Volatility Skew: Insights Into Market Sentiment and Options Trading Strategies

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Volatility skew is the difference in implied volatility (IV) between options on the same underlying asset with the same expiration date but different strike prices. If option prices followed the textbook assumption of a single, constant volatility, every strike would carry the same IV. In practice, plotting IV against strike produces a line that tilts or curves, showing where traders are paying up for protection or for upside exposure. In equity index options, the low strikes usually carry the highest IV (put skew).

What Volatility Skew Measures

Implied volatility is the volatility figure that, when plugged into an option pricing model, reproduces the option’s market price. The Black-Scholes model and its modified versions are the standard tools for backing out IV. Because the model assumes volatility is constant across strikes, a perfectly “Black-Scholes world” would produce a flat line of IV across the option chain.

Real option chains break that assumption. When traders bid up a strike, its price rises, and so does the IV implied from that price. Volatility skew records those differences: one strike is expensive relative to another in volatility terms, even after accounting for distance from the current price and time to expiration.

Under put-call parity, a European call and put with the same strike and expiration have the same implied volatility. “Put skew” is therefore really a statement about low strikes, where out-of-the-money (OTM) puts trade, and “call skew” a statement about high strikes, where OTM calls trade. The in-the-money call at a low strike shares the elevated IV of the OTM put at that strike. Traders talk about puts and calls because OTM options are the liquid contracts at each end of the chain.

What Causes Volatility Skew?

Demand for downside protection. In equity markets, investors tend to treat a drop as the bigger risk. Holders of stock portfolios buy put options to insure against declines, and that steady demand lifts the price and IV of low-strike options. Protection buyers are reacting to losses on positions they already own, which is why they pay a premium.

Crash risk and the 1987 break. Before October 1987, equity index option smiles were relatively flat. The crash, in which US stocks lost more than 20% in a single day, showed that large, sudden drops were far more likely than the bell-curve assumptions behind Black-Scholes implied. Investors rushed to buy puts, and a persistent put skew in index options has remained ever since.

Volatility rises when prices fall. In stocks, falling prices tend to come with rising realized volatility (often called the leverage effect). Option traders price that relationship in: a strike below the market is likely to be reached in a more turbulent environment, so it carries a higher volatility assumption.

Fat tails. Financial returns show skewness and excess kurtosis, meaning their distributions are asymmetric and produce extreme moves more often than a normal distribution predicts. OTM options are the instruments that pay off in those tails, so they trade at higher IV than a normal-distribution model would justify.

Supply from option sellers. Strategies that systematically sell OTM calls, such as covered call writing, add supply at the high strikes and can hold call IV down, which deepens the put skew on equities.

Upside shock risk. In some markets the feared move is up, not down. Commodities such as crude oil, natural gas or agricultural products can spike on supply disruptions or weather, so buyers want OTM calls. Heavily shorted or speculative stocks can show the same pattern when traders fear, or chase, a squeeze. These conditions produce call skew.

Scheduled events. Earnings announcements, central bank decisions and economic releases can create a temporary skew if traders expect a sharp move in one direction. That skew often fades once the event has passed.

Calculating Volatility Skew

There is no single official skew formula. Desks and data providers use a few standard measures.

Common Skew Measures

Delta-based skew. Compare equal-delta options on each side:

Skew = IV(25-delta put) − IV(25-delta call)

A positive result means puts are richer than calls (put skew); a negative result means calls are richer (call skew). Using delta, covered under option Greeks, rather than fixed dollar distance keeps the comparison consistent as price and time change, since a 25-delta option sits at roughly the same probability-adjusted distance from the money.

Risk reversal. Currency options quote the same idea with the sign flipped:

25-delta risk reversal = IV(25-delta call) − IV(25-delta put)

A negative risk reversal means puts on the base currency are priced at higher volatility than calls.

Moneyness-based skew. Compare a fixed percentage OTM strike with the at-the-money (ATM) strike, for example:

Put skew = IV(90% strike) − IV(100% strike)

Some traders express this as a ratio, such as IV(90%) ÷ IV(100%), so the measure is less affected by the overall level of volatility.

Butterfly or curvature. To measure the smile rather than the tilt:

25-delta butterfly = [IV(25-delta call) + IV(25-delta put)] ÷ 2 − IV(ATM)

A larger butterfly means both wings are expensive relative to the center.

Slope. Quants sometimes fit a curve (often a spline or a parametric model) through the IV of every strike and quote the slope of IV per unit of strike or moneyness. This uses the whole chain instead of two points.

Worked Example (Hypothetical)

Assume a stock trades at $100 and its options expiring in 30 days show these hypothetical implied volatilities:

• Moneyness put skew: 28% − 22% = 6 vol points at the 90% strike.
• Wing-to-wing skew: 28% − 19% = 9 vol points between the 90 and 110 strikes.
• Shape: IV falls steadily from low to high strikes, so this is a reverse (put) skew, sometimes drawn as a smirk.

To see what skew does to price, use vega, the option’s price sensitivity to a one-point change in IV. Assume the 90-strike put has a vega of $0.06 per share per vol point. Priced at the ATM volatility of 22% instead of 28%, it would cost roughly 6 × $0.06 = $0.36 per share less, or about $36 per contract on a standard 100-share US equity option. That $36 is the premium the market charges for downside protection beyond what a flat-volatility model would ask. The linear vega approximation loses accuracy for large IV gaps, but it shows the order of magnitude.

Interpreting Volatility Skew

Reverse (Negative) Skew, or Put Skew

Lower strikes carry higher IV than higher strikes. This is the typical shape for equity indexes and many large stocks. It reflects stronger demand for downside protection and a market that prices large drops as more likely, or more costly, than equally large rallies.

Forward (Positive) Skew, or Call Skew

Higher strikes carry higher IV than lower strikes. This is the pattern of the upside-shock markets described above, where call sellers demand more premium to take the other side. When an underlying that normally shows put skew flips so that OTM calls become richer than equivalent puts, the change is called an inverted call skew. The market now prices an upside jump as the larger risk, often because of short-squeeze potential, takeover speculation or aggressive speculative call buying.

Volatility Smile

IV is elevated at both low and high strikes, with the lowest point near the money, producing a U- or V-shaped curve. The market prices large moves in either direction as more likely than a normal distribution would imply. Smiles are associated with currency options, where either currency in a pair can be the one that moves sharply, and with single stocks ahead of binary events such as a court ruling or drug trial result.

Volatility Smirk

A smirk is an asymmetric smile: both wings may be elevated, but one side is clearly steeper. The equity version has IV highest at the low strikes, falling through the money, and flattening or turning up only slightly at high strikes. In practice, the terms “reverse skew” and “smirk” are often used interchangeably for equities.

Flat Skew

When IV is roughly the same at every strike, the market is not paying a premium for either tail. A flat skew is uncommon in liquid markets.

Steep vs Flat Skew

A steep put skew means OTM puts carry far more IV than ATM options, so the downside tail is expensive. A flattening skew means the gap has narrowed. Traders compare current steepness with the same asset’s own history at the same tenor and definition. A reading well above its usual range suggests unusual demand for crash protection, while a sudden flattening after a selloff can mean hedges are being sold or monetized. A large, fast change in skew is often a better signal of shifting sentiment than its absolute level.

Why Volatility Skew Matters for Options Trading

It changes what each strike costs. Two options equally far from the money can differ meaningfully in price because of skew, so ignoring it misjudges how expensive a hedge or speculation really is.

It shapes strategy selection. Spreads involve buying one strike and selling another, so they are directly exposed to skew:

• In a steep put skew, a bear put spread (buy a higher-strike put, sell a lower-strike put) sells the richer strike, which offsets part of the cost.
• A collar (own stock, buy an OTM put, sell an OTM call) costs more to put on when put skew is steep, because the put is rich and the call is cheap.
• In a call skew, covered calls and call spreads that sell the upper strike collect more premium than they would in a put-skew market.
• Risk reversals (buy one side, sell the other) are a direct trade on skew: buying calls and selling puts in a steep put skew lets a trader fund upside exposure with rich puts, at the cost of downside risk.

It informs volatility trades. A straddle bought at the money pays only ATM volatility, while a strangle bought with OTM strikes pays wing volatility, which in a steep skew can be noticeably higher on one leg.

It gives a read on market sentiment. Index-level gauges built from OTM option prices, such as the Cboe SKEW Index for the S&P 500, attempt to summarize how much the market is paying for tail risk. Combined with the overall level of IV and positioning data such as open interest, skew helps distinguish a market that is simply volatile from one specifically afraid of a crash or a squeeze.

It reveals model limits. Skew shows that a single-volatility model cannot price every strike correctly at once, so professional pricing uses a volatility surface, local volatility models or stochastic volatility models.

Volatility Skew in Currency Options

Foreign exchange options are quoted differently from equity options. Instead of prices by strike, dealers quote ATM volatility, 25-delta risk reversals and 25-delta butterflies for each tenor. The risk reversal measures the skew (which currency’s calls are richer), and the butterfly measures the smile (how expensive both wings are relative to the center).

Because an exchange rate is the price of one currency in terms of another, a “put” on one currency is a “call” on the other, which is why currency smiles tend to be more balanced than equity smirks. They still tilt toward the currency traders want protection against. A pair that includes a currency viewed as a haven in stress can show risk reversals favoring that currency’s calls, while a pair exposed to a possible devaluation or a policy shock can see the skew lean toward that currency weakening. A sharp shift in a pair’s risk reversal often shows positioning and fear changing before the spot rate moves.

Limitations of Volatility Skew

It does not predict direction. Skew shows how much traders pay for each tail, not where the price will go. A steep put skew can persist through a long rally, and a flat skew can precede a sharp selloff.

It reflects supply and demand, not just expectations. Hedging mandates, structured product issuance, and systematic call writing can move skew for reasons unrelated to any view on price. A rich put may be rich because institutions must buy protection, not because a crash is imminent.

Measures are not comparable across sources. A 25-delta skew, a 90%-moneyness skew and a fitted slope can give different readings for the same chain. Risk reversals reverse the sign convention. Always confirm which definition a figure uses.

Skew moves with the underlying. When price changes, it is not obvious whether IV stays attached to each strike (“sticky strike”) or to each moneyness or delta level (“sticky delta”). The answer affects how a position’s value and hedge ratios change, and markets do not consistently follow either rule.

Illiquid wings distort the curve. Far OTM options often trade rarely and have wide bid-ask spreads. IV backed out from a stale or wide quote can exaggerate or hide skew, especially in single stocks and short-dated contracts.

Volatility is itself volatile. IV reacts quickly to events, and calm and turbulent periods tend to persist, so a skew reading taken in one regime can be out of date within days.

Measured skew depends on inputs. IV depends on the model used to extract it and on assumptions about interest rates, dividends and early exercise, which can produce small but real differences in measured skew.

What Volatility Skew Is Often Confused With

Skew vs smile. Both describe IV across strikes for one expiration. Skew is the general term and usually means a tilt, steeper on one side. A smile is the specific, roughly symmetric case where both wings are elevated.

Skew vs term structure. Term structure compares IV across expiration dates at a similar moneyness, for example ATM IV for one-month versus six-month options. Skew holds expiration fixed and varies strike. Put together, the two form the volatility surface, a three-dimensional map of IV by strike and maturity. Skew is often steeper in short-dated options and flatter in longer ones, so the same underlying can show different skews by expiry.

Implied skew vs statistical skewness. Statistical skewness describes the asymmetry of a return distribution. Volatility skew describes option prices. They are connected, since a put skew implies the market prices a left-skewed distribution, but one is measured from price history and the other from option quotes.

Skew vs historical volatility. Historical volatility measures how much an asset has actually moved over a past window. Implied volatility and its skew are forward-looking prices.

FAQs

The Bottom Line

Volatility skew matters to options traders choosing strikes, hedges and spreads, since two options equally far from the money can differ meaningfully in price. It offers a read on how much the market pays for each tail, but it does not predict direction. Compare a reading with the same asset's history, and confirm which skew definition a figure uses.