TL;DR. Option-implied volatility isn’t a single number. Plot the implied volatility of same-expiry options across strike prices and you get a curve — a downward-sloping skew for equity indexes and a valley-shaped smile for currencies. That shape exists because markets pay up for crash protection, and the CBOE SKEW Index was built to summarize how steep the S&P 500 curve is on any given day.
What implied volatility actually is
An option’s price has two levers: the intrinsic value (how much it is in the money) and the extrinsic value (everything else — time, interest rates, dividends, and expected future movement). Implied volatility (IV) is the number you have to plug into an option pricing model to make its theoretical price match the market price. It is a market forecast of how much the underlying will move between now and expiry, expressed as an annualized standard deviation.
The Black-Scholes model assumes IV is the same for every strike on the same expiry — one flat plane. Real markets do not behave that way. When you compute IV for calls and puts across strikes and plot them, you get a curve, not a line.
Skew vs. smile: three shapes, three markets
Which shape you see depends on the asset:
- Equity index skew (S&P 500, Nasdaq-100, FTSE 100). Downward sloping. Low-strike puts trade at meaningfully higher IV than at-the-money calls. Often called a “smirk” or “half-frown.”
- FX smile (EUR/USD, USD/JPY). Symmetric valley. IV is lowest at the money and rises on both wings, because currencies can gap either direction.
- Commodity reverse skew (crude oil, natural gas). High-strike calls trade richer than puts. Supply shocks and geopolitical spikes make upside tails fatter than downside tails.
Cboe’s own SKEW whitepaper puts the equity story bluntly: “Equity options traded in American markets did not show a significant volatility smile before the Crash of 1987 but began showing one afterwards.” The 1987 crash rewrote how the market prices left-tail risk, and the shape has never gone back.
Why equity puts trade richer than calls
Three structural forces pin the curve in place:
- Crash memory and jump risk. The distribution of daily S&P 500 returns has a fat left tail — more extreme down days than a normal distribution predicts. Options are priced under a risk-neutral distribution that must reflect this, so out-of-the-money puts carry an insurance premium above and beyond their statistical fair value.
- Hedging demand. Pension funds, insurance companies, and structured product desks are structurally long equities and structurally short puts (or long put spreads for downside protection). Persistent buying of low-strike puts lifts their IV.
- Overwriter supply. Retail and institutional yield strategies systematically sell out-of-the-money calls (covered calls, buy-writes). Persistent selling of high-strike calls pushes their IV down. Buy pressure on puts + sell pressure on calls = an asymmetric curve.
A simple worked example
Suppose the S&P 500 is trading at 5,000 and 30-day options show these implied volatilities:
| Strike | Moneyness | Option type (OTM) | Implied vol | IV vs ATM |
|---|---|---|---|---|
| 4,500 | 90% | Put | 22.5% | +7.5 pts |
| 4,750 | 95% | Put | 18.0% | +3.0 pts |
| 5,000 | 100% | ATM | 15.0% | 0 |
| 5,250 | 105% | Call | 13.2% | -1.8 pts |
| 5,500 | 110% | Call | 12.5% | -2.5 pts |
The 10%-OTM put trades at 22.5% IV while the 10%-OTM call trades at 12.5% IV. Same distance from spot, same expiry — a 10-point vol gap. That gap is the skew, and it is what makes tail hedging structurally expensive.
Visualizing the curve
The CBOE SKEW Index: putting a number on the curve
To standardize the shape of the S&P 500 skew, Cboe launched the SKEW Index in 2011. It is built from the same OTM SPX option universe as VIX, but instead of measuring the level of implied variance it measures the third moment — how asymmetric the risk-neutral return distribution is.
The official formula is SKEW = 100 – 10 × S, where S is the risk-neutral skewness of the 30-day S&P 500 log return. When S = 0 the distribution is symmetric and SKEW reads 100. As the market prices in a fatter left tail, S becomes more negative and SKEW rises.
Cboe’s own historical study (1990–2010) showed SKEW ranging from a minimum of 101 to a maximum of 147, with the modal reading between 115 and 117.5. The last 12 months have run hotter: as of the August 31, 2026 close, SKEW printed 148.53 with a 52-week range of 126.41 to 161.86, while VIX closed at 14.92. The market’s headline vol reading is calm, but the price of insurance against a crash is at the high end of history.
What each SKEW level implies for tail probability
| SKEW value | Prob. of 2σ down move (30-day) | Prob. of 3σ down move (30-day) |
|---|---|---|
| 100 (normal dist.) | 2.30% | 0.15% |
| 115 | 6.35% | 1.04% |
| 125 | 9.05% | 1.63% |
| 135 | 11.75% | 2.22% |
| 145 | 14.45% | 2.81% |
SKEW is not directional — and it does not replace VIX
The Cboe whitepaper is explicit that SKEW and VIX are complements, not substitutes: “VIX captures the first layer of perceived risk … Once this is gauged, SKEW catches the additional layer of risk implied by the left tail of the distribution.” A low-VIX, high-SKEW tape — like today’s — is telling you the market is not braced for volatility on average, but it is willing to pay up for the tail.
Common mistakes
- Confusing skew with direction. A steep skew doesn’t mean the market thinks the S&P is going down. It means the market is willing to pay more for downside protection than for upside speculation. Two different statements.
- Comparing raw IV instead of moneyness. IV levels shift with underlying price and time to expiry. Institutional desks quote skew in terms of the 25-delta risk reversal — the IV of a 25-delta call minus the IV of a 25-delta put — precisely to normalize across regimes.
- Ignoring the term structure. The vol surface has two axes: strike and expiry. Skew is usually steeper at short-dated expiries and flattens further out. Selling short-dated puts is not the same trade as selling one-year puts.
- Treating SKEW as a timing signal. High SKEW says “market is paying for tail hedges,” not “crash next week.” Cboe’s own scatter plot shows SKEW readings above 130 have appeared in both very calm and very panicky VIX regimes.
- Assuming risk-neutral = real-world. The 14.45% probability of a 2σ down move at SKEW = 145 in Table 2 is a risk-adjusted figure inferred from option prices, not a forecast. It contains both actual expected probability and the risk premium investors demand to bear tail exposure.
How practitioners use skew
Once you can read the curve, a few standard uses fall out:
- Pricing put spreads. Because the low-strike wing is elevated, buying a put and selling a farther-OTM put (“put spread”) is often cheaper than a single put on a per-unit-of-protection basis.
- Risk reversals. Selling an OTM put to finance an OTM call is a bullish trade that collects skew — you sell the expensive wing and buy the cheap one. FX macro desks live in this trade.
- Tail hedging cost. Systematic tail-hedge programs benchmark their cost against SKEW. High SKEW = expensive insurance = the drag on the strategy is running high.
- Dispersion trades. Index skew is typically steeper than the average constituent skew, because index puts are the cheapest way to hedge broad equity risk. Dispersion traders sell index vol and buy single-name vol partly to exploit that difference.
Related concepts
- Implied volatility 101 — the input you actually need before you can talk about skew.
- The Greeks (delta, gamma, theta, vega, rho) — vega is what makes an option position sensitive to changes in IV; skew is where vega across strikes lives.
- Volatility term structure — how IV changes across expiries at a fixed strike, the other axis of the vol surface.
- Volatility surface — the 3-D combination of skew and term structure, and the object risk desks actually manage.
Sources
- Cboe, “The Cboe SKEW Index — SKEW®SM” (whitepaper, 2010). Primary source for the SKEW formula, tail-probability table, and historical range (100–147, 1990–2010).
- Yahoo Finance, Cboe SKEW Index quote page. Current value and 52-week range as of August 31, 2026.
- Yahoo Finance, Cboe Volatility Index (VIX) quote page. Current value and 52-week range as of August 31, 2026.
- Wikipedia: Volatility smile. Reference for asset-class differences (equity skew vs FX smile vs commodity reverse skew) and the post-1987 origin of the equity smirk.
- Wikipedia: Black-Scholes model. The constant-volatility benchmark that the observed skew violates.
Disclosure: This article is for informational purposes only and is not investment advice.