book
Checkout our new book! Hands on AI Trading with Python, QuantConnect, and AWS Learn More arrow

Option Strategies

Bear Put Ladder

Introduction

Bear put ladder, also known as long put ladder, is a combination of a bear put spread and short put with a lower strike price than the 2 legs of the put spread. All puts have the same underlying Equity and expiration date. This strategy profits from low volatility of the underlying asset. For instance, the underlying price stays similar to its current price.

Implementation

Follow these steps to implement the bear put ladder strategy:

  1. In the initialize method, set the start date, end date, cash, and Option universe.
    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_ladder(30, 5, 0, -5))
  2. In the on_data method, select the expiration and strikes of the contracts in the strategy legs.
    3. 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 and i.right == OptionRight.PUT]
    if not puts:
        return

    # Select the strike prices from the remaining contracts
    strikes = sorted(set(x.strike for x in puts))
    if len(strikes) < 3:
        return
    
    low_strike = strikes[0]
    middle_strike = strikes[1]
    high_strike = strikes[2]
  3. In the on_data method, select the contracts and place the orders.

    4. Approach A: Put the OptionStrategies.bear_put_ladder method with the details of each leg and then pass the result to the buy method.

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

    Approach B: Create a list of Leg objects and then put 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))
middle_strike_put = next(filter(lambda x: x.strike == middle_strike, puts))
high_strike_put = next(filter(lambda x: x.strike == high_strike, puts))

legs = [
    Leg.create(low_strike_put.symbol, -1),
    Leg.create(middle_strike_put.symbol, -1),
    Leg.create(high_strike_put.symbol, 1)
]
self.combo_market_order(legs, 1)

Strategy Payoff

The bear put ladding is an limited-profit strategy. The payoff is

PlowT=(Klow−ST)+PmidT=(Kmid−ST)+PhighT=(Khigh−ST)+PayoffT=(Plow0−PlowT+Pmid0−PmidT+PhighT−Phigh0)×m−fee wherePlowT=Lower-strike put value at time TPmidT=Middle-strike put value at time TPhighT=Higher-strike put value at time TST=Underlying asset price at time TKlow=Lower-strike put strike priceKmid=Middle-strike put strike priceKhigh=Higher-strike put strike pricePlow0=Lower-strike put value at position opening (credit received)Pmid0=Middle-strikeTM put value at position opening (debit paid)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 bear put ladder

The maximum profit is Khigh−Kmid+Plow0+Pmid0−Phigh0, which occurs when the underlying price is between the two lower strike prices.

The maximum loss is Khigh−Kmid−Klow+Plow0+Pmid0−Phigh0, which occurs when the underlying price decreases to $0.

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 put3.80822.50
Middle-strike put4.70825.00
Higher-strike put7.80827.50
Underlying Equity at expiration843.25-

Therefore, the payoff is

PlowT=(Klow−ST)+=(822.50−843.25)+=0PmidT=(Kmid−ST)+=(825.00−843.25)+=0PhighT=(Khigh−ST)+=(827.50−843.25)+=0PayoffT=(Plow0−PlowT+Pmid0−PmidT+PhighT−Phigh0)×m−fee=(3.80−0+4.70−0+0−7.80)×100−1.00×3=67

So, the strategy gains $67.

The following algorithm implements a bear put ladder Option strategy:

Select Language: 
class BearPutLadderOptionStrategy(QCAlgorithm):
    def initialize(self) -> None:
        self.set_start_date(2017, 4, 1)
        self.set_end_date(2017, 4, 23)
        self.set_cash(100000)
        
        option = self.add_option("GOOG", Resolution.MINUTE)
        self._symbol = option.symbol

        # set our strike/expiry filter for this option chain
        option.set_filter(lambda x: x.include_weeklys().put_ladder(30, 5, 0, -5))

    def on_data(self, 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 and i.right == OptionRight.PUT]
        if not puts:
            return

        # Select the strike prices from the remaining contracts
        strikes = sorted(set(x.strike for x in puts))
        if len(strikes) < 3:
            return
        
        low_strike = strikes[0]
        middle_strike = strikes[1]
        high_strike = strikes[2]
    
        option_strategy = OptionStrategies.bear_put_ladder(self._symbol, high_strike, middle_strike, low_strike, expiry)
        self.buy(option_strategy, 1)

You can also see our Videos. You can also get in touch with us via Discord.

Did you find this page helpful?

Contribute to the documentation: