--- title: "Short Put Butterfly" description: "Short Put butterfly is the combination of selling a bull put spread and a bear put spread." canonical: https://www.quantconnect.com/docs/v2/writing-algorithms/trading-and-orders/option-strategies/short-put-butterfly markdown: https://www.quantconnect.com/docs/v2/writing-algorithms/trading-and-orders/option-strategies/short-put-butterfly.md language: python source: https://github.com/QuantConnect/Documentation/tree/master/03%20Writing%20Algorithms/22%20Trading%20and%20Orders/08%20Option%20Strategies/08%20Short%20Put%20Butterfly modified: 2026-10-30 index: https://www.quantconnect.com/llms.txt --- # Short Put Butterfly [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 Put Butterfly > Code examples are shown in Python. Append `?lang=csharp` to this URL for the C# version of this page. ## Introduction **Short Put butterfly** is the combination of a [bull put spread](https://www.quantconnect.com/docs/v2/writing-algorithms/trading-and-orders/option-strategies/bull-put-spread.md) and a [bear put spread](https://www.quantconnect.com/docs/v2/writing-algorithms/trading-and-orders/option-strategies/bear-put-spread.md). In this strategy, all the puts have the same underlying stock, the same expiration date, and the strike price distance of ITM-ATM and OTM-ATM put pairs are the same. The short put butterfly strategy consists of selling an ITM put, selling an OTM put, and buying 2 ATM puts. This strategy profits from a drastic change in underlying price. ## Implementation Follow these steps to implement the short put butterfly 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(500000) self.universe_settings.asynchronous = True option = self.add_option("GOOG", Resolution.MINUTE) self._symbol = option.symbol option.set_filter(lambda universe: universe.put_butterfly(30, 5)) ``` The `put_butterfly` filter narrows the universe down to just the three contracts you need to form a short put butterfly. 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 # Get the OptionChain chain = slice.option_chains.get(self._symbol, None) if not chain: return # Get the furthest expiry date of the contracts expiry = max([x.expiry for x in chain]) # Select the call Option contracts with the furthest expiry puts = [i for i in chain if i.expiry == expiry and i.right == OptionRight.PUT] if len(puts) == 0: return # Select the ATM, ITM and OTM contracts from the remaining contracts atm_put = sorted(puts, key=lambda x: abs(x.strike - chain.underlying.price))[0] itm_put = sorted(puts, key=lambda x: x.strike)[-2] otm_put = [x for x in puts if x.strike == atm_put.strike * 2 - itm_put.strike][0] ``` 3. In the `on_data` method, place the orders. **Approach A:** Call the `OptionStrategies.short_butterfly_put` method with the details of each leg and then pass the result to the `buy` method. ```python option_strategy = OptionStrategies.short_butterfly_put(self._symbol, itm_put.strike, atm_put.strike, otm_put.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 legs = [ Leg.create(atm_put.symbol, 2), Leg.create(itm_put.symbol, -1), Leg.create(otm_put.symbol, -1) ] self.combo_market_order(legs, 1) ``` ## Strategy Payoff The short put butterfly is a limited-reward-limited-risk strategy. The payoff is $$ \begin{array}{rcll} P^{OTM}_T & = & (K^{OTM} - S_T)^{+}\\ P^{ITM}_T & = & (K^{ITM} - S_T)^{+}\\ P^{ATM}_T & = & (K^{ATM} - S_T)^{+}\\ P_T & = & (2\times P^{ATM}_T - P^{OTM}_T - P^{ITM}_T - 2\times P^{ATM}_0 + P^{ITM}_0 + P^{OTM}_0)\times m - fee \end{array} $$ $$ \begin{array}{rcll} \textrm{where} & P^{OTM}_T & = & \textrm{OTM put value at time T}\\ & P^{ITM}_T & = & \textrm{ITM put value at time T}\\ & P^{ATM}_T & = & \textrm{ATM put value at time T}\\ & S_T & = & \textrm{Underlying asset price at time T}\\ & K^{OTM} & = & \textrm{OTM put strike price}\\ & K^{ITM} & = & \textrm{ITM put strike price}\\ & K^{ATM} & = & \textrm{ATM put strike price}\\ & P_T & = & \textrm{Payout total at time T}\\ & P^{ITM}_0 & = & \textrm{ITM put value at position opening (credit received)}\\ & P^{OTM}_0 & = & \textrm{OTM put value at position opening (credit received)}\\ & P^{ATM}_0 & = & \textrm{ATM put value at position opening (debit paid)}\\ & m & = & \textrm{Contract multiplier}\\ & T & = & \textrm{Time of expiration} \end{array} $$ In this example, the underlying stock price at expiration is $829.08. You bought an ITM put at a strike of $832.50 for $37.80, sold 2 ATM puts at a strike of $800.00 for $14.70 each, and bought an OTM put at a strike of $767.50 for $5.70. The following chart shows the payoff at expiration: ![Short Put Butterfly strategy payoff at expiration](https://cdn.quantconnect.com/docs/i/writing-algorithms/trading-and-orders/option-strategies/short-put-butterfly.png) The maximum profit is the net credit received, $P^{ITM}_0 + P^{OTM}_0 - 2\times P^{ATM}_0$. It occurs when the underlying price is below the ITM strike or above the OTM strike at expiration. The maximum loss is $K^{ATM} - K^{OTM} - 2\times P^{ATM}_0 + P^{ITM}_0 + P^{OTM}_0$. It occurs when the underlying price at expiration is at the same price as when you opened the trade. 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 contracts you sell. ## Example The following table shows the price details of the assets in the short put butterfly algorithm: | Asset | Price ($) | Strike ($) | | --- | --- | --- | | ITM put | 37.80 | 832.50 | | ATM put | 14.70 | 800.00 | | OTM put | 5.70 | 767.50 | | Underlying Equity at expiration | 829.08 | - | Therefore, the payoff is $$ \begin{array}{rcll} P^{OTM}_T & = & (K^{OTM} - S_T)^{+}\\ & = & (829.08-832.50)^{+}\\ & = & 0\\ P^{ITM}_T & = & (K^{ITM} - S_T)^{+}\\ & = & (829.08-767.50)^{+}\\ & = & 61.58\\ P^{ATM}_T & = & (K^{ATM} - S_T)^{+}\\ & = & (829.08-800.00)^{+}\\ & = & 29.08\\ P_T & = & (-P^{OTM}_T - P^{ITM}_T + 2\times P^{ATM}_T - 2\times P^{ATM}_0 + P^{ITM}_0 + P^{OTM}_0)\times m - fee\\ & = & (-61.58-0+29.08\times2+5.70+37.80-14.70\times2)\times100-1.00\times4\\ & = & 1064 \end{array} $$ So, the strategy gains $1,064. The following algorithm implements a short put butterfly Option strategy: ```python class PutButterflyStrategy(QCAlgorithm): def initialize(self) -> None: self.set_start_date(2024, 9, 1) self.set_end_date(2024, 12, 31) self.set_cash(500000) option = self.add_option("GOOG", Resolution.MINUTE) self.symbol = option.symbol option.set_filter(self.universe_func) def universe_func(self, universe: OptionFilterUniverse) -> OptionFilterUniverse: return universe.put_butterfly(30, 5) def on_data(self, data: Slice) -> None: # avoid extra orders if self.portfolio.invested: return # Get the OptionChain of the self.symbol chain = data.option_chains.get(self.symbol, None) if not chain: return # sorted the optionchain by expiration date and choose the furthest date expiry = sorted(chain, key = lambda x: x.expiry, reverse=True)[0].expiry # filter the put options from the contracts which expire on the furthest expiration date in the option chain. puts = [i for i in chain if i.expiry == expiry and i.right == OptionRight.PUT] if len(puts) == 0: return # sort the put options with the same expiration date according to their strike price. put_strikes = sorted([x.strike for x in puts]) # get at-the-money strike atm_strike = sorted(puts, key=lambda x: abs(x.strike - chain.underlying.price))[0].strike # Get the distance between lowest strike price and ATM strike, and highest strike price and ATM strike. # Get the lower value as the spread distance as equidistance is needed for both side. spread = min(abs(put_strikes[0] - atm_strike), abs(put_strikes[-1] - atm_strike)) # select the strike prices for forming the option legs itm_strike = atm_strike + spread otm_strike = atm_strike - spread option_strategy = OptionStrategies.short_butterfly_put(self.symbol, itm_strike, atm_strike, otm_strike, expiry) # We open a position with 1 unit of the option strategy self.buy(option_strategy, 1) # self.sell(option_strategy, 1) if short put butterfly ``` ### Other Examples For more examples, see the following algorithms: **Demonstration Algorithm** - [LongAndShortButterflyPutStrategiesAlgorithm.py](https://github.com/QuantConnect/Lean/blob/master/Algorithm.Python/LongAndShortButterflyPutStrategiesAlgorithm.py) (Python)