Volatility Skew Analysis

Volatility skew shows how implied volatility varies across different strike prices for options with the same expiration date. This tool helps you visualize and analyze volatility patterns to identify market sentiment and potential trading opportunities.

When to use this calculator:

  • When evaluating market sentiment and tail risk pricing
  • When exploring relative value between options at different strike prices
  • When planning strategies that can exploit skew dynamics (ratio spreads, risk reversals)
  • When assessing how the market is pricing downside risk vs. upside potential
  • When comparing current skew patterns to historical norms

Implied Volatility Calculator

Calculate and analyze implied volatility

Understanding Volatility Skew

What is Volatility Skew?

Volatility skew represents the disparity in implied volatility levels across option strikes with the same expiration date.

  • • Negative/Downward Skew: Higher IVs for lower strikes than higher strikes (common in equity markets)
  • • Positive/Upward Skew: Higher IVs for higher strikes than lower strikes (rare, sometimes seen in commodities)
  • • Volatility Smile: Higher IVs for both low and high strikes compared to at-the-money options
  • • Flat Skew: Similar IVs across all strikes (rare, typically seen in low-volatility environments)

Key concept: The shape of the skew often reflects the market's perception of risk and direction.

Causes of Volatility Skew

Several factors contribute to the existence and shape of volatility skew:

  • • Crash Risk: Fear of market crashes driving demand for downside protection (puts)
  • • Supply/Demand Imbalance: Institutional hedging creating persistent demand for OTM puts
  • • Non-Normal Returns: Markets exhibit fat tails and skewness not captured by lognormal models
  • • Leverage Effect: Stocks tend to become more volatile as they fall (negative correlation between price and volatility)

Historical context: Volatility skew became pronounced after the 1987 market crash as traders began pricing in tail risk.

Skew Analysis Fields Explained

  • Stock Price:

    The current market price of the underlying asset.

  • Base Volatility:

    The at-the-money (ATM) implied volatility, serving as a reference point.

  • Strike Prices:

    A comma-separated list of option strike prices to analyze for the skew pattern.

  • Days to Expiry:

    Number of days until expiration for the option series being analyzed.

  • Interest Rate:

    Risk-free interest rate used in the model.

  • Option Type:

    Call or put options (skew analysis typically shows both).

Understanding Skew Analysis Results

Numerical Metrics

  • Skew Slope:

    Measures the steepness of the volatility skew. More negative values indicate steeper downward skew.

  • Put-Call Skew:

    The difference in IV between equidistant put and call strikes, showing the asymmetry in pricing.

  • IV Range:

    The spread between the highest and lowest implied volatilities across the analyzed strikes.

Graphical Analysis

  • Skew Curve:

    Visual representation of how implied volatility varies across different strike prices.

  • Moneyness:

    Displays strike prices as a ratio to the current stock price (Strike/Stock), normalizing across different underlyings.

  • At-The-Money Point:

    The reference point where the strike price equals the current stock price (moneyness = 1.0).

Common Skew Patterns & Market Implications

Steep Downward Skew

Much higher IV for OTM puts compared to ATM options:

  • Indicates high demand for downside protection
  • Often seen during market stress or ahead of anticipated negative events
  • May suggest expensive puts and relatively cheap calls
  • Common in equity indices and stocks with significant downside risk

Flattening Skew

Skew becoming less steep than historical norms:

  • May indicate decreasing concern about downside risk
  • Often occurs in strong bull markets or complacent periods
  • Can signal potential market tops when extremely flat
  • May represent relative value opportunity in buying downside protection

Steepening Skew

Skew becoming more pronounced than historical norms:

  • Suggests increasing fear about downside events
  • May precede market corrections or volatility events
  • Represents potential mispricing (expensive puts vs. calls)
  • Common before major economic releases or political events

Volatility Smile

Higher IV at both ends of strike spectrum:

  • Indicates market pricing in both upside and downside tail risk
  • Common in currency options and commodities
  • May appear during uncertain environments with binary outcomes
  • Sometimes seen in stocks with takeover speculation

Skew Dynamics Over Time

How skew patterns evolve with market conditions:

  • During Corrections: Skew typically steepens rapidly as put demand increases
  • During Bull Markets: Skew often gradually flattens as fear subsides
  • Pre-Events: Skew may steepen before known risk events (elections, earnings)
  • Post-Events: Skew typically normalizes after uncertainty resolves

Comparing Skews Across Assets

How skew patterns differ across markets:

  • Equity Indices: Typically have the steepest negative skews
  • Individual Stocks: Varied skews based on industry and risk profile
  • Commodities: Often exhibit volatility smiles rather than skews
  • Currencies: Skew reflects directional expectations and risk asymmetry

Trading Strategies Based on Volatility Skew

Risk Reversals

Exploiting differences in put vs. call pricing

  • Buy OTM call, sell OTM put (or vice versa)
  • Used when skew seems overly steep or flat
  • Benefits when skew normalizes
  • Directional exposure with skew component

Ratio Spreads

Taking advantage of relative pricing

  • Buy ATM options, sell multiple OTM options
  • Capitalizes on expensive OTM options
  • Can be structured with puts or calls
  • Profitable when skew is extreme

Put vs. Call Spreads

Selecting optimal spread types based on skew

  • Use call spreads when puts are expensive
  • Use put spreads when calls are expensive
  • Compare risk/reward across spread types
  • Optimize spread width based on skew slope

Skew Analysis Pitfalls & Limitations

  • Skew patterns can persist for extended periods without reverting to "normal"
  • Skew analysis requires comparison to historical norms for proper context
  • Changes in skew don't necessarily predict market direction
  • Liquidity differences across strikes can distort implied volatility measurements
  • Artificially steep skews can appear in stocks with corporate actions or special situations

Practical Tips for Skew Analysis

  • Compare current skew to historical patterns for the same underlying
  • Look for meaningful changes in skew rather than absolute levels
  • Consider combining skew analysis with other volatility metrics (IV rank, term structure)
  • Use normalized moneyness (Strike/Stock Price) when comparing skews across different assets
  • Pay attention to skew changes ahead of known events or when market sentiment shifts
  • Consider liquidity and bid-ask spreads when interpreting skew data from less liquid options