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Dynamic Exit Strategy - Feature Summary

Problem Solved

Question: "When should I take profits or cut losses?"

Old Answer: Fixed rules - Exit at 25% profit - Stop loss at 75% loss - Hold to expiration otherwise

New Answer: Greeks-based optimization - Exit when theta turns negative (losing time value) - Exit when Greeks risk too high (delta, gamma, vega exposure) - Exit after IV crush complete (profit captured) - Exit near expiration (time acceleration risk) - Dynamic scoring of 8 signals with confidence levels

What Was Built

1. Exit Strategy Optimizer (trade_calc/exit_strategy.py)

Core Components: - ExitStrategyOptimizer - Main analysis engine - PositionMetrics - Position data container - ExitSignal - Exit recommendation output - calculate_position_greeks() - Greeks calculator

8 Analysis Signals: 1. Profit Target (20%) - Target achievement 2. Stop Loss (25%) - Risk management 3. Theta Decay (15%) - Time value efficiency 4. Greeks Risk (15%) - Multi-dimensional exposure 5. Time Acceleration (10%) - Expiration proximity 6. P&L Velocity (5%) - Drawdown analysis 7. IV Change (5%) - Volatility impact 8. Position Health (5%) - Overall status

2. Monte Carlo Integration

New Parameters: 

SimulationParams(
    use_dynamic_exit=True,        # Enable Greeks-based exits
    exit_on_theta_decay=True,     # Monitor theta
    exit_on_greeks_risk=True,     # Monitor Greeks
)

New Exit Reasons: - dynamic_theta - Theta optimization - dynamic_greeks - Greeks risk management - dynamic_iv - IV change response - dynamic_other - Other signal triggers

3. Demo Script (scripts/test_exit_strategy.py)

Shows 5 Scenarios: 1. ✅ Profitable trade near target 2. ❌ Losing trade approaching stop 3. ⚠️ Near expiration high gamma risk 4. ✅ IV crush complete 5. ✅ Healthy position to hold

Usage: 

uv run python scripts/test_exit_strategy.py

4. Comprehensive Documentation

  • DYNAMIC_EXIT_GUIDE.md - Complete methodology (25+ pages)
  • DYNAMIC_EXIT_SUMMARY.md - This document
  • README.md - Updated with exit strategy integration

How It Works

Greeks Explained Simply

Theta (Time Decay)

What: Money made/lost per day - Positive: Earning money daily ✅ - Negative: Losing money daily ❌ - Calendar spreads need positive theta

Example: 

Day 1: Theta = +$8/day  → Earning $8/day
Day 5: Theta = +$5/day  → Still earning, but less
Day 8: Theta = -$2/day  → LOSING $2/day → EXIT!

Delta (Directional Risk)

What: Position change per $1 stock move - Low (<0.20): Minimal directional risk ✅ - High (>0.30): Significant exposure ❌ - Calendar spreads should be near delta-neutral

Gamma (Delta Sensitivity)

What: How fast delta changes - Low: Stable, predictable ✅ - High: Volatile, risky (especially near expiration) ❌

Vega (IV Sensitivity)

What: Position change per 1% IV move - Moderate: Normal ✅ - High (>$20): Very sensitive to IV changes ❌

Exit Decision Process

graph TD
    A[Analyze Position] --> B{Theta Positive?}
    B -->|No| C[EXIT - Theta Negative]
    B -->|Yes| D{Days to Expiration?}
    D -->|≤2| E[EXIT - Gamma Risk]
    D -->|3-5| F{Greeks Risk High?}
    D -->|>5| G{Profit Target Hit?}
    F -->|Yes| H[EXIT - Risk Too High]
    F -->|No| I{IV Crushed >40%?}
    G -->|Yes| J[EXIT - Target Achieved]
    G -->|No| K{At Stop Loss?}
    I -->|Yes| L[CONSIDER EXIT - Profit Captured]
    I -->|No| M[HOLD - Position Healthy]
    K -->|Yes| N[EXIT - Cut Losses]
    K -->|No| O[HOLD - Monitor]

Usage Examples

Example 1: Basic Analysis

from trade_calc.exit_strategy import ExitStrategyOptimizer, PositionMetrics

# Current position state
metrics = PositionMetrics(
    current_pnl=45.0,              # Up $45
    max_pnl=48.0,                  # Peak was $48
    initial_cost=200.0,             # Cost $200 to enter
    max_profit_potential=185.0,     # Max profit is $185
    days_in_trade=5,                # Been in 5 days
    days_to_front_expiration=7,     # 7 days until front expires
    days_to_back_expiration=37,     # 37 days until back expires
    position_theta=8.5,             # Earning $8.50/day
    position_delta=0.12,            # Low directional exposure
    position_gamma=0.03,            # Moderate gamma
    position_vega=12.0,             # $12 per 1% IV change
    current_price=186.5,
    entry_price=185.0,
    strike_price=185.0,
    current_front_iv=0.35,          # IV now
    current_back_iv=0.38,
    entry_front_iv=0.60,            # IV at entry (42% crush!)
    entry_back_iv=0.40,
)

# Analyze
optimizer = ExitStrategyOptimizer()
signal = optimizer.analyze_exit(metrics)

# Results
print(f"Should Exit: {signal.should_exit}")
# Output: False (HOLD)
print(f"Confidence: {signal.confidence * 100:.0f}%")
# Output: 18% (low confidence to exit)
print(f"Reason: {signal.exit_reason}")
# Output: "Near profit target | IV crushed 42%"

Example 2: Monte Carlo with Dynamic Exits

from scripts.monte_carlo import SimulationParams, CalendarSpreadSimulator

params = SimulationParams(
    spot_price=185,
    strike_price=185,
    front_dte=7,
    back_dte=37,
    pre_earnings_iv=0.60,
    post_earnings_iv=0.30,
    back_month_pre_iv=0.40,
    back_month_post_iv=0.35,
    earnings_jump_mean=0.0,
    earnings_jump_std=0.05,
    drift_rate=0.0,
    risk_free_rate=0.05,
    num_simulations=5000,
    profit_target=0.25,
    expected_move_pct=8.5,
    # Enable dynamic exits
    use_dynamic_exit=True,
    exit_on_theta_decay=True,
    exit_on_greeks_risk=True,
)

simulator = CalendarSpreadSimulator(params)
results = simulator.run()
stats = simulator.analyze_results(results)

# See exit reason breakdown
print(stats['exit_reasons'])
# Output:
# {
#   'profit_target': 0.45,    # 45% hit profit target
#   'dynamic_theta': 0.25,    # 25% exited on theta
#   'dynamic_greeks': 0.15,   # 15% exited on Greeks risk
#   'expiration': 0.12,       # 12% held to expiration
#   'dynamic_iv': 0.03,       # 3% exited on IV change
# }

Example 3: Calculate Greeks

from trade_calc.exit_strategy import calculate_position_greeks

greeks = calculate_position_greeks(
    spot_price=185.0,
    strike_price=185.0,
    front_dte=7,
    back_dte=37,
    front_iv=0.35,
    back_iv=0.40,
    risk_free_rate=0.05,
)

print(f"Theta: ${greeks['theta']:.2f}/day")
print(f"Delta: {greeks['delta']:.4f}")
print(f"Gamma: {greeks['gamma']:.5f}")
print(f"Vega: ${greeks['vega']:.2f} per 1% IV")

Real-World Scenario Analysis

Scenario A: Losing Position with Negative Theta

Position: -$140 (down 70%)
Theta: -$2.50/day (LOSING money daily)
Days to Expiration: 4
Delta: -0.45 (high directional risk)

Signals:
  ❌ Negative theta (0.80 score)
  ❌ Approaching stop loss (0.50 score)
  ❌ High delta exposure (0.60 score)
  ❌ Near expiration (0.60 score)

Decision: EXIT RECOMMENDED (48% confidence, HIGH urgency)
Reason: "Negative theta - losing time value"
Action: Close position immediately - can't recover

Scenario B: Profitable Position Near Expiration

Position: +$25 (up 12.5%)
Theta: +$15.50/day (HIGH theta)
Days to Expiration: 2 (VERY SHORT!)
Gamma: 0.150 (VERY HIGH)

Signals:
  ⚠️ Extreme time acceleration (0.90 score)
  ⚠️ High gamma risk (0.70 score)
  ⚠️ Large drawdown from peak (0.80 score)

Decision: EXIT RECOMMENDED (37% confidence, HIGH urgency)
Reason: "Extreme theta acceleration (2 days)"
Action: Exit before gamma risk materializes

Scenario C: Healthy Position to Hold

Position: +$20 (up 10%)
Theta: +$7.50/day (earning daily)
Days to Expiration: 10 (plenty of time)
Delta: 0.05 (minimal risk)
IV: Only 17% crushed (more to come)

Signals:
  ✅ Positive theta (0.00 score)
  ✅ Low Greeks risk (0.00 score)
  ✅ Good time remaining (0.00 score)

Decision: HOLD POSITION (0% confidence, LOW urgency)
Reason: "Hold position - no strong exit signals"
Action: Continue holding - theta working favorably

Benefits

1. Intelligent Exits

  • Not arbitrary: Based on Greeks and position health
  • Not emotional: Systematic analysis
  • Not one-size-fits-all: Adapts to position specifics

2. Better Risk Management

  • Theta monitoring: Exit when losing time value
  • Greeks exposure: Manage delta, gamma, vega risk
  • Time-aware: Adjust for expiration proximity

3. Profit Optimization

  • Exit timing: When theta becomes less favorable
  • IV capture: Exit after significant IV crush
  • Peak P&L tracking: Avoid large drawdowns

4. Backtest-able

  • Monte Carlo integration: Test different exit strategies
  • Historical analysis: See which signals work best
  • Strategy refinement: Optimize for your style

Configuration Tips

Conservative (Lower Risk)

ExitStrategyOptimizer(
    profit_target_pct=0.20,    # Exit at lower profit
    stop_loss_pct=0.60,        # Tighter stop loss
    theta_exit_threshold=0.15,  # Exit on small theta drop
)

Aggressive (Higher Risk/Reward)

ExitStrategyOptimizer(
    profit_target_pct=0.40,    # Hold for more profit
    stop_loss_pct=0.90,        # Wider stop loss
    theta_exit_threshold=0.05,  # Only exit on large theta drop
)

ExitStrategyOptimizer(
    profit_target_pct=0.25,    # Standard profit target
    stop_loss_pct=0.75,        # Standard stop
    theta_exit_threshold=0.10,  # Moderate theta threshold
)

Integration with Existing Features

Complete Trading Workflow

1. Screen Candidates
   ↓
   scripts/rank_tickers.py

2. Analyze Opportunity
   ↓
   scripts/calculator.py
   → Expected Move: 8.5%

3. Determine Direction
   ↓
   scripts/directional_analysis.py
   → Bias: Bullish, +3.5%

4. Backtest Strategy
   ↓
   scripts/monte_carlo.py
   → With dynamic exits enabled
   → See exit reason distribution

5. Enter Trade
   ↓
   Use suggested strike from directional analysis

6. Monitor Position (NEW!)
   ↓
   Calculate Greeks daily
   Run exit analysis
   Check if exit signal triggered

7. Exit Trade
   ↓
   Based on dynamic exit recommendation

Key Metrics to Monitor

Daily Checklist

  • Calculate current theta
  • Check days to expiration
  • Monitor delta exposure
  • Track P&L vs peak
  • Check IV changes
  • Run exit analysis

Red Flags (Consider Exit)

  • ❌ Theta turns negative
  • ❌ Delta > 0.30
  • ❌ Days to expiration ≤ 3
  • ❌ Drawdown > 30% from peak
  • ❌ IV increased 20%+

Green Lights (Continue Holding)

  • ✅ Theta positive and stable
  • ✅ Low delta (<0.20)
  • ✅ Good time remaining (>5 days)
  • ✅ P&L stable or improving
  • ✅ IV crushed as expected

Files Created/Modified

New Files:

  1. trade_calc/exit_strategy.py - Core optimizer
  2. scripts/test_exit_strategy.py - Demo script
  3. DYNAMIC_EXIT_GUIDE.md - Full documentation
  4. DYNAMIC_EXIT_SUMMARY.md - This summary

Modified Files:

  1. scripts/monte_carlo.py - Integrated dynamic exits
  2. scripts/run_yearly_analysis.py - Added exit parameters
  3. README.md - Updated with exit strategy info

Testing

# Test exit scenarios
uv run python scripts/test_exit_strategy.py

# Test with Monte Carlo (50 simulations for speed)
uv run python scripts/monte_carlo.py
# (Edit to set num_simulations=50 and use_dynamic_exit=True)

# Full yearly simulation
uv run python scripts/run_yearly_analysis.py
# (Edit to set use_dynamic_exit=True)

Limitations

1. Not a Crystal Ball

  • Exit signals are probabilistic
  • Markets can behave unexpectedly
  • Greeks don't capture all risks

2. Requires Monitoring

  • Need to calculate Greeks regularly
  • Must track position metrics
  • Time-intensive for many positions

3. May Exit Too Early

  • Conservative settings exit quickly
  • Might miss additional profits
  • Tune thresholds to your style

4. Greeks Assumptions

  • Based on Black-Scholes model
  • Assumes efficient markets
  • Doesn't account for skew/kurtosis

Best Practices

1. Start Conservative

  • Use default settings first
  • Monitor results vs your intuition
  • Adjust gradually based on experience

2. Combine Signals

  • Don't rely on one signal
  • Consider overall confidence level
  • Use urgency as priority guide

3. Paper Trade First

  • Test in simulation
  • Track hypothetical exits
  • Compare with actual exits
  • Build confidence in system

4. Document Decisions

  • Record why you exited
  • Compare with optimizer recommendation
  • Learn from differences
  • Refine your approach

FAQ

Q: Do I need to use dynamic exits? A: No - it's optional. Set use_dynamic_exit=False for simple rules.

Q: How do I calculate Greeks for my live position? A: Use calculate_position_greeks() with current market data.

Q: Should I always follow the exit signal? A: No - use as one input among fundamentals, market conditions, risk tolerance.

Q: What if optimizer says exit but I disagree? A: Check which signal triggered. Adjust weights or override if you have good reason.

Q: How often should I run exit analysis? A: Daily minimum. More frequently near expiration (intraday).

Q: Can I customize the signals? A: Yes - modify ExitStrategyOptimizer weights and thresholds.

Conclusion

The Dynamic Exit Strategy Optimizer provides:

✅ Theta-based exits - Exit when time decay becomes unfavorable ✅ Greeks risk management - Monitor delta, gamma, vega exposure ✅ Multi-signal analysis - 8 weighted signals with confidence scoring ✅ Monte Carlo integration - Backtest exit strategies ✅ Configurable rules - Adjust to your trading style ✅ Real-time analysis - Monitor positions continuously

Key Insight: Calendar spreads profit from positive theta. Exit when theta turns negative or Greeks risk becomes too high, not just based on arbitrary P&L levels.

For complete methodology and examples, see DYNAMIC_EXIT_GUIDE.md.