majiayu000 Bear Put Spread Strategy
Version: 1.0 Last Updated: 2025-12-12
Overview
A bear-put-spread is a vertical options strategy that profits from moderate downward price movement while limiting both risk and reward. The strategy involves buying a higher-strike put (closer to ATM) and selling a lower-strike put (further OTM), creating a net debit position with defined maximum loss and profit.
Quick Summary: Buy higher put + Sell lower put = Defined-risk bearish play
Strategy Characteristics
Position Structure:
- Buy 1 put at higher strike (long put)
- Sell 1 put at lower strike (short put)
- Same expiration date
- Same underlying stock
Risk Profile:
- Maximum Loss: Net debit paid (long premium - short premium)
- Maximum Profit: Spread width - Net debit
- Breakeven: Long strike - Net debit
- Best Use: Moderately bearish outlook with defined risk parameters
Cost Components:
- Long put premium (debit)
- Short put premium (credit)
- Net debit = Long premium - Short premium
- Transaction costs: ~$0.65 per contract × 2 legs = $1.30
Quick Start
Calculate bear-put-spread metrics:
from scripts.bear_put_calculator import BearPutSpread
# Example: Bearish on SPY at $450
position = BearPutSpread(
underlying_price=450.00,
long_put_strike=450.00, # Buy ATM put
short_put_strike=445.00, # Sell $5 OTM put
long_put_premium=7.50,
short_put_premium=5.00,
contracts=1
)
# Key metrics
print(f"Max Profit: ${position.max_profit:.2f}")
print(f"Max Loss: ${position.max_loss:.2f}")
print(f"Breakeven: ${position.breakeven_price:.2f}")
print(f"Risk/Reward: {position.risk_reward_ratio:.2f}")
Core Workflow
1. Market Analysis
Identify bearish opportunity with moderate downside target.
Criteria:
- Technical breakdown (support break, bearish pattern)
- Negative fundamental catalyst
- Downtrend confirmation
- Target price identified
2. Strike Selection
Long Put (Higher Strike):
- Typically ATM or slightly ITM
- Delta: -0.45 to -0.55
- Provides directional exposure
Short Put (Lower Strike):
- OTM below long strike
- Delta: -0.20 to -0.35
- Reduces cost, defines max profit
Common Spread Widths:
- Narrow ($2.50-$5): Lower cost, lower profit
- Standard ($5-$10): Balanced risk/reward
- Wide ($10-$20): Higher cost, higher profit potential
See references/strike-selection-guide.md for delta-based framework.
3. Spread Width Analysis
Compare spread configurations:
from scripts.spread_analyzer import analyze_spread_widths
# Compare $2.50, $5, $10 spreads
results = analyze_spread_widths(
underlying_price=450.00,
long_put_strike=450.00,
spread_widths=[2.5, 5.0, 10.0],
volatility=0.22,
days_to_expiration=45
)
# Analyze return on risk for each width
for width, metrics in results.items():
print(f"${width} spread: ROR {metrics['return_on_risk']:.1f}%")
See references/spread-width-analysis.md for optimization.
4. Expiration Cycle Selection
Standard Cycles:
- 30-45 days: Optimal theta decay, standard choice
- 45-60 days: More time for thesis to play out
- 60-90 days: Reduced urgency, lower theta
Considerations:
- Time for bearish thesis to materialize
- Theta decay acceleration (30-45 DTE sweet spot)
- Upcoming events (earnings, Fed meetings)
See references/expiration-analysis.md.
5. Position Sizing
Calculate appropriate contracts based on portfolio risk:
from scripts.position_sizer import calculate_position_size
contracts = calculate_position_size(
portfolio_value=100000,
risk_per_trade=0.02, # 2% portfolio heat
max_loss_per_contract=250 # From spread analysis
)
# Returns: 8 contracts (max risk $2,000)
See references/position-sizing.md.
6. Greeks Analysis
Monitor position Greeks:
from scripts.greeks_calculator import calculate_spread_greeks
greeks = calculate_spread_greeks(
long_put_strike=450.00,
short_put_strike=445.00,
underlying_price=450.00,
volatility=0.22,
time_to_expiration=45/365
)
print(f"Delta: {greeks['delta']:.3f}") # Negative (bearish)
print(f"Theta: {greeks['theta']:.3f}") # Time decay
print(f"Vega: {greeks['vega']:.3f}") # IV sensitivity
See references/greeks-guide.md.
7. Entry Execution
Order Types:
- Limit Order: Specify max net debit willing to pay
- Market Order: Immediate fill (wider slippage)
- Vertical Spread Order: Single order for both legs
Best Practices:
- Enter as single spread order (better pricing)
- Set limit at mid-point of bid/ask spread
- Adjust limit if not filled within 30 seconds
- Avoid wide markets (>10% spread width)
8. Management and Exit
Profit Targets:
- 50% max profit: Close early, reduce risk
- 75% max profit: Near maximum, theta slowing
- Max profit: Hold to expiration (if confident)
Stop Loss:
- 100% of debit: Full loss, thesis invalidated
- 150% of debit: Avoid if spread widens against you
Adjustments:
- Roll down: Lower both strikes if further bearish
- Roll out: Extend expiration if need more time
- Close early: Take profits or cut losses
See references/management-strategies.md.
Scripts
Calculator
# Calculate bear-put-spread metrics
python scripts/bear_put_calculator.py \
--underlying SPY \
--price 450 \
--long-strike 450 \
--short-strike 445 \
--long-premium 7.50 \
--short-premium 5.00 \
--contracts 1
Spread Analyzer
# Compare multiple spread widths
python scripts/spread_analyzer.py \
--underlying SPY \
--price 450 \
--widths 2.5 5.0 10.0 \
--dte 45
Position Sizer
# Calculate optimal contracts
python scripts/position_sizer.py \
--portfolio 100000 \
--risk-percent 2 \
--max-loss 250
References
Core Guides
- quickstart-guide.md - 5-minute overview
- installation-guide.md - Setup instructions
- developer-guide.md - Code standards
Strategy-Specific
- strike-selection-guide.md - Delta-based strike framework
- spread-width-analysis.md - Compare $2.50/$5/$10 spreads
- expiration-analysis.md - 30/45/60 day comparison
- greeks-guide.md - Delta, theta, vega calculations
- position-sizing.md - Portfolio heat calculations
- management-strategies.md - Profit targets, stop loss, adjustments
- examples.md - Real-world scenarios
Dependencies
Required Packages:
numpy>=1.24.0
pandas>=2.0.0
matplotlib>=3.7.0
scipy>=1.10.0
Installation:
pip install -r requirements.txt
Python Version: 3.11+
Risk Warnings
⚠️ Key Risks:
- Limited Profit: Capped at spread width - net debit
- Directional Risk: Requires downward movement to profit
- Time Decay: Theta works against long put if stock doesn't move
- Assignment Risk: Short put may be assigned if ITM at expiration
- Early Assignment: Possible if short put goes deep ITM (rare on index options)
Risk Mitigation:
- Define max loss before entry (net debit paid)
- Use stop loss at 100-150% of debit
- Avoid holding through earnings (IV crush risk)
- Monitor short put for early assignment (if deep ITM)
- Size positions appropriately (2-5% portfolio heat)
When to Use Bear Put Spread
✅ Ideal Scenarios:
- Moderately bearish outlook (5-10% downside expected)
- Want defined risk and defined reward
- Prefer lower cost than buying puts outright
- Time horizon: 30-60 days
- Normal to elevated IV environment
❌ Avoid When:
- Strongly bearish (>15% move expected) - consider long puts
- Neutral outlook - use different strategy
- Very low IV - debit may be too low for good R:R
- Need unlimited profit potential - use long puts
Comparison to Other Strategies
vs. Long Put:
- ✅ Lower cost (short put reduces debit)
- ❌ Limited profit (capped at spread width)
- ✅ Defined risk with better R:R ratio
vs. Put Ratio Spread:
- ✅ Simpler structure (1:1 ratio)
- ✅ No naked short exposure
- ❌ Lower profit potential
vs. Bear Call Spread:
- ❌ Requires debit (capital upfront)
- ✅ Profits from downside move (not time decay)
- ✅ Better for strong bearish conviction
Example Trade
Scenario: SPY at $450, expecting decline to $440-445 over 45 days
Setup:
- Buy 1 SPY $450 put @ $7.50 (debit)
- Sell 1 SPY $445 put @ $5.00 (credit)
- Net debit: $2.50 × 100 = $250 per spread
- Contracts: 4 (based on 2% portfolio risk on $50k account)
Risk Profile:
- Max Loss: $250 × 4 = $1,000 (if SPY > $450 at expiration)
- Max Profit: ($5.00 - $2.50) × 100 × 4 = $1,000 (if SPY ≤ $445)
- Breakeven: $450 - $2.50 = $447.50
- Risk/Reward: 1:1
Outcomes:
- SPY drops to $442: Max profit ($1,000)
- SPY at $447: Breakeven
- SPY at $451: Max loss ($1,000)
Version History
v1.0 (2025-12-12)
- Initial release using SKILL_PACKAGE_TEMPLATE v3.0
- Anthropic + Claude Code compliant (<500 lines)
- Progressive disclosure with references/
- Complete calculator and analysis scripts
- Delta-based strike selection framework
Compliance: Anthropic Best Practices ✅ | Claude Code Compatible ✅ Template: SKILL_PACKAGE_TEMPLATE v3.0 Lines: ~420 (under 500-line limit)