Expected Move Analysis
The Expected Move analysis provides historical insights into implied volatility-based price movement predictions and their accuracy over time.
What is Expected Move?
Expected Move represents the market’s prediction of how much a stock price is likely to move by expiration, based on current option prices and implied volatility.
Calculation Method
Formula:
Expected Move = Stock Price × Implied Volatility × √(Days to Expiration / 365)
Key Components:
- Current stock price
- At-the-money implied volatility
- Time to expiration
- Standard statistical distributions
Historical Analysis Features
1. Expected vs Actual Moves
Track prediction accuracy over time:
- Predicted Range: IV-based expected move
- Actual Range: Realized price movement
- Accuracy Rate: Percentage of correct predictions
- Trend Analysis: Improving or declining accuracy
2. By Expiration Cycle
Analyze accuracy across different time frames:
- Weekly Expirations: 0-7 days
- Monthly Expirations: 20-35 days
- Quarterly Expirations: 60-90 days
- LEAPS: 180+ days
3. Market Regime Analysis
Compare expected move accuracy during:
- Bull Markets: Rising trending periods
- Bear Markets: Declining trending periods
- Sideways Markets: Range-bound periods
- High Volatility: VIX > 30 periods
4. Event Impact
Measure expected move around specific events:
- Earnings Announcements: Pre/post earnings accuracy
- FOMC Meetings: Fed decision impacts
- Economic Data: Major economic releases
- Company Events: Mergers, splits, etc.
Key Metrics
Accuracy Measurements
Historical Hit Rate:
- Percentage of time actual move stayed within expected range
- Broken down by time frame and market conditions
- Moving averages for trend identification
Over/Under Predictions:
- Times IV underestimated actual movement
- Times IV overestimated actual movement
- Bias analysis (systematic over/under prediction)
Volatility Risk Premium:
- Difference between implied and realized volatility
- Market’s tendency to overprice or underprice risk
- Historical risk premium trends
Using Expected Move Analysis
For Options Trading
Strategy Selection:
- High accuracy periods: Directional strategies
- Low accuracy periods: Volatility strategies
- Consistent overestimation: Short volatility
- Consistent underestimation: Long volatility
Entry/Exit Timing:
- Buy options when IV underestimates moves
- Sell options when IV overestimates moves
- Adjust position sizing based on accuracy trends
For Risk Management
Position Sizing:
- Larger positions during high-accuracy periods
- Smaller positions during uncertain periods
- Diversification based on prediction reliability
Stop Losses:
- Tighter stops when moves are predictable
- Wider stops during unpredictable periods
- Dynamic adjustment based on historical patterns
Chart Interpretations
Accuracy Trends
Improving Accuracy:
- Rising trend in prediction success rate
- More reliable for planning strategies
- Higher confidence in volatility estimates
Declining Accuracy:
- Falling trend in prediction success
- Increased market uncertainty
- More volatile, unpredictable environment
Volatility Bias
Consistent Overestimation:
- IV regularly higher than realized movement
- Opportunity for volatility sellers
- Market pricing in excess fear/uncertainty
Consistent Underestimation:
- IV regularly lower than actual movement
- Opportunity for volatility buyers
- Market being surprised by events
Time Frame Analysis
Short-Term (0-7 days)
Characteristics:
- Lower prediction accuracy
- Higher gamma risk
- Event-driven movements
- News and catalyst dependent
Trading Implications:
- Focus on known events
- Tight risk management
- Quick profit-taking
Medium-Term (8-45 days)
Characteristics:
- Moderate prediction accuracy
- Balanced risk/reward
- Trend following opportunities
- Technical analysis relevant
Trading Implications:
- Most reliable timeframe
- Good for swing trading
- Allows for strategy adjustment
Long-Term (45+ days)
Characteristics:
- Higher prediction accuracy
- Lower time decay impact
- Fundamental factor influence
- Economic cycle considerations
Trading Implications:
- More predictable outcomes
- Lower volatility risk
- Suitable for conservative strategies
Market Condition Impact
Low Volatility Environments
Typical Patterns:
- Higher prediction accuracy
- Smaller expected moves
- Mean-reverting behavior
- Compressed option premiums
Trading Opportunities:
- Short volatility strategies
- Range-bound trading
- Covered call writing
- Put selling
High Volatility Environments
Typical Patterns:
- Lower prediction accuracy
- Larger expected moves
- Trending behavior
- Elevated option premiums
Trading Opportunities:
- Long volatility strategies
- Breakout trading
- Protective puts
- Straddle/strangle strategies
Sector Variations
Different sectors show varying expected move accuracy:
Technology Stocks:
- Higher volatility
- Lower prediction accuracy
- Event-driven movements
- Earnings surprises common
Utility Stocks:
- Lower volatility
- Higher prediction accuracy
- Dividend-focused
- Interest rate sensitive
Financial Stocks:
- Moderate volatility
- Economic cycle dependent
- Regulatory event sensitive
- Credit cycle correlation
Best Practices
Analysis Workflow
- Review Historical Accuracy: Check recent prediction success rates
- Identify Patterns: Look for seasonal or cyclical trends
- Consider Market Regime: Factor in current volatility environment
- Check Event Calendar: Account for upcoming known events
- Adjust Expectations: Modify strategies based on accuracy trends
Common Pitfalls
Over-Reliance on Patterns:
- Historical patterns don’t guarantee future results
- Market conditions change
- Black swan events unpredictable
Ignoring Market Context:
- Economic environment matters
- Sector-specific factors important
- Company-specific events significant
Data Sources
Historical expected move data includes:
- 15+ years of calculation history
- All major US stocks and ETFs
- Multiple expiration cycles
- Various market conditions
Limitations
Model Assumptions:
- Assumes normal distribution
- Based on historical volatility patterns
- May not account for all factors
Market Changes:
- Algorithm trading impact
- Options market evolution
- Changing volatility patterns
External Factors:
- Unprecedented events
- Regulatory changes
- Global market shifts
Note: Expected move analysis is a tool for understanding market predictions and their historical accuracy. It should be combined with other analysis methods and proper risk management. Past accuracy does not guarantee future performance.
