# Implied volatility

Also written implied vol.

*https://stockmarketstack.com/glossary/implied-volatility · next to Stock Market Data APIs*

**Definition:** The volatility figure that, put into an option pricing model, makes the model reproduce a price observed in the market. It is not measured from the underlying's history; it is solved for backwards from a quote. So it inherits every assumption in the model and every choice about which quote was used, which is why two vendors publish different implied volatilities for the same contract on the same day.

## How it works

Every other input to an option pricing model is observable: the underlying price, the strike, the
days to expiry, a rate, a dividend estimate. Volatility is not. So the calculation is usually run the
other way round — take the option's market price as given, and solve for the volatility number that
makes the model return it. That number is the implied volatility, and the arrow of causation is the
whole point: the price came first, the volatility is derived from it.

Two things follow immediately.

**It is a model inversion, so it is model-dependent.** Change the model and the same quote implies a
different figure. The SEC's guidance on valuing share-based payments, which has to survive an audit,
says plainly that it "does not specify a preference for a particular valuation technique or model",
notes that "option-pricing models require an estimate of expected volatility as an assumption
because an option's value is dependent on potential share returns over the option's term", and
allows a company with actively traded options to place "greater (or even exclusive) reliance on
implied volatility" only after weighing trading volume, strike similarity and comparable term. An
official document declining to name one method is the clearest statement available that there is no
single right answer to invert.

**It is solved from one particular price, and nobody agrees which.** Last trade, bid, ask, or the
midpoint of the two — four defensible choices, four different numbers, and on an illiquid series the
gap between them is not small. Cboe's volatility index mathematics, version 5.0 revised 26 February
2026, commits to the mid and says so: call and put prices "reflect the midpoint of each candidate
constituent option series' bid / ask quotes", with a defined mid of bid plus ask over two, and series
whose quotes are null or crossed are excluded outright. Making the convention explicit is what makes
a published figure checkable.

That same document is worth reading for a second reason. The VIX family does not invert a
Black-Scholes price at all — the methodology "is based on theoretical work in pricing variance swaps
to isolate exposure to volatility of an asset", weighting constituent options inversely to the square
of their strike. So "implied volatility" already names at least two different constructions: a
per-contract model inversion, and an index built from a portfolio of options without a per-contract
model. A number labelled IV on a chain is the first. A number labelled IV on an index is often the
second.

## Where vendors diverge after that

**Smoothing and fitting.** Raw per-contract implied volatilities are noisy, because the quotes they
came from are noisy. Most serious providers fit a surface across strikes and expiries and publish the
fitted value, which is a modelling decision applied on top of a modelling decision.

**Quote filtering.** Which series are dropped for being crossed, zero-bid, stale or off the pricing
grid. Cboe's published algorithm excludes options with a bid or ask price equal to zero and applies
a time-windowed quote filter; a vendor with no published rule has still made one.

**The rate and dividend inputs**, which feed the inversion exactly as they feed everything else. The
[greeks](https://stockmarketstack.com/glossary/greeks) entry works through that set, and this page is its input rather than its
sibling: vega is the sensitivity to this number, and the greeks are usually computed at the volatility
solved here.

**Snapshot timing.** An implied volatility from an option quote and an underlying price taken a
second apart is measuring the gap between the two clocks as much as anything else.

## Why it matters here

For the cards in this catalogue the practical consequences are narrow and worth stating flatly.

An IV series from two providers cannot be stitched together. The discontinuity at the join is their
methodologies changing, not the market, and it will look exactly like a real event. Same for an IV
rank or percentile computed off a spliced history.

A smoothed surface is a different purchase from a chain. [ORATS](https://stockmarketstack.com/tools/orats) sells the surface as
the product, going back years, which is what makes a consistent cross-sectional comparison possible
at all; a plain chain from a general-purpose API gives you quotes and leaves the fitting to you.
[Cboe DataShop](https://stockmarketstack.com/tools/cboe-datashop) sells exchange files with implied volatility attached as a more
expensive variant of the same day's summary, which prices the distinction honestly. Everything in the
catalogue that touches the asset class is on [options data](https://stockmarketstack.com/collections/options-data), and
[how to get an options chain](https://stockmarketstack.com/how-to/get-an-options-chain) covers what the free tiers hand over.

And if the figure has to be reproducible, own the inversion. [QuantLib](https://stockmarketstack.com/tools/quantlib) supplies the
models and no data; the [NBBO](https://stockmarketstack.com/glossary/nbbo) entry covers which quote you should be inverting, and
recording that choice is most of the difference between a number and a number somebody can check.

## Where you will meet this

- [ORATS](https://stockmarketstack.com/tools/orats.md)
- [QuantLib](https://stockmarketstack.com/tools/quantlib.md)
- [Cboe DataShop](https://stockmarketstack.com/tools/cboe-datashop.md)
- [Intrinio](https://stockmarketstack.com/tools/intrinio.md)
- [Market Chameleon](https://stockmarketstack.com/tools/market-chameleon.md)
- [Alpaca Market Data](https://stockmarketstack.com/tools/alpaca-market-data.md)
- [Finnhub](https://stockmarketstack.com/tools/finnhub.md)
- [Finviz Elite](https://stockmarketstack.com/tools/finviz-elite.md)
- [FirstRate Data](https://stockmarketstack.com/tools/firstrate-data.md)
- [MotiveWave](https://stockmarketstack.com/tools/motivewave.md)
- [skfolio](https://stockmarketstack.com/tools/skfolio.md)
- [Trademetria](https://stockmarketstack.com/tools/trademetria.md)

## FAQ

### Is implied volatility a forecast?

It is a restatement of a price, expressed in volatility units. The Options Industry Council describes it as what the marketplace expects the asset to move based on the price of the option, which is a description of the quote rather than a claim that the quote is correct. Read it as a normalised price that lets two contracts with different strikes be compared at all.

### Which price should the implied volatility be solved from?

Whichever one you can say out loud and apply consistently. A mid of the bid and ask is the usual choice and is what Cboe's published index mathematics uses. A last trade can be stale by hours on an illiquid series. The wrong answer is not knowing, or mixing two conventions inside one dataset without recording which line came from which.

## Sources

1. [Cboe Volatility Index Mathematics Methodology, version 5.0](https://cdn.cboe.com/resources/indices/Cboe_Volatility_Index_Mathematics_Methodology.pdf) — Cboe Global Indices, 2026-02-26
2. [Staff Accounting Bulletin Topic 14, Share-Based Payment](https://www.sec.gov/interps/account/sabcodet14.htm) — US Securities and Exchange Commission, read 2026-09-21
3. [Volatility and the Greeks](https://www.optionseducation.org/advancedconcepts/volatility-the-greeks) — The Options Industry Council, read 2026-09-21

*Last updated 2026-09-21. A reference page, corrected in place — not a dated post.*