---
title: "Long Strangle"
description: "A Long Strangle consists of simultaneously buying an OTM put and an OTM call, where both contracts have the same underlying asset and expiration date."
canonical: https://www.quantconnect.com/docs/v2/writing-algorithms/trading-and-orders/option-strategies/long-strangle
markdown: https://www.quantconnect.com/docs/v2/writing-algorithms/trading-and-orders/option-strategies/long-strangle.md
language: python
source: https://github.com/QuantConnect/Documentation/tree/master/03%20Writing%20Algorithms/22%20Trading%20and%20Orders/08%20Option%20Strategies/26%20Long%20Strangle
modified: 2026-10-29
index: https://www.quantconnect.com/llms.txt
---

# Long Strangle

[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) > Long Strangle

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

## Introduction

**Long Strangle** is an Options trading strategy that consists of simultaneously buying an OTM put and an OTM call, where both contracts have the same underlying asset and expiration date. This strategy aims to profit from volatile movements in the underlying stock, either positive or negative.

Compared to a [long straddle](https://www.quantconnect.com/docs/v2/writing-algorithms/trading-and-orders/option-strategies/long-straddle.md), the net debit of a long strangle is lower since OTM Options are cheaper. Additionally, the losing range of a long straddle is wider and the strike spread is wider.

## Implementation

Follow these steps to implement the long strangle 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(100000)

       self.universe_settings.asynchronous = True
       option = self.add_option("GOOG")
       self._symbol = option.symbol
       option.set_filter(lambda universe: universe.strangle(30, 5, -10))
   ```
   The `strangle` filter narrows the universe down to just the two contracts you need to form a long strangle.
2. In the `on_data` method, select the contracts of the strategy legs.
   ```python
   def on_data(self, slice: Slice) -> None:
       if self.portfolio.invested:
           return

       chain = slice.option_chain.get(self._symbol)
       if not chain:
           return

       # Find options with the farthest expiry
       expiry = max([x.expiry for x in chain])
       contracts = [contract for contract in chain if contract.expiry == expiry]

       # Order the OTM calls by strike to find the nearest to ATM
       call_contracts = sorted([contract for contract in contracts
           if contract.right == OptionRight.CALL and
               contract.strike > chain.underlying.price],
           key=lambda x: x.strike)
       if not call_contracts:
           return

       # Order the OTM puts by strike to find the nearest to ATM
       put_contracts = sorted([contract for contract in contracts
           if contract.right == OptionRight.PUT and
              contract.strike < chain.underlying.price],
           key=lambda x: x.strike, reverse=True)
       if not put_contracts:
           return

       call = call_contracts[0]
       put = put_contracts[0]
   ```
3. In the `on_data` method, place the orders.
   **Approach A:** Call the `OptionStrategies.strangle` method with the details of each leg and then pass the result to the `buy` method.
   ```python
   long_strangle = OptionStrategies.strangle(self._symbol, call.strike, put.strike, expiry)
   self.buy(long_strangle, 1)
   ```
   **Approach B:** Create a list of `Leg` objects and then call 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
   legs = [
       Leg.create(call.symbol, 1),
       Leg.create(put.symbol, 1)
   ]
   self.combo_market_order(legs, 1)
   ```

## Strategy Payoff

The payoff of the strategy is

$$ \begin{array}{rcll} C^{OTM}_T & = & (S_T - K^{C})^{+}\\ P^{OTM}_T & = & (K^{P} - S_T)^{+}\\ P_T & = & (C^{OTM}_T + P^{OTM}_T - C^{OTM}_0 - P^{OTM}_0)\times m - fee \end{array} $$ $$ \begin{array}{rcll} \textrm{where} & C^{OTM}_T & = & \textrm{OTM call value at time T}\\ & P^{OTM}_T & = & \textrm{OTM put value at time T}\\ & S_T & = & \textrm{Underlying asset price at time T}\\ & K^{C} & = & \textrm{OTM call strike price}\\ & K^{P} & = & \textrm{OTM put strike price}\\ & P_T & = & \textrm{Payout total at time T}\\ & C^{OTM}_0 & = & \textrm{OTM call value at position opening (debit paid)}\\ & P^{OTM}_0 & = & \textrm{OTM put value at position opening (debit paid)}\\ & m & = & \textrm{Contract multiplier}\\ & T & = & \textrm{Time of expiration} \end{array} $$

In this example, you traded a call at a strike of $835.00 for $8.80 and a put at a strike of $832.50 for $9.50.

The following chart shows the payoff at expiration:

![Long Strangle strategy payoff at expiration](https://cdn.quantconnect.com/docs/i/writing-algorithms/trading-and-orders/option-strategies/long-strangle.png)

The maximum profit is unlimited if the underlying price rises to infinity at expiration.

The maximum loss is the net debit paid, $C^{OTM}_0 + P^{OTM}_0$. It occurs when the underlying price at expiration is the same as when you opened the trade. In this case, both Options expire worthless.

## Example

The following table shows the price details of the assets in the algorithm at Option expiration (04/22/2017):

| Asset | Price ($) | Strike ($) |
| --- | --- | --- |
| Call | 8.80 | 835.00 |
| Put | 9.50 | 832.50 |
| Underlying Equity at expiration | 843.19 | - |

Therefore, the payoff is

$$ \begin{array}{rcll} C^{OTM}_T & = & (S_T - K^{C})^{+}\\ & = & (843.19-835.00)^{+}\\ & = & 8.19\\ P^{OTM}_T & = & (K^{P} - S_T)^{+}\\ & = & (832.50-843.19)^{+}\\ & = & 0\\ P_T & = & (C^{OTM}_T + P^{OTM}_T - C^{OTM}_0 - P^{OTM}_0)\times m - fee\\ & = & (8.19+0-8.80-9.50)\times100-1.00\times2\\ & = & -1013 \end{array} $$

So, the strategy loses $1,013.

The following algorithm implements a long strangle Option strategy:

```python
class LongStrangleAlgorithm(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")
        self.symbol = option.symbol
        option.set_filter(lambda universe: universe.strangle(30, 5, -10))

    def on_data(self, slice: Slice) -> None:
        if self.portfolio.invested:
            return

        # Get the OptionChain
        chain = slice.option_chains.get(self.symbol)
        if not chain:
            return

        # Find options with the nearest expiry
        expiry = max([x.expiry for x in chain])
        contracts = [contract for contract in chain if contract.expiry == expiry]

        # Order the OTM calls by strike to find the nearest to ATM
        call_contracts = sorted([contract for contract in contracts
            if contract.right == OptionRight.CALL and
               contract.strike > chain.underlying.price],
            key=lambda x: x.strike)
        if not call_contracts:
            return

        # Order the OTM puts by strike to find the nearest to ATM
        put_contracts = sorted([contract for contract in contracts
            if contract.right == OptionRight.PUT and
               contract.strike < chain.underlying.price],
            key=lambda x: x.strike, reverse=True)
        if not put_contracts:
            return

        call_strike = call_contracts[0].strike
        put_strike = put_contracts[0].strike

        long_strangle = OptionStrategies.strangle(self.symbol, call_strike, put_strike, expiry)
        self.buy(long_strangle, 1)
```