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Option Strategies

Short Put Backspread

Introduction

Short Put Backspread, consists of short 1 higher-strike put and short 2 lower-strike puts. It is a combination of a bear put spread and a short put with the same strike price as the lower-strike leg the put spread. All puts have the same underlying Equity and expiration date. This strategy profits from stable, consistent price of the underlying asset. For instance, the underlying price stays at its current price.

Implementation

Follow these steps to implement the short put backspread strategy:

  1. In the initialize method, set the start date, end date, cash, and Option universe. You can use the put_spread helper method in option universe filtering, since a put backspread consists of the same contracts as a put spread.
  2. Select Language:
    def initialize(self) -> None:
        self.set_start_date(2017, 4, 1)
        self.set_end_date(2017, 4, 22)
        self.set_cash(1000000)
    
        self.universe_settings.asynchronous = True
        option = self.add_option("GOOG", Resolution.MINUTE)
        self._symbol = option.symbol
        option.set_filter(lambda universe: universe.include_weeklys().put_spread(20, 5))
  3. In the on_data method, select the expiration and strikes of the contracts in the strategy legs.
  4. Select Language:
    def on_data(self, slice: Slice) -> None:
        if self.portfolio.invested:
            return
    
        # Get the OptionChain
        chain = slice.option_chains.get(self._symbol, None)
        if not chain:
            return
        
        # Select the put Option contracts with the furthest expiry
        expiry = max([x.expiry for x in chain])
        puts = [i for i in chain if i.expiry == expiry]
        if not puts:
            return
    
        # Select the strike prices from the remaining contracts
        strikes = sorted(set(x.strike for x in puts))
        if len(strikes) < 2:
            return
        
        low_strike = strikes[0]
        high_strike = strikes[1]
  5. In the on_data method, select the contracts and place the orders.
  6. Approach A: Call the OptionStrategies.short_put_backspread method with the details of each leg and then pass the result to the buy method.

    Select Language:
    option_strategy = OptionStrategies.short_put_backspread(self._symbol, high_strike, low_strike, expiry)
    self.buy(option_strategy, 1)

    Approach B: Create a list of Leg objects and then call the combo_market_order, combo_limit_order, or combo_leg_limit_order method.

    Select Language:
    low_strike_put = next(filter(lambda x: x.strike == low_strike, puts))
    high_strike_put = next(filter(lambda x: x.strike == high_strike, puts))
    
    legs = [
        Leg.create(low_strike_put.symbol, -2),
        Leg.create(high_strike_put.symbol, 1)
    ]
    self.combo_market_order(legs, 1)

Strategy Payoff

The short put backspread is an unlimited-profit-limited-risk strategy. The payoff is

PlowT=(KlowST)+PhighT=(KhighST)+PayoffT=(PhighTPhigh0PlowT×2+Plow0×2)×mfee
wherePlowT=Lower-strike put value at time TPhighT=Higher-strike put value at time TST=Underlying asset price at time TKlow=Lower-strike put strike priceKhigh=Higher-strike put strike pricePlow0=Lower-strike put value at position opening (credit received)Phigh0=Higher-strike put value at position opening (debit paid)m=Contract multiplierT=Time of expiration

The following chart shows the payoff at expiration:

Strategy payoff decomposition and analysis of short put backspread

The maximum profit is KhighKlowPhigh0+Plow0×2, which occurs when the underlying price is exactly at the lower strike at expiry.

The maximum loss is Plow0×2Phigh0ST, which occurs when the underlying price drops to zero.

If the Option is American Option, there is a risk of early assignment on the contract you sell.

Example

The following table shows the price details of the assets in the algorithm:

AssetPrice ($)Strike ($)
Lower-Strike put4.70825.00
Higher-strike put10.90835.00
Underlying Equity at expiration843.19-

Therefore, the payoff is

PlowT=(KlowST)+=(825.00843.19)+=0.00PhighT=(KhighST)+=(835.00843.19)+=0.00PayoffT=(PhighTPhigh0PlowT×2+Plow0×2)×mfee=(010.900.00×2+4.70×2)×1002.30=152.30

So, the strategy loses $152.30.

The following algorithm implements a short put backspread Option strategy:

Select Language:
class BackspreadOptionStrategyAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self.set_start_date(2017, 4, 1)
        self.set_end_date(2017, 4, 22)
        self.set_cash(1000000)

        self.universe_settings.asynchronous = True
        option = self.add_option("GOOG", Resolution.MINUTE)
        self._symbol = option.symbol
        option.set_filter(lambda universe: universe.include_weeklys().put_spread(20, 5))
        
    def on_data(self, slice: Slice) -> None:
        if self.portfolio.invested:
            return

        # Get the OptionChain
        chain = slice.option_chains.get(self._symbol, None)
        if not chain:
            return
        
        # Select the call Option contracts with the furthest expiry
        expiry = max([x.expiry for x in chain])
        puts = [i for i in chain if i.expiry == expiry]
        if not puts:
            return

        # Select the strike prices from the remaining contracts
        strikes = sorted(set(x.strike for x in puts))
        if len(strikes) < 2:
            return
        
        low_strike = strikes[0]
        high_strike = strikes[1]

        option_strategy = OptionStrategies.short_put_backspread(self._symbol, high_strike, low_strike, expiry)
        self.buy(option_strategy, 1)

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