Skip to content

Strangle Strategy

What is

A Strangle is an options trading strategy that involves buying or selling both a call option and a put option with the same expiration date but different strike prices. It is used to take advantage of expected volatility in the underlying asset.

Option Strangle Strategy

Types of Strangle Strategies

  1. Long Strangle (Buying a Strangle)
  2. Buy an out-of-the-money (OTM) call option.
  3. Buy an out-of-the-money (OTM) put option.

  4. Used when a trader expects high volatility but is unsure of the direction.

  5. Short Strangle (Selling a Strangle)

  6. Sell an out-of-the-money (OTM) call option.
  7. Sell an out-of-the-money (OTM) put option.
  8. Used when a trader expects low volatility and wants to collect premium.

Long Strangle Strategy

  • Objective: Profit from a significant price move in either direction.
  • Max Loss: Limited to the total premium paid.
  • Max Profit: Unlimited (if the stock moves significantly beyond the strike prices).
  • Breakeven Points:
  • Upper BEP = Call strike price + Premium paid.
  • Lower BEP = Put strike price - Premium paid.

✅ Best for: Volatile markets, earnings reports, major news events.

🔴 Risk: If the stock remains within the strike prices, the options expire worthless.

Short Strangle Strategy

  • Objective: Profit from low volatility and time decay.
  • Max Profit: Limited to the premium collected.
  • Max Loss: Potentially unlimited if the stock moves sharply.
  • Breakeven Points:
  • Upper BEP = Call strike price + Premium received.
  • Lower BEP = Put strike price - Premium received.

✅ Best for: Stable or low-volatility markets.

🔴 Risk: Large losses if the stock price moves sharply in either direction.

Example of a Long Strangle

Stock: XYZ trading at $100

  • Buy 110 Call at $2.00
  • Buy 90 Put at $2.00
  • Total Cost: $4.00

Breakeven Points:

  • Upper BEP = $110 + $4 = $114
  • Lower BEP = $90 - $4 = $86

Profit Scenarios:

  • If stock moves above $114, the call option gains value.
  • If stock moves below $86, the put option gains value.
  • If stock stays between $90 and $110, both options expire worthless, and you lose the $4 premium.

Example of a Short Strangle

Stock: XYZ trading at $100

  • Sell 110 Call for $2.00
  • Sell 90 Put for $2.00
  • Total Premium Collected: $4.00

Breakeven Points:

  • Upper BEP = $110 + $4 = $114
  • Lower BEP = $90 - $4 = $86

Profit Scenarios:

  • If stock stays between $90 and $110, both options expire worthless, and you keep the premium.
  • If stock moves above $114 or below $86, you face unlimited risk.

Key Takeaways

✔️ Long Strangle: Limited risk, unlimited profit potential, best for high volatility.
✔️ Short Strangle: Limited profit, unlimited risk, best for low volatility.
✔️ Breakeven Points: Critical to manage risk and set exit points.
✔️ Implied Volatility (IV): Higher IV makes long strangles more expensive, while lower IV makes short strangles more profitable.

Script to backtest this strategy 🚀

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import yfinance as yf

# Define parameters for the strangle strategy
ticker = "AAPL"
start_date = "2023-01-01"
end_date = "2024-01-01"
strike_diff = 5  # Difference from ATM for Call and Put
premium_paid = 4  # Estimated cost of buying both options
premium_received = 4  # Estimated premium collected for short strangle

# Fetch historical stock data
data = yf.download(ticker, start=start_date, end=end_date)
data["MidPrice"] = (data["High"] + data["Low"]) / 2

# Define breakeven points
data["Upper_BEP_Long"] = data["MidPrice"] + strike_diff + premium_paid
data["Lower_BEP_Long"] = data["MidPrice"] - strike_diff - premium_paid
data["Upper_BEP_Short"] = data["MidPrice"] + strike_diff + premium_received
data["Lower_BEP_Short"] = data["MidPrice"] - strike_diff - premium_received

# Calculate long strangle profit/loss
data["Long_Strangle_PL"] = np.where(
    (data["MidPrice"] > data["Upper_BEP_Long"]) | (data["MidPrice"] < data["Lower_BEP_Long"]),
    abs(data["MidPrice"] - data["Upper_BEP_Long"]) - premium_paid,
    -premium_paid
)

# Calculate short strangle profit/loss
data["Short_Strangle_PL"] = np.where(
    (data["MidPrice"] > data["Upper_BEP_Short"]) | (data["MidPrice"] < data["Lower_BEP_Short"]),
    -abs(data["MidPrice"] - data["Upper_BEP_Short"]) + premium_received,
    premium_received
)


# Display first few rows using pprint
pprint(data[["MidPrice", "Long_Strangle_PL", "Short_Strangle_PL"]].head())