Understanding Volatility Skew: Your Secret Weapon in Options Trading
The volatility skew refers to the difference in implied volatility (IV) between out-of-the-money (OTM) options, at-the-money (ATM) options, and in-the-money (ITM) options. This discrepancy in IV, influenced by market sentiment and the supply and demand for specific options, reveals where traders and investors place their bets on future price movements.
Also known as vertical skew, traders can leverage the changes in skew for various trading strategies.
Key Takeaways
- Volatility Skew Explained: Not all options on the same underlying asset and expiration date have the same IV.
- Market Sentiments: For stock options, skew suggests higher IV for downside strikes compared to upside strikes.
- Volatility Smile: A convex volatility smile indicates greater demand for ITM or OTM options.
Why Does Volatility Skew Occur?
Volatility skew arises from the differing IV levels of options with various strike prices but a shared expiration date. IV measures market expectations of how much the underlying asset’s price will move.
Drivers of Volatility Skew
The primary drivers include collective market expectations, perceived downside risk in equity markets, specific market events (like earnings announcements), and major market downturns. The shape of volatility skew can offer crucial insights into market trends.
Interpreting Volatility Skew
Interpreting volatility skew necessitates understanding its shape and slope, which can vary significantly:
- Positive Skew: Indicates higher IV for OTM call options, suggesting the market is expecting upward price movements.
- Negative Skew: Signifies higher IV for OTM put options, implying expectations of downward price movements.
- Volatility Smile: Higher IV for both OTM call and put options compared to ATM options, indicating potential large price movements in both directions.
- Flat Skew: Shows a uniform IV across all strike prices, signaling no significant directional market expectations.
Identifying Abnormal Volatility
A sudden change in volatility skew can signal abnormal volatility. A negative skew becoming more pronounced often indicates expectations of a downward price movement, accompanied by increased volatility.
Historical Comparisons
Comparing the current skew to historical levels helps determine if market expectations are abnormal. A steep or pronounced volatility smile or smirk can also hint at upcoming significant price movements.
The Formation of a Volatility Smile
A volatility smile occurs when IV increases for both ITM and OTM options compared to ATM options, typically forming a V-shaped curve. A volatility smile reflects significant market expectations of substantial moves in either direction.
The Implications of a Volatility Smile
- Market Expectations: Steep smiles reveal anticipated large price moves.
- Options Pricing: Options far ITM or OTM become more expensive due to higher IVs.
- Risk Assessment: Steep smiles suggest perceived high market risk.
- Arbitrage Opportunities: Potential, though often difficult, arbitrage plays due to differing IVs across strike prices.
- Jump Risk: Indicates potential sharp, sudden price jumps.
- Model Limitations: Undermine the assumption of constant volatility in classical pricing models like Black-Scholes.
Volatility Smirk: A Specialized Scenario
A volatility smirk happens when IV decreases as options become deeply ITM or OTM, resembling a downward-sloping curve.
The Implications of a Volatility Smirk
- Market Expectations: Higher IV for OTM put options suggests significant downward price movement expectations.
- Pricing & Risk: Far OTM puts become more expensive; steep smirks indicate perceived downstream market risks.
- Arbitrage & Jump Risk: Similar to volatility smiles, these might indicate potential for specific market opportunities.
- Limitations: Undermines constant volatility assumptions in pricing models.
Analyzing Volatility: Benefits and Limitations
Analyzing volatility reveals market sentiment and assists in strategies like risk management and diversification. Despite the insights it offers, volatility analysis comes with limitations:
- Unpredictability: Historical volatility isn’t a perfect future predictor.
- Dynamics: Volatility can change abruptly; stable future predictions are complex.
- Distribution Issues: Real financial returns aren’t perfectly normal but exhibit skewness and kurtosis.
- Lack of Direction: High volatility signals large price swings without indicating direction.
Complementary Volatility Analysis Techniques
Various methods supplement volatility analysis, including historical volatility, volatility indices, and GARCH models. These approaches collectively enhance understanding but shouldn’t be solely relied upon for future predictions.
Related Terms: implied volatility, volatility smile, volatility smirk, trading strategy, options pricing.
References
- CME Group. “Introduction to CVOL Skew”.
- Charles Schwab. “Options Volatility: The VIX, Rule of 16, and Skew”
- Corporate Finance Institute. “Volatility Skew, A technical tool that informs investors about the preference of fund managers”
- Calamos Investments. “Navigating Option Skew: When the Smile Turns Into a Smirk”
- TD Ameritrade. “The Ticker Tape. Options Volatility Skew: Why Off-Bal;nace Isn’t All Bad”
- IVolatility. “IVolatility Education. Analysis of options using volatility and other parameters”
- Analyst Prep. “Volatility Smiles”
- The Options Guide. “Volatility Smiles & Smirks”
- AvaTrade. “What is Volatility?”
- Quantconnect. “Historical Volatility and Implied Volatility”
- Basistha, A, et al. “Volatility Forecasting: The Role of Internet Search Activity and Implied Volatility”
- School of Stocks by Hyers. “Returns Distribution, Skewness, and Kurtosis”
- Econometrics with R. (2022) ‘Volatility Clustering and Autoregressive Conditional Heteroskedasticity’, Econometrics with R. Available at: https://www.econometrics-with-r.org/16-4-volatility-clustering-and-autoregressive-conditional-heteroskedasticity.html
