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))