---
title: "Long Straddle"
description: "A Long Straddle consists of buying an ATM call and an ATM put, where both contracts have the same underlying asset, strike price, and expiration date."
canonical: https://www.quantconnect.com/docs/v2/writing-algorithms/trading-and-orders/option-strategies/long-straddle
markdown: https://www.quantconnect.com/docs/v2/writing-algorithms/trading-and-orders/option-strategies/long-straddle.md
language: python
source: https://github.com/QuantConnect/Documentation/tree/master/03%20Writing%20Algorithms/22%20Trading%20and%20Orders/08%20Option%20Strategies/24%20Long%20Straddle
modified: 2026-10-30
index: https://www.quantconnect.com/llms.txt
---

# Long Straddle

[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 Straddle

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

## Introduction

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

## Implementation

Follow these steps to implement the long straddle 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.straddle(30))
   ```
   The `straddle` filter narrows the universe down to just the two contracts you need to form a long straddle.
2. In the `on_data` method, select the expiration date and strike price of the contracts in the strategy legs.
   ```python
   def on_data(self, slice: Slice) -> None:
       if self.portfolio.invested:
           return

       chain = slice.option_chains.get(self._symbol, None)
       if not chain:
           return

       # Find ATM options with the nearest expiry
       expiry = min([x.expiry for x in chain])
       strike = sorted(chain, key=lambda x: abs(x.strike - chain.underlying.price))[0].strike
   ```
3. In the `on_data` method, select the contracts and place the orders.
   **Approach A:** Call the `OptionStrategies.straddle` method with the details of each leg and then pass the result to the `buy` method.
   ```python
   long_straddle = OptionStrategies.straddle(self._symbol, strike, expiry)
   self.buy(long_straddle, 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
   contracts = [x for x in chain if x.expiry == expiry and x.strike == strike]
   if len(contracts) < 2:
       return

   atm_call = [x for x in contracts if x.right == OptionRight.CALL][0]
   atm_put = [x for x in contracts if x.right == OptionRight.PUT][0]

   legs = [
       Leg.create(atm_call.symbol, 1),
       Leg.create(atm_put.symbol, 1)
   ]
   self.combo_market_order(legs, 1)
   ```

## Strategy Payoff

The payoff of the strategy is

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

In this example, you traded a call and a put, both at a strike of $835.00, for $22.30 and $23.90 respectively.

The following chart shows the payoff at expiration:

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

The maximum profit is unlimited if the underlying price rises to infinity or substantial, $K^{P} - C^{OTM}_0 - P^{OTM}_0$, if it drops to zero at expiration.

The maximum loss is the net debit paid, $C^{ATM}_0 + P^{ATM}_0$. It occurs when the underlying price is the same at expiration as it was 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 (2017-05-20):

| Asset | Price ($) | Strike ($) |
| --- | --- | --- |
| Call | 22.30 | 835.00 |
| Put | 23.90 | 835.00 |
| Underlying Equity at expiration | 934.01 | - |

Therefore, the payoff is

$$ \begin{array}{rcll} C^{ATM}_T & = & (S_T - K^{C})^{+}\\ & = & (934.01-835.00)^{+}\\ & = & 99.01\\ P^{ATM}_T & = & (K^{P} - S_T)^{+}\\ & = & (835.00-934.01)^{+}\\ & = & 0\\ P_T & = & (C^{ATM}_T + P^{ATM}_T - C^{ATM}_0 - P^{ATM}_0)\times m - fee\\ & = & (99.01+0-22.3-23.9)\times100-1.00\times2\\ & = & 5279 \end{array} $$

So, the strategy gains $5,279.

The following algorithm implements a long straddle Option strategy:

```python
class LongStraddleAlgorithm(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.straddle(30))

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

        chain = slice.option_chains.get(self.symbol, None)
        if not chain:
            return

        # Find ATM options with the nearest expiry
        expiry = min([x.expiry for x in chain])
        contracts = sorted([x for x in chain if x.expiry == expiry],
            key=lambda x: abs(chain.underlying.price - x.strike))

        if len(contracts) < 2:
            return

        # The first two contracts are the ATM Call and the ATM Put
        contracts = contracts[0:2]

        long_straddle = OptionStrategies.straddle(self.symbol, contracts[0].strike, expiry)
        self.buy(long_straddle, 1)
```