CME Group Volatility Index (CVOL™)
Introducing a new view on volatility, derived from the world's most actively traded options on futures, across major asset classes. Made possible, uniquely, by CME Group.
Multi-asset class coverage
Derived from extremely liquid option contracts, traded on CME Group exchanges and creates a consistent and tractable metric across different products and asset classes.
Transparent and replicable
CVOL delivers the ability to easily replicate an equivalent simple variance options portfolio via equal weighted option strips.
Calculation methodology produces auxiliary indicators (DnVar, UpVar, Skew, Convexity, ATM) that enable more comprehensive sentiment analysis.
The CME Group Volatility Index (CVOL) delivers the first ever cross-asset class family of implied volatility indexes based on simple variance. Using our proprietary simple variance methodology that assigns equal weighting to strikes across the entire implied volatility curve, the CVOL Index produces a more representative measure of the market’s expectation of 30-day forward risk.
How to access
Direct from CME Group
Historical data available via CME DataMine.
The oversight committee will provide independent governance, and challenge to the Administrator on all aspects of the benchmark determination process in accordance with the Oversight Committee Terms of Reference.
Carrick Pierce (Chair)
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How the CVOL Index works
CVOL Indexes measure the expected risk or volatility of an underlying futures contract based on the information contained in the prices of options on that underlying futures contract. CVOL Indexes are generated using simple, or Gaussian, variance, as the base to provide a consistent and tractable metric that can be compared across different individual products for a given asset class, and additionally within and across asset classes themselves.
CVOL Indexes use the option prices from two tenors (expirations) of options in order to generate a time weighted average that centers on 30 days. Each of the two tenors has its own variance metric which uses the actual option prices to estimate the area under the curve of expected market outcomes for that tenor. Each option price is multiplied by the average distance to the two adjacent strikes to create an area under the outcome curve. The lower the option price (with the same width to the nearest strikes), the less probability of the underlying futures contract’s price ending up in that price range if the slice or section’s area is divided by the sum of all the areas across the range of possible outcomes. The sum of these areas is therefore meant to represent the expected variance of the underlying futures contract’s price.
By annualizing and taking the square root of the variance measurement, a standard, normal volatility number, as generally understood in the marketplace parlance, is produced.
By time-weighting the variances to a target of 30 days (prior to taking the square root) a 30-day expected variance is generated. That 30-day variance is then annualized and square-rooted to produce a 30-day forward-looking volatility estimate for the underlying futures.
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