Gamma Exposure (GEX) - How Dealer Hedging Shapes Market Volatility

By EC Assets Research Team, Derivatives Strategy · Published 12 August 2026 · Updated 12 August 2026

Gamma Exposure: Gamma exposure aggregates the option gamma held by dealers across the listed chain into a single dollar figure per one percent move in the underlying. When dealers are net long gamma their hedging leans against the move and suppresses volatility; when they are net short it runs with the move and amplifies it. The level where the aggregate flips sign is the zero-gamma level.

What Gamma Exposure Is

Gamma exposure, usually shortened to GEX, estimates how much option gamma the market's dealers are holding, expressed in dollars per unit move in the underlying. It is not a Greek of any single option but an aggregate over the whole listed chain, built to answer one practical question: when the index moves, are the people who hedge options forced to buy or to sell?

Because dealers hedge more or less continuously, their aggregate gamma position decides whether that hedging dampens or amplifies the move. GEX is therefore a positioning indicator, not a valuation measure. It says nothing about whether an option is cheap. It says what happens mechanically once the underlying starts to move.

Where the Position Comes From

A dealer who sells an option is short gamma; one who buys is long gamma. To turn published open interest into a dealer position, GEX applies a sign convention: dealers are assumed to be long the call open interest and short the put open interest, on the reasoning that end investors typically sell calls (overwriting) and buy puts (protection).

That convention is a heuristic, not a fact. Exchanges publish open interest but never who sits on which side of it. Every GEX figure inherits the accuracy of that single assumption, and in a market where retail and institutional demand for upside calls is heavy, the assumption can invert the sign of the entire estimate.

Calculation

For each strike, dealer dollar gamma is the option gamma times open interest times the contract multiplier times the square of spot, scaled to a one percent move:

GEX = Σ_calls Γᵢ × OIᵢ × 100 × S² × 0.01 - Σ_puts Γᵢ × OIᵢ × 100 × S² × 0.01

The S² term appears because gamma measures the change in delta per point, and each point of resulting hedging is itself worth S dollars per share. The output reads as: dealers must trade X dollars of the underlying for every one percent move.

Two Regimes

Positive GEX (dealers long gamma). Hedging runs against the move. Dealers sell as the market rises and buy as it falls. Realised volatility is suppressed, ranges compress, and spot tends to be pulled toward large strikes, the mechanism behind expiry pinning.

Negative GEX (dealers short gamma). Hedging runs with the move. Dealers buy strength and sell weakness. Moves feed on themselves, ranges expand, and declines can accelerate mechanically rather than for any fundamental reason.

The spot level at which the aggregate changes sign is the zero-gamma level, commonly called the gamma flip. Above it markets tend to behave in a mean-reverting way, below it in a trending one. It moves as positioning changes and is recomputed daily.

The Profile Matters More Than the Total

A single headline number hides the thing that drives behaviour: where the gamma actually sits. Gamma is concentrated at strikes carrying large open interest, and it is highest for options that are near the money and close to expiry. Practitioners therefore read the profile strike by strike rather than as one total.

Two consequences follow. First, the largest positive-gamma strikes behave as magnets into expiry, because dealer hedging around them intensifies exactly as spot approaches and time runs down. Second, the profile is rarely symmetric: below the zero-gamma level it usually turns steeply negative, which is why a sell-off that breaks through tends to extend rather than stabilise.

The profile also has a scheduled discontinuity. When a large monthly expiry rolls off, a substantial block of gamma leaves the book at once. The stabilising flow that had been suppressing moves is simply gone, and realised volatility frequently picks up in the days that follow, a pattern desks describe as the post-expiry release.

Worked Example

Suppose aggregate dealer gamma is estimated at plus 8 billion dollars per one percent. A one percent rally then implies dealers must sell roughly 8 billion of the underlying to stay delta neutral, a flow that leans against the rally and caps it.

Now suppose a sharp sell-off carries spot through the zero-gamma level and the aggregate turns to minus 5 billion. The same one percent decline now requires dealers to sell 5 billion into the fall. Nothing about the fundamentals changed. The sign of the hedging flow did, and with it the character of the tape.

Why the Metric Became Prominent

Dealer hedging has always existed; its visibility is what changed. Index option volume has grown sharply, with a large share now concentrated in very short-dated contracts whose gamma is enormous relative to their premium. At the same time, systematic call-overwriting funds and structured product issuance sell large and predictable blocks of volatility, which concentrates dealer positions at known strikes on known dates.

When hedging flow is small relative to cash-market liquidity, GEX is a curiosity. When it rivals that liquidity, the mechanism becomes visible in the price action, and that shift is why the measure moved from dealer desks into general market commentary.

Limitations

• The long-calls, short-puts convention is an assumption, and it breaks down in markets where end investors are buying calls aggressively.
• Open interest is an end-of-day figure. It misses intraday flow entirely, which matters most in markets where same-day expiries dominate volume and positions are opened and closed before the next snapshot exists.
• Gamma is one Greek among several. Vanna and charm flows, the sensitivity of delta to volatility and to the passage of time, can dominate around large expiries and are invisible in a pure gamma figure.
• Providers publish different numbers for the same market because they make different assumptions about the sign convention, the volatility surface used to compute gamma and which contracts to include.
• GEX describes the conditional size of hedging flow, not direction. It says how the market will react to a move, never whether the move will happen.

[!key] Gamma exposure is a map of forced hedging flow, not a forecast. Positive dealer gamma means hedging leans against the move and suppresses realised volatility; negative dealer gamma means hedging runs with the move and amplifies it. The zero-gamma level is where that behaviour switches.

[!warning] Every published GEX figure rests on an assumption exchanges never confirm: that dealers are long the call open interest and short the put open interest. In a market where end investors are buying calls heavily, that assumption can invert the sign of the entire estimate. Treat GEX as a conditional map with a known weak point, never as a trading signal.

Why It Matters for Institutional Investors

• Execution conditions. In a strongly positive-gamma regime dealer hedging absorbs flow, and a large order executes with less impact than the same order would face below the zero-gamma level. The regime is a liquidity condition rather than a market view.
• Sizing, not direction. Aggregate positioning indicates how violently the market is likely to react to a shock. That is an input to position sizing and stop placement, not to the decision whether to be invested.
• Reading air pockets correctly. Declines that accelerate without news are frequently the mechanical result of hedging in a negative-gamma regime. Recognising the mechanism prevents a flow-driven move from being misread as a fundamental signal.

References

1. SqueezeMetrics (2017). Gamma Exposure (GEX). White paper.
2. Ni, S. X., Pearson, N. D., & Poteshman, A. M. (2005). Stock price clustering on option expiration dates. Journal of Financial Economics, 78(1).
3. Golez, B., & Jackwerth, J. C. (2012). Pinning in the S&P 500 futures. Journal of Financial Economics, 106(3).
4. Barbon, A., & Buraschi, A. (2020). Gamma Fragility. Working paper.
5. Hull, J. C. (2022). Options, Futures, and Other Derivatives (11th ed.). Pearson.