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.
For how skew and volatility levels show up in single names, Tapeboard's IV rank page tracks where implied volatility sits, and options flow surfaces how premium is actually trading across the tape.
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.