---
title: "Bull Put Ladder"
description: "Bull put ladder consists of selling a put and buying two puts with decreasing strike price order and the same expiry."
canonical: https://www.quantconnect.com/docs/v2/writing-algorithms/trading-and-orders/option-strategies/bull-put-ladder
markdown: https://www.quantconnect.com/docs/v2/writing-algorithms/trading-and-orders/option-strategies/bull-put-ladder.md
language: python
source: https://github.com/QuantConnect/Documentation/tree/master/03%20Writing%20Algorithms/22%20Trading%20and%20Orders/08%20Option%20Strategies/37%20Bull%20Put%20Ladder
modified: 2026-11-01
index: https://www.quantconnect.com/llms.txt
---

# Bull Put Ladder

[Documentation](https://www.quantconnect.com/docs/v2.md) > [Writing Algorithms](https://www.quantconnect.com/docs/v2/writing-algorithms.md) > Trading and Orders > [Option Strategies](https://www.quantconnect.com/docs/v2/writing-algorithms/trading-and-orders/option-strategies.md) > Bull Put Ladder

> Code examples are shown in Python. Append `?lang=csharp` to this URL for the C# version of this page.

## Introduction

**Bull put ladder**, also known as **short put ladder**, is a combination of a [bull put spread](https://www.quantconnect.com/docs/v2/writing-algorithms/trading-and-orders/option-strategies/bull-put-spread.md) 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 increasing volatility of the underlying asset. For instance, the underlying price moves away from its current price.

## Implementation

Follow these steps to implement the bull put ladder strategy:

1. In the `initialize` method, set the start date, end date, cash, and [Option universe](https://www.quantconnect.com/docs/v2/writing-algorithms/universes/equity-options.md).
   ```python
   def initialize(self) -> None:
       self.set_start_date(2024, 9, 1)
       self.set_end_date(2024, 12, 31)
       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.put_ladder(30, 5, 0, -5))
   ```
2. In the `on_data` method, select the expiration and strikes of the contracts in the strategy legs.
   ```python
   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.
   **Approach A:** Put the `OptionStrategies.bull_put_ladder` method with the details of each leg and then pass the result to the `buy` method.
   ```python
   option_strategy = OptionStrategies.bull_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](https://www.quantconnect.com/docs/v2/writing-algorithms/trading-and-orders/order-types/combo-market-orders.md), [combo_limit_order](https://www.quantconnect.com/docs/v2/writing-algorithms/trading-and-orders/order-types/combo-limit-orders.md), or [combo_leg_limit_order](https://www.quantconnect.com/docs/v2/writing-algorithms/trading-and-orders/order-types/combo-leg-limit-orders.md) method.
   ```python
   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 bull put spread is an limited-risk strategy. The payoff is

$$ \begin{array}{rcll} P^{low}_T & = & (K^{low} - S_T)^{+}\\ P^{mid}_T & = & (K^{mid} - S_T)^{+}\\ P^{high}_T & = & (K^{high} - S_T)^{+}\\ Payoff_T & = & (P^{low}_T - P^{low}_0 + P^{mid}_T - P^{mid}_0 + P^{high}_0 - P^{high}_T)\times m - fee\\ \end{array} $$ $$ \begin{array}{rcll} \textrm{where} & P^{low}_T & = & \textrm{Lower-strike put value at time T}\\ & P^{mid}_T & = & \textrm{Middle-strike put value at time T}\\ & P^{high}_T & = & \textrm{Higher-strike put value at time T}\\ & S_T & = & \textrm{Underlying asset price at time T}\\ & K^{low} & = & \textrm{Lower-strike put strike price}\\ & K^{mid} & = & \textrm{Middle-strike put strike price}\\ & K^{high} & = & \textrm{Higher-strike put strike price}\\ & P^{low}_0 & = & \textrm{Lower-strike put value at position opening (credit received)}\\ & P^{mid}_0 & = & \textrm{Middle-strikeTM put value at position opening (debit paid)}\\ & P^{high}_0 & = & \textrm{Higher-strike put value at position opening (debit paid)}\\ & m & = & \textrm{Contract multiplier}\\ & T & = & \textrm{Time of expiration} \end{array} $$

In this example, the underlying stock price at expiration is $843.25. You traded a lower-strike put at $822.50 for $6.00, a middle-strike put at $825.00 for $4.70, and a higher-strike put at $827.50 for $5.60.

The following chart shows the payoff at expiration:

![Bull Put Ladder strategy payoff at expiration](https://cdn.quantconnect.com/docs/i/writing-algorithms/trading-and-orders/option-strategies/bull-put-ladder.png)

The maximum profit is $K^{mid} + K^{low} - K^{high} - P^{low}_0 - P^{mid}_0 + P^{high}_0$, which occurs when the underlying price decreases to $0.

The maximum loss is $K^{mid} - K^{high} - P^{low}_0 - P^{mid}_0 + P^{high}_0$, which occurs when the underlying price is between the two lower strike prices.

If the Option is American Option, there is a risk of [early assignment](https://www.quantconnect.com/docs/v2/writing-algorithms/reality-modeling/options-models/assignment.md) on the contract you sell.

## Example

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

| Asset | Price ($) | Strike ($) |
| --- | --- | --- |
| Lower-Strike put | 6.00 | 822.50 |
| Middle-strike put | 4.70 | 825.00 |
| Higher-strike put | 5.60 | 827.50 |
| Underlying Equity at expiration | 843.25 | - |

Therefore, the payoff is

$$ \begin{array}{rcll} P^{low}_T & = & (K^{low} - S_T)^{+}\\ & = & (822.50-843.25)^{+}\\ & = & 0\\ P^{mid}_T & = & (K^{mid} - S_T)^{+}\\ & = & (825.00-843.25)^{+}\\ & = & 0\\ P^{high}_T & = & (K^{high} - S_T)^{+}\\ & = & (827.50-843.25)^{+}\\ & = & 0\\ Payoff_T & = & (P^{low}_T - P^{low}_0 + P^{mid}_T - P^{mid}_0 + P^{high}_0 - P^{high}_T)\times m - fee\\ & = & (0 - 6.00 + 0 - 4.70 + 5.60 - 0)\times100-1.00\times3\\ & = & -513\\ \end{array} $$

So, the strategy loses $513.

The following algorithm implements a bull put ladder Option strategy:

```python
class BullPutLadderOptionStrategy(QCAlgorithm):
    def initialize(self) -> None:
        self.set_start_date(2024, 9, 1)
        self.set_end_date(2024, 12, 31)
        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 universe: universe.put_ladder(30, 5, 0, -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 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.bull_put_ladder(self._symbol, high_strike, middle_strike, low_strike, expiry)
        self.buy(option_strategy, 1)
```