A live three-lens projection of BTC/USDT. Mechanical demand and supply zones, deterministic Gann Square-of-Nine levels from key pivots, an auto-counted Elliott Wave structure, and a composite next-move forecast that the three lenses agree or disagree on.
BTC/USDT OHLCV from Binance public klines. Higher timeframes produce cleaner zones and Elliott counts but slower-moving forecasts. Pick the bar size that matches your decision horizon.
A demand zone is the consolidation range (1–3 bars) that immediately preceded a strong rally — institutional buying signature. A supply zone is the mirror: consolidation before a sharp drop. Detection: find candles whose body is > 1.8× ATR, then back up 1–3 bars and mark their range. Zones are fresh until price returns and either holds (validates) or breaks (invalidates).
| Type | Top | Bottom | Distance | Status | Strength |
|---|---|---|---|---|---|
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W.D. Gann's Square of Nine produces price levels by adding fractional rotations of √P back to itself. From a chosen pivot price P, the cardinal levels at 90° / 180° / 270° / 360° are (√P ± n)² for n = 2, 4, 6, 8. The 45° ordinals add n = 1, 3, 5, 7. Levels above the pivot act as resistance; below as support. Practitioners track price action around these levels for confirmations of turns.
An auto-counted Elliott Wave from the most recent significant pivots. The algorithm filters tiny swings, finds the longest valid impulse (5 waves: 1-2-3-4-5) or correction (3 waves: A-B-C) within rules — wave 2 doesn't retrace past wave 1's start, wave 3 isn't the shortest, wave 4 doesn't overlap wave 1's price territory — and labels the current position. Fibonacci projections from the prior wave give the next target.
| Wave | Date | Price | Length | Ratio to prior | Note |
|---|---|---|---|---|---|
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The bullish and bearish targets each method produces, aggregated and clustered. Where two or three methods agree on a level, the level gets stronger weight in the forecast scenario below.
| Method | Bias | Nearest Resistance | Nearest Support | Reading |
|---|---|---|---|---|
| computing… | ||||
A fresh zone is, by definition, a recent area of strong directional move. Whether another directional move follows when price returns is an empirical question, and the published statistics are messier than the technical-analysis blogs admit. Fresh zones do hold more often than they break — but the edge is small and asymmetric (when they fail, they often fail by a lot).
The math here is correct — (√P + n)² is a clean geometric construction, and the levels Gann's followers track are reproducible. The empirical question is whether price actually respects these levels more than chance alone would predict. Backtests across asset classes do not generally support the strong-form claim. As one input among several, fine. As a standalone strategy, no.
Any sufficiently long price series can be labelled as an Elliott Wave somehow. The discipline asks for many rules to be satisfied simultaneously — wave 2 doesn't break wave 1's origin, wave 4 doesn't overlap wave 1, wave 3 is rarely the shortest — but in practice analysts revise counts retrospectively when price doesn't cooperate, which deflates the predictive content. The auto-counter on this page picks one plausible interpretation; a careful analyst could draw two or three alternatives that fit equally well.
When zones, Gann, and Elliott all point to the same target, that target is more likely to be a place price visits, not a place price stops. Confluence concentrates attention — and stop orders — at predictable price points, which is why those points often get tested. The fade after the test is at least as common as the bounce.
The honest application of these methods is to organise your thinking about where reversals could happen, not to generate buy/sell signals. For a model-based predictor, see the BTC Predictor; for indicator confluence, the Signals × SMC page; for the deeper framework reasoning, the AI × ML Framework. Each is one input among many.