The market's tail risk barometer. The SKEW index quantifies the perceived probability of extreme downside moves in the S&P 500 using the options-implied risk-neutral distribution — updated daily from CBOE data.
What does the SKEW index measure?
The CBOE SKEW index measures the skewness of the S&P 500's risk-neutral return distribution, derived from out-of-the-money option prices. A reading of 100 means the distribution is symmetric (no tail risk premium). Higher readings indicate that options traders are pricing in a greater probability of large downside moves — so-called black swan events. Unlike VIX, which measures the overall level of expected volatility, SKEW captures the asymmetry of fear: how much more the market worries about crashes than rallies.
The CBOE SKEW index is a measure of perceived tail risk in the S&P 500, derived from the prices of S&P 500 options. While most volatility indicators focus on the second moment of the return distribution (variance, which VIX captures), the SKEW index targets the third moment: skewness. Skewness describes the asymmetry of a probability distribution. In financial markets, negative skewness means the left tail (large losses) is fatter than the right tail (large gains) — in other words, extreme downside moves are more probable than a symmetric distribution would suggest.
CBOE calculates the SKEW index using a portfolio of out-of-the-money S&P 500 options spanning a wide range of strike prices and two nearest-term expiration series (with at least 8 days to expiration). The methodology is conceptually similar to the VIX calculation but extracts the third moment rather than the second. The raw skewness value is then transformed into an index where 100 represents zero skew (a perfectly log-normal distribution) and each point above 100 reflects increasing negative skewness in the implied distribution.
In practice, the SKEW index typically trades between 100 and 150. A reading of 120 implies that options markets are pricing roughly a 6% probability of a two-standard-deviation downside move over the next 30 days — compared to the 2.3% probability that a normal distribution would suggest. At 140, that implied probability rises to approximately 9%. These numbers may seem small, but the difference between a 2% and 9% probability of a crash-magnitude move has enormous implications for portfolio risk and hedging costs.
The VIX and SKEW indices are often discussed together, but they measure fundamentally different aspects of the options-implied distribution. The VIX captures the expected magnitude of S&P 500 price changes over the next 30 days — it answers the question "how much will the market move?" without distinguishing between upside and downside moves. A VIX of 20 implies that the market expects annualised volatility of roughly 20%, meaning daily moves of about 1.25% in either direction.
The SKEW index, by contrast, measures the shape of the distribution rather than its width. It answers the question "is the market pricing crash risk above what a normal distribution implies?" When out-of-the-money puts become expensive relative to at-the-money options, the volatility smile steepens, and SKEW rises. This steepening reflects institutional demand for tail risk hedges — portfolio managers buying deep out-of-the-money puts as insurance against catastrophic losses.
The most informative regime is when SKEW and VIX diverge. Elevated SKEW combined with low VIX is the classic "calm before the storm" signal: the overall options market is pricing low day-to-day volatility, but the demand for crash insurance is elevated. This divergence occurred before several major drawdowns, including the 2018 "Volmageddon" event and portions of the 2019-2020 period. Conversely, high VIX with declining SKEW suggests the market has already priced in a crisis and tail risk premiums are normalising — often a sign that the worst of a selloff is past.
Elevated SKEW readings signal that the options market is pricing a higher-than-normal probability of extreme downside moves. This matters because options markets aggregate the views of some of the most sophisticated and well-capitalised participants in financial markets — institutional portfolio managers, hedge funds, and market makers who specialise in pricing risk. When these participants collectively bid up the price of out-of-the-money puts, the SKEW index rises, reflecting a genuine shift in perceived crash probability.
However, context is everything. A SKEW reading of 135 during a period of low VIX and strong equity momentum carries different implications than the same reading during a period of already-elevated volatility. In the first case, the divergence between calm surface conditions and elevated tail risk pricing is the signal — the market appears complacent on the surface but is quietly hedging against disaster underneath. In the second case, elevated SKEW simply confirms what VIX is already telling you: the market is stressed.
Historically, sustained periods of extreme SKEW (above 140) have been followed by increased market turbulence within 3 to 6 months, though the hit rate is far from perfect. The SKEW index spiked above 145 in June 2014, August 2018, and multiple times in 2021, with mixed subsequent outcomes. This inconsistency is why experienced risk managers use SKEW as one input among many rather than a standalone crash predictor. It is best understood as a gauge of how much institutional money is flowing into tail risk hedges, not as a market timing tool.
Monitor SKEW-VIX divergence: The highest-information regime is when SKEW and VIX move in opposite directions. Rising SKEW with falling or stable VIX suggests institutional hedging activity is increasing despite calm surface conditions. This divergence warrants a review of portfolio exposures, hedging positions, and concentration risk.
Calibrate hedge sizing: The SKEW index directly reflects the cost of out-of-the-money put protection. When SKEW is elevated, puts are expensive — buying protection during periods of high SKEW means paying a premium for insurance that the market already perceives as necessary. Conversely, when SKEW is low, tail risk hedges are relatively cheap. Risk managers can use the SKEW index to time their hedge implementation, buying protection when it is inexpensive and allowing existing hedges to work when it is dear.
Contextualise with term structure: The SKEW index is a 30-day measure, but tail risk perceptions can vary across time horizons. Comparing near-term SKEW with longer-dated skewness (available from options chains of different expirations) reveals whether the market fears an imminent event or a more gradual risk build-up. A steep skewness term structure — where near-term SKEW exceeds longer-term — often coincides with specific event risk such as elections, central bank decisions, or geopolitical flashpoints.
Combine with credit and breadth signals: SKEW is most powerful when confirmed by other risk indicators. Widening credit spreads (high-yield OAS), declining market breadth (fewer stocks making new highs), and rising SKEW together paint a more reliable picture of building systemic risk than any single indicator in isolation. When all three deteriorate simultaneously, the probability of a meaningful drawdown rises materially.
The options market is pricing a near-normal return distribution with modest tail risk premiums. Out-of-the-money puts are not in unusual demand. This reading is typical during low-volatility trending markets where institutional hedging activity is routine rather than urgent.
Options traders are paying above-average premiums for crash protection. The implied probability of a two-standard-deviation downside move is roughly 6-9%, compared to the 2.3% a normal distribution suggests. Worth monitoring, especially if VIX remains subdued.
Institutional demand for tail risk hedges is intense. The risk-neutral distribution is pricing black swan probabilities well above historical norms. Readings above 145 are rare and have historically preceded periods of elevated market turbulence within 3 to 6 months.
SKEW index values are sourced from the Chicago Board Options Exchange (CBOE). The index is calculated from S&P 500 option prices using the two nearest-term expiration series with at least 8 days remaining, spanning a wide range of out-of-the-money strikes. S&P 500 price data is provided as a reference overlay. Data is updated each trading day after market close. Charts are rendered using Quadesto's time-series visualisation engine.
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