A technical reference for interpreting ScalpNet's options flow charts, wall signals, and volatility markers.
Options walls represent strike prices where the aggregate notional hedging obligation of market makers (dealers) is at its greatest. When large volumes of puts or calls are open at a given strike, dealers who sold those contracts must dynamically hedge their exposure by transacting in the underlying — creating consistent, repeatable price magnetism.
ScalpNet identifies these levels by computing the net signed volume and open interest across every strike in the active options chain, weighted by delta to reflect true hedging pressure. The result is a real-time map of where the market's structural gravity lives.
The strike with the highest net put volume or open interest. Dealers who sold puts at this level must buy the underlying as price falls toward it — creating a natural support floor. Price frequently decelerates, consolidates, or reverses at the put wall.
The strike with the highest net call volume or open interest. Dealers who sold calls must sell the underlying as price rises toward it — creating a structural ceiling. Rallies often stall or reverse at the call wall unless accompanied by a volatility regime shift.
The strike with net exposure closest to zero between the put and call walls. This is the level where dealer hedging obligations are most balanced — price tends to gravitate toward the POC during low-volatility periods as dealers neutralize their books.
ScalpNet overlays vertical markers on the candlestick chart to identify intraday VIX regime shifts — the moments when implied volatility structurally changes direction. These events consistently precede the largest directional moves of the session.
Marks a moment where the VIX makes a rapid directional drop while SPY is trading below the put wall. Compression events indicate dealers are reducing their hedge ratios — the market is pricing out near-term risk. These are high-probability long setups when occurring at or below the put wall, as the structural bid from dealer re-hedging typically drives price higher.
Marks a moment where the VIX spikes rapidly while SPY approaches or exceeds the call wall. Expansion events indicate dealers are increasing hedge ratios — the market is repricing tail risk higher. These events frequently coincide with breakdowns through key support or failed breakouts above the call wall.
Signed net volume (puts minus calls) for the 0DTE options chain. Green bars indicate net put dominance at that strike; red bars indicate call dominance. The magnitude reflects the scale of dealer hedging at each level.
Same computation applied to the nearest monthly expiry chain. Monthly expirations carry significantly more open interest and define the medium-term structural levels that day traders should treat as high-significance zones.
Net OI at each strike for the monthly chain. Unlike volume (which resets daily), open interest reflects the accumulated positioning of all participants with active contracts — making OI walls more persistent and structurally significant.
Composite of 0DTE volume, 0DTE OI, and monthly OI — the single most complete picture of where dealer hedging obligations are concentrated across the full term structure.
Volume and OI multiplied by the option's delta at each strike. This adjusts for moneyness — deep ITM options carry near-full delta and require proportionally larger hedges than OTM options of the same volume.
The rate of change of delta with respect to time (∂Δ/∂t). Charm exposure peaks near ATM strikes as expiration approaches, indicating where dealer hedges will need the most intraday adjustment — a forward-looking measure of where activity concentrates.
All greeks (delta, vanna, charm) are computed in real-time using Black-Scholes with implied volatility solved via Brent's method on live bid-ask midpoints. Data is sourced directly from exchange-cleared options chains and refreshed every 30 seconds during market hours.
Walls are determined by the signed aggregate of net dealer exposure at each strike — not by arbitrary thresholds. The methodology reflects how institutional desks monitor their own books, not retail heuristics.
Reach the ScalpNet team at [email protected]