Volatility Metrics
Volatility measures price variability over time. Understanding volatility is essential for options trading, position sizing, and risk management. This guide covers volatility concepts in depth.
Types of Volatility
Historical (Realized) Volatility
Actual price variability that has occurred, measured from past price data.
Standard Calculation:
1. Calculate daily log returns: r = ln(Close_t / Close_t-1)
2. Calculate standard deviation of returns over N days
3. Annualize: RV = StdDev × √252
Common Windows:
- 10-day RV: Short-term actual volatility
- 20-day RV: Standard comparison period
- 30-day RV: Matches VIX horizon
Interpretation:
- Higher RV indicates larger recent price swings
- Lower RV indicates stable, range-bound price action
- RV is backward-looking (what actually happened)
Implied Volatility
The market's expectation of future volatility, derived from option prices.
Key Concept: Option prices contain an implied volatility component. Given the price of an option, you can solve for the volatility assumption that would produce that price.
VIX as Implied Volatility:
- VIX measures 30-day implied volatility for S&P 500
- Derived from weighted strip of SPX option prices
- Forward-looking (market's expectation)
Interpretation:
- Higher IV: Market expects larger future price swings
- Lower IV: Market expects stability
- IV is a market consensus, not a prediction
The VIX Family
VIX Index
The CBOE Volatility Index, measuring expected 30-day S&P 500 volatility.
Historical Ranges:
| Level | Interpretation |
|---|---|
| 9-12 | Extremely low, complacent |
| 12-15 | Low volatility |
| 15-20 | Normal volatility |
| 20-25 | Elevated |
| 25-35 | High volatility |
| 35-50 | Very high, market stress |
| 50+ | Extreme, crisis |
VIX Characteristics:
- Mean-reverting (extremes tend to normalize)
- Spikes quickly, declines slowly
- Negatively correlated with S&P 500
- Cannot go below zero
VVIX (Volatility of VIX)
Expected volatility of the VIX itself, derived from VIX options.
Purpose: Measures uncertainty about future VIX levels.
Interpretation:
| Level | Interpretation |
|---|---|
| 70-80 | Low VIX uncertainty |
| 80-100 | Normal range |
| 100-120 | Elevated uncertainty |
| 120-150 | High uncertainty |
| 150+ | Extreme uncertainty |
Applications:
- VVIX spikes often precede major market moves
- Extreme VVIX readings can signal regime changes
- Low VVIX may indicate complacency
VIX3M and VIX6M
Longer-horizon volatility expectations.
- VIX3M: Expected 3-month volatility
- VIX6M: Expected 6-month volatility
Term Structure Ratio:
Ratio = VIX3M / VIX
- Ratio > 1.0: Contango (normal)
- Ratio < 1.0: Backwardation (stressed)
VIX Term Structure
Contango (Normal State)
Front-month VIX futures trade below back-month futures.
Why It Occurs:
- VIX tends to spike during stress
- Longer-dated futures price in higher average volatility
- Insurance premium for uncertainty further out
Frequency: Approximately 85% of the time
Implications:
- VIX futures buyers face roll cost (buy high, sell low)
- Volatility products (VXX, UVXY) decay over time
- Selling volatility has structural edge
Backwardation (Stressed State)
Front-month VIX futures trade above back-month futures.
Why It Occurs:
- Current volatility is high
- Market expects volatility to decrease
- Near-term demand for protection exceeds supply
Frequency: Approximately 15% of the time
Implications:
- VIX futures sellers face roll cost
- Volatility products can rally sharply
- Often signals climactic conditions
Volatility Risk Premium
The spread between implied and realized volatility.
Calculation:
VRP = VIX - Realized Volatility (20-day)
Why VRP Exists
Several factors create the volatility risk premium:
- Insurance Demand: Investors pay for downside protection
- Uncertainty Aversion: Markets price in worst-case scenarios
- Gamma Risk: Option sellers demand compensation for gap risk
- Behavioral Factors: People overweight recent volatility events
VRP Levels
| VRP | Interpretation |
|---|---|
| Negative | Rare; realized > implied |
| 0-2 | Low premium |
| 2-5 | Normal premium |
| 5-10 | Elevated premium |
| 10+ | High premium |
Historical Average: VRP averages 3-5 points over time.
Trading VRP
When VRP is High:
- Options are "expensive" relative to actual volatility
- Selling premium may be attractive
- Consider short volatility strategies
When VRP is Low/Negative:
- Options are "cheap" relative to actual volatility
- Buying protection is relatively inexpensive
- Consider long volatility strategies
Caution: VRP can remain at extremes for extended periods.
Volatility Regimes
Markets cycle through different volatility regimes.
Low Volatility Regime
Characteristics:
- VIX in 10-15 range
- Steep contango
- Low VVIX
- Extended duration possible
Implications:
- Options are cheap
- Trend strategies work well
- Complacency risk builds
Normal Volatility Regime
Characteristics:
- VIX in 15-25 range
- Moderate contango
- Normal VVIX
- Most common regime
Implications:
- Standard risk management applies
- Both trend and mean reversion work
- Balanced approach appropriate
High Volatility Regime
Characteristics:
- VIX above 25
- Backwardation possible
- Elevated VVIX
- Often follows market selloff
Implications:
- Reduce position sizes
- Wider stops required
- Mean reversion opportunities emerge
- Options are expensive
Crisis Regime
Characteristics:
- VIX above 40
- Deep backwardation
- VVIX extremely elevated
- Market in freefall
Implications:
- Preservation mode
- Capitulation indicators
- Eventual mean reversion opportunity
- Recovery can be swift
Practical Applications
Position Sizing
Use volatility for position sizing:
Position Size = Risk Dollars / (ATR × Multiplier)
Smaller positions in high volatility environments.
Stop Placement
Volatility-based stops adapt to market conditions:
Stop = Entry - (ATR × Multiplier)
Common Multipliers:
- Tight: 1.5× ATR
- Normal: 2× ATR
- Wide: 3× ATR
Options Trading
High VRP Environment:
- Consider selling premium (covered calls, credit spreads)
- Iron condors in range-bound markets
- Put writing in uptrends
Low VRP Environment:
- Consider buying protection
- Long straddles before events
- Calendar spreads for time decay