What is the CBOE SKEW Index? Definition, Formula, and Example
The CBOE SKEW Index measures the perceived tail risk of the S&P 500 by quantifying how much more expensive far out-of-the-money puts are than at-the-money options.
CBOE SKEW Index Definition
The CBOE SKEW Index (ticker: ^SKEW) measures the perceived tail risk of the S&P 500 over a 30-day horizon by quantifying the price difference between far out-of-the-money (OTM) puts and at-the-money (ATM) options. It is calculated from the same SPX option strip used to compute the VIX, but instead of measuring expected volatility, SKEW measures the asymmetry of that volatility — specifically, how heavily traders are paying up for crash protection. Values range from roughly 100 to 170. A SKEW of 100 implies a symmetric, normal-distribution outlook; readings above 130 imply elevated demand for OTM puts and a fatter left tail.
How the SKEW Index Is Calculated
CBOE derives SKEW from the third moment (skewness) of the implied risk-neutral distribution of 30-day SPX log returns. The formula is:
SKEW = 100 − 10 × S
Where S is the skewness of the 30-day SPX log return distribution implied by option prices. Skewness itself is computed from a strip of OTM SPX puts and calls using a variance-swap-style replication:
S = E[(R − μ)³] / σ³
The CBOE methodology weights each strike by the inverse square of its price, integrates across the full strike chain, and interpolates between the two nearest expirations to produce a constant 30-day measure. Probabilities of a two-standard-deviation S&P decline rise from roughly 2.3% at SKEW = 100 to roughly 12% at SKEW = 145, based on CBOE's published mapping.
Worked Example
On May 14, 2026, the CBOE SKEW Index closed at 142.6 while the VIX closed at 14.20. The VIX reading suggested calm — implied volatility for ATM SPX options was below the long-run average of 19. But the SKEW reading was at the 88th percentile of its three-year range, meaning traders were paying steep premiums for SPX puts struck 10-15% below spot. This divergence — low VIX, high SKEW — is the classic "complacency with hidden hedging" setup. Eight trading days later, the SPY dropped 4.2% over a single week on weaker-than-expected jobs data, validating the tail-risk premium the SKEW had been pricing.
When Traders Use the SKEW Index
Portfolio managers use SKEW as a sentiment gauge for institutional hedging activity. Persistent readings above 140 indicate that smart money is buying crash protection even when the VIX is low — a warning sign that often precedes corrections. Options traders use SKEW to time put-spread sales: when SKEW is extreme, far-OTM puts are rich relative to closer strikes, making put credit spreads asymmetrically attractive. SKEW is also a key input for risk-parity and tail-hedge funds (Universa, Cambria) that systematically buy puts when skew is low and sell premium when skew is rich.
Limitations and Common Misconceptions
SKEW is not a market-crash predictor — it has produced many false positives (142+ readings followed by quiet markets) and missed several crashes that came from unexpected catalysts. The "probability of a tail event" CBOE publishes is risk-neutral, not real-world — it overstates true crash probability because OTM puts carry a volatility-risk premium. SKEW also says nothing about timing; a high reading can persist for months. Finally, SKEW is sensitive to which OTM strikes are most actively traded — single large institutional hedges can move the index without representing broad market sentiment.