Key Takeaways
- Implied volatility varies by option strike price.
- Negative skew signals bearish sentiment, puts expensive.
- Positive skew indicates bullish demand for calls.
- Skew helps traders gauge market risk aversion.
What is Volatility Skew?
Volatility skew refers to the uneven distribution of implied volatility (IV) across different strike prices for options on the same underlying asset and expiration date. This phenomenon reveals market sentiment by showing how IV varies for out-of-the-money (OTM), at-the-money (ATM), and in-the-money (ITM) options, contrary to the assumption of constant volatility in models like Black-Scholes.
Understanding volatility skew helps you interpret supply-demand imbalances and risk preferences in the options market, offering insights into potential price movements and investor behavior.
Key Characteristics
Volatility skew displays unique features that reflect market dynamics:
- Asymmetric IV distribution: IV is typically higher for OTM options than ATM ones, forming either a smile or an asymmetric skew curve.
- Negative skew: Higher IV on OTM puts signals bearish sentiment and demand for downside protection, common in equity markets like JPMorgan Chase.
- Positive skew: Elevated IV on OTM calls indicates bullish optimism, often seen during strong rally phases.
- Flat skew: Rare cases where IV is uniform across strikes, suggesting neutral market expectations.
- Risk reversal metric: The difference between 25-delta call and put IV quantifies skew direction and magnitude.
How It Works
Volatility skew emerges because investors value downside protection differently than upside potential, causing supply-demand imbalances for options. Typically, OTM puts carry higher premiums due to their role in hedging against sudden drops or tailrisk events.
For example, the implied volatility of 25-delta puts often exceeds that of ATM options, reflecting increased risk aversion. Traders measure skew by comparing IV at various strikes, using this data to identify market sentiment and adjust strategies accordingly.
Examples and Use Cases
Volatility skew plays an important role in real-world trading and risk management:
- Technology sector: Companies like Microsoft often show positive skew during strong market rallies, as investors seek leverage through OTM calls.
- Financial stocks: JPMorgan Chase exhibits typical negative skew patterns, highlighting demand for downside protection in uncertain times.
- Market indices: The S&P 500 ETF SPY frequently displays pronounced negative skew, reflecting broad market risk aversion and hedging activity.
Important Considerations
When analyzing volatility skew, keep in mind that skew varies across asset classes and time horizons, often steepening before market downturns. Relying solely on skew without considering broader market context or objective probability can lead to misinterpretation.
Incorporate skew analysis alongside other indicators and maintain awareness of data limitations to enhance your options trading and risk management decisions effectively.
Final Words
Volatility skew reveals how market sentiment shapes option pricing across strike prices, signaling risk appetite or fear. To leverage this insight, compare skew patterns when evaluating option strategies or assessing market outlooks.
Frequently Asked Questions
Volatility skew refers to the uneven distribution of implied volatility across different strike prices for options on the same underlying asset and expiration date. It shows how market expectations of future volatility vary, often revealing investor sentiment through higher implied volatility on out-of-the-money puts or calls.
Volatility skew occurs due to supply and demand imbalances for options at different strikes, contradicting the Black-Scholes assumption of constant volatility. It indicates market sentiment, where higher implied volatility on out-of-the-money puts suggests bearishness, while higher IV on calls points to bullish optimism.
There are three main types: negative skew where out-of-the-money puts have higher implied volatility indicating bearish sentiment; positive skew where out-of-the-money calls have higher IV suggesting bullishness; and flat skew where implied volatility is roughly equal across strikes, which is rare.
Traders interpret a steep negative skew as a sign of increased risk aversion and panic selling of puts for downside protection, often before market drops. Conversely, a positive skew indicates optimism and demand for upside exposure, helping traders anticipate market moves.
Volatility skew is often measured by comparing implied volatility differences between out-of-the-money options and at-the-money options, such as the 25-delta put or call IV minus the ATM IV. Another method involves the risk reversal, which is the difference between 25-delta call IV and 25-delta put IV.
Historical crashes tend to amplify the negative volatility skew because investors rush to buy downside protection through puts. For example, after the 1987 crash, implied volatility for out-of-the-money puts surged, reflecting heightened market fear and risk aversion.
Traders exploit volatility skew by selling expensive out-of-the-money puts in a negative skew environment to collect premiums or using risk reversals—buying out-of-the-money calls while selling puts—to bet on direction and capture skew differences. These strategies aim to profit from perceived mispricings in option premiums.
