Married Put Strategy

Married-Put Strategy

A married-put strategy provides downside protection for stock holdings by purchasing put options as insurance against price declines while maintaining unlimited upside potential.

Strategy Overview

Definition: Buy (or own) 100 shares of stock + Buy 1 put option contract

Key Characteristics:

• Maximum Loss: Limited to stock purchase price minus put strike price, plus net premium paid
• Maximum Gain: Unlimited (stock can rise indefinitely)
• Breakeven: Stock price at purchase + net premium paid
• Best Use: Protecting newly acquired positions or holdings during uncertain periods

Cost Components:

• Stock purchase: Number of shares × stock price
• Put premium: Option price × 100 shares
• Transaction cost: $0.65 per option contract

Quick Start

Calculate married-put metrics for a position:

from scripts.married_put_calculator import MarriedPut

# Create position: 100 shares at $45, put strike $43, premium $2.10
position = MarriedPut(
    stock_price=45.00,
    shares=100,
    put_strike=43.00,
    put_premium=2.10,
    transaction_cost=0.65
)

# Calculate key metrics
print(f"Breakeven: ${position.breakeven_price:.2f}")
print(f"Max Loss: ${position.max_loss:.2f}")
print(f"Total Cost: ${position.total_cost:.2f}")
print(f"Protection Level: {position.protection_percentage:.1f}%")

Strike Price Comparison

Compare ITM, ATM, and OTM puts to optimize cost vs. protection:

from scripts.strike_comparison import compare_strike_prices

# Compare different strike prices for AAPL position
results = compare_strike_prices(
    stock_price=175.50,
    shares=100,
    strike_prices=[165, 170, 175, 180],  # OTM to ITM
    premiums=[2.30, 3.85, 6.10, 9.45],
    days_to_expiration=45
)

# View comparison table
print(results.to_dataframe())

Strike Selection Guidelines:

• OTM Puts (strike < stock price): Lower cost, reduced protection

  • Best for: High-conviction positions, cost-conscious protection
  • Typical protection: 5-10% below current price

• ATM Puts (strike ≈ stock price): Balanced cost and protection

  • Best for: Standard hedging, moderate risk tolerance
  • Typical protection: Current price level

• ITM Puts (strike > stock price): Higher cost, maximum protection

  • Best for: Maximum downside protection, risk-averse strategies
  • Typical protection: Locks in guaranteed minimum exit price

Expiration Cycle Analysis

Evaluate 30-day, 60-day, and 90-day options:

from scripts.expiration_analysis import compare_expirations

# Compare different expiration cycles
analysis = compare_expirations(
    stock_price=52.75,
    shares=100,
    put_strike=50.00,
    premiums_30d=1.85,
    premiums_60d=2.95,
    premiums_90d=3.85
)

print(f"30-day: ${analysis['monthly_cost_30d']:.2f}/month")
print(f"60-day: ${analysis['monthly_cost_60d']:.2f}/month")
print(f"90-day: ${analysis['monthly_cost_90d']:.2f}/month")

Expiration Selection Criteria:

• 30-day: Lowest total premium, highest monthly cost, frequent rolling required
• 60-day: Balanced cost/maintenance, moderate time decay
• 90-day: Highest total premium, lowest monthly cost, reduced transaction frequency

Position Sizing

For positions $5,000 to $50,000:

from scripts.position_sizer import calculate_position_size

# Determine optimal position size with protection
position_params = calculate_position_size(
    capital_available=25000,
    stock_price=48.25,
    put_premium=2.15,
    max_position_pct=0.40  # Maximum 40% of capital
)

print(f"Recommended shares: {position_params['shares']}")
print(f"Put contracts: {position_params['contracts']}")
print(f"Total investment: ${position_params['total_cost']:.2f}")
print(f"Remaining capital: ${position_params['remaining']:.2f}")

Profit/Loss Analysis

Calculate P/L at various stock prices:

# Generate P/L table
position = MarriedPut(stock_price=45.00, shares=100,
                      put_strike=43.00, put_premium=2.10)

# Calculate P/L at different price points
price_points = [35, 40, 43, 45, 50, 55, 60]
for price in price_points:
    pl = position.calculate_pl_at_price(price)
    print(f"Stock at ${price}: P/L = ${pl:.2f}")

Visualization

Generate payoff diagram:

from scripts.visualizations import plot_married_put_payoff

# Create payoff diagram
plot_married_put_payoff(
    stock_price=45.00,
    put_strike=43.00,
    put_premium=2.10,
    price_range=(30, 60),
    save_path="married_put_diagram.png"
)

Real-World Examples

Five example positions with varying volatility levels:

Low Volatility (15-20% IV):

• Large-cap, stable companies
• Lower premium costs
• Suitable for conservative protection

Medium Volatility (25-35% IV):

• Mid-cap growth stocks
• Moderate premium costs
• Standard hedging scenarios

High Volatility (40-60% IV):

• Small-cap or volatile stocks
• Higher premium costs
• Aggressive protection needed

See examples/sample_positions.csv for detailed scenarios.

Advanced Analysis

For detailed Greeks calculations, volatility analysis, and advanced scenarios:

See reference.md for:

• Greeks (Delta, Gamma, Theta, Vega) calculations
• Implied volatility impact
• Rolling strategies
• Tax implications
• Break-even analysis across time

Usage Workflow

1. Identify Position: Determine stock, shares, and capital allocation
2. Analyze Strikes: Compare ITM/ATM/OTM protection levels
3. Select Expiration: Choose 30/60/90-day based on cost and maintenance
4. Calculate Metrics: Compute breakeven, max loss, total cost
5. Visualize Payoff: Generate diagram to confirm risk profile
6. Execute Trade: Place stock and put orders simultaneously
7. Monitor Position: Track P/L and plan for put expiration/rolling

Risk Considerations

Advantages:

• Defined maximum loss
• Unlimited profit potential
• Known upfront cost
• Psychological comfort in volatile markets

Disadvantages:

• Reduces overall returns by premium amount
• Time decay erodes put value
• May encourage holding losing positions
• Transaction costs on frequent rolling

Best For:

• New positions in uncertain markets
• Protecting unrealized gains
• Risk-averse investors
• Compliance with mandate risk limits

Required Dependencies

numpy>=1.24.0
pandas>=2.0.0
matplotlib>=3.7.0
scipy>=1.10.0

See requirements.txt for complete list.

Quick Reference

File Organization

married-put-strategy/
├── SKILL.md                    # Main documentation (this file)
├── reference.md                # Advanced Greeks and analysis
├── requirements.txt            # Python dependencies
├── scripts/
│   ├── married_put_calculator.py    # Core calculations
│   ├── strike_comparison.py         # Compare strike prices
│   ├── expiration_analysis.py       # Compare expiration cycles
│   ├── position_sizer.py            # Position sizing logic
│   └── visualizations.py            # Plotting functions
└── examples/
    ├── sample_positions.csv         # 5 example scenarios
    └── README.md                    # Examples documentation