Historical Volatility Skew

Track implied volatility curves across strikes over time

Historical Volatility Skew

Volatility skew, also called the IV smile or smirk, shows how implied volatility varies across different strike prices. Analyzing historical skew patterns helps traders identify mispricings, understand market sentiment, and predict potential market moves.

What Is Volatility Skew?

Volatility skew refers to the pattern of implied volatility across strikes:

  • Put Skew: Downside puts have higher IV than ATM (protective puts premium)
  • Call Skew: Upside calls have higher IV than ATM (tail risk pricing)
  • Smile: Both wings have elevated IV (uncertainty in both directions)

Why Skew Matters

Market Sentiment Indicator

  • Steep put skew: Fear of downside, protective buying
  • Steep call skew: Upside uncertainty or event risk
  • Flat skew: Neutral sentiment or complacency

Trading Opportunities

  • Overpriced options: High IV strikes to sell
  • Underpriced options: Low IV strikes to buy
  • Relative value: Compare skew to historical norms

Chart Components

Skew Curve

  • X-Axis: Strike prices (or moneyness %)
  • Y-Axis: Implied volatility (%)
  • Call Curve: Green line showing call IV by strike
  • Put Curve: Red line showing put IV by strike
  • ATM Marker: Reference point at current price

Key Metrics

  • Skew Steepness: How rapidly IV changes with strike
  • 25-Delta Skew: IV difference between 25-delta put and call
  • 90/110 Skew: IV at 90% vs 110% of spot price
  • Minimum IV: Usually occurs near ATM

Historical Analysis Use Cases

Trend Identification

Increasing Put Skew:

  • Growing fear or uncertainty
  • Hedging demand increasing
  • Often precedes market weakness
  • Can indicate volatility regime change

Decreasing Put Skew:

  • Reducing fear
  • Complacency increasing
  • Often occurs in strong uptrends
  • May signal overconfidence

Mean Reversion Trading

  • Extreme skew often reverts to mean
  • Historically steep skew suggests overpricing
  • Flat skew in typically skewed markets suggests underpricing
  • Compare current skew to historical range

Event Risk Pricing

  • Earnings approach: Skew often flattens (straddle buying)
  • Post-earnings: Skew normalizes (IV crush)
  • Special events: Directional skew based on expected impact
  • Binary events: Often create call or put skew

Interpreting Skew Patterns

Normal Equity Skew (Put Skew)

  • Puts more expensive than calls at same delta
  • Reflects crash insurance premium
  • Typical in bull markets
  • Historical norm for stocks

Reverse Skew (Call Skew)

  • Calls more expensive than puts
  • Often seen in:
    • Commodities (supply disruption fear)
    • Takeover targets (upside cap uncertainty)
    • Momentum stocks (FOMO)
    • Beaten-down stocks (recovery potential)

Symmetric Smile

  • Both wings elevated equally
  • Indicates:
    • Binary event (earnings, FDA approval)
    • High uncertainty in both directions
    • Potential large move, direction unknown
    • Often before major announcements

Trading Strategies Based on Skew

Skew Trades

Sell Expensive Wing:

  • Sell overpriced far OTM puts when skew is steep
  • Sell call skew when calls are elevated
  • Use spreads to define risk

Buy Cheap Wing:

  • Buy relatively cheaper side of skew
  • Ratio spreads to take advantage
  • Calendar spreads at different skew points

Relative Value

  • Compare current skew to historical average
  • Trade deviations from norm
  • Sell abnormally high skew, buy abnormally low

Volatility Arbitrage

  • Exploit skew mispricings
  • Delta-hedge to isolate volatility
  • Capture mean reversion in skew

Skew by Market Condition

Bull Markets

  • Typical: Moderate put skew
  • Risk: Complacency flattens skew dangerously
  • Opportunity: Cheap downside protection

Bear Markets

  • Typical: Extreme put skew
  • Risk: Overpaying for protection
  • Opportunity: Sell elevated put premium

High Volatility Environments

  • Typical: Overall higher IV across all strikes
  • Skew: Often steepens significantly
  • Trading: Sell premium strategies more attractive

Low Volatility Environments

  • Typical: Flatter skew
  • Risk: Underpricing of tail risks
  • Trading: Cheap protection, long volatility plays

Advanced Skew Analysis

Skew Momentum

  • Increasing skew: Fear building
  • Decreasing skew: Fear subsiding
  • Rapid changes: Important sentiment shifts
  • Divergences: Skew vs price action

Term Structure + Skew

  • Near-term skew vs far-term skew
  • Event impact on skew
  • Skew changes across expirations
  • Calendar spread opportunities

Skew vs Realized Volatility

  • Skew predicts tail moves
  • Compare to actual tail movements
  • Identify if tail risk over/underpriced
  • Historical accuracy of skew pricing

Best Practices

Analysis Workflow

  1. Check current skew vs historical average
  2. Identify any unusual patterns or extremes
  3. Consider market context and upcoming events
  4. Compare to other volatility indicators
  5. Determine if current pricing is rational

Warning Signs

  • Extremely flat skew: Potential complacency
  • Unprecedented steepness: Possible panic
  • Sudden skew changes: Major sentiment shift
  • Skew divergence from fundamentals: Potential mispricing

Common Pitfalls

  • Assuming skew always mean reverts (it doesn’t)
  • Ignoring upcoming catalysts
  • Not adjusting for market regime changes
  • Over-trading small skew variations

Integration with Other Indicators

Put/Call Ratios

  • High put/call + steep put skew = extreme fear
  • Low put/call + flat skew = complacency
  • Divergences may signal reversals

Volume Analysis

  • High volume in skewed strikes confirms pricing
  • Low volume in expensive strikes = fade opportunity
  • Volume shifts can predict skew changes

Price Action

  • Skew should align with technical levels
  • Support/resistance affects local skew
  • Breakouts often compress skew

Data and Availability

Calculation: IV extracted from option prices using Black-Scholes Strikes Analyzed: Typically 10-20% OTM on each side Expirations: Focus on near-term (30-60 DTE) for most liquid data Historical Data: 15+ years available Update Frequency: Daily Subscription: Delta plan and higher

Example Scenarios

Pre-Earnings

  • Before: Flat skew, elevated overall IV (straddle buying)
  • After: Skew normalizes, IV crushes
  • Trade: Sell elevated IV before event

Market Correction

  • During: Steep put skew develops
  • Recovery: Skew slowly normalizes
  • Trade: Sell put premium as fear subsides

Takeover Rumor

  • Develops: Call skew emerges (upside uncertainty)
  • Resolution: Skew disappears if deal announced
  • Trade: Buy cheap puts (hedge), sell elevated calls

Disclaimer: Skew analysis is probabilistic and doesn’t guarantee outcomes. Always consider skew in context of broader market analysis and use proper risk management.


Related Docs

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Historical Analytics
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