AB AnchorVWAP

How it works

–  Multi-anchor engine — Session, Weekly, Monthly and Quarterly VWAPs simultaneously, plus auto-anchored VWAPs from the most recent significant swing high and low, plus unlimited manual click-to-anchor points (news, earnings, breakouts).

–  True sigma bands — ±1/±2/±3 sigma computed from the volume-weighted variance of price around VWAP, not a lazy standard deviation of closes. Bands expand realistically with participation.

–  Interaction signals — first-touch pullback to session VWAP in trend, ±2-sigma fade signals in balance (optionally gated by a built-in trend/range filter), and VWAP compression when multiple anchors converge — the highest-energy decision points.

–  Value migration — slope and band width classify the session as accepting higher, accepting lower or balancing.

Marketplace description

VWAP is the benchmark every institutional execution desk answers to — and most MT5 VWAPs compute it wrong. AnchorVWAP calculates true volume-weighted average price with true volume-weighted sigma bands, runs session/weekly/monthly/quarterly anchors simultaneously, auto-anchors from significant swing points, and lets you click-anchor from any event bar. First-touch pullback signals in trends, 2-sigma fade signals in balance, and a VWAP-compression detector that flags when multiple anchors converge. Slope-and-width analytics tell you whether the session is accepting higher, accepting lower, or balancing. The complete institutional VWAP toolkit in one indicator. Non-repainting, EA-ready.


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How it works –   Impulse-leg detection — identifies displacement legs (velocity + range expansion + structural break) worth continuing with. –   Zone projection — for each impulse, projects the confluence-cluster pullback zone: the overlap of the 38–62% retracement band, the breakout origin (old resistance/new support), any fair value gap inside the leg, and the auto-anchored VWAP from the leg's origin. Where two or more overlap, a graded continuation zone prints. –   Regime gate — zones only pr
How it works –   Detection with quality filters — true three-candle imbalances filtered by minimum gap size (ATR-scaled), displacement quality of the middle candle and volume, killing the micro-gap spam that makes FVG tools unusable on low timeframes. –   Fill-state tracking — each gap tracked live: Untouched, Partially filled (with fill %), Fully mitigated, Inverted. –   The headline feature — Inversion (failed FVG): when price closes entirely through a gap, the imbalance inverts. Failed bullis
How it works –   Pool detection — equal highs/lows (within an ATR-scaled tolerance), unswept swing highs/lows, session and daily/weekly extremes, and trendline liquidity (3+ touch diagonal clusters where stops accumulate). –   Pool weighting — each pool scored by touch count, age, round-number proximity and origin timeframe, then drawn with thickness/opacity proportional to score. The chart literally shows where the fuel is. –   Sweep engine — a sweep registers when price wicks through a pool an
How it works An inducement trap is a sequence, not a candle pattern. TrapRadar's state machine requires all four legs: –   Bait — an obvious level forms (minor swing, equal highs/lows, range boundary) that retail will trade the breakout of. –   Trigger — price breaks the level and actually attracts participation; relative volume rises on the breakout bar, confirming traders took the bait. –   Trap spring — within K bars a displacement candle (range greater than 1.5× ATR, closing 70%+ through its
ATR tells you yesterday's range. VolCore models the volatility cycle itself: –   Estimator stack — Parkinson, Garman-Klass and Yang-Zhang realized volatility (OHLC-based estimators are 5–8× more efficient than close-to-close). Select one or blend. –   Percentile ranking — current volatility ranked within its own 250-bar distribution, giving a universal 0–100 Vol Rank comparable across all symbols. –   Squeeze detection — Vol Rank below a threshold and still compressing (negative vol-of-vol slope
How it works No RSI, no stochastic. VectorMomentum measures momentum three independent ways and demands agreement: –   Regression-slope t-statistic — a linear regression on log price over N bars; the t-stat of the slope (slope divided by its standard error) gives statistically-significant momentum that self-normalizes across symbols and volatility levels. –   Volume-pressure-weighted rate of change — ROC weighted by relative tick volume, so momentum on dead volume scores lower than the same move
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