Wetín Be Gamma Exposure (GEX)? Dealer Hedging

Gamma exposure, wey people dey usually shorten to GEX, dey estimate how much stock or futures hedging options dealers need do for every one-percent move for underlying. Na positioning statistic wey come from three things: open contracts, option pricing model, plus one big assumption about who dey which side of every trade. This page dey explain the calculation, state the assumptions clearly, and measure the tape underneath am for one July 2026 session wey get fixed date.

Wetín gamma exposure (GEX) dey measure

Make we start one level below. Delta na how sensitive option be to underlying price: delta of 0.40 mean say contract gain roughly 40 cents for every dollar wey stock add. Gamma na the rate wey delta itself dey change. Contract wey get high gamma go see delta change quickly as underlying dey move across the strike, and our option gamma explainer dey trace that curve on real contracts.

Dealer wey sell option and hedge am dey hold position for underlying, then resize that position as price dey move. Gamma set how much resizing every dollar of movement require. Gamma exposure dey scale that per-contract number up to dollar figure for the whole market. The standard process be:

1. For every listed strike and expiry, take open interest, meaning the number of contracts wey still dey outstanding.
2. Calculate each contract gamma with option pricing model, usually Black-Scholes. Feed the model with underlying price, strike, time to expiry, interest rate, and implied volatility.
3. Multiply gamma by open interest, by the 100-share contract multiplier, and by underlying price squared. Then divide by 100. The result na dollars of stock for every 1% move.
4. Give am sign under the convention say dealers hold calls long and puts short. Then add everything across every strike and expiry.

One clearly hypothetical example: 10,000 open contracts wey carry gamma of 0.05, on $100 underlying, give 10,000 times 0.05 times 100 times 100 squared, divided by 100. That na $5,000,000 of stock for every 1% move. Published index-level readings dey reach billions with this same arithmetic.

Positive gamma and negative gamma regimes

The sign na wetin carry the whole meaning.

Positive (long) gamma. Dealer book gain delta as underlying dey rise and lose delta as e dey fall. To keep hedge flat, dealer need sell shares when price strong and buy when price weak. So hedging flow dey move opposite the price move.

Negative (short) gamma. The book lose delta as underlying dey rise and gain delta as e dey fall. To keep hedge flat, dealer need buy when price strong and sell when price weak. That flow dey move in the same direction as price.

People for the market dey call the first one dampening or pinning condition, while the second one na accelerant condition. The level where aggregate estimate cross zero na gamma flip point. All these names describe hedging rulebook, not forecast. Dealer hedging na only one flow among many for market wey dey trade billions of shares in one session, and the estimate no fit see the others. To understand wetin hedging desk dey actually do throughout the day, see how market makers make money.

Where the contracts really dey

Gamma per contract dey peak close to the money and close to expiry, so strikes wey dey nearest to spot carry most of the arithmetic. This na how that concentration show for the tape: every same-day SPY contract wey trade on Monday, July 6, 2026, grouped by strike and ranked by contracts traded.

SELECT strike_label AS strike,
       round(sumIf(contracts, opt_type = 'C') / 1e3, 1) AS call_contracts_k,
       round(sumIf(contracts, opt_type = 'P') / 1e3, 1) AS put_contracts_k,
       round(sum(contracts) / 1e3, 1)                   AS total_contracts_k
FROM (
    SELECT substring(ticker, length(ticker) - 8, 1)              AS opt_type,
           toUInt32OrZero(substring(ticker, length(ticker) - 7, 8)) AS strike_thousandths,
           toString(intDiv(strike_thousandths, 1000))            AS strike_label,
           sum(toFloat64(volume))                                AS contracts
    FROM global_markets.options_minute_aggs
    WHERE window_start >= toDateTime('2026-07-06 08:00:00')
      AND window_start <  toDateTime('2026-07-07 04:00:00')
      AND startsWith(ticker, 'O:SPY260706')
    GROUP BY ticker, opt_type, strike_thousandths, strike_label
)
GROUP BY strike_label
ORDER BY sum(contracts) DESC
LIMIT 10

The busiest strike for the session na $751, with 1817.5 thousand contracts. The total split into 1082.3 thousand calls against 735.2 thousand puts. The next strike down the list, $750, take 1725.9 thousand. By the tenth-ranked strike, the count reach 159.6 thousand. Ten strikes, only a few dollars apart, hold most of the day’s activity for instrument wey dey above $700.

The call and put mix dey change across spot. Na this tilt signed GEX calculation dey try capture. At $753, above the money, calls lead puts 587.8 thousand to 74.8 thousand. At $748, below am, puts lead, 457.4 thousand against 107 thousand.

One important point wey the panel show: this na volume, meaning number of contracts wey change hands, no be open interest, meaning number wey still dey outstanding after the bell. GEX dey use the second one. Options volume vs open interest dey explain the difference.

Front-dated contracts dominate the tape

SELECT multiIf(dte = 0, '0 (expires today)',
               dte = 1, '1 day',
               dte <= 7, '2-7 days',
               dte <= 30, '8-30 days',
               '31+ days') AS days_to_expiry,
       round(sum(volume) / 1e6, 2) AS contracts_mm,
       round(100.0 * sum(volume) / sum(sum(volume)) OVER (), 1) AS pct_of_volume
FROM (
    SELECT toFloat64(volume) AS volume,
           dateDiff('day',
                    toDate(toTimeZone(window_start, 'America/New_York')),
                    toDateOrNull(concat('20', substring(ticker, length(ticker) - 14, 6)))) AS dte
    FROM global_markets.options_minute_aggs
    WHERE window_start >= toDateTime('2026-07-06 08:00:00')
      AND window_start <  toDateTime('2026-07-07 04:00:00')
      AND toDate(toTimeZone(window_start, 'America/New_York')) = toDate('2026-07-06')
)
WHERE dte >= 0
GROUP BY days_to_expiry
ORDER BY min(dte)

Contracts wey expire that same afternoon make up 38.8% of all US options volume for the session. That na 23.52 million contracts, against 18.6% for everything wey get more than one month before expiry. Gamma per contract dey biggest for exactly that front bucket. Na also the bucket wey open interest turn over fastest. GEX figure wey use the previous evening clearing file dey describe book wey don already change. Zero days to expiry dey cover the same-day contract in detail.

The estimate dey cluster around small number of products

SELECT root AS underlying,
       round(sum(volume) / 1e6, 2) AS zero_dte_contracts_mm,
       round(100.0 * sum(volume) / sum(sum(volume)) OVER (), 1) AS pct_of_zero_dte_volume
FROM (
    SELECT substring(ticker, 3, length(ticker) - 17) AS root,
           toFloat64(volume) AS volume
    FROM global_markets.options_minute_aggs
    WHERE window_start >= toDateTime('2026-07-06 08:00:00')
      AND window_start <  toDateTime('2026-07-07 04:00:00')
      AND toDate(toTimeZone(window_start, 'America/New_York')) = toDate('2026-07-06')
      AND toDateOrNull(concat('20', substring(ticker, length(ticker) - 14, 6))) = toDate(toTimeZone(window_start, 'America/New_York'))
)
WHERE root != 'SPCX'
GROUP BY root
ORDER BY sum(volume) DESC
LIMIT 8

Same-day flow dey concentrate heavily: SPY take 36.1%, QQQ take another 21.2%, while SPXW, the weekly cash-settled S&P 500 root, take 11.3%. Published GEX series dey quote this same short list of underlyings. Their chains deep enough for strike-by-strike sum to carry meaningful information. Single-name GEX for thinly traded ticker na arithmetic based on only a few contracts.

The assumptions wey GEX dey depend on

Open interest no get side. Exchanges publish how many contracts dey outstanding for every strike, but dem no publish who dey long and who dey short. The convention say dealers hold calls long and puts short come from broad assumption about customer behaviour: retail dey buy calls, while institutions dey buy puts for protection. Na heuristic, and for individual strikes on individual days, e fit simply be wrong.

Gamma dey come from model. Black-Scholes need implied volatility for every strike, a rate, and dividend assumption. If volatility surface change, every gamma inside the sum go change too.

Open interest stale by design. E dey publish once per session from clearing data after close. So intraday GEX print dey anchor to yesterday’s book.

Product boundary na choice. SPX index options, SPY ETF options and E-mini futures options all reference S&P 500, but dem get different multipliers. Including or excluding any of dem fit move the total by billions of dollars.

Why two GEX numbers no dey agree

Two dashboards fit read the same market and print totals wey far apart. Every possible reason for the difference dey inside the list above: which products dem include, which volatility surface enter the model, whether the figure dey quote per 1% move or per one index point, whether dealer sign apply per strike or to aggregate, and how dem handle expiry-day contracts. Level from one publisher compared with threshold from another na comparison of two different statistics. If you read one source series against its own history, the units go remain consistent.

Max pain, the neighbouring statistic

Max pain na the strike where the biggest total dollar value of open contracts go expire worthless. E dey calculate from open interest alone, without volatility model or dealer-side assumption, and e name a price instead of sizing a flow. People dey quote both side by side around monthly expiries, but dem answer different questions: max pain point to a strike, while gamma exposure size hedging bill. Our max pain walkthrough dey run the calculation strike by strike on real SPY chain and check how close settlement actually land to the answer.

Wetín practitioners dey actually use

Open-source GEX and positioning dashboards common for code-sharing sites. Reading one na the fastest way to see these assumptions in concrete form. Chain snapshot, model inputs, sign convention and aggregation step all fit dey inside a few hundred lines. As of July 2026, several of these projects still dey actively maintained. The ones wey worth your time dey state their volatility source and dealer-side convention from the beginning. Number wey derivation no publish, nobody fit check am. Traders wey read GEX together with flow often pair am with unusual options activity and the wider option Greeks.

Gamma exposure FAQ

Wetín positive gamma exposure mean?

Positive GEX describe estimated dealer book wey gain delta as underlying dey rise and lose delta as underlying dey fall. To keep that book hedged, dealer need sell when price strong and buy when price weak. Practitioners describe the condition as dampening or pinning. Na description of hedging rulebook, no be price forecast.

Wetín be gamma flip point?

Gamma flip na underlying price where aggregate estimate of GEX model cross from positive to negative. Above that level, modelled hedging flow dey move opposite the price move. Below am, flow dey move with the move. The level go change whenever open interest, volatility surface or model assumptions change, so two publishers rarely quote the same flip.

Where open interest behind GEX dey come from?

Open interest dey publish once every trading session from clearing data after close. E show number of contracts outstanding for each strike and expiry. E no show which counterparty dey long or short. That na the biggest single assumption inside any GEX calculation.

Gamma exposure na the same thing as gamma squeeze?

No. Gamma exposure na standing estimate of hedging sensitivity across one whole book. Gamma squeeze na description for specific episode where rapid buying dey happen in one name and hedging flow na one of the moving parts. GEX na attempt to measure something; squeeze label na description of event after e happen.

GEX fit calculate for one stock?

Mechanically, yes. The same sum fit run on any listed chain. But estimate go become noisy quickly for thin chains, where small number of strikes and wide implied-volatility marks dominate the total. For the July 2026 session above, same-day volume outside the index products drop quickly after the top few single-name roots.

Every panel above na stored query, and you fit access the SQL with one click. Run the same scan on any chain for the Strasmore terminal.