---
title: "Short Call Backspread"
description: "Short call backspread, a combination of bull call spread and short call, consists of buying a lower-strike call and selling two higher-srtike calls with the same expiry."
canonical: https://www.quantconnect.com/docs/v2/writing-algorithms/trading-and-orders/option-strategies/short-call-backspread
markdown: https://www.quantconnect.com/docs/v2/writing-algorithms/trading-and-orders/option-strategies/short-call-backspread.md
language: python
source: https://github.com/QuantConnect/Documentation/tree/master/03%20Writing%20Algorithms/22%20Trading%20and%20Orders/08%20Option%20Strategies/39%20Short%20Call%20Backspread
modified: 2026-10-29
index: https://www.quantconnect.com/llms.txt
---

# Short Call Backspread

[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) > Short Call Backspread

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

## Introduction

**Short Call Backspread**, consists of long 1 lower-strike call and short 2 higher strike calls. It is a combination of a [bull call spread](https://www.quantconnect.com/docs/v2/writing-algorithms/trading-and-orders/option-strategies/bull-call-spread.md) and a short call with the same strike price as the higher-strike leg the call spread. All calls 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 call backspread 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). You can use the `call_spread` helper method in option universe filtering, since a call backspread consists of the same contracts as a call spread.
   ```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.call_spread(20, 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 call Option contracts with the furthest expiry
       expiry = max([x.expiry for x in chain])
       calls = [i for i in chain if i.expiry == expiry and i.right == OptionRight.CALL]
       if not calls:
           return

       # Select the strike prices from the remaining contracts
       strikes = sorted(set(x.strike for x in calls))
       if len(strikes) < 2:
           return

       low_strike = strikes[0]
       high_strike = strikes[1]
   ```
3. In the `on_data` method, select the contracts and place the orders.
   **Approach A:** Call the `OptionStrategies.short_call_backspread` method with the details of each leg and then pass the result to the `buy` method.
   ```python
   option_strategy = OptionStrategies.short_call_backspread(self._symbol, low_strike, high_strike, expiry)
   self.buy(option_strategy, 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
   low_strike_call = next(filter(lambda x: x.strike == low_strike, calls))
   high_strike_call = next(filter(lambda x: x.strike == high_strike, calls))

   legs = [
       Leg.create(low_strike_call.symbol, 1),
       Leg.create(high_strike_call.symbol, -2)
   ]
   self.combo_market_order(legs, 1)
   ```

## Strategy Payoff

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

$$ \begin{array}{rcll} C^{low}_T & = & (S_T - K^{low})^{+}\\ C^{high}_T & = & (S_T - K^{high})^{+}\\ Payoff_T & = & (C^{low}_T - C^{low}_0 + C^{high}_0 \times 2 - C^{high}_T \times 2)\times m - fee\\ \end{array} $$ $$ \begin{array}{rcll} \textrm{where} & C^{low}_T & = & \textrm{Lower-strike call value at time T}\\ & C^{high}_T & = & \textrm{Higher-strike call value at time T}\\ & S_T & = & \textrm{Underlying asset price at time T}\\ & K^{low} & = & \textrm{Lower-strike call strike price}\\ & K^{high} & = & \textrm{Higher-strike call strike price}\\ & C^{low}_0 & = & \textrm{Lower-strike call value at position opening (credit received)}\\ & C^{high}_0 & = & \textrm{Higher-strike call value at position opening (debit paid)}\\ & m & = & \textrm{Contract multiplier}\\ & T & = & \textrm{Time of expiration} \end{array} $$

In this example, the underlying stock price at expiration is $843.19. You traded a lower-strike call at $825.00 for $15.10 and two higher-strike calls at $835.00 for $8.00 each.

The following chart shows the payoff at expiration:

![Short Call Backspread strategy payoff at expiration](https://cdn.quantconnect.com/docs/i/writing-algorithms/trading-and-orders/option-strategies/short-call-backspread.png)

The maximum profit is $K^{high} - K^{low} - C^{low}_0 + C^{high}_0 \times 2$, which occurs when the underlying price is exactly at the higher strike at expiry.

The maximum loss is unlimited, which occurs when the underlying price increases indefinitely.

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 call | 15.10 | 825.00 |
| Higher-strike call | 8.00 | 835.00 |
| Underlying Equity at expiration | 843.19 | - |

Therefore, the payoff is

$$ \begin{array}{rcll} C^{low}_T & = & (S_T - K^{low})^{+}\\ & = & (843.19-825.00)^{+}\\ & = & 18.19\\ C^{high}_T & = & (S_T - K^{high})^{+}\\ & = & (843.19-835.00)^{+}\\ & = & 8.19\\ Payoff_T & = & (C^{low}_T - C^{low}_0 - C^{high}_T \times 2 + C^{high}_0 \times 2)\times m - fee\\ & = & (18.19 - 15.10 - 8.19\times2 + 8.00\times2)\times100-2.30\\ & = & 268.70\\ \end{array} $$

So, the strategy gains $268.70.

The following algorithm implements a short call backspread Option strategy:

```python
class BackspreadOptionStrategyAlgorithm(QCAlgorithm):
    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.call_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])
        calls = [i for i in chain if i.expiry == expiry and i.right == OptionRight.CALL]
        if not calls:
            return

        # Select the strike prices from the remaining contracts
        strikes = sorted(set(x.strike for x in calls))
        if len(strikes) < 2:
            return

        low_strike = strikes[0]
        high_strike = strikes[1]

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