Signal Metrics Guide

Methodology

Confirm Above is derived from the nearest significant resistance level above the current price — typically a prior swing high, VWAP reclaim, or order block ceiling. The scanner requires a candle close above this level with a Volume Z-Score ≥ 1.5 before marking a signal as actionable. It exists to filter out fake breakouts and liquidity grabs where price briefly spikes above resistance but immediately reverses. Waiting for confirmation reduces win rate slightly but dramatically improves risk-reward on trades that do trigger.

Methodology

TP1 is calibrated to the nearest significant resistance — the level where the majority of sell-side pressure is expected. It typically represents a 1:1 to 1:1.5 risk-reward ratio from entry. TP2 is set at the next resistance cluster above, usually derived from a volume profile Point of Control or historical supply zone. A signal with both targets reached represents a full win; stopping at TP1 after scaling is a partial win. The scanner grades a signal as "HIT_TARGET" when TP1 is hit.

Methodology

Moon is computed as the next major supply zone above TP2, often a prior all-time high, a round number psychological level, or a Fibonacci extension (1.618× or 2.618×) from the current move base. It is not a primary target — it is included to give traders a ceiling for position sizing decisions when managing runners. Price reaching Moon requires sustained institutional momentum and typically happens in less than 15% of signals that hit TP2.

Methodology

Stop Loss is placed below the most recent significant support level — typically a recent swing low, demand zone, or order block floor. It is NOT a percentage-based stop; it is structure-based. This means the stop distance will vary by asset volatility and setup quality. The R:R ratio shown with each signal accounts for the stop distance relative to TP1. Signals with very wide stops relative to the entry-to-TP1 range have lower R:R and should be sized accordingly.

Methodology

Computed via rescaled range (R/S) analysis over a 90-day rolling window on the 4-hour price series. The Hurst exponent measures the long-range dependence of the price series — whether past returns predict future returns. A reading above 0.6 on a signal means the asset is in a persistent uptrend regime, making trend-continuation setups statistically more likely to succeed. It is a regime filter, not a directional signal on its own.

Methodology

Implements the Moskowitz–Ooi–Pedersen time-series momentum factor. Returns over 1, 3, 6, and 12-month look-backs are sign-weighted and normalised by realised volatility. A positive TSMOM means the asset has been trending up persistently across most look-back windows — conditions historically associated with trend-continuation. When TSMOM is negative and a BUY signal fires, the setup is a counter-trend trade and warrants reduced position size.

Methodology

Average True Range normalised by dividing by current price, giving a volatility measure that is comparable across different price levels. A low ATR% reading is one of the strongest precursors to a breakout move — tight, low-volatility ranges historically precede sharp directional expansions. When ATR% is low alongside a high Breakout Score, the conditions resemble a coiled spring. Conversely, a high ATR% on signal entry means the trade may have started late — risk management becomes more critical.

Methodology

Z = (today's volume − 30d mean) / 30d standard deviation. High positive Z-scores indicate volume spikes that often precede significant price moves. A signal with Volume Z-Score > 2 means unusually large participation is driving the setup — historically the strongest signals combine a high score, positive TSMOM, and a volume spike. Note: the Z-score alone is not directional — the CVD / Volume Intent metric adds the buy/sell direction layer.

Methodology

Computed from the level-2 order book snapshot at time of signal generation, summing bid depth and ask depth across the top 20 price levels. The ratio (bids ÷ asks) gives a real-time snapshot of market participant intent. Importantly, this is a snapshot — large orders can be placed and pulled within seconds (spoofing). A consistently high ratio across multiple snapshots (as the scanner observes) is more meaningful than any single reading. Used in combination with CVD and Absorption to triangulate buy-side intent.

Methodology

Measures how much sell-side pressure is being absorbed without corresponding downward price movement. Computed by comparing price range to volume over a rolling window: if volume is high but range is tight, it implies that a large buy-side participant is absorbing sell orders (accumulating a position). This pattern is characteristic of institutional "smart money" building a position before a markup phase. An Absorption score above 65 is one of the highest-conviction signals in the scanner's toolkit.

Methodology

Cumulative Volume Delta (CVD) is the running sum of (buy volume − sell volume) over the signal window. Positive and rising = buyers are in control. Negative and falling = sellers. ABSORPTION is flagged when CVD is near zero despite high total volume — price is held tight by a large participant absorbing one side. DISTRIBUTION is the inverse: price is rising but CVD is declining, indicating that smart money is selling into retail buy orders. CVD is the most direct window into institutional intent available without exchange-level data.

Methodology

The Score aggregates 8 detection sub-engines into a single integer: price action structure (3 points), volume delta alignment (3 points), order flow quality (3 points), trend regime compatibility (2 points), ATR compression (2 points), Hurst persistence (2 points), session momentum (2 points), and macro regime (3 points). Each sub-engine contributes independently — a maximum score requires all factors to align simultaneously. Historically, signals scoring 18+ have had a hit rate 22% higher than the average signal.

Methodology

Grade is computed by combining the normalised Score (0–20) with the Institutional Confidence percentage. Both are bucketed independently and cross-referenced in a grade matrix. An A+ requires both a Score ≥ 18 and Institutional Confidence ≥ 85%. A signal can score 20/20 but receive a B grade if confidence layers are partially misaligned. Grades are the primary filter users should apply to their Telegram bot configuration — setting a minimum grade of A effectively filters out the bottom 60% of signals by quality.

Methodology

Institutional Confidence counts the number of institutional-grade pattern detectors that fired on this signal, expressed as a percentage. The detectors are: order book absorption, CVD intent alignment, Hurst persistence confirmation, TSMOM multi-window agreement, anomalous volume, on-chain whale activity (where available), smart money footprint score, and market regime compatibility. Each adds ~12.5% to confidence. A score of 100% means all 8 layers confirmed simultaneously — extremely rare but historically the highest-performing category of signal.

Methodology

A weighted composite of three sub-factors: (1) range compression quality — how tight and well-defined the base is, (2) volume build-up into the breakout — is volume accumulating before the move, and (3) price action structure — clean higher lows forming, no overhead supply immediately above. A Breakout Score above 80 correlates with the breakout being genuine rather than a liquidity sweep. Low Breakout Scores combined with low ATR% indicate price has not yet entered the breakout zone but may be coiling.

Methodology

Measures the distance between current price and the key breakout level identified by the scanner. A signal fired with 0.5% Breakout Distance means the entry is very close to the structural trigger point — maximum risk-reward. A signal with 4%+ Breakout Distance means price has already extended significantly and the entry is less favourable from a risk-management perspective. High Breakout Distance reduces R:R but may still be valid if the Breakout Score and Institutional Confidence are exceptional.

Methodology

The session tag reflects which major market session was active when the scanner fired the signal. LONDON (08:00–17:00 UTC) and NY (13:00–22:00 UTC) overlap from 13:00–17:00 UTC — this 4-hour window historically concentrates the most institutional order flow in crypto. ASIA (00:00–08:00 UTC) tends to have lower liquidity and more frequent fakeouts. The session weight is one of the 8 sub-inputs to the Institutional Confidence calculation.

Methodology

Expansion Type is classified by comparing ATR% to typical session ranges and analysing the speed and straightness of the current move. A CONTROLLED MOVE expands at 1–2× the typical session ATR with clean candle structure. A VOLATILE MOVE is 3–5× ATR with wicks, indicating emotional or algorithmic panic. PARABOLIC is anything beyond 5× ATR in a single session — these can continue but reversals are violent. RETEST is the highest-quality continuation pattern — price has already broken out and is returning to the breakout level for validation before the next leg.

Methodology

Market Regime combines the Hurst Exponent with the on-chain anomaly detector and BTC correlation to classify the current macro state. TRENDING is confirmed when Hurst > 0.58 and there is no anomaly-driven regime disruption. RANGING is flagged when Hurst is between 0.42–0.55 and price is oscillating within a defined range (detected via Bollinger Band width percentile). TRANSITIONING occurs when Hurst is in flux or the anomaly detector fires — indicating a potential regime shift. All signals include the regime context so you can weight them appropriately.