← back to dashboard
quant primer

GEX — dealer gamma
& market regime

How delta hedging by market makers shapes intraday realized volatility — and why one number on the dashboard can tell you whether to fade extremes or follow breakouts.

01

The Greeks — Δ and Γ

delta is the slope, gamma is how fast the slope itself changes

spot price S → option value V ATM (K) slope = Δ curvature = Γ

Delta ($\Delta$) is the first derivative of an option's value with respect to the underlying — how much the option's price moves for a $1 move in the stock.

Gamma ($\Gamma$) is the second derivative — the curvature. It tells you how fast delta itself is changing.

$$\Delta = \frac{\partial V}{\partial S}, \qquad \Gamma = \frac{\partial \Delta}{\partial S} = \frac{\partial^2 V}{\partial S^2}$$

An ATM option has the highest gamma — small spot moves cause big delta swings, which forces dealers into the most hedging activity.

02

Dealers run a delta-neutral book

market makers do not take directional bets — they neutralize delta with the underlying

OPTIONS short 1000 calls Δ = +550 HEDGE short 550 shares Δ = −550 Δₜₒₜₐₗ ≈ 0

When a market maker sells 1,000 ATM calls with $\Delta \approx 0.55$, they immediately short 550 shares of the underlying to cancel out the directional exposure.

The dealer's P&L is now insensitive to small moves in $S$ — they earn the bid-ask spread on the option, not a directional bet.

But this hedge only works for an instant. As $S$ moves, $\Delta$ changes — and the hedge must be rebalanced. That's where gamma comes in.

03

Gamma → re-hedge frequency

a 1-point move in S forces the dealer to trade Γ · OI · 100 shares to stay flat

spot price S(t) shares re-traded to stay Δ-neutral time →

As $S$ moves by $\Delta S$, dealer delta shifts by $\Gamma \cdot \Delta S$. To stay neutral, they must trade that many delta-equivalent shares:

$$\Delta \text{Hedge} = \Gamma \cdot \Delta S \cdot OI \cdot 100$$

High $|\Gamma|$ ⇒ constant rebalancing. The direction of that rebalancing — whether dealers buy on rallies or sell on rallies — depends on whether they're net long or net short gamma.

04

Long vs short gamma

retail buys premium, so dealers are usually short gamma in heavily-traded names

Long gamma — rare

dealer P&L

price ↑ → dealer SELLS shares · price ↓ → dealer BUYS. Profits from realized vol. Trades counter-trend. Supplies liquidity. Stabilizes the market.

Short gamma — typical

dealer P&L

price ↑ → dealer BUYS shares · price ↓ → dealer SELLS. Loses to realized vol. Trades with the trend. Drains liquidity. Amplifies moves.

05

The GEX formula

aggregate dealer dollar-gamma summed across the whole option chain

per-strike Γ contribution (Σ → total GEX) + calls − puts strike →

Summed across every strike on every expiry, weighted by open interest:

$$\text{GEX} = \sum_i \Gamma_i \cdot OI_i \cdot 100 \cdot S^2 \cdot s_i$$

$s_i = +1$ for calls, $-1$ for puts  ·  units: dollars of dealer hedging required per 1% move in S.

Positive total ⇒ dealers stabilize (long gamma). Negative total ⇒ dealers amplify (short gamma).

06

Zero-gamma flip level

the strike where dealer gamma flips sign — your single best regime indicator

0 FLIP spot today NEGATIVE trending · breakouts POSITIVE mean-reverting spot price S →

Plotting cumulative dealer GEX as a function of spot, the curve crosses zero at one strike — the gamma flip level.

Above the flip: dealers are net long gamma → vol compresses, mean-reverting day.

Below the flip: dealers are net short gamma → vol expands, trending day.

Your day-trading playbook should look at distance from the flip, not the absolute GEX number.

✓ positive GEX regime

  • realized vol < implied vol — dealers buy dips & sell rips
  • mean-reverting intraday
  • OPEX pin risk near max-OI strikes
  • short premium / iron condors have edge

⚡ negative GEX regime

  • realized vol > implied vol — dealers chase moves
  • trending intraday — breakouts work
  • gap risk into close
  • long gamma / straddles have edge
Caveat: public GEX models — including this dashboard — assume dealers are net short calls and net long puts (the retail-buys-premium baseline). Real OMM positioning is opaque and can deviate, especially around earnings or sector rotation. Vanna ($\partial \Delta / \partial \sigma$) and charm ($\partial \Delta / \partial t$) flows also drive systematic hedging near OPEX and are not captured here.