Methodology & GEX Explained

An experimental playground to find the best way to calculate GEX for SPX, which can be useful in figuring out dealer's positioning and gamma exposure levels.

What is GEX?

Gamma Exposure (GEX) measures the estimated hedging exposure of Market Makers (Dealers). Dealers are contractually obligated to provide liquidity, meaning they must take the other side of your trade. To manage their risk, they must hedge their positions by buying or selling the underlying asset (SPX/ES futures) as the price moves.

By calculating the total Gamma Exposure across all option strikes, we can predict where Dealers will be forced to Buy (Support/Resistance) or Sell (Acceleration).

The Formula

We calculate the Notional Gamma Exposure for every single strike across all expiration dates.

Where:

• Gamma: The rate of change of Delta. This tells us how much the Dealer's hedge ratio changes for a 1 point move in SPX.
• IV_Adjustment: √(Strike_IV / ATM_IV) — weights gamma by implied volatility relative to at-the-money. See below.
• Open Interest: The total number of active contracts at that strike.
• SpotPrice²: Converts the raw share count into a Notional Dollar Value (the actual capital dealers must deploy).

IV-Adjusted Gamma

Standard GEX calculations use flat volatility assumptions. We improve on this by weighting gamma based on each strike's implied volatility relative to ATM IV:

Why this matters:

• Put Skew: OTM puts typically have higher IV due to demand for downside protection. This adjustment gives put gamma more weight, reflecting the market's asymmetric risk perception.
• Spot-Vol Correlation: When SPX drops, IV typically spikes. Higher IV strikes become more impactful, and our adjustment captures this dynamic.
• Real-World Hedging: Dealers hedge based on actual vol dynamics, not flat assumptions. A 22% IV put carries more hedging urgency than a 12% IV call.

The square root (exponent 0.5) provides a moderate adjustment — a strike with 50% higher IV gets ~22% more gamma weight, not 50%. This balances sensitivity with stability.

IV Trend Indicator

We track ATM implied volatility changes and display the trend in the market regime badge:

• IV↑: Volatility is rising — typically bearish, expect larger moves
• IV↓: Volatility is falling — typically bullish, expect mean reversion

Standard Assumptions

The standard industry heuristic for the S&P 500 index:

• Dealers are Long Calls: Customers (Institutions) typically sell calls for yield (Overwriting). Dealers take the other side (Long).
• Dealers are Short Puts: Customers typically buy puts for protection (Hedging). Dealers take the other side (Short).

This model holds true for the vast majority of market conditions, where structural flows dominate.

Our Approaches

While the standard model is robust, it can be inaccurate during specific events (e.g., retail FOMO rallies). A more precise method involves Trade Flow Analysis:

• Aggressor Logic: Instead of assuming, we analyze every trade tick. If a trade hits the Ask, the customer is buying (Dealer Selling). If it hits the Bid, the customer is selling (Dealer Buying).
• Real-Time Inventory: This builds a cumulative profile of actual Dealer positioning rather than relying on static assumptions.

"Customer vs Market Maker" volume data

• Distinguish customer buy-to-open (dealer short) vs customer sell-to-open (dealer long)
• To fix this, we use tick data and bid/ask to categorize customer/dealer.

  Dealer GEX = (Customer Buy Volume - Customer Sell Volume) × Gamma × OI

Real-Time Gamma Convexity

• Most GEX tools provide static levels based on yesterday's close. We go further.
• We recalculates intraday gamma for every single option strike every 10 seconds based on live Spot Price.
• This allows you to see how the 'Gamma Gravity' shifts in real-time as price approaches key levels, revealing the true hedging pressure dealers face right now, not yesterday.

OI vs Volume Confusion (Stale vs Active)

• Old, huge OI strikes (like LEAPS or old hedges) often have "Zombie Gamma". Dealers hedged them months ago, and they don't generate new urgent hedging flow (dynamic hedging happens, but it's gradual).
• Why This Is Wrong:
  • High OI but no volume = stale positions, dealers already hedged
  • High volume but low OI = intraday trading, no lasting dealer exposure
  • OI increasing = new dealer short positions (more hedging pressure)
  • OI decreasing = positions closing (reduced hedging needs)

We mitigate this via:

Weight by volume recency:
    Effective_OI = OI × (Volume_Today / Average_Volume_10day)
    Weighted_GEX = Gamma × Effective_OI × Multiplier × Spot²

Track OI changes:
    Delta_OI = OI_today - OI_yesterday
    Active_GEX = Gamma × Delta_OI × Multiplier × Spot²        

Key Levels Explained

1. The Call Wall (Solid Green)

The strike with the largest positive Net GEX based on Open Interest. This acts as a major Resistance level. Dealers are heavily Long Gamma here, suppressing volatility and absorbing buying pressure.

2. The Put Wall (Solid Red)

The strike with the largest Put GEX based on Open Interest. This is typically the major Support floor.

3. Active Walls (Dashed Green/Red)

These levels are calculated using Volume-Weighted GEX (VW-GEX). While standard walls show where positions are established (Open Interest), Active Walls reveal where the action is today (Volume).

• Active Call Wall: Where traders are aggressively positioning/defending calls intraday.
• Active Put Wall: Where the highest intraday hedging/shorting activity is occurring.

4. Zero Gamma (Orange) — the Gamma Flip

The "Flip Line." We compute it as the precise zero-crossing of the aggregate dealer gamma profile: we sweep net dealer gamma across price and interpolate the exact point where it changes sign, rather than just picking the nearest strike. The line can therefore sit between strikes, where the real flip happens.

Above the flip — positive gamma: dealers dampen moves. Low volatility, mean reversion; walls act as reliable support/resistance.
Below the flip — negative gamma: dealers amplify moves. High volatility, trend acceleration; walls stop holding and become breakout triggers. When price drops below the flip, the Call/Put walls are relabeled Call Wall ↑ break / Put Wall ↓ break and recolored, and the Zero Gamma line thickens — it becomes the magnet price tends to revert toward.

5. Max Gamma Strike (Dotted Yellow)

The single strike with the highest absolute Net GEX magnitude. This acts as a "Magnet" or "Pin." Because dealer hedging requirements maximize here, price action often gravitates toward and sticks to this level, especially into market close or expiration.

6. Projected Pin (Purple) (PRO)

Calculates the probability of SPX "pinning" at a specific strike by 4:00 PM ET. It combines the Black-Scholes probability density function (PDF) with current Dealer Gamma gravity to find the highest confidence magnetic zone for the close.

7. Gamma Acceleration (Dashed Green/Red) (PRO)

Identifies "Squeeze Zones" where dealer hedging velocity is steepening rapidly.

• Gamma Accel Buy: Dealers must buy underlying assets at an accelerating rate as price rises.
• Gamma Accel Sell: Dealers must sell underlying assets at an accelerating rate as price falls.

8. Significant Strikes (Dotted White)

Secondary levels of high interest where price often "pins" or pauses, regardless of directional bias. These are now selected and ranked by the React-at Importance Score below — so the strikes we surface are the ones actually in play near price, not just the biggest raw gamma far away.

9. React-at Importance Score & Visual Emphasis

On a busy day the chart can carry a dozen levels of different types. Instead of treating them as a flat list, every level gets a React-at score (0–100) — an estimate of how likely price is to react there right now. Each level stays on the chart, but its line thickness and opacity scale with the score: levels in play are bold and bright, while distant or stale ones fade to faint context (nothing disappears).

The score combines, per strike:

• Proximity — a Gaussian weight on distance from spot, scaled by the day's Expected Move (ATM implied vol × √time). This is the dominant term: you react where price actually interacts, so a near-the-money strike outranks a huge but far-away wall.
• Gamma magnitude — blended from Open Interest gamma (positioning) and today's Volume gamma (fresh flow), so the ranking tracks where the action is now.
• Gamma gradient — how steeply dealer hedging changes around the strike; the steepest-slope strikes are the real pivots.
• Regime tilt — below the Gamma Flip (negative gamma) strikes near the flip get boosted, because price is trending and reverts toward it; above the flip no tilt is needed.

Hold Probability

When you hover over any level, we display a Hold Probability — our estimate of how likely that level is to act as support/resistance. (This hover estimate is separate from the React-at score above: React-at decides how strongly a level is drawn; Hold Probability is the per-touch read you get on hover.) This is calculated using multiple real-time factors:

Factors Explained

• GEX Strength (+0 to +25%): How strong is this level relative to the max? We use Total GEX (Call + Put), not Net GEX, because a strike with high positioning on both sides is very magnetic regardless of net direction.
• Touch Decay (-5% per touch): Each time price touches a level, it weakens. We track touches with a 60-second cooldown. A level touched 3 times is weaker than a fresh level.
• IV Trend (±10%): Rising IV (IV↑) indicates expanding volatility — levels are harder to hold. Falling IV (IV↓) means contracting volatility — levels hold better.
• Momentum (±15%): Strong momentum toward a resistance/support level reduces hold probability. For pin/magnet levels, we instead give a bonus when price is nearby.
• Time of Day (±10%): Market open (9:30 AM) and close (3:00+ PM) are volatile — levels weaker. Lunch hours (11 AM - 2 PM) are stable — levels stronger. Pin levels get an extra boost after 3 PM (expiration pin effect).

Level Types

• Call Wall / Active Call Wall: Resistance levels — penalized when price has upward momentum toward them.
• Put Wall / Active Put Wall: Support levels — penalized when price has downward momentum toward them.
• Max Gamma / Significant Levels: Pin/magnet levels — bonus when price is close, extra boost near market close.
• Gamma Accel Zones: Squeeze zones — bonus when momentum is strong in either direction.

The final probability is clamped between 10% and 95%. Color coding: Green (≥70%) = strong hold, Orange (50-70%) = moderate, Red (<50%) = weak.

Frequently Asked Questions

Papers & Inspiration

OpenSera stands on the shoulders of the academics and practitioners who first formalized how dealer hedging shapes price. The models behind our gamma flip, react-at level ranking, expected-move sizing, and the hold/break calibration we're building all trace back to the work below — a thank-you and a reading list. (Titles link to a scholar search.)

• Barbon & Buraschi (2021) — "Gamma Fragility." Quantifies how dealer gamma imbalance amplifies or dampens intraday price impact — the basis for our gamma-regime tilt and proximity-weighted level scoring.
• Gârleanu, Pedersen & Poteshman (2009) — "Demand-Based Option Pricing." The theoretical foundation for why dealer inventory and hedging move prices at all.
• Avellaneda & Lipkin (2003) — "A Market-Induced Mechanism for Stock Pinning." The mechanics of price being drawn toward strikes — behind our Projected Pin and Max Gamma magnets.
• Ni, Pearson & Poteshman (2005) — "Stock Price Clustering on Option Expiration Dates." Empirical evidence that options positioning pins the underlying near expiration.
• Baltussen, Da, Lammers & Martens (2021) — "Hedging Demand and Market Intraday Momentum." How dealer hedging creates intraday momentum and reversal — informs our time-of-day and regime logic.
• Kyle (1985) — "Continuous Auctions and Insider Trading." Kyle's λ (price impact per unit of order flow) — the lens for turning a gamma imbalance into an expected move size.
• Almgren & Chriss (2000) — "Optimal Execution of Portfolio Transactions." Market-impact modeling that frames how forced hedging flow translates into price displacement.
• López de Prado (2018) — "Advances in Financial Machine Learning." Triple-barrier labeling and meta-labeling — the method behind our hold/break dataset and the calibrated probabilities to come.
• SqueezeMetrics (2017) — "The Implied Order Book" (GEX white paper). Popularized the Gamma Exposure metric and the gamma-flip regime framing this whole tool is built on.
• And the practitioner research on vanna & charm hedging flows (notably Kolanovic / JPM) that explains why option-expiration and the opening bell are so reflexive.

Listing these works is an acknowledgement of inspiration, not an endorsement by their authors. Any errors in how we've applied the ideas are entirely our own.