Derived from the world’s most actively traded options on futures contracts across major asset classes, 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.
CVOL is currently available in the form of historical reference indexes (daily, close-to-close basis, using settlement prices) on benchmark products spanning five asset classes across financial and commodity markets:
We publish the following CVOL Indexes and indicators on each supported product:
CVOL Indexes and indicators are published once-per-day and available with two or more years of history.
CVOL Indexes measure the expected risk or implied volatility of an underlying future based on the information contained in the prices of options on that underlying future. In general, the expectation has a 30-day forward-looking horizon. The metric is an annualized standard deviation as used in typical option pricing models. The index family also includes metrics predicated on just out-of-the-money (OTM) calls and out-of-the-money OTM puts, ‘UpVar’ and ‘DnVar’, which are holistically consistent with the metric generated by using both the calls and the puts together. These related indexes provide insight into the direction that the collective marketplace is expecting greater risk.
CVOL Indexes use the option prices from one or 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 all 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 future.
Simple variance, also known as Gaussian variance, is the square of the standard deviation of a normally distributed population. Simple variance allows for the underlying asset or futures prices to be negative, such as interest rates, or even commodities, such as oil.
This characteristic of simple variance distinguishes itself from log variance. Log variance, or the assumption that the underlying asset or future will exhibit a log normal distribution, does not allow for prices below zero. In fact, log variance swaps, which have been the most commonly employed variance swaps in the marketplace for several decades, will have an infinite value if an asset actual priced at zero. Other volatility indexes that use all the option prices from a specific tenor often attempt to build a replicating portfolio of that potentially infinite payoff. This renders those log variance metrics as being not very “simple.”
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 across asset classes themselves.
In addition to the primary implied volatility, CVOL Index, there are five other accompanying indicators which will price specific properties of the underlying asset’s expected future risk, as reflected by its options prices.
The five additional indicators are: ‘UpVariance’ or ‘UpVar;’ ‘DownVariance’ or ‘DnVar;’ Skew; ‘at-the-money’ or ‘ATM’; and ‘Convexity’.
Up Variance, or UpVar, is a metric that employs the same method for estimating the standard deviation as simple variance, but specifically uses only OTM calls in the calculation. The variance estimate is then doubled or mirrored in order to provide an apples-to-apples analogue to the two-sided set of options used in the regular index calculation.
Down Variance, or DnVar, like Up Variance, employs the same method for estimating the standard deviation as simple variance, but uses only OTM puts in the calculation. Similarly, the variance estimate is then doubled or mirrored in order to provide an apples-to-apples analogue to the two-sided set of options used in the regular calculation.
Skew compares the Up Variance and Down Variance numbers to provide insight into how much implied volatility is priced into Calls compared to Puts. Two Skew numbers are provided, one showing the difference between the two (UpVar – DnVar), such that negative values indicate that the implied volatility is collectively higher for puts than for calls. The other Skew metric is the ratio of the two calculated by dividing the UpVar by the DnVar. In this case, if the puts had collectively higher implied volatility, the resulting measurement would be less than 1.0.
For Treasury products, there are two numeraires, price and yield. Since yields move inversely with the price of bonds, the yield version of UpVar is actually calculated using the puts that inform the DnVar for the price version. And the yield DnVar is similarly drawn from the calls that inform the price UpVar.
The ‘at-the-money’ (ATM) indicator is the implied volatility of an option that has a strike exactly equal to the futures price. If the futures price happens to be exactly equal to an existing strike that is used in the CVOL calculation, that price is transformed into an implied volatility number using a closed-form formula. (Brenner-Subramaniam). If the futures price is between existing strikes, a synthetic ATM price is generated for that price using the closest existing option price and an assumption of 50 delta multiplied by the difference between that closest strike and the futures price. This synthetic price will undergo that same transformation using the same closed-form formula as above.
The convexity indictor is the ratio of the CVOL metric to the ‘at-the-money’ (ATM) indicator. This metric will be above one when the overall measurement drawn from all the strikes is higher than the ATM implied volatility and less than one if the overall CVOL metric is less than the ATM implied volatility. It is intended to provide a measure of the volatility “smile” that results from OTM options having individual implied volatilities that are successively greater.
We calculate and publish CVOL Indexes and indicators on 29 products across five asset classes, in addition to six broad-based market indexes on G5 FX, US Treasuries, Energy, Metals, Agriculture, and cross-asset commodities.
Broad-based CVOL Indexes are calculated by taking the component CVOL Indexes and weighting them by each products’ respective dollar vega open interest for all options of that product. This weighting system reflects each product’s overall risk profile in the market in a normalized dollar amount. The weighted values are then summed to arrive at the broad-based index value.
Each official daily index fixing and each indicator fixing will be published same-day, after preliminary settlement prices and files have been published.
CME Group will begin publishing CVOL Indexes on a daily, close-to-close basis, using settlement prices. These initial publications will also provide two years of historical EOD implied volatility numbers for each index and indicator series on each product being published.
It is our goal to begin publishing real-time index calculations in H1 2022.
CVOL is a family of benchmarks based on industry best practices, complying with the IOSCO Principles for Financial Benchmarks (July 2013), including but not limited to implementing a governance structure and creating a transparent methodology. The methodology and benchmark statements will be made publicly available.
CVOL Indexes are administered by CME Group Benchmark Administration Limited (CBA). In line with the IOSCO Principles for Financial Benchmarks, CBA has appointed an Oversight Committee, to review the integrity of the benchmark and challenge the administrator in all aspects of the benchmark determination process. CVOL Indexes will be subject to a regular audit process
We have several resources you can access to learn more about the CVOL Indexes, all of which are available on the CVOL Index homepage.
The latest index values and indicators are displayed on our CVOL Index Visualizer tool, provided by QuikStrike.
Registered users can also download at least two years of history for each index through CME DataMine.
The full description for the CVOL Index methodology is available here.
CME will offer a variety of direct licensing options including redistribution, historical usage, derived usage, and other common customer data licensing needs. Please contact CME Data Sales to discuss your specific licensing needs.
CME Group is working with redistributors to make this data available in their platforms and other data services. Ultimately, many third parties prioritize new data products based upon their direct customer demand. Please contact your redistributor to request this data as part of your data services.
As the world’s leading derivatives marketplace, CME Group is where the world comes to manage risk. Comprised of four exchanges - CME, CBOT, NYMEX and COMEX - we offer the widest range of global benchmark products across all major asset classes, helping businesses everywhere mitigate the myriad of risks they face in today's uncertain global economy.
Follow us for global economic and financial news.