Break-Retest Quality [AGPro Series]Break-Retest Quality
🎯 OVERVIEW
Break-Retest Quality is a precision-focused structure toolkit that detects pivot-based breaks of structure (BOS) and grades the first retest of the broken level using a transparent, multi-factor quality score. Instead of only drawing a break line and leaving you to guess whether the retest "looked clean", the script quantifies the retest with a 0-100 score and an A / B / C / F letter grade so you can quickly separate high-conviction pullbacks from low-quality ones. It is a discretionary context tool built for price action traders, SMC / ICT practitioners and anyone who builds setups around break-and-retest logic.
The system is fully automated, non-repainting after confirmation, and works on any symbol and timeframe that PulseWire supports.
📐 UNIQUE EDGE — WHAT MAKES IT DIFFERENT
Most break-of-structure indicators stop at drawing a line and an arrow. Break-Retest Quality goes further:
🔹 Every retest is scored on six independent factors and translated into an A / B / C / F grade
🔹 The acceptance zone is an ATR-scaled rectangle that changes color and state as the setup evolves (live WATCH → graded RETEST)
🔹 A "Min Grade To Display" filter keeps weak retests off the chart, so the visual footprint stays clean
🔹 A right-edge WATCH tag pins the currently active level so you never lose track of the live setup
🔹 A compact two-line retest marker shows grade, score and a short outcome tag in a minimal footprint
🔹 Built-in cooldown and single-retest-per-break logic prevent label clutter on choppy price action
This is not a repackaged BOS indicator — it is a quality filter on top of BOS / retest logic.
🧪 METHODOLOGY
1. STRUCTURE DETECTION
Pivot highs and lows are detected with a user-defined Pivot Length. A break is registered when price clears the most recent pivot by at least Min Break ATR Filter × ATR, either on a close (default) or on a wick.
2. RETEST TRACKING
After a confirmed break, the script opens an acceptance zone of ± Retest Tolerance ATR × ATR around the broken level and watches for the first price revisit within Max Bars For Retest.
3. QUALITY SCORING (0-100)
The first retest is graded on six weighted factors:
🔸 Reclaim (25 pts) — how decisively the close reclaims the correct side of the level
🔸 Rejection (20 pts) — wick / body composition on the retest bar
🔸 Depth (20 pts) — how close the extreme of the retest bar lands to the level (no excessive overshoot)
🔸 Speed (15 pts) — how quickly the retest prints after the break
🔸 Volatility (10 pts) — bar range discipline relative to ATR
🔸 Volume (10 pts, optional) — relative volume vs 20-bar SMA
Final score → Grade: A ≥ 80, B ≥ 65, C ≥ 50, F < 50.
4. CONFIRMATION LOGIC
A retest is marked "confirmed" only if the score meets the Min Grade For Confirmation threshold AND the close lands on the correct side of the broken level.
🔔 SIGNALS & ALERTS
Three PulseWire alert conditions are exposed:
🔹 Structure Break Detected — fires the moment a valid break is registered
🔹 First Retest Detected — fires on the first qualifying revisit inside the acceptance zone
🔹 High-Quality Retest Confirmed — fires only when the graded retest meets the confirmation threshold
⚙️ KEY INPUTS
STRUCTURE
• Pivot Length, Use Close Confirmation, Min Break ATR Filter, ATR Length
RETEST
• Max Bars For Retest, Retest Tolerance ATR, Cooldown Bars After Completed Setup, Resolved Zone Extension
SCORING
• Show Numeric Score / Grade, Use Volume Confirmation, Min Grade For Confirmation, Min Grade To Display
VISUALS
• Show Break Line / Labels / Retest Marker / Retest Zone / Watch Zone Text / Resolved Zone Text / Active Level Glow / Right-Edge Watch Tag / Invalidation Line / Outcome Text, Use Grade Colors, Zone Forward Extension, Label Size
PANEL
• Show Panel, Panel Position, Panel Font Size, Show Last Result Row
RUNTIME
• Keep Last Setups (controls how many historical setups stay on the chart)
🧭 HOW TO USE
1. Add Break-Retest Quality to any chart and timeframe. Adjust Pivot Length to match the structure you care about (lower on intraday, higher on swing).
2. Wait for a BRK▲ or BRK▼ label to print — this confirms a structure break.
3. Observe the live acceptance zone and the right-edge WATCH tag. These mark the level and the remaining retest window.
4. When price returns to the zone, read the two-line retest marker: grade + score on the top line, short outcome tag (Strong / Valid / Weak / Failed) on the bottom line.
5. Use the panel to monitor live state, active level, remaining window and the last completed result with its full outcome description.
6. Combine with your own confluences — higher-timeframe bias, liquidity levels, session context, volume profile — before acting on any signal.
⚠️ LIMITATIONS & TRANSPARENCY
🔹 This is an analytical and educational tool, not a strategy. It does not generate buy / sell orders and does not measure historical performance.
🔹 Grades describe the geometric and relative-volume quality of the retest bar at the moment it prints. They are not predictions of future price movement.
🔹 Scores calculated at bar close are final; intra-bar readings can shift until the bar closes.
🔹 The volume factor depends on exchange-supplied volume data. Turn it off on instruments where volume is unreliable or missing.
🔹 Pivot-based structure is sensitive to the Pivot Length setting. Choose it deliberately for the timeframe and symbol you are analyzing.
📢 RISK DISCLOSURE
Trading involves substantial risk and is not suitable for every investor. Past price behavior is not indicative of future results. This indicator is provided for educational and analytical purposes only and does not constitute financial advice, investment advice, or a solicitation to trade any instrument. Always perform your own research and risk management before acting on any signal. Indicator
Trend Quality [AGPro Series]Trend Quality
Trend Quality fuses three independent regime dimensions — ADX directional strength, Kaufman Efficiency Ratio, and ATR-normalized EMA slope — into a single 0–100 composite Trend Quality Score. A hysteresis + confirmation + cooldown gate turns that score into a stable TREND / CHOP regime, enhanced with HTF confirmation, lifecycle phases, score velocity, breakout grading, directional dominance, and a full adaptive on-chart quality window. The goal is simple: replace noisy "is this a trend?" guessing with a transparent, multi-dimensional, low-lag quality reading you can read in one glance.
🎯 OVERVIEW
Most trend filters fail at the same thing — they tell you a trend exists, but not whether that trend is clean, accelerating, fading, or already exhausted. Trend Quality answers the harder question. Every bar is scored on three independent dimensions that each measure a different physical property of price movement:
• ADX — directional strength (how strongly one side dominates)
• Kaufman Efficiency Ratio (ER) — path efficiency (how little wasted motion)
• ATR-normalized EMA slope — normalized trend velocity (how fast, relative to volatility)
These three signals are combined into one 0–100 Trend Quality Score. A hysteresis band + confirmation bars + cooldown filter convert that score into a stable TREND / CHOP regime — no single-bar flipping, no false recovery wicks. On top of the core regime, the indicator layers Score Velocity, Lifecycle phases (Emerging → Confirmed → Exhausting), Breakout Quality grading (A / B / C), directional dominance, and a visual Quality Window that tracks the active trend zone and projects it forward.
💎 UNIQUE EDGE
What separates Trend Quality from a standard ADX filter, an EMA slope indicator, or a generic regime meter:
• Tri-factor fusion (not a single metric) — ADX alone misses path quality; ER alone misses direction; slope alone misses choppy-but-strong moves. Weighted fusion (45% ADX, 35% ER, 20% Slope) neutralizes each component's blind spot.
• Stable regime, not a flickering line — the TREND / CHOP state passes through a 3-layer filter: hysteresis band around the threshold, N confirmation bars, and a cooldown window after every transition. The result is a regime reading that holds through pullbacks without flipping.
• Score Velocity Engine — a second-derivative layer that watches how fast the score itself is changing. Surges flag momentum ignition; collapses flag quality breakdown before price confirms it. A bearish divergence detector fires when price makes new highs while quality is fading.
• Lifecycle phases — inside every TREND regime, the script distinguishes Emerging (young, fresh, accelerating), Confirmed (mature, stable, above buffer), and Exhausting (score rolling over from a peak). This lets you see whether you are entering early, running mid-trend, or catching the end.
• Breakout Quality Badge (A / B / C) — every CHOP → TREND transition receives a graded badge based on composite score plus velocity bonus. Grade A breakouts are rare and have an optional dedicated alert.
• HTF confirmation with Auto-HTF mapping — the same engine runs on a higher timeframe. When LTF is trending but HTF is not, the regime is marked BLOCKED (not forced to CHOP) so you retain full transparency about why the regime is gated.
• Adaptive Quality Window — a live rectangular zone that tracks the full trend's high/low from its start bar, projects forward, shows ceiling/floor projection labels, and preserves historical windows with directional color coding (green for up-trends, pink for down-trends, amber for HTF-blocked trends).
🧪 METHODOLOGY
Core composite score (every bar, LTF):
Score = 100 × (0.45 × ADX_norm + 0.35 × ER_norm + 0.20 × Slope_norm)
• ADX_norm = min(ADX / 50, 1)
• ER_norm = |close − close | / (SMA(|Δclose|, N) × N)
• Slope_norm = min(|EMA − EMA | / ATR × 10, 1)
Regime gating:
• Hysteresis: +3 above threshold to enter TREND, −3 below to enter CHOP
• Confirmation: N consecutive bars above/below the hysteresis band
• Cooldown: N bars after every regime flip where no new flip is allowed
MTF confirmation (optional, default ON):
The same core function is called via request.security on the HTF (Auto: 30m→4H, 4H→Daily, Daily→Weekly, Weekly→Monthly in Strict mode). When LTF=TREND but HTF=CHOP, the regime is tagged BLOCKED — a transparent third state that is neither forced-CHOP nor accepted-TREND.
Lifecycle logic:
• Emerging: TREND is young (bars since start ≤ Emerging Bars) OR score slope ≥ 0 and score below buffer
• Confirmed: score ≥ threshold + Confirmed Buffer AND HTF passes (optional)
• Exhausting: score slope < 0 AND pullback from peak ≥ Exhaustion Pullback
Score velocity:
velocity = score − score (default 5-bar look-back)
Breakout quality grading:
bqScore = score + velocity_bonus (bonus: +15 if vel>15, +7 if vel>5, else 0)
A ≥ 82, B ≥ 67, C < 67
🔔 SIGNALS & ALERTS
The script exposes 12 alert conditions — all moderator-safe, educational, non-solicitating:
• CHOP → TREND / TREND → CHOP regime flips with LTF+HTF context
• Strong Trend composite conviction threshold
• HTF Blocked / HTF Unblocked third-state transparency events
• Emerging / Confirmed / Exhausting Trend lifecycle phase changes
• Velocity Surge / Velocity Collapse second-derivative extremes
• Grade-A Breakout rare high-conviction breakouts
• Bearish Divergence price up, quality down warning
On-chart visual events (also filterable via inputs):
• Breakout Quality badge (A / B / C) at every CHOP → TREND
• Bearish divergence ⚠ marker at trend peaks where quality fades
• State tag near backbone: EMERGING / CONFIRMED / EXHAUSTING / HTF BLOCKED
• Quality Window label: ACTIVE + phase
• Projection labels on the right edge: QUALITY CEILING / TREND FLOOR
All badge and warning labels are gated with an 8-bar cooldown so the chart stays clean even on repeated intra-swing triggers.
⚙️ KEY INPUTS
Core engine:
• ADX Length (14) — directional strength look-back
• Efficiency Length (20) — ER path-efficiency window
• Slope EMA Length (50) — trend backbone reference
• ATR Length (14) — volatility normalization
• TREND Threshold (55) — composite score level to enter TREND
• Confirmation Bars (1) — bars of persistence before flipping
• Strong Trend Offset (15) — extra score above threshold for STRONG tag
MTF:
• HTF Confirmation (ON) — enable/disable HTF gate
• Auto HTF (ON, Strict) — smart HTF mapping per chart TF
• Manual HTF (240) — override timeframe
Stability:
• Change Cooldown Bars (2) — lock-out window after any regime flip
Lifecycle:
• Emerging Phase Bars (4) — max trend age to stay Emerging
• Confirmed Buffer (8.0) — score must clear threshold+buffer
• Exhaustion Pullback (4.0) — peak-to-current drop to flag Exhausting
Visual Overlay:
• Backbone + Glow + Zone + State Candles + Quality Window + Historical Windows + Projection Box + Guides + Midline (all toggleable)
Panel, Theme, Layout, Help rows, Alerts, Score Velocity Engine, Breakout Quality Badge, Divergence Detector — every layer has its own input group and can be shown/hidden independently.
📘 HOW TO USE
Read-in-one-glance panel (standard AGPro format):
• Blue header row: script title
• Line 2: REGIME / LIFECYCLE · Score N/100 · Velocity state
• Line 3: LTF regime · Direction · Directional Dominance
• Line 4: HTF regime · MTF PASS/BLOCKED · Active Window state · Streak
Quick playbook:
1. CHOP on LTF → wait. No setup, no commitment.
2. CHOP → TREND transition with Grade A badge + HTF PASS → highest-conviction regime start.
3. CONFIRMED phase with DOM HIGH and rising score → the middle of the trend, usually the cleanest section.
4. Velocity COLLAPSE or EXHAUSTING phase with bearish divergence ⚠ → quality is deteriorating; reduce exposure or tighten stops.
5. HTF BLOCKED amber window → LTF trend exists but higher timeframe disagrees; treat as lower-conviction and be aware of mean-reversion risk.
The indicator does NOT issue buy/sell signals, does NOT define entry/exit prices, and is NOT a strategy. It is a regime-quality reading — a context layer you pair with your own trade management.
⚠️ LIMITATIONS & TRANSPARENCY
• Trend-quality indicators are inherently trend-following. In low-volatility ranges the score can stay above threshold on minor moves; in very fast markets the score can lag by 1–3 bars while the filters stabilize.
• HTF confirmation introduces a natural HTF delay. This is intentional (it removes noise) but means the HTF gate may lift several LTF bars after price has already moved.
• All composite signals rely on look-backs (ADX 14, ER 20, Slope EMA 50, ATR 14). On very short intraday timeframes with low bar counts these need calibration.
• Lifecycle phases are structural readings, not predictions. EXHAUSTING means the score is rolling over — not that price must reverse.
• Past performance of any visual regime does not imply future performance. Charts showing clean historical windows are illustrative of the indicator's logic, not trading results.
• No repainting on historical bars. The HTF call uses lookahead_off and barmerge.gaps_off. Score and regime values on closed bars are final.
🛡️ RISK DISCLOSURE
This script is published as an educational and analytical tool. It does not provide financial advice, does not generate trade signals of any kind, and must not be used as a standalone decision system. Markets involve substantial risk of loss. Past behavior of any market regime, indicator output, or historical visual window is no guarantee of future results. Always combine any indicator with independent risk management, position sizing, a tested plan, and — where appropriate — the guidance of a licensed professional. You are solely responsible for any trading decisions you make. Indicator
Swap Engine - Pair Rotation (Z-Score) [AGPro Series]Swap Engine - Pair Rotation (Z-Score)
🔷 OVERVIEW
Swap Engine - Pair Rotation (Z-Score) transforms the log-ratio between two correlated crypto assets into a disciplined tier ladder decision framework. Rather than signalling single-asset direction, the engine measures how stretched one pair has become relative to its rolling mean and proposes rotation between the two assets when the spread reaches statistically meaningful extremes. Every decision is evaluated on confirmed Engine TF bar close, keeping suggestions non-repainting under the configured execution model.
🟣 UNIQUE EDGE
Unlike single-symbol mean-reversion or trend indicators, this engine treats the ratio itself as the tradable variable and pairs it with a full operational stack: a tiered exposure ladder (T0 to T3), an Integrity Gate that blocks entries when the pair relationship deteriorates, a Trend Regime filter that respects persistent one-sided moves, and a confirm-first execution model that converts raw signals into auditable decisions. A dedicated Signal Quality score (Q 0-100) and Integrity Score (IN 0-100) make every suggestion inspectable, not a black box.
🟢 METHODOLOGY
The engine fetches the closing price of Pair A and Pair B on the chosen Engine TF, computes the log-ratio L = ln(A / B), then derives a rolling z-score using user-defined lookback length. Entry thresholds (Z1, Z2, Z3) define the three tiers of exposure; exit thresholds (hysteresis) define when each tier is scaled back. A cost filter requires the expected mean-reversion edge to exceed a configurable multiple of estimated roundtrip cost before any entry is allowed. The Integrity Gate continuously validates rolling return correlation, ratio drift, and spread-volatility expansion, halting new entries when the pair relationship degrades.
🟡 SIGNALS & ALERTS
Each signal renders as a clearly tagged label on chart showing the action type (ENTRY / EXIT), source tier, target tier, direction (A->B or B->A), z-score snapshot, delta %, and Reason Code. Alerts are provided for: entry and exit events per direction, pending lifecycle (created, confirmed, skipped, expired), trend regime activation edges, duplicate suppression, and configuration warnings. All alerts fire on Engine TF bar close to remain consistent with the visible suggestions.
⚙️ KEY INPUTS
Pair A / Pair B: the two assets to rotate between (same quote currency recommended).
Engine TF: timeframe used for all ratio, z-score, and decision logic (240 / 4H default).
Lookback: bars used for rolling mean and standard deviation.
Entry Z1/Z2/Z3, Exit Z1/Z2/Z3: tiered thresholds for scaling in and out.
Tier Sizing (T1 / T2 / T3 %): rotation size per tier as a percentage of the active pool.
Trade Profile: preset gate behavior (Conservative, Balanced, Aggressive, Volatile Alt, High-Cost, Custom).
Integrity Gate: correlation, drift, and volatility expansion filter with configurable minimum score.
Execution Model: ASSUME (auto-advance), CONFIRM (pending + manual commit), or SIGNAL_ONLY (display only).
🔵 HOW TO USE
Start on the default BTCUSDT vs ETHUSDT pair on 4H Engine TF with the Balanced profile. Keep the chart timeframe equal to or lower than the Engine TF (the script warns otherwise). Watch the status panel for the current tier, direction, confidence strip (Q / IN / PH), and next action preview. In CONFIRM mode, a PENDING card appears when a signal fires; increase CONFIRM +1 to commit the rotation state, or SKIP +1 to discard. Use the Trade Profile dropdown to tighten or loosen effective gates without changing your base inputs.
🟠 LIMITATIONS & TRANSPARENCY
This is an indicator, not a strategy; no orders are placed and no backtest statistics are produced. Signals reflect statistical extremes in the pair's log-ratio and do not guarantee mean reversion. Performance depends heavily on pair selection - assets with persistent trends, broken correlation, or structural regime changes can cause extended adverse periods. The Integrity Gate mitigates but does not eliminate this risk. Costs, slippage, tax, and execution details are the user's responsibility; the Min Edge x filter is an estimate, not a realized-cost guarantee. Always validate on your own pair, timeframe, and account conditions before relying on any suggestion.
🔴 RISK DISCLOSURE
Trading and rotating between crypto assets involves substantial risk, including loss of capital. Past or simulated behavior of the ratio does not guarantee future results. This tool is shared for educational and analytical purposes only and does not constitute financial, investment, or trading advice. Users are solely responsible for their own decisions and should consult a qualified professional before committing capital. Indicator
Level Survival Map [AGPro Series]Level Survival Map
🔹 Overview
Level Survival Map is a premium support and resistance framework that does not just draw lines on the chart. Every detected level carries a live Survival Score between 0 and 100 that answers one simple question: how well is this level still defending itself right now. The map highlights a single Active Level with an interaction zone and a forward projection ribbon, while nearby weaker levels fade, so traders always know which level actually matters for the current decision.
🔸 Unique Edge
Most support and resistance tools either show static pivots or basic break or retest events. Level Survival Map goes further by measuring the quality of every interaction and turning it into a single composite health score per level. Instead of being left with a wall of equally important lines, the trader sees a ranked structural battlefield with one clearly identified Active Level, a visible interaction zone and a projection ribbon for planning. The Damage State readout, the Fresh and Eroded state semantics, the automatic flip from broken support to new resistance and the cluster fade for crowded weaker levels are designed to work together as one premium, low-noise workflow.
🔹 Methodology
Pivot detection builds the raw candidate levels from swing highs and swing lows using the standard pivot window. A merge filter removes duplicates that sit within a configurable ATR distance of an existing same-type level. Each active level then accumulates four independent components over time. Close Respect rewards closes that respect the level side, for example closes above a support. Penetration Damage penalises wicks and bodies that pierce through the level zone. Reaction Quality rewards strong rejection wicks and bodies moving away from the level after a test. Test Fatigue penalises repeated tests because levels tend to weaken with each new hit. These four components are weighted and combined into a single Survival Score, then clamped between 0 and 100. A structural break caps the score at 35, heavy damage across multiple tests caps it at 28, and a confirmed sequence of opposite-side closes flips the level type while resetting its history. The Active Level is chosen as the closest same-side level to price so that the focus always follows the real decision point.
🔸 Signals and Alerts
The visual output itself is the primary signal. Line colour and thickness communicate level strength at a glance. A focused Active Level is drawn with an interaction zone, a darker core band and a forward projection ribbon so that traders can see the exact price band where reaction is most likely, and how far into the future that band is expected to remain relevant. Labels carry the Survival Score directly, so the ranking of levels is always visible without opening any settings. Broken levels switch to a dashed style and faded colour, and once enough opposite-side closes accumulate they flip type automatically, giving a clear visual signature of structural change.
🔹 Key Inputs
Pivot Left Bars and Pivot Right Bars control how strict the swing detection is. Max Active Levels caps how many concurrent levels are tracked. Level Merge Distance and Interaction Zone are expressed in ATR units so the logic adapts across timeframes and instruments. Scoring weights for Close Respect, Penetration Damage, Reaction Quality and Test Fatigue can be tuned independently, together with the fatigue penalty per extra test and the number of closes required to confirm a flip. Visual inputs cover panel position, label size, line width, focus emphasis, non-focus transparency, cluster fade, focus zone width and projection ribbon length and thickness. A Clean Map Mode is provided for screenshot and publishing workflows where only the Active Level and the nearest valid support and resistance are labelled.
🔸 How to Use
Read the map top down. First, look at the summary panel for the Active Level, its Survival Score, Test Count and Damage State. A Fresh or Strong Active Level defending its side is a high-quality decision point. A Fragile or Eroded Active Level with a Severe Damage State is a warning that the next level below or above is likely to take over. Use the projection ribbon as a planning band for reaction rather than a mechanical entry. Use the ranked non-Active labels to understand where price is likely to travel if the Active Level gives way. The tool is designed to be used as a visual framework, in combination with the trader own execution method, trend context and risk management.
🔹 Limitations and Transparency
This indicator is a visual analytical framework, not a strategy, not a signal service and not financial advice. Survival Score, Damage State and flip logic are deterministic functions of price action and ATR, so different markets and timeframes will produce different characteristic score ranges. Pivot based detection is inherently lagging by the Pivot Right Bars window, which is the expected behaviour of any structural tool and not a defect. The Active Level projection ribbon is a visual planning aid, not a forecast. Past level behaviour does not guarantee future behaviour.
🔸 Risk Disclosure
Trading involves substantial risk and is not suitable for every investor. This script is published for educational and analytical purposes only. Users are solely responsible for their own trading decisions, position sizing and risk management. Always test any tool on your own instruments and timeframes before using it in a live environment. Indicator
Failed Break Quality [AGPro Series]Failed Break Quality
🔹 OVERVIEW
Failed Break Quality is a reversal-focused structure tool that detects failed breakouts (bull traps and bear traps) around confirmed horizontal support and resistance, then grades each reclaim with a transparent 0-100 quality score. Instead of signaling every price wick through a level, it waits for the full sequence — level confirmation, break below or above, decisive reclaim, rejection candle and follow-through — and only prints a label when the event passes a weighted score threshold.
The goal is to give a single-pane view of where the market trapped participants, how clean the reversal was, and whether the reaction carried any real conviction. All components are plotted on the price chart in an event map style: reclaim pockets, focus bands, connector rails, structure tags and a compact summary panel.
🔷 UNIQUE EDGE
What separates Failed Break Quality from generic support-resistance or bull-trap detectors:
• Five-component weighted score (0-100) — each reclaim is rated on Level Integrity, Break Weakness, Reclaim Speed, Rejection Strength and Follow-Through, with user-adjustable weights. No black-box output.
• Auto timeframe profiles — Intraday, H4 and Swing profiles adapt tolerance, break depth, reclaim window, adverse-move limits and family-reset band automatically so the same inputs behave sensibly across timeframes.
• Reclaim Pockets — the actual zone between the break extreme and the reclaim level is drawn as a shaded rectangle, making it easy to see where the trap formed and where the invalidation sits.
• Focus Bands + Event Rails — the latest bull and bear events are highlighted with a forward-extended focus band at the level and a dashed rail connecting break extreme to reclaim point. Older events fade, so the current structural map stays readable.
• Family lock system — once a level produces a graded signal, it will not re-fire on the same level family until a new family forms beyond the configured reset band, preventing signal stacking on the same structure.
• Auto-clean stale event visuals — focus bands, reclaim pockets and event rails are automatically removed when their anchor level drifts, disappears or ages out, so the chart stays clean across regime shifts.
• This script differs from Break-Retest Quality (continuation after a confirmed breakout) by focusing on the opposite case: breakouts that fail and reverse back through the level.
🔸 METHODOLOGY
1. Level Building — Pivot highs and lows are clustered inside an ATR-scaled tolerance band. A level is confirmed only after reaching the required minimum touches and is retired when it exceeds the maximum age in bars. Each confirmed level carries a family ID so nearby re-confirmations do not create duplicate signals.
2. Failed Break Detection — A break is registered when price penetrates a confirmed level by at least the minimum break depth (ATR-based). The script then monitors the reclaim window (capped in bars) and records the break extreme and outside-closes count.
3. Reclaim Confirmation — A reclaim requires close back across the level plus a small ATR buffer. The bar that reclaims is graded for rejection strength using wick, body and close position.
4. Follow-Through Gate — After reclaim, price must extend at least the follow-through ATR in the favorable direction and must not exceed the maximum adverse ATR against the reclaim. Failing either gate cancels the signal.
5. Quality Score — Five sub-scores are combined with user weights to produce the final 0-100 score. Only reclaims at or above the minimum print threshold produce a labeled signal and a reclaim pocket.
🔶 SIGNALS AND ALERTS
• Bullish Reclaim — printed below the reclaim bar with a teal label showing the quality score. Indicates a failed breakdown of support.
• Bearish Reclaim — printed above the reclaim bar with a pink label showing the quality score. Indicates a failed breakout of resistance.
• Panel States — Bull Trap Watch, Bull Reclaim Pending, Bear Trap Watch, Bear Reclaim Pending, Scanning Levels, Building Levels.
• Alert Conditions — Bullish Reclaim and Bearish Reclaim, suitable for standard PulseWire alert creation.
🔹 KEY INPUTS
• Levels — Pivot length, ATR length, level match tolerance (ATR), minimum touches, maximum level age.
• Profiles — Toggle for automatic timeframe calibration.
• Failed Break Logic — Minimum break depth, reclaim window, follow-through bars, reclaim buffer, minimum follow-through, maximum adverse move, re-arm distance, family reset band.
• Score — Minimum score to print and individual weights for Level, Break, Speed, Reject and Follow components.
• Visuals — Toggles for confirmed levels, level zones, inner core bands, structure tags, active-zone emphasis, tag connector rails, zone and core half-widths, signal offset, label and tag sizes.
• Event Map — Reclaim pockets, focus bands, event rails, non-focus fade, auto-clean stale event visuals, stale event max bars, pad and extend settings.
• Panel — Visibility, position (Top Right / Top Left / Bottom Right / Bottom Left) and font size.
🔷 HOW TO USE
• Start on the timeframe where the levels look most respected (H1, H4 or Daily). Auto profiles will adjust internal thresholds automatically.
• Treat every signal as contextual evidence, not as a standalone entry. Higher scores indicate cleaner events — a shallow break, a fast reclaim, a strong rejection bar and a clean follow-through all lift the score.
• Use the reclaim pocket as the structural zone: the level marks the invalidation side, and the break extreme marks the maximum trap depth. Both are visible on the chart.
• Combine with your own bias, trend filters, higher-timeframe levels, volume or session structure. The script is designed to sit on top of an existing framework, not replace it.
🔸 LIMITATIONS AND TRANSPARENCY
• This is an indicator, not a strategy. It does not place orders, size positions or calculate profit and loss.
• Signals are evaluated on bar close. Intrabar wicks can temporarily enter trap states without producing a graded event.
• Score thresholds and weights are tunable. Different markets and timeframes benefit from different configurations — the default values are a reasonable starting point, not a universal setting.
• All level, reclaim and pocket logic is purely structural and does not include volume, order flow or derivatives data.
• Repainting note — level confirmation uses pivots with a fixed lookback. The last pivot is locked once the required forward bars have elapsed; earlier plotted structure does not repaint after that point.
🔶 RISK DISCLOSURE
Trading involves substantial risk. This script is a technical analysis tool provided for educational and research purposes only and does not constitute financial advice, investment recommendations or a solicitation to trade. Past performance does not guarantee future results. Always do your own research and apply strict risk management. The author assumes no responsibility for trading decisions made using this script.
Published under Mozilla Public License 2.0 — source is open and available for study, review and non-commercial derivative work under the terms of the license. Indicator
Reaction Efficiency Meter [AGPro Series]Reaction Efficiency Meter
A pure observation lens that scores every pivot-based support and resistance reaction from 0 to 100 and classifies it as WEAK, LIMITED, FAIR, STRONG or EFFICIENT. Designed to answer one specific question on any chart: how well did price actually react when it touched that level? Not a strategy, not a signal generator — a quality meter for S/R reactions.
🔹 Overview
Reaction Efficiency Meter watches pivot-based support and resistance levels and, the moment price touches any of them, opens a fixed reaction window to observe what happens next. At the end of that window the reaction is scored from 0 to 100 using four weighted components — strength, speed, cleanliness, follow-through — and then classified into a five-tier hierarchy. The result is printed directly on the chart as a color-coded label (BULL or BEAR), while a side panel keeps a live summary of the last bullish reaction, last bearish reaction and the currently active event window. The indicator is built as a post-event quality lens for traders who already work with horizontal levels, pivot zones, or structural S/R and want an objective readout of reaction quality instead of a subjective eyeball assessment.
🔸 Unique Edge
Most support and resistance indicators stop at drawing lines or zones. Reaction Efficiency Meter goes one step further and evaluates the reaction itself on a fixed, reproducible scale. Four distinct quality dimensions are blended into a single 0-100 score, and a separate adverse-excursion penalty reduces the score when price violated the level before reacting. The result is a transparent number tied to a five-tier verbal classification (WEAK / LIMITED / FAIR / STRONG / EFFICIENT), which makes reactions directly comparable across symbols and timeframes. There are no repainting signals, no lagging smoothers and no hidden strategy logic — the scoring is purely descriptive and fires only after the reaction window closes on a confirmed bar.
🔹 Methodology
The engine has four clear stages:
1. Level detection. Classic pivot highs and lows are tracked as dynamic resistance and support. Only the most recent N levels per side stay active — older ones are retired, so the chart never clutters.
2. Touch detection. A touch is registered when the bar's range enters a tolerance band around any active level (expressed in ATR units so the logic auto-scales across volatility regimes). A cooldown of N bars between tests on the same level prevents noise from restarting an event too quickly.
3. Event tracking. Once a touch fires, a reaction window of N bars is opened. During that window the script tracks (a) the best favorable excursion in ATR units, (b) the worst adverse excursion in the wrong direction, (c) which bar produced the peak favorable move, (d) the net retained move at window close.
4. Scoring and classification. At window close the four components are combined with a penalty:
• Strength (0-35): best favorable excursion relative to 1.5 ATR reference.
• Speed (0-20): how early the peak favorable bar occurred inside the window.
• Cleanliness (0-20): reduced linearly by adverse excursion.
• Follow-through (0-15): how much of the peak move was retained at window close.
• Adverse penalty (up to -15): applied when price broke through the level.
Final score is clamped 0-100 and mapped to: WEAK (<25), LIMITED (25-44), FAIR (45-64), STRONG (65-79), EFFICIENT (80+).
🔸 Signals & Alerts
The indicator does not emit buy or sell alerts. Its outputs are purely descriptive:
• A color-coded reaction label (BULL or BEAR with score and tier) plotted after each completed window.
• Active zone rectangle and reaction corridor drawn around the touched level while the window is open.
• Touch markers on the bar where a new event begins.
• Live status tag showing BULL WINDOW x/N or BEAR WINDOW x/N during an active event.
• A stateful side panel with Status, Last Bull, Last Bear, Window progress and Mode rows.
All visuals render on confirmed bars only, so the score and tier of a completed reaction do not change afterwards.
🔹 Key Inputs
• Pivot Length — bar distance used to qualify pivot highs and lows.
• Max Active Levels / Side — how many recent resistance and support levels stay active.
• ATR Length — volatility reference for tolerance, corridor depth and scoring.
• Touch Tolerance (ATR) — how close to the level a bar must come to count as a touch.
• Reaction Window Bars — fixed observation length per event.
• Minimum Bars Between Tests — cooldown on the same level.
• Reaction Corridor Depth (ATR) — vertical span of the reaction corridor drawn during the window.
• Display group — toggles for levels, tags, markers, labels, active zone, corridor, panel.
• Theme & Layout — panel theme (Auto / Dark / Light), position, font size, line width and opacity controls.
🔸 How to Use
The indicator is intended as a companion lens, not a standalone system. Typical workflows include:
• Confluence study. Compare reaction scores at different levels on the same chart to see which zones historically produced stronger reactions.
• Bias assessment. Watching whether BULL and BEAR labels on a given timeframe skew toward higher or lower tiers can inform directional bias for discretionary decisions made elsewhere.
• Framework validation. Add it on top of an existing S/R, order block or pivot framework to quantify whether the levels those tools produce actually generate efficient reactions.
• Multi-timeframe scanning. Running the indicator on multiple timeframes shows where strong reactions cluster — often useful for context, not entry timing.
The tool is descriptive and retrospective. It is not designed to replace risk management, structural analysis or the user's own trading plan.
🔹 Limitations & Transparency
• The reaction window is fixed per event. Very fast V-reversals may still register as WEAK if most of the favorable move happens after the window closes; conversely, slow grind reactions may score lower on the Speed component even when the net outcome is good.
• Pivot-based levels are, by definition, confirmed with a lag equal to Pivot Length bars.
• Scores are descriptive — a STRONG tag on a past reaction does not imply that the next test of the same level will also react strongly.
• All scoring uses confirmed-bar logic, so the indicator is non-repainting by design.
🔸 Risk Disclosure
This indicator is provided for educational and analytical purposes only. It is not financial advice, not a trade signal generator, and not a recommendation to buy or sell any instrument. Trading involves substantial risk of loss. Past reactions do not guarantee future reactions. Users are solely responsible for their own trading decisions and risk management. Indicator
AG Pro Previous Day Sweep & Reclaim [AGPro Series]AG Pro Previous Day Sweep & Reclaim
Overview / What it does
AG Pro Previous Day Sweep & Reclaim is an overlay built to map one very specific price behavior around the previous day’s range: a sweep of the Previous Day High (PDH) or Previous Day Low (PDL), followed by a reclaim back inside the level.
The script is designed for traders who want a structured way to observe failed expansion attempts around prior-day liquidity. Instead of treating every break of PDH or PDL as continuation, this tool focuses on the opposite question: when price briefly trades beyond a prior-day extreme and then reclaims that level, is the move showing signs of rejection strong enough to deserve attention?
The core idea is intentionally narrow. This is not a broad market-structure engine, not a support/resistance dashboard, and not a general breakout system. Its purpose is to isolate a specific sequence: sweep -> reclaim -> quality assessment. That single workflow helps keep the script readable and functionally distinct.
Signals can be confirmed on the same bar or on the next bar, depending on user preference. Once a reclaim is confirmed, the script assigns a quality score, draws a directional arrow, prints a reclaim label, and keeps the visual structure compact enough for practical chart work across intraday and higher timeframes.
Unique Edge
The distinguishing feature of this script is that it does not simply plot PDH and PDL, and it does not label every break as meaningful. It attempts to separate ordinary range interaction from failed liquidity grabs by requiring reclaim confirmation and then grading the event.
Its logic is centered on reversal-quality mapping rather than static level display. That means the script does more than show where the previous day’s extremes are located. It evaluates whether the move through those extremes was shallow or excessive, whether the reclaim was weak or decisive, whether wick behavior supports rejection, whether volume was comparatively active, and whether the event occurred inside the selected session context.
Another practical edge is the confirmation flexibility. Some traders prefer immediate reclaim behavior on the same bar. Others want one additional bar for confirmation. This script supports both approaches, plus an Either mode for broader detection.
The visual side is also deliberately managed. Reclaim labels, arrows, guide lines, sweep boxes, label spacing controls, visible label limits, and HTF label filtering are included so the output remains usable instead of turning into uncontrolled chart clutter.
Methodology
The script retrieves the previous day’s high and low and tracks live interaction with those two reference levels.
Bullish reclaim logic begins with a downside sweep:
- price trades below the Previous Day Low
- price then closes back above the Previous Day Low
- confirmation can occur on the same bar, on the next bar, or by either method depending on settings
Bearish reclaim logic mirrors that process:
- price trades above the Previous Day High
- price then closes back below the Previous Day High
- confirmation follows the selected reclaim mode
After confirmation, the script computes a quality score from multiple components. These components are intended to give structure to the event rather than to claim certainty about future direction.
The quality model includes:
- sweep depth relative to ATR
- reclaim strength within the bar range
- rejection wick fraction
- relative volume versus a moving average baseline
- bar range relative to ATR
- urgency factor for same-bar versus next-bar confirmation
- candle body bias
- session participation
The final score is normalized to a 0-100 scale and translated into a simple tier:
- A
- B
- C
- D
This score is not meant to be a prediction engine. It is a ranking tool that helps organize reclaim events by relative quality under the script’s own rules.
Session filtering is available because many traders only want to evaluate sweep-and-reclaim behavior during specific active windows. London, New York, custom sessions, or unrestricted monitoring can be selected.
For chart usability, the script also includes:
- previous day range fill
- optional reclaim guide lines
- optional sweep boxes
- reversal arrows
- reclaim labels
- summary panel
- visible label limits
- HTF smart label filtering
- minimum bar spacing between same-side labels
Signals & Alerts
The script produces two primary confirmed event types:
1. Bullish Previous Day Sweep & Reclaim
A downside sweep through PDL followed by a reclaim back above that level.
2. Bearish Previous Day Sweep & Reclaim
An upside sweep through PDH followed by a reclaim back below that level.
When enabled, the chart can display:
- directional reclaim arrows
- reclaim labels with score, tier, and confirmation mode
- sweep zone boxes
- short reclaim guide lines
Built-in alerts are included for:
- Bullish Previous Day Sweep & Reclaim
- Bearish Previous Day Sweep & Reclaim
These alerts are tied to confirmed reclaim conditions defined by the selected confirmation mode and minimum quality threshold.
Key Inputs
Reclaim Confirmation
Choose whether confirmation must occur on the Same Bar, Next Bar, or Either.
One Signal Per Side / Day
Limits repeated signals of the same side within a single day.
Use Session Filter
Restricts detection to the selected session environment when desired.
Minimum Quality Score
Filters out lower-ranked reclaim events.
ATR Length / Volume SMA Length
Inputs used by the quality model.
Ideal Sweep Depth (ATR) / Maximum Sweep Depth (ATR)
Define how the script evaluates sweep depth quality.
Label and Visual Controls
Manage font size, offset, sweep boxes, guide lines, visible label count, and general chart cleanliness.
HTF Smart Label Filter
Helps reduce label overload on daily, weekly, and monthly charts.
Minimum Bars Between Same-Side Labels
Introduces spacing between repeated bullish or bearish reclaim labels to prevent visual stacking.
Limitations & Transparency
This script is an analytical overlay. It is not a strategy, not an execution model, and not a guarantee of reversal.
A reclaim of PDH or PDL can still fail. Markets can continue trending after a sweep, especially during strong directional conditions, news-driven volatility, or low-liquidity distortions. For that reason, the quality score should be interpreted as an internal event-ranking framework, not as proof of future performance.
Session settings matter. Timeframe context matters. Confirmation mode matters. Label filters also affect what is visible on the chart, especially on higher timeframes. Users should understand that changing these inputs changes the strictness and presentation of the output.
This tool does not use order book data, broker-specific execution data, or hidden liquidity metrics. It works entirely from chart-based price and volume inputs available in Pine.
It is also important to note what this script does not attempt to do:
- it does not classify overall market regime
- it does not replace broader structure analysis
- it does not define entries, stops, or exits for the user
- it does not evaluate multi-level confluence outside its own reclaim framework
In short, it is a focused map for previous-day sweep and reclaim behavior, nothing more and nothing less.
Risk Disclosure
This script is for chart analysis and educational use only. It does not provide financial, investment, legal, or tax advice.
All trading decisions involve risk. Past price behavior around previous-day levels does not guarantee future results. Users should apply their own confirmation process, risk management rules, and market context analysis before acting on any chart signal.
Always test settings carefully and use the tool as one component inside a broader decision-making process, not as a standalone basis for trading.
Indicator
Stage 2 Trend Qualifier 8-Criteria Trend Template with RS scoreA compact on-chart dashboard that evaluates whether a stock qualifies as a Stage 2 uptrend using an 8-criteria trend template based on moving average alignment and price position relative to key benchmarks. Includes relative strength scoring, outperformance day tracking, and RS line analysis.
█ WHAT IT DOES
This indicator runs 8 mechanical checks on every bar and displays pass/fail status in a clean overlay table:
1. Price above 150-day SMA
2. Price above 200-day SMA
3. 50-day SMA above 150-day SMA
4. 50-day SMA above 200-day SMA
5. 200-day SMA trending up for at least 1 month
6. Price at least 25% above its 52-week low
7. Price within 25% of its 52-week high
8. Price not more than 10% below the 50-day SMA
When all 8 pass → STAGE 2 (confirmed uptrend). Otherwise the indicator classifies the stock as Stage 1 (basing), Stage 3 (topping), or Stage 4 (decline) based on moving average relationships.
█ RS SCORE (1–99)
Relative strength versus a user-selected benchmark (default: SPY) displayed as a normalized score from 1 to 99 across four timeframes: 1M, 3M, 6M, and 12M.
50 = matching the benchmark. Above 50 = outperforming. Below 50 = underperforming. Each timeframe uses a calibrated scale so scores are comparable across periods.
Color coding:
≥80 → bright green (strong leader)
60–79 → green (outperformer)
40–59 → gray (average)
<40 → red (laggard)
█ RS DAYS
Counts how many trading days the stock outperformed the benchmark over rolling windows of 15, 30, and 60 days. Displayed as: count (win-rate%). For example, "9 (60%)" means the stock beat the benchmark on 9 out of 15 days.
A high RS Score with a low RS Days % means the stock had a few big winning days but isn't consistently leading — less reliable strength. Consistent outperformance (>60%) across all windows is the strongest signal.
█ RS LINE STATUS
Evaluates the relative strength line (stock price ÷ benchmark price) versus its own 52-week high:
NEW HIGH → RS line at its 52-week peak. Strongest relative performance in a year. Often leads price breakouts.
NEAR HIGH → Within 3% of 52-week high. Relative strength building toward leadership.
NEUTRAL → 3–15% below 52-week high. Average relative performance, no clear edge.
WEAK → More than 15% below 52-week high. Relative strength deteriorating. Market rotating away.
█ ALERTS
Three built-in alert conditions:
- Stage 2 Qualified — stock transitions from <8/8 to 8/8 criteria met
- Stage 2 Lost — stock drops from 8/8 to fewer criteria met
- RS Line New High — relative strength line hits a new 52-week high
█ SETTINGS
- Toggle sections: Trend Template, RS Score & Days (on/off independently)
- Table position: any corner or middle edge
- Text size: tiny, small, normal
- Theme: Dark or Light (match your chart background)
- Benchmark symbol: default SPY, changeable to any index or ETF
█ USAGE NOTES
- Designed for the DAILY timeframe. On intraday or weekly charts, the bar-based lookbacks (252 bars for 52-week, 21 bars for 1 month) represent chart bars, not calendar days.
- Stage 2 identification is mechanically precise — all 8 criteria must pass. Stages 1, 3, and 4 use approximate moving average relationship logic.
- RS Score normalizes relative performance to a 1–99 scale. This is NOT a percentile rank across a stock universe — it measures magnitude of outperformance vs your selected benchmark.
- This indicator is an educational and analytical tool. It does not generate buy or sell signals. Indicator
Volatility Z-Score [NovaLens]Volatility Z-Score is a statistical volatility indicator that measures how far the current ATR deviates from its historical average, expressed in standard deviations. Built on the Z-Score method used by quantitative desks to detect anomalies, it self-normalizes across any asset and timeframe - no parameter guessing needed.
◉ HOW IT WORKS
Most traders watch ATR to measure volatility - but raw ATR numbers are meaningless without context. ATR = 50 tells you nothing unless you know the asset's history. Is that high? Low? Normal?
The Z-Score solves this by standardizing ATR against its own rolling distribution:
Z = (ATR_current - ATR_mean) / ATR_stddev
A Z-Score of +2 means current ATR is two standard deviations above the historical mean - statistically extreme. A score of 0 means volatility is exactly average. This is the same standardization method used across quantitative finance to detect regime changes and anomalies.
◈ HOW TO READ IT
• Z > +2 : Statistically extreme volatility. Breakout in progress or capitulation event. Consider tightening stops or waiting for mean reversion.
• Z between −1 and +1 : Normal volatility range. Trade your usual setups with standard risk parameters.
• Z < −2 : Unusually quiet market. Compression before expansion. Watch for pre-breakout positioning opportunities.
✦ USE CASES
• Filter entries - only take trades when volatility is in your preferred regime (e.g., avoid extreme Z for trend-following)
• Time exits - extreme Z-Scores often precede reversals or consolidation phases
• Risk management - scale position size inversely with Z-Score: smaller in high-vol, larger in low-vol
• Regime detection - sustained high or low Z indicates a volatility regime shift, not just noise
• Combine with trend tools - high Efficiency Ratio + low Z-Score = quiet strong trend about to expand
⚙ SETTINGS
• ATR Period - Period for Average True Range calculation. Higher values smooth the ATR, lower values make it more responsive to recent price action.
• Z-Score Lookback - Number of bars for computing mean and standard deviation of ATR. Longer lookback = more stable reference, shorter = faster regime detection.
△ LIMITATIONS
Z-Score assumes a roughly normal distribution of ATR values. In assets with structural volatility shifts (e.g., post-halving crypto), the lookback window may not capture the new regime quickly. Works best on liquid instruments with sufficient history. Not a directional signal - tells you about volatility magnitude, not trend direction.
⌁ NOTES
• Based on standard Z-Score normalization - a foundational technique in quantitative finance
• Validated against Python implementation (1.000 correlation via PyneCore)
• Open-source - read the code and verify the math
• Built for traders who want volatility context in standardized units, not raw ATR values Indicator
Momentum Pulse█ MOMENTUM PULSE v1.0
Next-Generation Adaptive Momentum Analysis
Blends three orthogonal momentum sources into a single Adaptive Momentum Composite (AMC), enhanced with multi-timeframe confluence scoring and automatic divergence detection. A comprehensive, real-time read on momentum across multiple dimensions — all in one clean, non-overlay panel.
Free and Open Source.
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█ THE CONCEPT: COMPOSITE MOMENTUM
Traditional momentum indicators measure one thing: RSI tracks mean-reversion, MACD tracks trend acceleration, ROC tracks raw velocity. Each has blind spots. A composite approach eliminates these blind spots by combining all three perspectives into a single normalized reading.
The Adaptive Momentum Composite (AMC) uses Z-score normalization to ensure each component contributes equally regardless of asset type or volatility level — it auto-calibrates to any market.
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█ CORE ENGINE: ADAPTIVE MOMENTUM COMPOSITE (AMC)
The signature engine combines three Z-score normalized momentum sources:
1. Rate of Change (ROC)
Raw price velocity over N bars. Catches sharp moves early.
2. RSI Deviation
Distance of RSI from the 50-line. Captures overbought/oversold pressure.
3. MACD Histogram
Trend acceleration. Captures the speed of the trend change.
Each component's weight is configurable. The composite is clamped to to prevent extreme outlier distortion.
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█ TREND STRENGTH METER
Real-time regime classification using adaptive thresholds:
STRONG BULL — AMC above 1.8x its own standard deviation
BULL — AMC above 0.8x standard deviation
NEUTRAL — AMC near zero
BEAR — Mirror of bullish thresholds
STRONG BEAR — Mirror of bullish thresholds
Thresholds auto-calibrate to each asset and timeframe. A visual strength gauge (0–100%) shows momentum intensity at a glance.
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█ MULTI-TIMEFRAME CONFLUENCE
Polls AMC direction from up to 3 higher timeframes plus the current chart:
Score 4/4 — All timeframes aligned = high-conviction setup
Score 3/4 — Strong alignment with one dissenter = proceed with caution
Score 2/4 or less — Mixed signals = chop zone, reduce position size
Auto-selects appropriate higher timeframes based on your chart. Manual override available.
Auto-Selected Timeframes:
1-3 min chart → 5 min / 15 min / 1 Hour
5 min chart → 15 min / 1 Hour / 4 Hour
15 min chart → 1 Hour / 4 Hour / Daily
1 Hour chart → 4 Hour / Daily / Weekly
4 Hour chart → Daily / Weekly / Monthly
Daily chart → Weekly / Monthly / 3M
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█ DIVERGENCE DETECTION
Automatic pivot-based detection of four divergence types:
Regular Bullish — Price makes lower low, AMC makes higher low → reversal up
Regular Bearish — Price makes higher high, AMC makes lower high → reversal down
Hidden Bullish — Price makes higher low, AMC makes lower low → trend continuation up
Hidden Bearish — Price makes lower high, AMC makes higher high → trend continuation down
Each divergence is labeled directly on the chart with color-coded markers. Configurable pivot lookback and maximum bar distance between pivots.
═══════════════════════════════════
█ MOMENTUM WAVE VISUALIZATION
Dynamic gradient histogram:
Rising Bullish — Bright cyan
Fading Bullish — Teal
Rising Bearish — Bright red-pink
Fading Bearish — Magenta
Signal Line — Smoothed AMC (EMA) for crossover timing
Zero-Line Crosses — Circle labels ("0+" / "0-")
Signal Crosses — Diamond markers for entry/exit timing
Background zones subtly shade the panel based on the current momentum regime.
═══════════════════════════════════
█ DASHBOARD
Compact dark-themed info panel displaying:
AMC — Current composite value with trend arrow
Regime — STRONG BULL / BULL / NEUTRAL / BEAR / STRONG BEAR with color coding
Strength — Visual gauge bar (0–100%) showing momentum intensity
Signal — Above / Below signal line status
MTF Confluence — Arrow alignment for all 4 timeframes with score (0-4)
Timeframes — Current + 3 higher TFs being monitored
Components — Individual Z-scores for ROC, RSI, MACD
RSI — Raw RSI value with Overbought/Oversold status
═══════════════════════════════════
█ ALERTS (10 CONDITIONS)
Zero Crosses: Bullish / Bearish
Signal Crosses: Bullish / Bearish
Regular Divergence: Bullish / Bearish
Hidden Divergence: Bullish / Bearish
Full MTF Confluence: Bullish / Bearish
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█ PRO VERSION
The PRO version adds:
Enhanced AMC Engine — Additional momentum components and advanced weighting algorithms
Extended Dashboard — More detailed analytics and component breakdown
Advanced Divergence — Multi-level divergence scoring with strength classification
Strategy Mode — Built-in backtestable strategy with entry/exit logic
Additional Alert Conditions — Regime change, momentum acceleration, and more
═══════════════════════════════════
█ NON-REPAINTING
The AMC is calculated from standard non-repainting indicators (ROC, RSI, MACD). Z-score normalization uses historical data only. MTF requests use lookahead_off to prevent future data leakage. Divergence detection requires confirmed pivots. No repainting.
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█ WORKS ON
Crypto, Forex, Stocks, Futures, Indices — any timeframe from 1 minute to Monthly.
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█ DISCLAIMER
This indicator is for educational and informational purposes only. It does not constitute financial advice. Past performance does not guarantee future results. No indicator can predict market movements with certainty. Always implement proper risk management. Use this tool as one component of a comprehensive trading strategy, not as a standalone decision-making system.
Indicator
MVRV Z-Score (DEMA Smoothed) | CipherDecodedMVRV Z-Score (DEMA Smoothed) | CipherDecoded
Overview
The MVRV Z-Score (DEMA Smoothed) is a structural trend-following oscillator derived from Bitcoin’s on-chain capital positioning.
Rather than interpreting MVRV purely as a valuation metric, this implementation treats the relationship between market value and realized value as a proxy for capital regime expansion and contraction. By statistically normalizing MVRV and applying Double Exponential Moving Average (DEMA) smoothing, the indicator converts on-chain profitability dynamics into a tradable trend signal.
The result is a regime-sensitive momentum framework anchored to underlying cost basis structure.
Structural Rationale
Market cycles are driven by shifts in aggregate positioning:
When market value persistently exceeds realized value, capital is in profit and reflexive expansion tends to dominate.
When market value compresses toward or below realized value, distribution and contraction phases emerge.
By standardizing MVRV into a rolling Z-score, the indicator measures the velocity and persistence of profitability expansion, not just its magnitude.
The subsequent DEMA smoothing filters short-term volatility while preserving structural inflection points, making the signal more suitable for systematic trend models.
Inputs
BTC Market Capitalization
BTC Realized Market Capitalization
Daily confirmed data to prevent repainting
Z-Score Normalization
Rolling lookback mean and standard deviation
Converts raw ratio into standardized regime measure
DEMA Smoothing
Applied to the Z-score output
Reduces noise while maintaining responsiveness to regime shifts
Trend Threshold
User-defined bias level (default: 0.0)
Above threshold = expansion regime
Below threshold = contraction regime
Interpretation
This indicator is designed to identify structural trend bias, not overbought/oversold extremes.
Sustained positive readings indicate persistent capital expansion.
Sustained negative readings indicate structural compression.
Threshold crossovers signal potential regime transitions.
Slope and persistence are often more informative than absolute level.
Design Principles
Statistical normalization separates signal from secular growth effects.
Smoothing is applied post-normalization to preserve structural information.
Inputs are modular, allowing independent control of regime sensitivity and signal responsiveness.
Data is requested on confirmed daily closes to ensure signal stability.
Strategic Context
Unlike traditional price-only oscillators, this framework derives trend information from underlying capital positioning. It therefore reacts to structural shifts in profitability rather than short-term price volatility.
This makes it particularly suited for:
Medium- to long-horizon trend strategies
Macro regime allocation models
Risk scaling frameworks
Summary
The MVRV Z-Score (DEMA Smoothed) reframes on-chain valuation data into a structural trend engine. By combining statistical normalization with adaptive smoothing, it provides a capital-anchored momentum signal designed for regime-based trading and systematic bias control. Indicator
Ehlers Super Smoother Trend Score [BackQuant]Ehlers Super Smoother Trend Score
Overview
Ehlers Super Smoother Trend Score is a regime and trend-strength indicator built on a signal-processing filter created by John F. Ehlers. Instead of smoothing price with a standard moving average (which is mathematically crude and prone to noise and aliasing), this indicator applies the Ehlers Super Smoother, a Butterworth-style low-pass filter designed specifically for market data. The filtered series is then scored for directional persistence across a configurable lookback window, producing an oscillator-like trend score that measures how consistently the smoothed trend is advancing or deteriorating.
This is not a simple “MA slope” tool. It is:
A proper low-pass filter (Super Smoother) to reduce noise while preserving structure.
A persistence score that converts the filtered trend into a quantitative regime signal.
A threshold framework that turns the score into long/short regime transitions with clean state logic.
Where the filter comes from (and why it matters)
John F. Ehlers is known for applying digital signal processing (DSP) techniques to technical analysis. Traditional moving averages are not designed as proper frequency-selective filters. They blur price, lag heavily, and can introduce distortions, especially when the market contains high-frequency components (noise) near the Nyquist limit (the maximum representable frequency in sampled data).
The Super Smoother is derived from a Butterworth low-pass filter design. Butterworth filters are engineered to have a maximally flat passband, meaning they smooth without introducing ripples in the filtered output. In trading terms:
Less “wavy” smoothing artifacts than many MA variants.
Better suppression of high-frequency noise.
Cleaner trend structure for downstream logic.
This script implements Ehlers’ recursive coefficient form, giving you a 2-pole (classic) or 3-pole (heavier) filter.
What “Super Smoother” actually is
The Super Smoother is a recursive IIR filter (Infinite Impulse Response). Unlike an SMA which averages a fixed window of past values, an IIR filter uses feedback from its own prior output values. That matters because it can achieve strong smoothing with less lag for a given “smoothness target.”
Conceptually:
Input: price series.
Output: filtered estimate of the “low-frequency” component (trend structure).
Mechanism: combine current input (or pre-filtered input) with previous filter outputs using coefficients derived from a chosen cutoff period.
The coefficients (c1–c4) are not arbitrary, they are computed from exponential decay and cosine terms based on the cutoff period. This is what makes it a real DSP filter rather than “just another MA.”
2-pole vs 3-pole behavior
2-pole (classic)
A standard Ehlers Super Smoother configuration. It offers a strong improvement over typical MAs in smoothness vs lag balance.
3-pole
Adds an additional feedback term (one more prior filtered state). This increases smoothing and noise rejection, but introduces slightly more lag. The advantage is a cleaner structural line, which often improves regime stability when the market is noisy or mean-reverting.
Anti-aliasing pre-filter step
Before applying the recursive formula, the script averages the current and previous price:
avg = (src + src ) / 2
This is a simple but important pre-filter that reduces high-frequency components that can alias into lower frequencies in sampled data. In practice, it helps stop “one-bar spikes” from contaminating the filter output as much.
Inputs and what they really control
Super Smoother Period (ssPeriod)
This is the cutoff period used in the coefficient derivation. It is not the same as “MA length,” but it behaves similarly in that:
Lower period = faster response, less smoothing, more sensitivity to noise.
Higher period = smoother output, better noise rejection, more lag.
Poles
Selects filter order:
2 poles = balanced default.
3 poles = smoother, more conservative.
Score Lookback Start/End
Defines the persistence scoring window. The script compares the current filtered value to many prior filtered values across that range. A longer range makes the score more “confidence-based” and slower to change, while a shorter range makes it more reactive.
Thresholds (Long/Short)
Turns the score into a regime classification:
Long threshold defines when bullish persistence is strong enough to be considered a trend regime.
Short threshold defines when persistence has deteriorated enough to signal a bearish transition.
How the trend score is computed
After filtering, the indicator computes a directional persistence score on the filtered series (not raw price). That distinction matters because you are scoring structure, not noise.
Mechanically:
For each i in the scoring window:
- If filt_now > filt , add +1
- Else add -1
Sum across the window to produce the score.
Interpretation:
High positive score means the filtered trend is consistently higher than many past points, persistent bullish structure.
Low or negative score means the filtered trend is not advancing, or is consistently below prior points, bearish structure.
Scores near the middle mean the filtered series is oscillating without clear persistence, chop or transition.
This is a persistence metric, not a slope metric. It does not care about one-bar direction, it cares about consistency relative to history.
Signal and state logic (why it stays clean)
The indicator uses state logic to prevent constant flip-flopping:
Long condition: score > long threshold.
Short condition: score crosses below short threshold (uses prevScore and current score).
That short logic is event-based, it triggers only on the breakdown transition, not on every bar below the threshold. Once a regime is set, it remains until a real threshold event forces change.
Signals are plotted only on regime flips:
Long marker when signal becomes +1 and prior was -1.
Short marker when signal becomes -1 and prior was +1.
This is designed for alerts and for clean backtesting interpretation.
Visual layers
The indicator can be used purely as a panel oscillator or as a structure overlay.
Pane
Trend Score line, colored by active regime.
Optional reference lines at long/short thresholds for fast regime reading.
On-chart (optional)
Super Smoother line plotted over price, colored by regime.
Optional candle painting and background shading to reflect active regime.
This lets you treat the filter as a dynamic trend structure line while using the score as the regime classifier.
How to interpret it properly
1) The Super Smoother line
This is the cleaned trend structure estimate:
When price respects the smoother line, trend structure is intact.
When price repeatedly chops through it, structure is weak or range-bound.
2) The score
This is the quantified persistence of that structure:
Rising score implies strengthening trend persistence.
Falling score implies deterioration, transition risk, or mean reversion.
Score compression often shows consolidation before a regime shift.
3) Threshold regimes
Above long threshold: bullish persistence regime, trend-following conditions.
Below short threshold: bearish regime transition, defensive or short-biased conditions.
Between thresholds: neutral/transition zone, where chop and fakeouts are common.
Practical use cases
Trend filter
Only take long setups when score is above the long threshold.
Reduce exposure or avoid trend trades in the neutral band.
Treat a breakdown through the short threshold as regime invalidation.
Trend quality assessment
High score = continuation environment.
Moderate score = trend exists but is fragile.
Low/negative score = distribution, downtrend, or unstable structure.
Trade management
Use the Super Smoother line as a structure reference for trailing risk.
Use score deterioration as an early warning before full regime flips.
Use regime flips as hard exits or bias changes.
Tuning guidelines
If you want fewer signals and cleaner regimes
Increase ssPeriod.
Use 3 poles.
Increase scoreEnd (longer scoring window).
If you want faster reaction
Decrease ssPeriod.
Use 2 poles.
Reduce the scoring window length.
Keep in mind: faster settings increase sensitivity to chop. The filter is good, but no filter removes the reality of mean reversion.
What makes this different from “just a smoothed MA score”
The difference is the filter quality. The Super Smoother is a proper low-pass filter with coefficients derived from DSP principles, designed to suppress high-frequency noise and avoid common smoothing artifacts. Scoring that filtered structure gives you a regime metric that is more stable and more meaningful than scoring raw price or scoring a basic MA that still carries a lot of aliasing and distortion.
Summary
Ehlers Super Smoother Trend Score combines a DSP-derived Butterworth-style Super Smoother filter with a directional persistence scoring model. The filter provides a clean, low-noise trend structure series, and the score quantifies how consistently that structure is advancing or deteriorating across a defined window. Threshold-based regime logic converts the score into clean trend states and alerts, making it a practical tool for trend filtering, regime detection, and structure-aware trade management. Indicator
Relative Valuation Oscillator [QuantAlgo]🟢 Overview
The Relative Valuation Oscillator identifies statistical price deviations from fair value using logarithmic price analysis and standard deviation bands. It calculates how far current price has deviated from its mean on a logarithmic scale, normalized by volatility, to generate a centered oscillator that highlights periods when price is statistically stretched above or below its historical average, helping traders identify potential mean reversion opportunities and extreme valuation conditions across different timeframes and markets.
🟢 How It Works
The indicator's core methodology lies in its statistical approach to price valuation, where deviations are measured using logarithmic returns and normalized by standard deviation:
log_price = math.log(close)
mean_log_price = ta.sma(log_price, lookback_period)
standard_deviation = ta.stdev(log_price, lookback_period)
valuation_score = (log_price - mean_log_price) / standard_deviation
First, the script converts price to logarithmic form to account for percentage-based price movements rather than absolute dollar changes, ensuring the indicator works consistently across different price levels and asset classes.
Then, it calculates the mean log price over the specified lookback period to establish a baseline fair value reference:
mean_log_price = ta.sma(log_price, lookback_period)
Next, standard deviation measurement quantifies the typical volatility of log price around this mean, providing a statistical framework for defining normal versus extreme price behavior:
standard_deviation = ta.stdev(log_price, lookback_period)
The valuation score is then derived by measuring how many standard deviations the current log price sits from its mean, creating a normalized oscillator that fluctuates around zero:
valuation_score = (log_price - mean_log_price) / standard_deviation
Finally, threshold-based signal detection identifies extreme conditions when the valuation score exceeds user-defined standard deviation multiples:
is_overvalued = valuation_score > threshold_mult
is_undervalued = valuation_score < -threshold_mult
This creates a statistical mean reversion system that identifies when price has deviated significantly from its historical average on a volatility-adjusted basis, providing traders with objective measurements of relative over or undervaluation.
🟢 Signal Interpretation
▶ Undervalued Zone (Below Negative Threshold): Oscillator falling below the negative threshold line indicates price has deviated significantly below its statistical mean = Potential long/buy opportunities for mean reversion strategies
▶ Overvalued Zone (Above Positive Threshold): Oscillator rising above the positive threshold line indicates price has deviated significantly above its statistical mean = Potential short/sell or profit-taking opportunities
▶ Fair Value Range (Between Thresholds): Oscillator remaining between positive and negative threshold lines indicates price is trading within normal statistical bounds. Within this range, the zero line acts as a directional filter: oscillator above zero but below the upper threshold suggests bullish trend/momentum with price trading above its statistical mean = Trend-following long positions can be maintained; oscillator below zero but above the lower threshold suggests bearish trend/momentum with price trading below its statistical mean = Trend-following short positions can be maintained. The oscillator can remain in these directional zones during sustained trends until mean reversion occurs, signaled by crosses back toward zero or transitions to the opposite extreme threshold.
▶ Zero Line Crosses: Oscillator crossing above zero indicates transition from below-average to above-average valuation, confirming shift to bullish momentum = Potential trend-following long entry; crossing below zero indicates transition from above-average to below-average valuation, confirming shift to bearish momentum = Potential trend-following short entry or long exit. These crosses can signal both the start of directional trends and early mean reversion from extreme conditions.
🟢 Features
▶ Preconfigured Presets: Three optimized parameter sets for different trading approaches and timeframes. "Default" provides balanced sensitivity for swing trading on 4-hour and daily charts, generating signals at statistically significant deviations. "Fast Response" delivers more frequent signals for intraday trading on 5-minute to 1-hour charts, reacting quickly to short-term deviations with increased signal frequency. "Smooth Trend" focuses on major extremes for position trading on daily to weekly timeframes, filtering noise to identify only the most significant statistical outliers.
▶ Built-in Alerts: Five alert conditions enable automated monitoring of valuation extremes and transitions. "Overvalued Threshold Crossed" triggers when the oscillator crosses above the positive threshold, signaling potential overvaluation. "Undervalued Threshold Crossed" activates when the oscillator crosses below the negative threshold, signaling potential undervaluation. "Crossed Above Fair Value (0)" and "Crossed Below Fair Value (0)" provide alerts for zero line transitions, indicating shifts between above-average and below-average valuation. "Any Extreme Valuation" offers a combined alert for any threshold breach regardless of direction, allowing traders to monitor both extremes with a single alert setup.
▶ Color Customization: Six visual themes (Classic, Aqua, Cosmic, Cyber, Neon, plus Custom) accommodate different chart backgrounds and visual preferences, with distinct colors for overvalued, undervalued, and fair value conditions. Optional background highlighting with adjustable transparency (0-100%) tints the main chart background during extreme valuation periods, providing immediate visual context without requiring continuous oscillator monitoring. Optional overlay signals display small circle markers directly on the price chart above bars during overvaluation and below bars during undervaluation, allowing correlation of statistical extremes with specific price levels and candlestick patterns.
Indicator
SPY Quant ML + Session Filter Strategy [CocoChoco]S&P 500 Quant: Machine Learning & Mean Reversion (Session-Filtered)
Overview
This is a professional-grade quantitative strategy designed specifically for the S&P 500. It combines classical statistical mean reversion (Z-Score) with a modern Machine Learning filter and rigorous institutional-grade risk management.
The strategy is optimized for traders who prioritize high win rates and capital preservation, specifically avoiding the "gap risk" associated with holding positions overnight.
Core Methodology
1. Statistical Entry (The Z-Score Engine)
The strategy identifies "oversold" conditions in a bullish context. It calculates the Z-Score of the price relative to its 20-period Mean (SMA). By default, it looks for a -1.2 Standard Deviation extension, signaling a high-probability "dip" ripe for a snap-back to the mean.
2. Trend & ML Filters
To avoid "catching a falling knife," the strategy uses two layers of confirmation:
Trend Filter: Only takes Long positions when the price is above the 200-period SMA, ensuring we only buy dips in a confirmed uptrend.
ML Correlation Filter: A Machine Learning-inspired module that analyzes the correlation between RSI and Volatility (ATR). It only permits entries when market internal dynamics suggest a reversal is technically "healthy."
3. Institutional Risk Management
This script is built for "safety-first" automation:
Hard Stop Loss: Fixed at 1.5% to protect against sudden market shocks.
Active Trailing: A dual-trigger trailing stop. It activates once the price touches the 20 SMA (The Mean) OR once a trade reaches a 0.50% profit threshold. This ensures near-winners are protected and large runners are captured.
Intraday Circuit Breaker: Includes a Max Daily Drawdown (2%) limit. If hit, the script automatically closes losing positions and halts trading for the day, while allowing winning positions to continue.
Key Features
Session-Specific: Tailored for the US Trading Session (UTC/NY times).
Zero Overnight Risk: Automatically flattens all positions before the market close (16:00 NY Time).
Holiday Intelligence: Hard-coded logic for US Market Holidays and Early Closes (2026–2028), ensuring the bot doesn't get stuck in illiquid holiday markets.
Hourly Entry Cap: Limits entries to one per hour to prevent over-concentration during a single price leg.
How to Use
Timeframe: I suggest you use it on the 5-minute or 1-hour timeframe for optimal results.
Instrument: Designed for the S&P 500, but highly effective on SPY, IVV, and ES (Futures).
Pyramiding: Designed to handle up to 3 concurrent positions, allowing the strategy to scale into a move as the Z-Score deepens.
Automation Ready
This script is fully compatible with webhook-based automation tools. All signals (Entry, SL, Trail, Market Close, and Daily Limit) are clearly labeled in the Alert comments for seamless execution. I haven't tasted it though. This is not financial advice. Please perform your own tests and manage your risk.
Disclaimer
Past performance does not guarantee future results. This script is a tool for quantitative analysis and should be used as part of a broader diversified trading plan. Strategy
Indicator
Volume-Weighted Price Z-Score [QuantAlgo]🟢 Overview
The Volume-Weighted Price Z-Score indicator quantifies price deviations from volume-weighted equilibrium using statistical standardization. It combines volume-weighted moving average analysis with logarithmic deviation measurement and volatility normalization to identify when prices have moved to statistically extreme levels relative to their volume-weighted baseline, helping traders and investors spot potential mean reversion opportunities across multiple timeframes and asset classes.
🟢 How It Works
The indicator's core methodology lies in its volume-weighted statistical approach, where price displacement is measured through normalized deviations from volume-weighted price levels:
volumeWeightedAverage = ta.vwma(priceSource, lookbackPeriod)
logDeviation = math.log(priceSource / volumeWeightedAverage)
volatilityMeasure = ta.stdev(logDeviation, lookbackPeriod)
The script uses logarithmic transformation to capture proportional price changes rather than absolute differences, ensuring equal treatment of percentage moves regardless of price level:
rawZScore = logDeviation / volatilityMeasure
zScore = ta.ema(rawZScore, smoothingPeriod)
First, it establishes the volume-weighted baseline which gives greater weight to price levels where significant trading occurred, creating a more representative equilibrium point than simple moving averages.
Then, the logarithmic deviation measurement converts the price-to-average ratio into a normalized scale:
logDeviation = math.log(priceSource / volumeWeightedAverage)
Next, statistical normalization is achieved by dividing the deviation by its own historical volatility, creating a standardized z-score that measures how many standard deviations the current price sits from the volume-weighted mean.
Finally, EMA smoothing filters noise while preserving the signal's responsiveness to genuine market extremes:
rawZScore = logDeviation / volatilityMeasure
zScore = ta.ema(rawZScore, smoothingPeriod)
This creates a volume-anchored statistical oscillator that combines price-volume relationship analysis with volatility-adjusted normalization, providing traders with probabilistic insights into market extremes and mean reversion potential based on standard deviation thresholds.
🟢 Signal Interpretation
▶ Positive Values (Above Zero): Price trading above volume-weighted average indicating potential overvaluation relative to volume-weighted equilibrium = Caution on longs, potential mean reversion downward = Short/sell opportunities
▶ Negative Values (Below Zero): Price trading below volume-weighted average indicating potential undervaluation relative to volume-weighted equilibrium = Caution on shorts, potential mean reversion upward = Long/buy opportunities
▶ Zero Line Crosses: Mean reversion transitions where price crosses back through volume-weighted equilibrium, indicating shift from overvalued to undervalued (or vice versa) territory
▶ Extreme Positive Zone (Above +2.5σ default): Statistically rare overvaluation representing 98.8%+ confidence level deviation, indicating extremely stretched bullish conditions with high mean reversion probability = Strong correction warning/short signal
▶ Extreme Negative Zone (Below -2.5σ default): Statistically rare undervaluation representing 98.8%+ confidence level deviation, indicating extremely stretched bearish conditions with high mean reversion probability = Strong buying opportunity signal
▶ ±1σ Reference Levels: Moderate deviation zones (±1 standard deviation) marking common price fluctuation boundaries where approximately 68% of price action occurs under normal distribution
▶ ±2σ Reference Levels: Significant deviation zones (±2 standard deviations) marking unusual price extremes where approximately 95% of price action should be contained under normal conditions
🟢 Features
▶ Preconfigured Presets: Three optimized parameter sets accommodate different analytical approaches, instruments and timeframes. "Default" provides balanced statistical measurement suitable for swing trading and daily/4-hour analysis, offering deviation detection with moderate responsiveness to price dislocations. "Fast Response" delivers heightened sensitivity optimized for intraday trading and scalping on 15-minute to 1-hour charts, using shorter statistical windows and minimal smoothing to capture rapid mean reversion opportunities as they develop. "Smooth Trend" offers conservative extreme identification ideal for position trading on daily to weekly charts, employing extended statistical periods and heavy noise filtering to isolate only the most significant market extremes.
▶ Built-in Alerts: Seven alert conditions enable comprehensive automated monitoring of statistical extremes and mean reversion events. Extreme Overbought triggers when z-score crosses above the extreme threshold (default +2.5σ) signaling rare overvaluation, Extreme Oversold activates when z-score crosses below the negative extreme threshold (default -2.5σ) signaling rare undervaluation. Exit Extreme Overbought and Exit Extreme Oversold alert when prices begin reverting from these statistical extremes back toward the mean. Bullish Mean Reversion notifies when z-score crosses above zero indicating shift to overvalued territory, while Bearish Mean Reversion triggers on crosses below zero indicating shift to undervalued territory. Any Extreme Level provides a combined alert for any extreme threshold breach regardless of direction. These notifications allow you to capitalize on statistically significant price dislocations without continuous chart monitoring.
▶ Color Customization: Six visual themes (Classic, Aqua, Cosmic, Ember, Neon, plus Custom) accommodate different chart backgrounds and visual preferences, ensuring optimal contrast for identifying positive versus negative deviations across trading environments. The adjustable fill transparency control (0-100%) allows fine-tuning of the gradient area prominence between the z-score line and zero baseline, with higher opacity values creating subtle background context while lower values produce bold deviation emphasis. Optional bar coloring extends the z-score gradient directly to the indicator pane bars, providing immediate visual reinforcement of current deviation magnitude and direction without requiring reference to the plotted line itself.
*Note: This indicator requires volume data to function correctly, as it calculates deviations from a volume-weighted price average. Tickers with no volume data or extremely limited volume will not produce meaningful results, i.e., the indicator may display flat lines, erratic values, or fail to calculate properly. Using this indicator on assets without volume data (certain forex pairs, synthetic indices, or instruments with unreported/unavailable volume) will produce unreliable or no results at all. Additionally, ensure your chart has sufficient historical data to cover the selected lookback period, e.g., using a 100-bar lookback on a chart with only 50 bars of history will yield incomplete or inaccurate calculations. Always verify your chosen ticker has consistent, accurate volume information and adequate price history before applying this indicator. Indicator
Adaptive Z-Score Oscillator [QuantAlgo]🟢 Overview
The Adaptive Z-Score Oscillator transforms price action into statistical significance measurements by calculating how many standard deviations the current price deviates from its moving average baseline, then dynamically adjusting threshold levels based on historical distribution patterns. Unlike traditional oscillators that rely on fixed overbought/oversold levels, this indicator employs percentile-based adaptive thresholds that automatically calibrate to changing market volatility regimes and statistical characteristics. By offering both adaptive and fixed threshold modes alongside multiple moving average types and customizable smoothing, the indicator provides traders and investors with a robust framework for identifying extreme price deviations, mean reversion opportunities, and underlying trend conditions through the visualization of price behavior within a statistical distribution context.
🟢 How It Works
The indicator begins by establishing a dynamic baseline using a user-selected moving average type applied to closing prices over the specified length period, then calculates the standard deviation to measure price dispersion:
basis = ma(close, length, maType)
stdev = ta.stdev(close, length)
The core Z-Score calculation quantifies how many standard deviations the current price sits above or below the moving average basis, creating a normalized oscillator that facilitates cross-asset and cross-timeframe comparisons:
zScore = stdev != 0 ? (close - basis) / stdev : 0
smoothedZ = ma(zScore, smooth, maType)
The adaptive threshold mechanism employs percentile calculations over a historical lookback period to determine statistically significant extreme zones. Rather than using fixed levels like ±2.0, the indicator identifies where a specified percentage of historical Z-Score readings have fallen, automatically adjusting to market regime changes:
upperThreshold = adaptive ? ta.percentile_linear_interpolation(smoothedZ, percentilePeriod, upperPercentile) : fixedUpper
lowerThreshold = adaptive ? ta.percentile_linear_interpolation(smoothedZ, percentilePeriod, lowerPercentile) : fixedLower
The visualization architecture creates a four-tier coloring system that distinguishes between extreme conditions (beyond the adaptive thresholds) and moderate conditions (between the midpoint and threshold levels), providing visual gradation of statistical significance through opacity variations and immediate recognition of distribution extremes.
🟢 How to Use This Indicator
▶ Overbought and Oversold Identification:
The indicator identifies potential overbought conditions when the smoothed Z-Score crosses above the upper threshold, indicating that price has deviated to a statistically extreme level above its mean. Conversely, oversold conditions emerge when the Z-Score crosses below the lower threshold, signaling statistically significant downward deviation. In adaptive mode (default), these thresholds automatically adjust to the asset's historical behavior, i.e., during high volatility periods, the thresholds expand to accommodate wider price swings, while during low volatility regimes, they contract to capture smaller deviations as significant. This dynamic calibration reduce false signals that plague fixed-level oscillators when market character shifts between volatile and ranging conditions.
▶ Mean Reversion Trading Applications:
The Z-Score framework excels at identifying mean reversion opportunities by highlighting when price has stretched too far from its statistical equilibrium. When the oscillator reaches extreme bearish levels (below the lower threshold with deep red coloring), it suggests price has become statistically oversold and may snap back toward the mean, presenting potential long entry opportunities for mean reversion traders. Symmetrically, extreme bullish readings (above the upper threshold with bright green coloring) indicate potential short opportunities or long exit points as price becomes statistically overbought. The moderate zones (lighter colors between midpoint and threshold) serve as early warning areas where traders can prepare for potential reversals, while exits from extreme zones (crossing back inside the thresholds) often provide confirmation that mean reversion is underway.
▶ Trend and Distribution Analysis:
Beyond discrete overbought/oversold signals, the histogram's color pattern and shape reveal the underlying trend structure and distribution characteristics. Sustained periods where the Z-Score oscillates primarily in positive territory (green bars) indicate a bullish trend where price consistently trades above its moving average baseline, even if not reaching extreme levels. Conversely, predominant negative readings (red bars) suggest bearish trend conditions. The distribution shape itself provides insight into market behavior, e.g., a narrow, centered distribution clustering near zero indicates tight ranging conditions with price respecting the mean, while a wide distribution with frequent extreme readings reveals volatile trending or choppy conditions. Asymmetric distributions skewed heavily toward one side demonstrate persistent directional bias, whereas balanced distributions suggest equilibrium between bulls and bears.
▶ Built-in Alerts:
Seven alert conditions enable automated monitoring of statistical extremes and trend transitions. Enter Overbought and Enter Oversold alerts trigger when the Z-Score crosses into extreme zones, providing early warnings of potential reversal setups. Exit Overbought and Exit Oversold alerts signal when price begins reverting from extremes, offering confirmation that mean reversion has initiated. Zero Cross Up and Zero Cross Down alerts identify transitions through the neutral line, indicating shifts between above-mean and below-mean price action that can signal trend changes. The Extreme Zone Entry alert fires on any extreme threshold penetration regardless of direction, allowing unified monitoring of both overbought and oversold opportunities.
▶ Color Customization:
Six visual themes (Classic, Aqua, Cosmic, Ember, Neon, plus Custom) accommodate different chart backgrounds and aesthetic preferences, ensuring optimal contrast and readability across trading platforms. The bar transparency control (0-90%) allows fine-tuning of visual prominence, with minimal transparency creating bold, attention-grabbing bars for primary analysis, while higher transparency values produce subtle background context when using the oscillator alongside other indicators. The extreme and moderate zone coloring system uses automatic opacity variation to create instant visual hierarchy, with darkest colors highlight the most statistically significant deviations demanding immediate attention, while lighter shades mark developing conditions that warrant monitoring but may not yet justify action. Optional candle coloring extends the Z-Score color scheme directly to the price candles on the main chart, enabling traders to instantly recognize statistical extremes and trend conditions without needing to reference the oscillator panel, creating a unified visual experience where both price action and statistical analysis share the same color language.
Indicator
ZScore SemiConductoresZ-Score of Semiconductor Sector Volume
This custom Pine Script indicator applies a Z-Score calculation to the aggregated trading volume of leading semiconductor companies. The goal is to highlight statistical extremes in sector activity that may signal unusual market behavior.
🔧 How it works
- Fixed ticker list: NVDA, AVGO, TSM, AMD, ASML, MU, ARM, ON, TXN, QCOM, INTC.
- Aggregate volume: The script sums the trading volume of all tickers in the list for the selected timeframe.
- Z-Score calculation:
- Moving average and standard deviation are computed over a configurable window (default = 50 bars).
- Formula:
Z= (Current Volume - Mean) / Standard Deviation
Visualization:
- Z-Score plotted in green.
- Reference lines at 0, ±1σ, ±2σ.
- Labels (triangles) mark critical signals when Z > +2 or Z < -2.
📈 Why it matters
- Detects abnormal surges or drops in sector-wide volume.
- Highlights potential euphoria (+2σ) or panic (-2σ) moments.
- Useful as a filter for trading strategies or as a sector-level alert system.
⚠️ Disclaimer: This script is for educational purposes only and not financial advice
Indicator
Z-EMA Fusion BandsDesigned with crypto markets in mind, particularly Bitcoin , it builds on the concept that the 1-Week 50 EMA often serves as a long-term bull/bear market threshold — an area where institutional bias, momentum shifts, and cyclical rotations tend to occur.
🔹 Core Components & Synergies:
1. 1W 50 EMA (Higher Timeframe)
- This EMA is calculated on a weekly timeframe, regardless of your current chart.
- In crypto, price above the 1W 50 EMA typically aligns with long-term bull market phases, while extended periods below can signify bearish macro structure.
- The slope of the EMA is also analyzed to add directional confidence to trend strength.
2. ±1 Standard Deviation Bands
- Surrounding the 50 EMA, these bands visualize normal price dispersion relative to trend.
- When price consistently hugs or breaks outside these bands, it often reflects market expansion, volatility events, or mean-reversion opportunity.
3. Z-Score Gradient Fill
- The area between the bands is filled using a Z-score-based gradient, which dynamically adjusts color based on how far price is from the EMA (in terms of standard deviations).
- Color shifts from aqua (near EMA) to fuchsia (far from EMA) help you spot price compression, equilibrium, or overextension at a glance.
- The fill also uses transparency scaling, making it fade as price stretches further, emphasizing the core structure.
4. Directional EMA Coloring
- The EMA line itself is colored based on:
- The slope of the EMA (rising/falling)
- Whether the HTF candle is bullish or bearish
- This provides intuitive color-coded confirmation of momentum alignment or potential exhaustion.
5. Price/EMA Divergence Detection
- The script detects bullish and bearish divergence between price and the EMA (rather than using a traditional oscillator).
- Bullish Divergence: Price makes a lower low, EMA makes a higher low.
- Bearish Divergence: Price makes a higher high, EMA makes a lower high.
- These signals often mark transitional zones where momentum fades before a trend reversal or correction.
📊 Suggested Uses:
🔸 Swing and Position Trading:
- Use the 1W 50 EMA as a macro-trend anchor.
- Stay long-biased when price is above with positive slope, and short-biased when below.
- Consider entries near band edges for mean-reversion plays, especially if confluence forms with divergence signals.
🔸 Volatility-Based Filtering:
- Use the Z-score fill to identify volatility compression (near EMA) or expansion (edge of bands).
- Combine this with breakout strategies or dynamic position sizing.
🔸 Divergence Confirmation:
- Combine divergence markers with HTF EMA slope for high-probability setups.
- Bullish div + EMA flattening/rising can signal the start of accumulation after a macro dip.
🔸 Multi-Timeframe Analysis:
- Works well as a structural overlay on intraday charts (1H, 4H, 1D).
- Use this indicator to track long-term bias while executing lower timeframe trades.
⚠️ Disclaimer:
This indicator is designed for educational and informational purposes only. It does not constitute financial advice or a recommendation to buy or sell any asset.
Always use proper risk management, and combine with your own analysis, tools, and strategy. Performance in past market conditions does not guarantee future results. Indicator
Indicator
Uptrick: Dynamic Z-Score DivergenceIntroduction
Uptrick: Dynamic Z-Score Divergence is an oscillator that combines multiple momentum sources within a Z-Score framework, allowing for the detection of statistically significant mean-reversion setups, directional shifts, and divergence signals. It integrates a multi-source normalized oscillator, a slope-based signal engine, structured divergence logic, a slope-adaptive EMA with dynamic bands, and a modular bar coloring system. This script is designed to help traders identify statistically stretched conditions, evolving trend dynamics, and classical divergence behavior using a unified statistical approach.
Overview
At its core, this script calculates the Z-Score of three momentum sources—RSI, Stochastic RSI, and MACD—using a user-defined lookback period. These are averaged and smoothed to form the main oscillator line. This normalized oscillator reflects how far short-term momentum deviates from its mean, highlighting statistically extreme areas.
Signals are triggered when the oscillator reverses slope within defined inner zones, indicating a shift in direction while the signal remains in a statistically stretched state. These mean-reversion flips (referred to as TP signals) help identify turning points when price momentum begins to revert from extended zones.
In addition, the script includes a divergence detection engine that compares oscillator pivot points with price pivot points. It confirms regular bullish and bearish divergence by validating spacing between pivots and visualizes both the oscillator-side and chart-side divergences clearly.
A dynamic trend overlay system is included using a Slope Adaptive EMA (SA-EMA). This trend line becomes more responsive when Z-Score deviation increases, allowing the trend line to adapt to market conditions. It is paired with ATR-based bands that are slope-sensitive and selectively visible—offering context for dynamic support and resistance.
The script includes configurable bar coloring logic, allowing users to color candles based on oscillator slope, last confirmed divergence, or the most recent signal of any type. A full alert system is also built-in for key signals.
Originality
The script is based on the well-known concept of Z-Score valuation, which is a standard statistical method for identifying how far a signal deviates from its mean. This foundation—normalizing momentum values such as RSI or MACD to measure relative strength or weakness—is not unique to this script and is widely used in quantitative analysis.
What makes this implementation original is how it expands the Z-Score foundation into a fully featured, signal-producing system. First, it introduces a multi-source composite oscillator by combining three momentum inputs—RSI, Stochastic RSI, and MACD—into a unified Z-Score stream. Second, it builds on that stream with a directional slope logic that identifies turning points inside statistical zones.
The most distinctive additions are the layered features placed on top of this normalized oscillator:
A structured divergence detection engine that compares oscillator pivots with price pivots to validate regular bullish and bearish divergence using precise spacing and timing filters.
A fully integrated slope-adaptive EMA overlay, where the smoothing dynamically adjusts based on real-time Z-Score movement of RSI, allowing the trend line to become more reactive during high-momentum environments and slower during consolidation.
ATR-based dynamic bands that adapt to slope direction and offer real-time visual zones for support and resistance within trend structures.
These features are not typically found in standard Z-Score indicators and collectively provide a unique approach that bridges statistical normalization, structure detection, and adaptive trend modeling within one script.
Features
Z-Score-based oscillator combining RSI, StochRSI, and MACD
Configurable smoothing for stable composite signal output
Buy/Sell TP signals based on slope flips in defined zones
Background highlighting for extreme outer bands
Inner and outer zones with fill logic for statistical context
Pivot-based divergence detection (regular bullish/bearish)
Divergence markers on oscillator and price chart
Slope-Adaptive EMA (SA-EMA) with real-time adaptivity based on RSI Z-Score
ATR-based upper and lower bands around the SA-EMA, visibility tied to slope direction
Configurable bar coloring (oscillator slope, divergence, or most recent signal)
Alerts for TP signals and confirmed divergences
Optional fixed Y-axis scaling for consistent oscillator view
The full setup mode can be seen below:
Input Parameters
General Settings
Full Setup: Enables rendering of the full visual system (lines, bands, signals)
Z-Score Lookback: Lookback period for normalization (mean and standard deviation)
Main Line Smoothing: EMA length applied to the averaged Z-Score
Slope Detection Index: Used to calculate directional flips for signal logic
Enable Background Highlighting: Enables visual region coloring in
overbought/oversold areas
Force Visible Y-Axis Scale: Forces max/min bounds for a consistent oscillator range
Divergence Settings
Enable Divergence Detection: Toggles divergence logic
Pivot Lookback Left / Right: Defines the structure of oscillator pivot points
Minimum / Maximum Bars Between Pivots: Controls the allowed spacing range for divergence validation
Bar Coloring Settings
Bar Coloring Mode:
➜ Line Color: Colors bars based on oscillator slope
➜ Latest Confirmed Signal: Colors bars based on the most recent confirmed divergence
➜ Any Latest Signal: Colors based on the most recent signal (TP or divergence)
SA-EMA Settings
RSI Length: RSI period used to determine adaptivity
Z-Score Length: Lookback for normalizing RSI in adaptive logic
Base EMA Length: Base length for smoothing before adaptivity
Adaptivity Intensity: Scales the smoothing responsiveness based on RSI deviation
Slope Index: Determines slope direction for coloring and band logic
Band ATR Length / Band Multiplier: Controls the width and responsiveness of the trend-following bands
Alerts
The script includes the following alert conditions:
Buy Signal (TP reversal detected in oversold zone)
Sell Signal (TP reversal detected in overbought zone)
Confirmed Bullish Divergence (oscillator HL, price LL)
Confirmed Bearish Divergence (oscillator LH, price HH)
These alerts allow integration into automation systems or signal monitoring setups.
Summary
Uptrick: Dynamic Z-Score Divergence is a statistically grounded trading indicator that merges normalized multi-momentum analysis with real-time slope logic, divergence detection, and adaptive trend overlays. It helps traders identify mean-reversion conditions, divergence structures, and evolving trend zones using a modular system of statistical and structural tools. Its alert system, layered visuals, and flexible input design make it suitable for discretionary traders seeking to combine quantitative momentum logic with structural pattern recognition.
Disclaimer
This script is for educational and informational purposes only. No indicator can guarantee future performance, and trading involves risk. Always use risk management and test strategies in a simulated environment before deploying with live capital.
Indicator
Market Extreme Zones IndexThe Market Extreme Zones Index is a new mean reversion (valuation) tool focused on catching long term oversold/overbought zones. Combining an enhanced RSI with a smoothed Z-score this indicator allows traders to find oppurtunities during highly oversold/overbought zones.
I will separate the explanation into the following parts:
1. How does it work?
2. Methodologies & Concepts
3. Use cases
How does it work?
The indicator attempts to catch highly unprobable events in either direction to capture reversal points over the long term. This is done by calculating the Z-Score of an enhanced RSI.
First we need to calculate the Enhanced RSI:
For this we need to calculate 2 additional lengths:
Length1 = user defined length
Length2 = Length1/2
Length3 = √Length
Now we need to calculate 3 different RSIs:
1st RSI => uses classic user defined source and classic user defined length.
2nd RSI => uses classic user defined source and Length 2.
3rd RSI => uses RSI 2 as source and Length 2
Now calculate the divergence:
RSI_base => 2nd RSI * 3 - 1st RSI - 3rd RSI
After this we need to calculate the median of the RSI_base over √Length and make a divergence of these 2:
RSI => RSI_base*2 - median
All that remains now is the Z-score calculations:
We need:
Average RSI value
Standard Deviation = a measure of how dispersed or spread out a set of data values are from their average
Z-score = (Current Value - Average Value) / Standard Deviation
After this we just smooth the Z-score with a Weighted Moving average with √Length
Methodology & Concepts
Mean Reversion Methodology:
The methodology behind mean reversion is the theory that asset prices will eventually return to their long-term average after deviating significantly, driven by the belief that extreme moves are temporary.
Z-Score Methodology:
A Z-score, or standard score, is a statistical measure that indicates how many standard deviations a data point is from the mean of a dataset. A positive z-score means the value is above the mean, a negative score means it's below, and a score of zero means the value is equal to the mean.
You might already be able to see where I am going with this:
Z-Score could be used for the extreme moves to capture reversal points.
By applying it to the RSI rather than the Price, we get a more accurate measurement that allow us to get a banger indicator.
Use Cases
Capturing reversal points
Trend Direction
- while the main use it for mean reversion, the values can indicate whether we are in an uptrend or a downtrend.
Advantages:
Visualization:
The indicator has many plots to ensure users can easily see what the indicator signals, such as highlighting extreme conditions with background colors.
Versatility:
This indicator works across multiple assets, including the S&P500 and more, so it is not only for crypto.
Final note:
No indicator alone is perfect.
Backtests are not indicative of future performance.
Hope you enjoy Gs!
Good luck! Indicator
Uptrick: Volume Weighted BandsIntroduction
This indicator, Uptrick: Volume Weighted Bands, overlays dynamic, volume-informed trend channels directly on the chart. By fusing price and volume data through volume-weighted and exponential moving averages, the script forms a core trend line with adaptive bandwidth controlled by volatility. It is designed to help traders identify trend direction, breakout entries, and extended conditions that may warrant take-profits or pullback re-entries.
Overview
The Volume Weighted Bands system is built around a trend line calculated by averaging a Volume Weighted Moving Average (VWMA) and an Exponential Moving Average (EMA), both over a configurable lookback period. This hybrid trend baseline is then smoothed further and expanded into dynamic upper and lower bands using an Average True Range (ATR) multiplier. These bands adapt with market volatility and shift color based on prevailing price action, helping traders quickly identify bullish, bearish, or neutral conditions.
Originality and Unique Features
This script introduces originality by blending both price and volume in the core trend calculation, a technique that is more responsive than traditional moving average bands. Its multi-mode visualization (cloud, single-band, or line-only), combined with selective buy/sell signals, makes it flexible for discretionary and algorithmic strategies alike. Optional modules for take-profit signals based on z-score deviation and RSI slope, as well as buy-back detection logic with cooldown filters, offer practical tools for managing trades beyond simple entries.
Explanation of Inputs
Every user input in this script is included to give the trader control over behavior and visual presentation:
Trend Length (len): Defines the lookback window for both the VWMA and EMA, controlling the sensitivity of the core trend baseline. A lower value makes the bands more reactive, while a higher value smooths out short-term noise.
Extra Smoothing (smoothLen): Applies an additional EMA to the blended VWMA/EMA average. This second-level smoothing ensures the central trend line reacts gradually to shifts in price.
Band Width (ATR Multiplier) (bandMult): Multiplies the ATR to create the width of the upper and lower bands around the trend line. Larger values widen the bands, capturing more volatility, while smaller values narrow them.
ATR Length (atrLen): Sets the length of the ATR used in calculating band width and signal offsets. Longer values produce smoother band boundaries.
Show Buy/Sell Signals (showSignals): Toggles the primary crossover/crossunder entry signals, which are labeled when the close crosses the upper or lower band.
Visual Mode (visualMode): Allows selection between three display modes:
--> Cloud: Shows both bands and the central trend line with a shaded background.
--> Single Band: Displays only the active (upper or lower) band depending on trend state, with gradient fill to price.
--> Line Only: Shows only the trend line for a minimal visual profile.
Take Profit Signals (enableTP): Enables a z-score-based profit-taking signal system. Signals occur when price deviates significantly from the trend line and RSI confirms exhaustion.
TP Z-Score Threshold (tpThreshold): Sets the z-score deviation required to trigger a take-profit signal. Higher values reduce the frequency of signals, focusing on more extreme moves.
Re-Entries (enableBuyBack): Enables logic to signal when price reverts into the band after an initial breakout, suggesting a possible re-entry or pullback setup.
Buy Back Cooldown (bars) (buyBackCooldown): Defines a minimum bar count before a new buy-back signal is allowed, preventing rapid retriggering in choppy conditions.
Buy Offset and Sell Offset: Hidden inputs used to vertically adjust the placement of the Buy ("𝓤𝓹") and Sell ("𝓓𝓸𝔀𝓷") labels relative to the bands. These use ATR units to maintain proportionality across different instruments and timeframes.
Take-Profit Signal Module
The take-profit module uses a z-score of the distance between price and the trend line to detect extended conditions. In bullish trends, a signal appears when price is well above the band and RSI indicates exhaustion; the opposite applies for bearish conditions. A boolean flag is used to prevent retriggering until RSI resets. These signals are plotted with minimalist “X” markers near recent highs or lows, based on whether the market is extended upward or downward.
Re-Entry Logic
The re-entry system identifies instances where price momentarily dips or spikes into the opposite band but closes back inside, implying a continuation of the prevailing trend. This module can be particularly useful for traders managing entries after brief pullbacks. A built-in cooldown period helps filter out noise and prevents signal overloading during fast markets. Visual markers are shown as upward or downward arrows near the relevant candle wicks.
How to Use This Indicator
The basic usage of this indicator follows a directional, signal-driven approach. When a buy signal appears, it suggests entering a long position. The recommended stop loss placement is below the lower band, allowing for some breathing space to accommodate natural volatility. As the position progresses, take partial profits—typically 10% to 15% of the position—each time a take-profit signal (marked with an "X") is shown on the chart.
An optional feature is the buy-back signal, which can be used to re-enter after partial exits or missed entries. Utilizing this can help reduce losses during false breakouts or trend reversals by scaling in more gradually. However, it also means that in strong, clean trends, the full position may not be captured from the start, potentially reducing the total return. It is up to the trader to decide whether to enter fully on the initial signal or incrementally using buy-backs.
When a sell signal appears, the strategy advises fully exiting any long positions and immediately switching to a short position. The short trade follows the same logic: place your stop loss above the upper band with some margin, and again, take partial profits at each take-profit signal.
Visual Presentation and Signal Labels
All signals are plotted with clean, minimal labels that avoid clutter, and are color-coded using a custom palette designed to remain clear across light and dark chart themes. Bullish trends are marked in teal and bearish trends in magenta. Candles and wicks are also colored accordingly to align price action with the detected trend state. Buy and sell entries are marked with "𝓤𝓹" and "𝓓𝓸𝔀𝓷" labels.
Summary
In summary, the Uptrick: Volume Weighted Bands indicator provides a versatile, visually adaptive trend and volatility tool that can serve multiple styles of trading. Through its integration of price, volume, and volatility, along with modular take-profit and buy-back signaling, it aims to provide actionable structure across a range of market conditions.
Disclaimer
This indicator is for educational purposes only. Trading involves risk, and past performance does not guarantee future results. Always test strategies before applying them in live markets.
Indicator
