Volatility Smile & Volatility Skew: Why IV Varies by Strike

The volatility smile is one of the most revealing patterns in options markets. If you’ve looked at an options chain and noticed that implied volatility is not the same for every strike price, you’ve already observed it. Rather than being flat across strikes — as the constant-volatility Black-Scholes model assumes — IV varies systematically, forming distinctive curves that tell you what the market really thinks about risk. Understanding these patterns is essential for anyone working with the option Greeks and pricing options accurately. Learn more in our Options Greeks course.

What Is the Volatility Smile?

When you plot implied volatility on the vertical axis against strike prices on the horizontal axis — for options sharing the same expiration — the resulting curve often forms a U-shape that traders call the volatility smile.

The volatility smile was first widely observed in currency and commodity options markets, where large price moves can occur in either direction. In these markets, both deep OTM puts and deep OTM calls trade at elevated IV compared to ATM options — reflecting the market’s expectation of jump risk on both sides.

This pattern directly contradicts the constant-volatility Black-Scholes model, which assumes a single implied volatility (σ) applies to all options on the same underlying with the same expiration. If Black-Scholes were perfectly accurate, IV would be flat across all strikes. The smile’s existence is evidence that real-world return distributions have heavier tails than the log-normal distribution assumed by the model.

When analyzing the smile, traders typically compare IV at delta-matched strikes (e.g., 25-delta put, ATM, 25-delta call) rather than arbitrary strike prices. This standardizes the comparison across different underlying prices and makes the smile comparable across stocks and time periods.

While the symmetric smile appears in currencies and some commodity markets, equity markets tell a different story — they display an asymmetric pattern known as volatility skew.

What Is Implied Volatility Skew?

Volatility skew — sometimes called the volatility “smirk” — describes the pattern where OTM puts have systematically higher IV than OTM calls. Instead of the symmetric U-shape of a true smile, equity options typically display a downward-sloping curve from left to right: lower strikes (OTM puts) have the highest IV, ATM options sit in the middle, and higher strikes (OTM calls) have the lowest IV.

To quantify skew consistently, this article uses the following convention:

• Put skew = 25-delta (25Δ) put IV minus ATM IV. A positive number means OTM puts are priced richer (higher IV) than ATM options.
• Risk reversal = 25Δ call IV minus 25Δ put IV. A negative number means put skew dominates — which is the norm for equity options.

Historical context: Before the 1987 Black Monday crash, equity options displayed a relatively flat IV curve across strikes. After the crash — in which the S&P 500 fell over 20% in a single day — the market permanently repriced downside tail risk. OTM put IV rose sharply and has remained elevated relative to ATM and OTM call IV ever since. This structural shift created the persistent put skew observed in equity markets today.

Index options (such as SPX options) typically show steeper skew than single-stock options. This is because index-level crash insurance demand is concentrated — institutional portfolio managers collectively hedge using index puts, which drives up their premiums disproportionately. Single-stock skew exists but is generally less pronounced.

While equity options predominantly show put skew, exceptions exist. Call skew can appear in commodity markets facing supply shocks (where sudden price spikes are the primary fear) or in single stocks subject to takeover speculation (where a large upward jump is possible).

Why Does the Volatility Smile Exist?

The volatility smile and skew exist because the constant-volatility Black-Scholes model’s assumptions do not match real-world market behavior. Several forces drive the patterns:

1. Non-lognormal return distributions. Black-Scholes assumes stock returns follow a log-normal distribution with constant volatility. In reality, returns exhibit fat tails (extreme moves happen more frequently than the model predicts) and negative skewness (large down-moves are more common than symmetrically large up-moves in equities). The smile and skew are the market’s way of correcting for these deviations.

2. Risk-neutral distribution interpretation. The smile and skew reveal that the market-implied (risk-neutral) probability distribution has heavier tails than log-normal — particularly on the downside for equities. Higher IV at OTM strikes means the market assigns greater risk-neutral probability to extreme moves than Black-Scholes would suggest (note: risk-neutral probabilities reflect pricing, not necessarily real-world forecasts). In effect, the smile is a visual map of the market’s tail-risk pricing.

3. Crash risk premium. After the 1987 Black Monday crash, market participants permanently repriced tail risk. The experience demonstrated that markets can fall dramatically in a single session, and OTM puts — which provide insurance against such events — now command a persistent premium. This crash risk premium has never fully dissipated.

4. Supply and demand dynamics. Institutional investors systematically buy OTM puts for portfolio insurance. This persistent demand for downside protection drives up OTM put premiums (and therefore their implied volatility) above what a constant-volatility model would produce. The demand is structural, not cyclical — pension funds, endowments, and asset managers continuously maintain hedging programs.

5. Jump risk. Markets can gap down suddenly — overnight, over weekends, or during flash crashes. OTM puts protect against these discontinuous moves, which cannot be dynamically hedged using the underlying stock. The premium for this jump protection is embedded in higher OTM put IV.

6. Leverage effect. As stock prices decline, a company’s debt-to-equity ratio increases mechanically, raising financial leverage and amplifying future volatility. This creates a negative feedback loop: falling prices → higher leverage → higher expected volatility → higher IV for lower strikes — reinforcing the skew.

Volatility Smile vs Volatility Skew

While the terms “smile” and “skew” are sometimes used interchangeably, they describe distinct IV patterns with different characteristics and market contexts.

Volatility Smile Across Asset Classes

The shape and steepness of the IV curve varies significantly across asset classes, driven by the distinct risk profiles and market structures of each.

The key takeaway is that smile and skew patterns are not universal — they reflect the specific risk characteristics and participant behavior of each market. Traders who move between asset classes must adjust their expectations for IV behavior accordingly.

The Volatility Surface

So far, we’ve examined how IV varies across strikes at a single expiration. But IV also varies across expirations at a single strike — a dimension called the term structure. When you combine both dimensions, you get the volatility surface: a three-dimensional map of implied volatility.

• X-axis: Strike price (or delta)
• Y-axis: Time to expiration
• Z-axis: Implied volatility

The volatility surface captures the full picture of how the market prices risk across all strikes and expirations simultaneously. Near-term options may show steeper skew than longer-dated options — especially ahead of a known event like earnings. After the event passes, the near-term surface typically flattens as uncertainty resolves.

How to Read the Volatility Skew

Reading the skew gives you actionable insight into how the market is pricing risk at a given moment. Here’s how to interpret the key metrics for equity options.

What Skew Levels Signal

Steep skew (large put skew, deeply negative risk reversal) signals elevated fear in the market. Causes include rising hedging demand ahead of uncertain events, recent market drawdowns that increase crash-risk awareness, or concentrated institutional put buying. Steep skew often coincides with elevated implied volatility levels overall.

Flat skew (small put skew, risk reversal near zero) signals relative complacency. The market sees similar risk in both directions, which can occur during low-volatility, range-bound environments. However, flat skew does not mean low risk — it means the market is not differentiating between upside and downside tail risk.

How to Analyze Volatility Patterns

You can systematically assess volatility smile and skew patterns using this practical framework:

1. Compare IV across strikes at a single expiration. Pull up the options chain and look at the IV column. Note whether IV increases as you move away from ATM — and whether the increase is symmetric (smile) or asymmetric (skew).
2. Calculate the put skew and risk reversal. Find the 25Δ put IV, ATM IV, and 25Δ call IV. Compute put skew (25Δ put IV − ATM IV) and risk reversal (25Δ call IV − 25Δ put IV). These two metrics summarize the shape of the curve in a single number.
3. Compare to historical levels. Is the current skew steep or flat relative to recent history? A sudden steepening may signal emerging hedging demand or event risk. A flattening may signal complacency.
4. Check the term structure. Does near-term skew differ from longer-dated skew? A sharp near-term skew with flatter longer-dated skew often indicates a specific upcoming event (like earnings) rather than a structural shift.
5. Factor skew into spread pricing. Vertical spreads are directly affected by IV differences across strikes. A bull put spread where the short put has lower IV than the long put (due to skew) may offer less net premium than expected. Always check individual strike IVs, not just the overall ATM IV.

For a deeper understanding of how IV works and how it connects to the Greeks, see our guides on implied volatility and option vega.

Common Mistakes

These are the most frequent errors traders make when working with the volatility smile and skew:

1. Assuming IV is flat across all strikes. Many beginner options traders use a single IV number for the entire options chain — typically the ATM level. This ignores the smile and skew, leading to mispriced spreads and inaccurate risk assessment. Every strike has its own IV, and the differences matter.

2. Ignoring skew when pricing vertical spreads. A bull put spread’s net premium depends heavily on the IV difference between the two strikes. Because skew gives the lower (OTM) put a higher IV, the long put in a bull put spread is more expensive (in IV terms) than many traders expect. Ignoring skew misestimates the true risk/reward of the position.

3. Confusing the volatility smile with volatility term structure. The smile and skew describe IV across strikes at a single expiration. Term structure describes IV across expirations at a single strike. They are different dimensions of the volatility surface. Mixing them up leads to confused analysis — always specify whether you’re comparing strikes (smile/skew) or expirations (term structure).

4. Treating skew as static. Skew levels change with market conditions, sentiment shifts, and events. A strategy designed to profit from steep skew (such as selling expensive OTM puts) may not work when skew flattens. Monitor skew levels regularly and adjust strategies accordingly.

5. Mixing expirations when assessing skew. Comparing IV from options with different expiration dates when trying to measure skew introduces term structure effects and produces misleading readings. Always compare strikes within the same expiration to isolate the skew dimension.

6. Using illiquid strike IV as representative. Thinly traded strikes with wide bid-ask spreads or stale last-trade prints produce noisy IV readings that can distort the apparent smile or skew shape. Focus on liquid strikes and use mid/mark prices (not last-trade) for reliable skew assessment.

Limitations of Volatility Smile and Skew Analysis

1. Asset-class dependence. Skew patterns vary across asset classes. Strategies or assumptions calibrated to equity skew do not transfer to currency, commodity, or interest rate options. Always verify the typical IV pattern for the specific market you are trading.

2. Model limitations. The constant-volatility Black-Scholes model cannot produce a smile or skew — it assumes flat IV across all strikes by construction. More advanced models (stochastic volatility, jump-diffusion, local volatility) can capture the surface more accurately, but each model has its own assumptions and limitations. The smile is a property of the market, not of any single model.

3. Skew is not stationary. What constitutes “normal” skew changes over time. The skew regime of the early 2000s differs from post-2008, which differs from the current environment. Historical skew comparisons are useful but must account for evolving market structure, regulation, and participant behavior.

4. Liquidity distortion. Illiquid strikes — especially deep OTM options with low open interest — may display IV readings that reflect wide bid-ask spreads rather than genuine market expectations. These noisy readings can make the tail of the smile appear steeper or more volatile than it truly is.