Direct Answer
Vomma, also called volga, is the sensitivity of vega to a change in implied volatility (dVega/dVol, the second derivative d2V/dsigma2). Vomma exposure aggregates it across open interest to estimate convexity to volatility. Positive vomma means vega rises as volatility rises, so the position gains convexity to a volatility spike; far out-of-the-money options typically have the largest vomma.
Vomma Exposure: Formula, Meaning, Signals, Examples and How to Use It
How Is Vomma Exposure Calculated?
Vomma, also called volga, is the sensitivity of vega to a change in implied volatility (dVega/dVol, the second derivative d2V/dsigma2). Vomma exposure aggregates it across open interest to estimate convexity to volatility.
Formula: vomma = vega x d1 x d2 / sigma; vomma exposure = sum of (sign_i x vomma_i x open interest_i x 100)
Inputs:
- Vega, d1, d2 and implied volatility sigma from an option pricing model
- Open interest by strike and expiry
- Contract multiplier (100)
- Assumption about which side dealers hold
Worked example. With vega 12.0, d1 of 0.25, d2 of 0.10 and volatility of 25%, vomma is 1.20 per unit of volatility. The inputs are illustrative numbers, not market data.
Reading it. Positive vomma means vega rises as volatility rises, so the position gains convexity to a volatility spike; far out-of-the-money options typically have the largest vomma. Aggregates are used to reason about how sensitive total vega is to volatility changes.
Limits. It is a dealer-positioning estimate: open interest does not reveal who is long or short, so the sign is assumed. Vomma is model dependent, small near the money, and unit conventions (per unit or per point of volatility) vary.
What is Vomma Exposure?
Vomma, also called volga, is the sensitivity of vega to a change in implied volatility (dVega/dVol, the second derivative d2V/dsigma2). Vomma exposure aggregates it across open interest to estimate convexity to volatility.
How to use Vomma Exposure
Positive vomma means vega rises as volatility rises, so the position gains convexity to a volatility spike; far out-of-the-money options typically have the largest vomma. Aggregates are used to reason about how sensitive total vega is to volatility changes. A reading alone is never a buy or sell signal; it needs context from price structure, volume, volatility and the broader market regime.
Strengths
- Vomma measures how vega itself grows as volatility rises, so the aggregate shows convexity to volatility and not just linear volatility exposure.
- Because vomma is built from vega, d1, d2 and volatility, it uses inputs already available from any standard pricing model.
- Reproducible when the formula and data convention are fixed.
Weaknesses and limitations
- It matters mostly for a large volatility move, so for ordinary day-to-day changes in implied volatility its effect is small next to vega.
- As a second-order volatility effect, it cannot be interpreted without vega exposure alongside it to provide the first-order scale.
- Correlated indicators can create false confidence by repeating the same underlying information.
Editorial and risk note
This page is educational content, not individualized investment advice. It should not imply guaranteed prediction, accuracy or outperformance.
Frequently Asked Questions
Is Vomma Exposure a buy or sell signal?
No. Positive vomma means vega rises as volatility rises, so the position gains convexity to a volatility spike; far out-of-the-money options typically have the largest vomma. It is a dealer-positioning estimate: open interest does not reveal who is long or short, so the sign is assumed. A trade built on it still needs a trigger, an invalidation rule, a position size and realistic execution assumptions.
What is the best setting for Vomma Exposure?
Vomma Exposure takes these inputs: vega, d1, d2 and implied volatility sigma from an option pricing model; open interest by strike and expiry; contract multiplier (100). There is no universal best setting for the tunable ones, so test them across instruments, regimes and out-of-sample periods and favor stable parameter regions over one historical winner.
Can Vomma Exposure be used by itself?
It is a dealer-positioning estimate: open interest does not reveal who is long or short, so the sign is assumed. Vomma is model dependent, small near the money, and unit conventions (per unit or per point of volatility) vary. For that reason it is read next to measures of direction, participation, valuation, liquidity and risk, not alone.
Does Vomma Exposure work on every timeframe?
The calculation (vomma = vega x d1 x d2 / sigma; vomma exposure = sum of (sign_i x vomma_i x open interest_i x 100)) can be run on any bar size, but behavior is not portable: a reading on a five-minute chart describes a very different market window from the same reading on a daily chart. Validate the exact timeframe before relying on it.
Why does Vomma Exposure give false signals?
It matters mostly for a large volatility move, so for ordinary day-to-day changes in implied volatility its effect is small next to vega. As a second-order volatility effect, it cannot be interpreted without vega exposure alongside it to provide the first-order scale. Lag, noise and regime changes add to this, because market participants react to new information after the reading is calculated.
How should Vomma Exposure be backtested?
Rebuild Vomma Exposure from vega, d1, d2 and implied volatility sigma from an option pricing model using point-in-time data, write the rules before testing, include delisted securities where relevant, model realistic fills and costs, reserve a validation sample and compare with a simpler baseline.