Volatility Skew: Why Implied Volatility Changes Across Option Strikes

What is Volatility Skew?

Volatility skew is the pattern in which Implied Volatility differs across option strikes for the same underlying asset and expiration, often with one side of the strike distribution carrying systematically higher implied volatility than the other.

For equity-index options, a common shape is a downside skew: out-of-the-money puts trade at higher implied volatility than at-the-money options, while upside calls may trade at lower implied volatility.

A simplified snapshot might look like:

1Strike       Implied volatility
290 put       30%
395 put       26%
4100 ATM      22%
5105 call     20%
6110 call     19%

The slope is the important feature. The market is not using one constant volatility number for every strike.

Skew is evidence that one-volatility models are incomplete

In the basic Black-Scholes-Merton Model, a single volatility input is used for otherwise comparable options on the same underlying.

If every BSM assumption held exactly, solving market prices backward for implied volatility would produce the same volatility across strikes.

Real markets do not behave that way.

Different strikes often require different implied volatilities to reconcile observed prices with the same reference model.

That is why skew is not merely a display preference. It is market evidence that the combination of constant volatility, lognormal price dynamics, continuous paths, and other simple assumptions does not fully describe option prices.

Why downside puts often have higher implied volatility

Several economic forces can contribute to equity downside skew.

One is demand for protection. Investors who own stocks may be willing to pay relatively high premiums for out-of-the-money puts that protect against severe losses.

Another is the asymmetry of equity crashes. Large negative market moves can be abrupt, and volatility itself often rises when equity prices fall. A simple constant-volatility model does not fully capture that relationship.

Supply also matters. Market makers and option sellers require compensation for warehousing difficult-to-hedge downside jump risk, balance-sheet usage, and liquidity risk.

These forces can make downside options expensive relative to a flat-volatility benchmark.

The resulting skew should not be reduced to one causal story. Option prices reflect many participants, constraints, and risks at once.

Skew is not the same as moneyness

Option Moneyness describes the relationship between an option's strike and the underlying price.

Skew describes how implied volatility changes across those strikes.

Two options can be equally far from at the money in opposite directions and carry different IVs.

For example, a 10% out-of-the-money put might have 28% IV while a 10% out-of-the-money call has 20% IV.

Their moneyness distances can be similar while their implied volatilities differ materially.

That difference is part of the skew.

Skew and smile are related but not identical

A Volatility Smile generally describes a curve where implied volatility is elevated on both wings relative to options near the money.

A skew is asymmetric.

Conceptually:

1Smile:
2high IV -> lower IV near ATM -> high IV
3
4Downside skew:
5high IV on low strikes -> lower IV toward high strikes

Market practitioners do not always use the vocabulary identically. Terms such as skew, smirk, smile, and risk reversal can overlap in casual discussion.

The important analytical task is to identify the actual strike-by-strike IV pattern rather than infer too much from the label.

The same skew can be quoted in different coordinates

A strike-based chart is intuitive, but professionals may compare skew using several coordinate systems:

• absolute strike;
• strike divided by spot;
• forward moneyness;
• log-moneyness;
• delta; or
• standardized distance from at the money.

A 4,000 strike means something different when an index trades at 4,100 than when it trades at 5,000.

Delta-based or forward-based measures can make comparisons across dates and maturities more meaningful, but they introduce their own model conventions.

When someone says "25-delta skew," the term already depends on how delta is calculated.

Risk reversals are one way to summarize skew

A common market shorthand compares implied volatility on an out-of-the-money call with implied volatility on an out-of-the-money put at similar deltas.

For example:

125-delta risk reversal
2= 25-delta call IV - 25-delta put IV

If the put IV is substantially higher, this quantity is negative under that convention.

Some markets or vendors may reverse the subtraction order, so sign conventions must be checked.

The statistic compresses a whole curve into two points. It can be useful for tracking one section of skew over time but does not describe the entire smile or surface.

Skew can change even if at-the-money IV barely moves

Suppose at-the-money implied volatility remains at 20%.

On Monday:

190% strike IV   25%
2ATM IV          20%
3110% strike IV  19%

On Friday:

190% strike IV   32%
2ATM IV          20%
3110% strike IV  18%

At-the-money IV looks unchanged, but downside protection has become much more expensive relative to the center and upside wing.

A single headline IV number would miss that shift.

This is one reason option analysis often needs an Implied Volatility Surface rather than one volatility statistic.

Skew can vary by expiration

There is no universal skew for an underlying.

A one-week expiration can have a very different strike pattern from a six-month expiration.

A known event can distort a short maturity. Longer maturities incorporate more time for other risks to matter. Supply and demand can also differ across tenors.

That means a statement such as "skew is steep" is incomplete unless the expiration or maturity region is specified.

The full surface combines strike shape with the term structure across expiration.

Earnings can create single-stock skew changes

Before a corporate earnings announcement, short-dated options can become expensive because the stock may jump when results are released.

The strike pattern can also change if investors assign different probabilities to large positive and negative outcomes.

After earnings, both the overall level of implied volatility and the skew can reprice sharply.

A trader who correctly predicts the direction of the stock but ignores the option's starting skew and post-event volatility repricing can still experience an unexpected result.

This connects skew analysis to Option Vega, Option Delta, and Option Gamma.

Skew affects strategy comparisons

Suppose an investor compares buying an out-of-the-money protective put with selling an out-of-the-money covered call.

If downside put IV is much higher than upside call IV, the put may be relatively expensive in implied-volatility terms.

That does not automatically mean the put is a bad purchase or the call is a good sale. The exposures are different, and high put IV may compensate a seller for severe downside risk that the investor specifically wants to insure.

Likewise, a vertical spread combines options at different strikes. Its value depends partly on the skew between those strikes, not merely on one shared volatility assumption.

A flat-volatility scenario can misrepresent the actual cost of a strategy when the market curve is strongly skewed.

Skew is not a direct probability distribution

Option prices contain information about how the market prices different states, but the observed implied-volatility curve should not be read as a literal histogram of future returns.

The curve reflects risk-neutral pricing, risk premia, supply and demand, liquidity, funding, and model conventions.

Advanced methods can infer a risk-neutral distribution from option prices under assumptions, but that distribution is not necessarily the same as the real-world probability distribution investors expect to occur.

A steep downside skew can indicate expensive downside states without proving that a crash is objectively more likely by a particular amount.

Steep skew does not automatically mean bearish traders

It is tempting to translate expensive puts into a simple sentiment statement: "the market is bearish."

That can be too strong.

Institutional investors may buy puts as insurance while remaining fully invested in equities. Dealers may demand premium for difficult hedging. Structural mandates may create persistent demand for downside protection.

The same skew can exist even when the median investor expects positive equity returns.

Skew measures relative option pricing across strikes. It does not reveal one unified market opinion.

Liquidity can distort the curve

Far out-of-the-money options can have wide bid-ask spreads and sparse trading.

If implied volatility is calculated from a stale last trade or unreliable midpoint, the apparent skew can be noisy.

A professional surface construction process may filter quotes, enforce no-arbitrage constraints, interpolate between strikes, or use option prices rather than raw displayed IVs.

Different data vendors can therefore show slightly different skews for the same market snapshot.

A precise chart does not guarantee equally precise underlying quotes.

Skew can contain arbitrage constraints

Not every imaginable option-price curve is economically valid.

Across strikes, option prices must respect basic no-arbitrage conditions such as monotonicity and convexity relationships. A poorly constructed implied-volatility curve can correspond to option prices that permit static arbitrage.

This is one reason surface fitting is more than drawing a smooth line through IV points.

The fitted curve should ideally remain consistent with economically sensible option prices.

Put-Call Parity provides another no-arbitrage relationship linking calls and puts under matched terms.

What volatility skew cannot tell you

Volatility skew does not by itself forecast market direction, realized volatility, crash probability, or strategy profitability.

It is also not one fixed property of an asset. Skew changes with expiration, market conditions, supply and demand, and the coordinate system used to measure it.

Its useful role is to reveal that option prices assign different implied volatilities to different strikes, which exposes information that one at-the-money IV number cannot show.

Grizzly Bulls' Models can provide broader systematic-research context, while Indicators can frame market regimes. Neither route publishes a canonical live volatility-skew curve or option-chain feed.

Sources and further reading

• CFA Institute: Options Strategies, 2026 curriculum
• CFA Institute: Valuation of Contingent Claims, 2026 curriculum
• Options Industry Council: Volatility Skew and Options: An Overview

Explore more topics in the Financial Research Encyclopedia.