Overall Statistics |
Total Trades 1 Average Win 0% Average Loss 0% Compounding Annual Return 0% Drawdown 0% Expectancy 0 Net Profit 0% Sharpe Ratio 0 Probabilistic Sharpe Ratio 0% Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha 0 Beta 0 Annual Standard Deviation 0 Annual Variance 0 Information Ratio 0 Tracking Error 0 Treynor Ratio 0 Total Fees $15.13 Estimated Strategy Capacity $80000000.00 Lowest Capacity Asset SPY R735QTJ8XC9X |
# Watch my Tutorial: https://youtu.be/Lq-Ri7YU5fU from datetime import timedelta class VIXCallProtection(QCAlgorithm): def Initialize(self): # set start/end date for backtest self.SetStartDate(2019, 10, 1) self.SetEndDate(2020, 10, 1) # set starting balance for backtest self.SetCash(1000000) # add asset self.equity = self.AddEquity("SPY", Resolution.Minute) self.equity.SetDataNormalizationMode(DataNormalizationMode.Raw) # add underlying for option data self.opt_equity = self.AddData( CBOE, "VIX" ) self.opt_equity.SetDataNormalizationMode(DataNormalizationMode.Raw) # add vix self.vix = self.AddEquity("VIX", Resolution.Minute) self.vix.SetDataNormalizationMode(DataNormalizationMode.Raw) # initialize the option contract with empty string self.contract = str() self.contractsAdded = set() # parameters ------------------------------------------------------------ self.DaysBeforeExp = 2 # number of days before expiry to exit self.DTE = 25 # target days till expiration self.OTM = 0.05 # target percentage OTM of put self.lookbackIV = 150 # lookback length of IV indicator self.percentage = 0.9 # percentage of portfolio for underlying asset self.options_alloc = 90 # 1 option for X num of shares (balanced would be 100) # ------------------------------------------------------------------------ # schedule Plotting function 30 minutes after every market open self.Schedule.On(self.DateRules.EveryDay(self.equity.Symbol), \ self.TimeRules.AfterMarketOpen(self.equity.Symbol, 30), \ self.Plotting) # warmup for IV indicator of data self.SetWarmUp(timedelta(self.lookbackIV)) def OnData(self, data): '''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here. Arguments: data: Slice object keyed by symbol containing the stock data ''' if(self.IsWarmingUp): return # buy underlying asset if not self.Portfolio[self.equity.Symbol].Invested: self.SetHoldings(self.equity.Symbol, self.percentage) # self.BuyPut(data) if self.Securities[self.opt_equity.Symbol].Price > 20: self.BuyPut(data) # close put before it expires if self.contract: if (self.contract.ID.Date - self.Time) <= timedelta(self.DaysBeforeExp): self.Liquidate(self.contract) self.Log("Closed: too close to expiration") self.contract = str() def BuyPut(self, data): # get option data if self.contract == str(): self.contract = self.OptionsFilter(data) return # if not invested and option data added successfully, buy option elif not self.Portfolio[self.contract].Invested and data.ContainsKey(self.contract): #self.Buy(self.contract, round(self.Portfolio[self.symbol].Quantity / self.options_alloc)) self.Buy(self.contract, 1) def OptionsFilter(self, data): ''' OptionChainProvider gets a list of option contracts for an underlying symbol at requested date. Then you can manually filter the contract list returned by GetOptionContractList. The manual filtering will be limited to the information included in the Symbol (strike, expiration, type, style) and/or prices from a History call ''' #contracts = self.OptionChainProvider.GetOptionContractList(self.symbol, data.Time) #self.underlyingPrice = self.Securities[self.symbol].Price contracts = self.OptionChainProvider.GetOptionContractList(self.opt_equity.Symbol, data.Time) #contracts = self.OptionChainProvider.GetOptionContractList(self.vix.Symbol, data.Time) self.underlyingPrice = self.Securities[self.opt_equity.Symbol].Price # filter the out-of-money put options from the contract list which expire close to self.DTE num of days from now otm_calls = [i for i in contracts if i.ID.OptionRight == OptionRight.Call and i.ID.StrikePrice - self.underlyingPrice > self.OTM * self.underlyingPrice and self.DTE - 8 < (i.ID.Date - data.Time).days < self.DTE + 8] if len(otm_calls) > 0: # sort options by closest to self.DTE days from now and desired strike, and pick first contract = sorted(sorted(otm_calls, key = lambda x: abs((x.ID.Date - self.Time).days - self.DTE)), key = lambda x: x.ID.StrikePrice - self.underlyingPrice)[0] if contract not in self.contractsAdded: self.contractsAdded.add(contract) # use AddOptionContract() to subscribe the data for specified contract self.AddOptionContract(contract, Resolution.Minute) #option=self.AddOptionContract(contract, Resolution.Minute) return contract else: return str() def Plotting(self): # plot underlying's price self.Plot("Data Chart", self.equity.Symbol, self.Securities[self.equity.Symbol].Close) # plot strike of put option option_invested = [x.Key for x in self.Portfolio if x.Value.Invested and x.Value.Type==SecurityType.Option] if option_invested: self.Plot("Data Chart", "strike", option_invested[0].ID.StrikePrice) def OnOrderEvent(self, orderEvent): # log order events self.Log(str(orderEvent))