()[1:] self.sign = -1 volatility = daily_returns.std() * 252**0.5 # Annualized volatility based on 252 trading days self.Log(volatility) self.Log(self.contract.ImpliedVolatility) # Decide to go long or short based on implied volatility and historical volatility if volatility > self.contract.ImpliedVolatility: self.sign = 1 # Check available margin before placing the trade margin_remaining = self.Portfolio.MarginRemaining required_margin = self.contract.LastPrice * self.size # Use LastPrice for margin calculation if margin_remaining > required_margin: self.trade = False self.size = self.size * self.sign self.MarketOrder(self.contract.Symbol, self.size) self.MarketOrder(self.stock, 100 * self.size * self.contract.Greeks.Delta) # Delta for puts is positive when short self.Debug(str(self.contract.Greeks.Delta)) self.previous = self.contract.Greeks.Delta else: chain = slice.OptionChains.get(self.symbol) if chain: # Change to target put options (Right == 1 for puts) contract_list = [x for x in chain if x.Expiry == DateTime(2021, 12, 17) and x.Right == 1 and x.Strike <= x.UnderlyingLastPrice] self.highest_put = sorted(contract_list, key=lambda x: x.Strike, reverse=True)[0].Strike self.contract = [contract for contract in contract_list if contract.Strike == self.highest_put][0] self.MarketOrder(self.stock, 100 * self.size * (self.contract.Greeks.Delta - self.previous)) # Adjust for put's delta self.previous = self.contract.Greeks.Delta # Track highest PnL current_pnl = self.Portfolio.TotalProfit if current_pnl > self.highest_pnl: self.highest_pnl = current_pnl self.Debug(f"New highest PnL: {self.highest_pnl}")
