Indicator
Indicator
Volume Liquidity Trend [ChartPrime]Volume Liquidity Trend
🔶 OVERVIEW
Standard trend indicators track price direction but completely ignore the volume profile structural footprints left behind during the trend's development. The Volume Liquidity Trend indicator solves this by combining advanced mathematical smoothing with a dynamic, trend-isolated Volume Node Mapping Engine .
This script filters price streams through a stabilization algorithm to establish a core trend, tracks the exact duration of that trend lifecycle, and continuously projects significant historical volume anchors into the future as active liquidity levels until price completely invalidates or "mitigates" them.
🔶 HOW IT WORKS
The indicator executes its calculations through a multi-tiered pipeline:
Kalman-Based Trend Filter: The indicator filters a user-defined price source using an adaptive stabilization equation. It calculates volatility bands relative to this smoothed average (using a 2 x ATR boundary). A close above the upper band establishes a Bullish Trend , while a close below the lower band triggers a Bearish Trend .
Trend-Isolated Volume Mapping: When a trend changes, a clean data sweep resets the history array. The script tracks every single candle inside the active trend and identifies the absolute highest transaction point (the 100% Peak Volume Anchor).
Normalized Liquidity Vectors: Every candle within the trend has its volume calculated relative to that peak volume anchor (0% to 100%). If a historical level passes your volume cutoff threshold, the script maps a horizontal liquidity line from that candle's average price (HLC3) out into the future margin space.
Automated Mitigation Tracking: The script continuously tests these horizontal volume tracks against historical price action. If subsequent candle bodies cross through an established volume line, that line is marked as "mitigated" (crossed) and automatically stripped from the screen to keep your chart uncluttered.
🔶 KEY FEATURES
Adaptive Vector Widths & Gradients: Unmitigated volume lines feature a dynamic visual profile. Lines are automatically thicker and more heavily saturated based on their relative volume strength. Furthermore, lines dynamically shift color depending on whether price is trading above (Bullish Support) or below (Bearish Resistance) the volume node.
Anomalous 100% Peak Tracker: Includes a specialized alert line that forces the historical 100% transaction anchor to remain visible as a bright dashed line only after price has broken through it, signaling a breached institutional base.
Real-Time Trend Analytics Panel: A sleek UI dashboard positioned at the top right tracking:
• Current Trend Status: Active market direction matching the volatility bands.
• Trend Duration: Exact bar runtime age since the initial structural breakout.
• 100% Vol Level: The exact price coordinate where the heaviest volume anomaly occurred during the current sequence.
🔶 TRADING APPLICATIONS
High-Volume Pullback Entries: During a strong trend, look for pullback entries directly into unmitigated lines that have high volume percentages (75% - 95%). These thick vector nodes represent massive resting buy/sell block clusters where institutions are likely to defend their positions.
Breakout Confirmation Diamonds: The trend reversal points are highlighted on your chart with sharp diamond markers. A breakout accompanied by an immediate generation of high-percentage liquidity trails suggests an institutional backed expansion.
Support & Resistance Confluence Trim: When multiple volume lines cluster closely together at a specific price zone, it builds a structural wall of institutional liquidity, marking a prime zone for target take-profits or reversal entries.
🔶 SETTINGS
Stabilization Coefficient: Controls the responsiveness of the underlying filtering mechanism. Lower values yield exceptionally smooth lines that are highly tolerant of short-term volatility spikes.
Volume Cutoff Threshold: The sensitivity slider for plotting liquidity vectors (0.0 to 1.0). A higher setting like 0.50 filters out quiet trading periods and only draws lines for bars with significant volume footprints.
Extend Lines Into Future: Determines the number of bars to project active unmitigated volume tracks into the right-hand margin blank space.
🔶 CONCLUSION
The Volume Liquidity Trend indicator offers an institutional perspective by integrating volume data directly into a trailing trend model. By isolating volume profile nodes specifically to the lifetime of the current trend and introducing adaptive coloring based on price positioning, it ensures your support and resistance targets perfectly match real-time market participant behavior. Indicator
EMA 21/55/100/200EMA 8/21/55/100/200 均线组
一个简洁实用的多周期 EMA 均线系统：将 EMA 8、21、55、100、200 五条指数移动平均线整合到一张图上，帮助快速识别趋势方向、支撑压力位与关键均线突破。适用于股票、指数、外汇、加密货币等品种与任意周期。
与其他均线指标的不同之处
1. EMA 8 智能显隐：默认隐藏；手动开启后，仅在非加密货币市场显示，在加密货币市场中自动隐藏，避免短线均线干扰。
2. 显示长度控制：默认只绘制最近 25 根 K 线内的均线，一键切换全部长度，图表更清爽。
3. 末端数值标签：最后一根 K 线自动标注各均线当前数值，EMA 8 和 EMA 21 额外显示与现价的偏离百分比，方便快速判断乖离。
4. 五档独立警报：价格分别触及 EMA 8、21、55、100、200 时触发提醒。
设置说明
1. 周期：自定义五条均线的周期。
2. 显示长度：是否显示全部长度、最近显示 K 线根数。
3. EMA 开关：各均线的显示开关（EMA 8 智能显隐）。
4. 标签：字号、缩写、差值百分比、标签颜色。
5. 线条颜色与粗细在"样式"页调整。
使用建议
1. 趋势跟随：价格站上 EMA 21/55 且均线多头排列时顺势看多；跌破关键均线时注意风险。
2. 乖离预警：EMA 8 或 EMA 21 偏离现价过大（如超过 1%）时，警惕短线回撤。
3. 支撑压力：EMA 55、100、200 常作为中期与长期支撑压力参考。
风险提示
本指标仅用于技术分析参考，不构成任何投资建议。市场有风险，交易需谨慎。
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EMA 8/21/55/100/200 Moving Average Group
A clean and practical multi-timeframe EMA system that combines five exponential moving averages (8, 21, 55, 100, 200) on one chart, helping you quickly identify trend direction, support/resistance levels, and key moving-average breakouts. Works across stocks, indices, forex, crypto, and any timeframe.
What makes it different
1. Smart EMA 8: hidden by default; when enabled, it only appears on non-crypto markets and auto-hides on crypto charts to reduce noise.
2. Display length control: by default, MAs are drawn only over the most recent 25 bars; one click switches to full length for a cleaner chart.
3. Last-bar value labels: the latest bar shows each MA's current value, with EMA 8 and EMA 21 also showing the % distance from price for quick overextension checks.
4. Five independent alerts: get notified when price touches EMA 8, 21, 55, 100, or 200.
Settings
1. Periods: customize each EMA period.
2. Display length: show full length or limit to recent bars.
3. EMA switches: show/hide each EMA (EMA 8 smart show/hide).
4. Labels: size, abbreviation, % difference and label colors.
5. Line colors and widths are adjusted in the Style tab.
Usage tips
1. Trend following: price above EMA 21/55 with bullish MA alignment suggests an uptrend; watch risk below key MAs.
2. Overextension warning: if EMA 8 or EMA 21 deviates too far from price (e.g. more than 1%), be alert to short-term pullbacks.
3. Support and resistance: EMA 55, 100, and 200 often act as medium- and long-term support/resistance references.
Disclaimer
This indicator is for technical analysis reference only and does not constitute investment advice. Trade at your own risk. Indicator
Trend Integrity Oscillator [MQLSoftware]Trend Integrity Oscillator answers one question in a measurable way: is the current pullback a pause inside an intact trend, or the start of a reversal? Instead of pairing two generic oscillators and eyeballing their relationship, it separates the two things that actually diverge in a pullback — trend efficiency and structural integrity — and then measures the outcome of that divergence on the chart's own history.
This is a visual analytical tool for chart study. It does not execute trades and does not provide financial advice.
Key Features
Outcome signals on the price chart: when a pullback resumes, the ▲/▼ marker prints this chart's measured resume rate for that direction; when the structure is closed through, ✕ BREAK prints at the violated anchor
Pullback Survival Zone on the price chart: while a pullback is armed, the pullback territory is shaded and the survival line marks the P75 depth of all pullbacks on this chart that eventually resumed — between that line and the anchor is territory most survivors never visited
Anchor line — the structural pivot whose confirmed close-through turns a pullback into a reversal (frozen at arm time for the live episode)
Trend Efficiency line 0–100 — multiscale signed efficiency computed on three horizons (chart window plus two senior windows equal in wall-clock time to auto-selected higher timeframes), weighted toward the seniors
Structure Integrity area 0–100 — a composite of three confirmed-pivot facts: anchor hold, pivot-chain consistency, and retracement depth ranked against this chart's own resumed pullbacks
Pullback state machine — aligned → pullback armed → resumed / broken, confirmed bars only
Measured base rates in the panel: how often armed pullbacks actually resumed on this chart, per direction, with sample sizes; live pullback depth percentile
Phase lane, pane event marks, optional armed bar-paint and pane tint, five alerts + one dynamic alert
Core Concept — what is original here
1. Multiscale signed efficiency. sER(n) = (close − close ) / path(n): a Kaufman-style efficiency ratio kept with its sign. +1 means the last n bars traveled their entire path upward, −1 downward, ~0 churn. Three horizons are blended 0.5/0.3/0.2 with the seniors heaviest, and everything is computed straight on chart bars — the script contains zero request.security calls, so the higher-timeframe re-resolution bug class is structurally impossible.
2. Structure Integrity 0–100. Not a second oscillator but a composite of three confirmed-pivot facts: (a) anchor hold — how firmly price holds the structural anchor pivot, ATR-scaled; (b) pivot-chain consistency — the share of recent pivot steps that agree with the structural direction; (c) retracement depth — the live pullback ranked as a percentile against the depths of pullbacks on this chart that eventually resumed. Self-calibrating; no fixed depth settings.
3. The pullback state machine. ARMED = trend efficiency flips against the trend while the structure holds. RESUMED = efficiency recovers, or price prints a confirmed close beyond the pre-pullback extreme. BROKEN = a confirmed close beyond the anchor pivot as it stood when the pullback started — a reversal, not a pullback. A structural direction flip during an armed episode counts as a failed pullback; nothing is silently dropped.
4. Measured base rates. The panel reports observed frequencies with sample sizes — measured per chart, per direction, not asserted. Below 10 completed episodes the panel says "collecting" instead of quoting noise.
Anatomy of the Display
On the price chart (the overlay layer):
Survival Zone while a pullback is armed: neutral slate = ordinary pullback territory, amber band = deeper than 75% of this chart's resumed pullbacks, dotted amber = the survival line, solid line = the frozen anchor
▲/▼ resume markers with the measured per-direction resume rate printed on them (tooltip: bars in pullback, max depth, base rate with n)
✕ BREAK marker at the anchor price on the confirmed close-through
Optional amber bar tint while armed (off by default)
In the oscillator pane:
Trend Efficiency line — teal above the bull threshold, ember below the bear threshold; brighter when |efficiency| is high; soft glow
Structure Integrity — quiet slate area (3-bar display smoothing; the engine reads the raw series); turns amber while a pullback is armed
Midline 50 and dotted 60/40 guides — the guides sit exactly on the direction-flip hysteresis thresholds
Phase lane (top strip): trend color = aligned, amber = pullback armed, grey = no established state
Pane event marks: • pullback armed, ▲/▼ trend resumed, ✕ structure broken; optional pane tint while armed
Panel: Trend, Structure (tooltip shows the three components), State, base rates per direction, live pullback depth percentile
Notes on Repainting
All state transitions, signal markers, base-rate counters and alerts fire on confirmed bars only and never move once printed
The oscillator lines, the live zone's right edge, the anchor line and the panel's live rows update intrabar — visual context, not signals
The survival line and the episode anchor are frozen at arm time — they do not follow price during the episode
Pivots confirm with the standard pivot lag (Pivot Length bars each side) and never move once confirmed
No request.security anywhere in the script
Typical Analysis Workflow
Read the State row: ALIGNED means efficiency and structure agree; NO ALIGNMENT means stand aside or dig deeper
When PULLBACK ARMED appears, check the live depth percentile — a pullback deeper than most that ever resumed deserves more suspicion
Use the base rates as context: a market where pullbacks resume 50% of the time is a coin flip and the panel will say so honestly
Treat ✕ structure broken as the line between "pullback" and "reversal" — the anchor pivot was closed through
Configuration
Response: Fast / Balanced / Strict — measured smoothing presets, not guesses
Auto Senior Horizons on by default; two manual timeframe inputs when disabled
Pivot Length, Min Integrity to Arm
Chart Overlay group: signals on price, survival zone, completed episodes to keep, anchor line mode (During pullbacks / Always / Off), bar paint, pane tint
All identity colors are inputs (dark-theme defaults; pick deeper tones on light charts)
Markets and Timeframes
Any symbol and timeframe. The engine is percentile- and ATR-based, so it self-calibrates per instrument. On low-history charts the panel reports "collecting" until the sample is real.
Alerts
Pullback armed · Trend resumed · Structure broken · Alignment started · Deep pullback (live depth crossed P75 of resumed history, once per episode) · plus one dynamic alert() with direction and integrity context. Indicator
EMA/SMA Classics V1.0 by SRTEMA/SMA Classics V1.0 by SRT
The EMA/SMA Classics indicator was designed to answer one simple question:
"Which side of the market currently has the structural advantage?"
Instead of flooding the chart with buy and sell arrows, this indicator focuses on market structure, trend alignment, and high-quality price action, allowing traders to make their own execution decisions with greater confidence.
Whether you trade Forex, Indices, Commodities or Crypto, this indicator combines multiple market concepts into a clean workflow while remaining highly configurable through both EMA and SMA combinations.
What This Indicator Includes
• Flexible EMA / SMA Engine
Unlike traditional moving average indicators that are locked to one MA type, every moving average in this indicator can independently be configured as either:
EMA
SMA
Default settings:
MA 1 : 7
MA 2 : 40
MA 3 : 150
MA 4 : 200
You may use the default configuration or customise the periods to fit your own trading methodology.
• Dynamic Moving Average Stack Detection
The indicator continuously evaluates whether the visible moving averages are properly stacked.
Bullish Stack
Fast MA > Medium MA > Slow MA
Bearish Stack
Fast MA < Medium MA < Slow MA
When the moving averages lose their proper order, the market is treated as neutral instead of forcing a directional bias.
This helps reduce many false trend signals that occur during consolidations.
• ATR-Based MA Spacing Filter
One common problem with MA strategies is entering when all moving averages have already compressed together.
This indicator measures the spacing between moving averages using ATR.
When the moving averages become too compressed, trend quality deteriorates.
The spacing filter helps identify these lower-quality environments before momentum fully develops.
• Ladder Structure
One of the core concepts inside this indicator is the Ladder System.
Instead of only observing moving averages, the indicator also evaluates the market using multiple dynamic support and resistance structures.
Resistance
R9
R40
R70
R100
R150
Support
S9
S40
S70
S100
S150
These levels automatically update with market structure and are used to generate an additional Ladder Bias.
When both the moving averages and Ladder Bias agree, market structure is generally stronger than relying on moving averages alone.
• Flush Dot System
The indicator displays visual Flush Dots beneath or above candles whenever trend alignment exists.
Small Green Dot
Bullish MA alignment.
Small Red Dot
Bearish MA alignment.
Large Green Dot
Moving Average alignment + Bullish Ladder confirmation.
Large Red Dot
Moving Average alignment + Bearish Ladder confirmation.
The larger dots represent stronger structural agreement across multiple components.
• KeyBar Detection
The indicator automatically identifies two important price action patterns.
Engulfing Bars
Bullish Engulfing (EBull)
Bearish Engulfing (EBear)
These are filtered using ATR and minimum body size to avoid insignificant candles.
Long Tail Bars (LTB)
Bullish Long Tail Bars
Bearish Long Tail Bars
These identify strong rejection candles with defined tail proportions and body positioning.
An optional body-size filter is also available for traders wanting stricter candle selection.
Daily Pivot (DP)
Automatically plots the previous day's pivot.
Useful as:
Dynamic support
Dynamic resistance
Intraday reaction level
Weekly Pivot (WP)
Automatically plots the previous week's pivot.
Many swing traders use weekly pivots as major reaction zones throughout the trading week.
RSI Momentum Alerts
The indicator includes two independent RSI event types.
RSI Breakout
Signals when RSI breaks into extreme momentum territory.
Bullish breakout
Bearish breakout
RSI Retracement
Designed to identify momentum continuation after RSI exits an extreme condition while confirming with the RSI Moving Average.
These alerts can be useful for traders looking to participate after momentum has begun to recover instead of chasing extremes.
Information Panel
A compact table summarises the current market condition.
Displays:
Moving Average Bias
Ladder Bias
Long Tail Bar presence
This provides a quick snapshot without needing to inspect every component individually.
How To Use This Indicator
This indicator is not designed to generate automatic Buy or Sell signals.
Instead, it acts as a Market Context Indicator.
A typical workflow may look like this:
Step 1
Observe whether the moving averages are properly stacked.
A clean stack generally indicates directional order.
Step 2
Check whether the Ladder Bias agrees with the moving averages.
When both align, the market structure is generally stronger.
Step 3
Watch for KeyBars.
Examples include:
Bullish Engulfing
Bearish Engulfing
Bullish Long Tail Bar
Bearish Long Tail Bar
These often represent meaningful reactions within the prevailing structure.
Step 4
Use Daily Pivot and Weekly Pivot as areas where price may react.
These levels should be considered areas of interest rather than guaranteed reversal zones.
Step 5
Monitor RSI alerts for momentum shifts.
Momentum signals are generally more useful when they occur in the same direction as the prevailing market structure.
Suitable Timeframes
Although the indicator can be applied to multiple chart intervals, it generally performs best on:
M15
M30
H1
H4
Daily
The moving averages, Ladder System, and KeyBar detection adapt naturally across different timeframes.
Difference Between EMA/SMA Classics & H1 EMA/SMA + Higher Timeframe Analysis (Classic)
Although both indicators belong to the same ecosystem, they serve different purposes.
EMA/SMA Classics
Designed as a general-purpose structural trend indicator.
Features include:
Flexible EMA/SMA stacking
Ladder System
Flush Dots
Engulfing Bars
Long Tail Bars
Daily Pivot
Weekly Pivot
RSI Alerts
It can be used on virtually any timeframe and is ideal for traders who prefer to analyse the chart directly.
H1 EMA/SMA + Higher Timeframe Analysis (Classic)
The H1 version is a significantly more advanced market context engine.
In addition to everything above, it introduces:
Dedicated H1 Bias Engine
H4 Trend Analysis
Daily Trend Analysis
Higher Timeframe Bias Aggregation
H1TF Composite Bias
Overall Market Verdict Engine
Multi-layer Bias Table
Higher Timeframe Confirmation Workflow
Rather than focusing solely on the current chart, the H1 version continuously evaluates whether multiple timeframes are aligned before presenting an overall market verdict.
If the EMA/SMA Classics indicator answers:
"What is my current chart doing?"
Then the H1 version answers:
"What is the broader market structure telling me across multiple timeframes?"
The two indicators are complementary and can be used together depending on your preferred trading workflow.
Disclaimer
This indicator is designed to assist with market structure analysis and decision-making. It does not provide financial advice or guarantee profitable trades. Always combine indicator signals with sound risk management, personal analysis, and appropriate position sizing. Indicator
Multi-Timeframe Trend & Consolidation Table### Overview
The **Multi-Timeframe Trend & Consolidation Table** is a lightweight dashboard indicator designed to give traders a quick, multi-timeframe overview of the market trend and consolidation status directly on their chart.
Instead of switching between multiple timeframes or cluttering your chart with dozens of moving averages, this tool consolidates trend data across 10 different timeframes into a clean, customizable table.
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### Key Features
* **Multi-Timeframe Analysis:** Monitors **1m, 3m, 5m, 10m, 15m, 1h, 4h, 1D, 1W, and 1M** timeframes simultaneously.
* **Customizable EMA Periods:** Set unique Exponential Moving Average (EMA) lengths for every individual timeframe (e.g., EMA 10 for 1m, EMA 50 for 1h, EMA 200 for 1D).
* **Consolidation Detection:** Built-in threshold logic identifies when price is hovering extremely close to the EMA line, signaling potential range-bound/chop market conditions.
* **Dynamic Table UI:** Displays the specific EMA length assigned to each timeframe directly inside the table for clear tracking. Fully customizable position (Top Right, Bottom Left, etc.) and text sizes.
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### How It Works
The indicator compares the price of each timeframe against its assigned EMA line:
1. **BULLISH 🟢:** Current close price is above the timeframe's EMA (outside the consolidation zone).
2. **BEARISH 🔴:** Current close price is below the timeframe's EMA (outside the consolidation zone).
3. **RANGE 🟡:** Price percentage difference from the EMA is smaller than the set threshold (e.g., within 0.15%), indicating market consolidation or flat movement.
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### How to Use
1. **Trend Alignment:** Look for timeframes aligning in the same direction (e.g., 1h, 4h, and 1D all green) to trade with the macro trend.
2. **Avoiding Chop:** When lower timeframes show `RANGE 🟡`, it indicates low volatility or moving average compression, warning you to avoid breakout trades or wait for confirmation.
3. **Execution Timeframes:** Tune lower timeframes (1m, 3m, 5m) to fast EMAs for scalp setups, while keeping higher timeframes (1D, 1W) on key levels like the 200 EMA.
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### Settings & Inputs
* **EMA Lengths per Timeframe:** Set custom EMA periods for all 10 available timeframes.
* **Enable Consolidation Detection:** Toggle range detection on or off based on your strategy preference.
* **Consolidation Threshold (%):** Adjust the distance percentage between close price and EMA to define a range zone (default is 0.15%).
* **Table Display:** Adjust table placement on your screen and text font size. Indicator
GEEN Smart Signal What it does
GEEN Smart Signal is not a single-indicator tool. It combines several classic analysis engines into one weighted Decision Engine that scores every trade candidate from 0 to 100, then only prints signals that pass a minimum confidence threshold. Every signal comes with a full breakdown showing exactly why it was accepted.
How it works
A signal candidate is generated by an ATR trailing-stop flip (with optional Heikin Ashi smoothing of the calculation source). The candidate is then evaluated by 8 engines, each contributing a weighted score:
Market Structure (20 pts) — pivot-based HH/HL/LH/LL classification, BOS and CHoCH detection
Trend (20 pts) — EMA 50/100/200 stack, classified into 5 states from strong bullish to strong bearish
Momentum (15 pts) — RSI position + ADX strength, used as confirmation only
Volume (15 pts) — current volume vs. 20-bar average, rewarding volume spikes
Liquidity (10 pts) — liquidity sweeps of prior swings, price inside a Demand/Supply zone or FVG, and Premium/Discount location vs. equilibrium
Volatility (10 pts) — ATR vs. its average, filtering out dead markets
Multi-Timeframe (10 pts) — 1H/4H/D trend alignment (closed-bar data only)
Risk (10 pts) — estimated reward-to-risk toward the nearest opposing swing
The total is normalized to 100. Below the minimum threshold (default 60) the signal is rejected (WAIT). 60–75 prints as weak, 75–85 as good, above 85 as strong. Clicking any signal arrow shows the per-engine score breakdown, entry, ATR stop, and 1R/2R/3R targets.
Chart elements
Structure labels (HH/HL/LH/LL, BOS, CHoCH), auto Order Blocks with mitigation removal, Fair Value Gaps, Equal Highs/Lows (EQH/EQL), session Kill Zones (Asia/London/New York, with an optional session filter), a main panel (decision, confidence, trend, momentum, risk, entry/SL/TP, RR, 5-timeframe view, active session, SMT check vs. a correlated symbol), and a monthly statistics panel that tracks how many signals reached TP1/TP2/TP3 or hit the stop — so you can measure performance yourself on any symbol and timeframe.
Anti-repaint design
Signals are confirmed on bar close only, higher-timeframe data uses closed bars with lookahead off, and structure breaks are evaluated on confirmed closes.
How to use
Works on any symbol and timeframe. Start with defaults, or raise the minimum confidence and enable the London/New York session filter for intraday trading. Alerts are included for buy/sell and for strong (85+) signals. This tool is for educational purposes and is not financial advice; no indicator guarantees results — always use proper risk management. Indicator
Volume Regression Channel [BOSWaves]Volume Regression Channel - Regression-Anchored Volume Flow Visualization with Inward Pressure Bars, Edge Flares, and Cumulative End Profile
Overview
Volume Regression Channel is a regression-anchored volume flow analysis system that fits a polynomial or linear curve to recent price history and maps buy and sell volume pressure inward from the channel boundaries toward the centerline on every bar, where bar height, coloring, edge flare intensity, and end profile distribution are all driven by actual volume participation and close-position-derived directional weighting rather than fixed histogram positions or arbitrary price levels.
Instead of displaying volume as a separate panel histogram detached from price context, this system integrates volume directly into the regression channel structure. Each bar's volume is split into buy and sell components based on where close sat within the bar's range, and those components are rendered as inward-pointing bars anchored to the upper and lower channel edges, with bar height proportional to normalized volume and coloring distinguishing above-average from below-average participation. The result is a channel where the volume activity on every bar is visible in spatial relationship to the channel boundaries that define the structural context.
This creates a complete price and volume framework within a single overlay. The regression curve defines the trend's expected path. The gradient channel fills communicate the statistical distance from the centerline. The inward volume bars reveal participation intensity and directional split at each bar. The flow-colored centerline segments expose directional pressure evolution across the window. Edge flares highlight exceptional volume events occurring near the channel boundaries. Bound diamond markers identify the first bar of each new boundary touch. And the cumulative end profile extending from the current bar provides a full buy-sell volume distribution summary across the channel's price range for the entire regression window.
Price is therefore evaluated not just for its position within the regression channel but for the volume participation and directional flow composition supporting its location at every bar across the full lookback window.
Conceptual Framework
Volume Regression Channel is founded on the principle that a regression channel becomes significantly more analytically powerful when volume participation is integrated directly into its structure rather than displayed separately, allowing the trader to simultaneously assess where price sits relative to the statistical trend expectation and how much and what type of volume supported each bar's position within that channel.
Standard regression channel tools provide structural price context through the curve and its standard deviation bounds but offer no volume intelligence, leaving traders to consult a separate panel to understand participation dynamics. This framework eliminates that separation by embedding volume directly into the channel geometry, with inward bars, edge flares, centerline flow coloring, and the end profile all deriving from the same volume and price data that defines the channel itself.
Three core principles guide the design:
Volume should be displayed in direct spatial relationship to the channel structure it relates to, with inward bars anchored to the boundaries and sized proportionally to participation intensity so that high-volume bars are immediately identifiable within their structural context.
Buy and sell volume should be separated using close position within the bar range, rendering the directional split of each bar's participation as distinct inward segments that reveal whether volume at each price location was predominantly absorbed by buyers or sellers.
A cumulative end profile should summarize the full window's volume distribution at the current channel position, providing a reference for where participation has been most concentrated across the regression window without requiring a separate profile indicator.
This shifts regression channel analysis from structural price context alone into an integrated price-volume framework where participation intensity, directional flow composition, and cumulative distribution are all visible within the channel geometry itself.
Theoretical Foundation
The indicator combines matrix ordinary least squares regression fitting to HL2 price data, standard deviation channel construction, close-position buy-sell volume splitting, volume SMA normalization for significance classification, three-layer gradient polyline fill construction, inward volume bar rendering with dynamic width scaling, flow-weighted centerline segment coloring, edge flare detection combining volume and boundary proximity conditions, and an overlap-weighted cumulative buy-sell profile with smoothing applied across the channel rows.
The regression is computed using the same OLS matrix approach as conventional polynomial regression, producing a prediction array covering all bars in the lookback window for both linear and quadratic modes. The channel width is scaled by the rolling standard deviation of HL2, ensuring channel boundaries adapt to the instrument's actual price variability. Volume splitting uses close position within the high-low range as the proxy for directional commitment, with bars closing near the high allocating more volume to buying and bars closing near the low allocating more to selling. The end profile smooths each row's accumulated buy and sell volume with a three-point weighted average before normalizing and rendering.
Four internal systems operate in tandem:
Regression Channel Engine : Computes OLS curve fitting in linear or polynomial mode, derives the standard deviation channel width, and constructs all polyline geometry for the gradient fills, glow boundary lines, and centerline using chart.point arrays that follow the regression curve.
Inward Volume Bar System : For each bar in the recent display window, normalizes volume against the window maximum, splits the normalized height into buy and sell components by close position, and renders inward lines from the channel edges with dynamic width scaling and above-average volume coloring.
Edge Flare and Bound Marker System : Monitors each recent bar for the combination of above-threshold volume and boundary zone proximity, rendering bright glowing line segments on the channel edge when qualifying conditions are met, and places diamond markers at the first bar of each new boundary touch.
Centerline Flow and End Profile Engine : Divides the centerline into sixty flow segments and computes volume-weighted directional bias for each, coloring segments by flow direction and strength. Simultaneously accumulates overlap-weighted buy and sell volume into channel rows across the full window, smooths the distribution, and renders horizontal profile bars extending from the current bar edge.
This design ensures volume participation is embedded into every layer of the channel visualization while the end profile provides a complete cumulative distribution summary that updates with each new bar.
How It Works
Volume Regression Channel evaluates price through a sequence of regression-aware and volume-integrated processes:
Regression Curve Fitting : On the last bar, the OLS matrix computation produces a prediction array covering all bars in the configured lookback window using either a linear or polynomial fit to HL2, providing the baseline curve that all channel geometry and volume positioning follows.
Channel Width Calculation : The standard deviation of HL2 over the regression window multiplied by the SD multiplier defines the channel half-width, establishing the upper and lower boundary distances from the curve at each bar position.
Gradient Fill Construction : Three polyline polygon regions are constructed for each of the upper and lower channel halves at proportional fractions of the standard deviation width, filled with progressively increasing opacity from inner to outer to produce a smooth visual gradient across the channel depth.
Boundary Glow Rendering : Triple polylines at the upper and lower channel boundaries create a glow effect using wide low-opacity outer lines and a narrow full-opacity core line, providing visually prominent boundary markers that follow the regression curve.
Volume Normalization and Splitting : For each bar in the volume display window, raw volume is normalized against the window maximum to produce a proportional height score. Close position within the high-low range splits this height into buy and sell components, with the buy portion anchored to the lower boundary and the sell portion anchored to the upper boundary pointing inward.
Inward Bar Rendering : Buy and sell component heights are rendered as inward-pointing lines from the respective channel edges with dynamic width scaling based on relative volume and opacity intensifying for above-average participation bars.
Edge Flare Detection : Each recent bar is tested for the combination of volume exceeding the flare multiplier threshold and price high or low reaching within the configured edge zone percentage of the channel boundary. Qualifying bars receive bright dual-layer line segments on the boundary edge with width scaling by relative volume strength.
Bound Diamond Placement : Each bar is tested for initial channel boundary contact, with a diamond marker placed at the first bar of each new upper or lower boundary touch to mark where price newly reached the statistical extremes.
Centerline Flow Coloring : The centerline is divided into sixty equal segments and each segment's volume-weighted close position bias is computed across its constituent bars. Segments are colored green, red, or neutral based on the directional flow value and intensity with line width scaling to strength.
End Profile Construction : All bars in the regression window contribute their volume to the profile rows based on price overlap between the bar range and each row boundary, with the contribution split into buy and sell portions by close position. The accumulated distribution is smoothed and normalized before rendering as horizontal buy and sell bars extending from the current bar.
Together, these elements form a continuously updating integrated price-volume framework where the regression structure, volume participation, flow direction, and cumulative distribution are all rendered within the same channel geometry on each bar update.
Interpretation
Volume Regression Channel should be interpreted as a regression-anchored structural framework with embedded volume participation intelligence at every level:
Regression Curve : The fitted centerline represents the trend's statistical best-fit path through the lookback window, with the flow-colored segments revealing whether volume-weighted directional bias above or below the curve was predominantly bullish or bearish across each portion of the window.
Channel Boundaries : The upper boundary with its red glow represents the upper standard deviation limit where price is statistically extended above the regression expectation. The lower boundary with its green glow represents the lower limit where price is statistically extended below.
Gradient Fill Depth : The three-layer gradient within each channel half provides visual depth cues, with the innermost near-transparent fill representing mild deviation and the outermost fully opaque fill representing maximum channel boundary proximity.
Inward Buy Bars (Green) : Lines extending upward from the lower channel boundary reflect the buy-attributed volume portion of each bar. Taller bars indicate greater buying participation. Brighter coloring indicates above-average total volume on that bar.
Inward Sell Bars (Red) : Lines extending downward from the upper channel boundary reflect the sell-attributed volume portion of each bar. Taller bars indicate greater selling participation. Brighter coloring indicates above-average total volume.
Neutral Volume Bars (Gray) : Below-average volume bars render in neutral gray regardless of direction, identifying periods of low participation where the directional split carries reduced analytical significance.
Edge Flares : Bright glowing line segments on the channel boundary mark bars where significant volume occurred close to the boundary edge, identifying high-participation boundary interaction events that frequently precede reversals or continuations from the statistical extremes.
Bound Diamonds : Small colored diamonds at boundary touch initiation bars mark where price first reached the channel edge after a period of interior activity, identifying the onset of boundary interaction sequences.
End Profile : The horizontal bar chart extending from the right edge shows the cumulative volume distribution across the channel's price range for the full regression window, with green segments showing buy-attributed volume and red segments showing sell-attributed volume at each price row. The longest bars identify the price levels with the greatest total participation concentration.
Colored Candles : Optional candle coloring reflects whether price is above or below the regression centerline, providing a continuous directional bias reference directly on the price chart.
Boundary proximity, inward bar height and direction, edge flare frequency, centerline flow coloring, and end profile distribution collectively provide more analytical depth than any element in isolation.
Signal Logic & Visual Cues
Volume Regression Channel does not generate discrete buy or sell signals but provides continuous structural and volume participation reference through several interaction cues:
Edge Flare Events : High-volume boundary proximity bars highlighted by bright edge flares identify exceptional participation at the statistical extremes, marking the bars most likely to precede structural reactions from channel boundaries.
Bound Diamond Initiation : Diamond markers at the first bar of new boundary touches identify where price has newly entered channel extreme territory, providing early warning of boundary interaction sequences before their outcome is determined.
Centerline flow segment coloring provides ongoing directional pressure context across the full window, with color and width encoding whether the volume-weighted bias at each point in the regression history was bullish, bearish, or neutral.
Strategy Integration
Volume Regression Channel fits within regression-informed structural and volume-participation-based analytical approaches:
Boundary Interaction Trading : Use channel boundary touches combined with edge flare presence as elevated-significance interaction events. High-volume flares at the boundary suggest meaningful participation at the statistical extreme that frequently precedes a reaction back toward the centerline or a volume-supported continuation beyond it.
End Profile Acceptance Reading : Use the end profile distribution to identify the price rows with the greatest cumulative participation concentration. Price returning to high-volume profile rows encounters levels where the greatest historical participation occurred within the regression window, making them structurally significant references for support, resistance, or reversion.
Inward Bar Volume Divergence : Monitor situations where price is approaching a boundary but inward bar height from the opposing direction is increasing, indicating growing participation against the directional move and potentially signaling that the boundary interaction will result in rejection rather than continuation.
Centerline Flow Direction : Use centerline flow coloring as a mid-channel directional bias indicator. Sustained green flow segments suggest dominant buying pressure within the regression window. Sustained red segments suggest dominant selling. Neutral gray segments indicate a contested equilibrium without clear directional participation weight.
Regression Mode Selection : Use Polynomial mode for markets with visible curvature in their trend structure where the quadratic bend produces a more accurate fit. Use Linear mode for markets trending in a straight consistent direction where the polynomial's additional degree of freedom would overfit noise.
Profile Distribution Skew Analysis : Compare the buy and sell distribution balance in the end profile to assess whether the window's participation was predominantly concentrated above or below the centerline, providing a volume-based directional bias reading that complements the price-based trend assessment.
Technical Implementation Details
Regression Engine : Matrix OLS with design matrix construction, normal equation formation, matrix inversion, and prediction array application for linear or polynomial curve fitting to HL2
Channel Construction : Standard deviation-scaled channel width with three-layer gradient polyline fills and triple-line glow boundaries following the regression curve
Inward Volume System : Window-maximum normalization with close-position buy-sell splitting, dynamic width scaling by relative volume, and above-average volume color intensification
Edge Flare System : Volume multiplier threshold combined with boundary zone percentage proximity testing with dual-layer glow line rendering and width scaling by relative volume
Centerline Flow : Sixty-segment volume-weighted close-position bias computation with directional color and width encoding
End Profile : Overlap-weighted row accumulation across the full regression window with three-point smoothing, normalization, and horizontal buy-sell bar rendering with curved outline polyline
Performance Profile : All rendering triggered on last bar with full object cleanup and rebuild each cycle, configurable regression length capped at 490 bars for object management
Optimal Application Parameters
Timeframe Guidance:
1 - 5 min : Intraday regression flow tracking with shorter length and tighter SD multiplier for fast-adapting channel that captures intraday trend structure with responsive volume distribution
15 - 60 min : Session-level structural volume analysis with balanced regression length and moderate SD multiplier for meaningful channel geometry across typical session directional moves
4H - Daily : Swing-level regression channel profiling with longer lookback and polynomial mode for a curve-following channel spanning multi-session trend structures
Suggested Baseline Configuration:
Regression Length : 236
SD Multiplier : 1.75
Mode : Polynomial
Volume SMA : 15
Bar Height (ATR×) : 2.1
Show Edge Flares : Enabled
Show Bound Diamonds : Enabled
Show Centerline : Enabled
Show End Profile : Enabled
Color Candles : Enabled (requires disabling original chart candles in chart settings)
These suggested parameters should be used as a baseline; their effectiveness depends on the instrument's volatility characteristics, volume behavior, and preferred channel sensitivity, so fine-tuning is expected for optimal performance.
Parameter Calibration Notes
Use the following adjustments to refine behavior without altering the core logic:
Channel too wide or narrow : Adjust SD Multiplier to expand or contract the channel width relative to the instrument's typical deviation from the regression curve, calibrating boundary distance to realistic price excursion ranges.
Curve fits too loosely to recent price : Decrease Regression Length to shorten the lookback window, producing a tighter curve that adapts more quickly to recent structural changes. Switch to Polynomial mode if visible trend curvature is present.
Inward bars too tall or short : Adjust Bar Height (ATR×) to scale the maximum inward bar height, making volume bars more prominent during high-participation sessions or more subtle on instruments with lower volume variance.
Too many or too few edge flares : Increase Flare Volume Multiplier to restrict flares to only exceptional volume events, or adjust Flare Edge Zone % to control how close to the boundary price must be before a flare qualifies.
End profile too wide or compact : Adjust Profile Width to control the maximum horizontal extent of the end profile bars, calibrating the profile size to the available chart space at the current zoom level.
Profile rows too coarse or granular : Adjust Profile Rows to increase or decrease vertical resolution, with higher values providing finer detail across the channel's price range and lower values producing broader, more readable rows.
Too many bound diamonds cluttering the chart : The diamond system marks only first-bar boundary touches. On instruments with frequent boundary contact the marker density may be high. Disable Show Bound Diamonds and rely on edge flares alone for boundary interaction identification.
Adjustments should be incremental and evaluated across multiple session types rather than isolated market conditions.
Performance Characteristics
High Effectiveness:
Trending markets where the regression curve provides an accurate fit to the directional price path and the channel boundaries represent meaningful statistical extremes with genuine participation significance
Liquid instruments with consistent volume where the buy-sell splitting produces reliable directional participation readings and the end profile accumulates a statistically meaningful distribution across the regression window
Boundary interaction strategies where edge flares and bound diamond markers identify high-participation channel extreme events that frequently precede structural reactions
Distribution analysis workflows where the end profile provides a regression-relative volume profile summary that replaces or complements standalone volume profile indicators
Reduced Effectiveness:
Choppy, directionless markets where the regression curve has no clear shape and channel boundaries are penetrated frequently without the sustained trend structure required for meaningful boundary interaction analysis
Low-liquidity instruments where thin volume produces unreliable buy-sell splits and end profile distributions that reflect random participation patterns rather than genuine directional flow
Markets with frequent gaps where the HL2 series used for regression produces curves distorted by discontinuous price events that shift the channel relative to actual price structure
Very short regression windows where insufficient bars per channel row produce end profiles dominated by noise rather than statistically meaningful participation concentration
Consolidation environments where price oscillates near the regression centerline without reaching channel boundaries, reducing the analytical value of edge flares and bound diamonds while producing uniformly short inward bars
Integration Guidelines
Confluence : Combine with BOSWaves momentum tools, order block analysis, or structural indicators to validate channel boundary interactions and edge flare events with broader analytical context
End Profile Reference : Use the end profile distribution as a volume-based reference layer for price levels visited by price within the regression window. High-volume rows in the profile identify price levels with the greatest historical participation concentration, making them structurally significant references for future interaction.
Inward Bar Divergence Monitoring : Monitor inward bar height on opposing sides as price approaches boundaries. Growing opposing-side bars during boundary approach suggest increasing counter-directional participation that may oppose the boundary continuation.
Regression Mode Consistency : Maintain a consistent regression mode when using the channel as an ongoing structural reference. Switching between Linear and Polynomial shifts the curve and redistributes the channel geometry, making successive comparisons of profile distribution and boundary levels unreliable.
Centerline Cross Awareness : Treat price crossing the regression centerline as a potential flow transition event. Combined with a centerline flow segment color change from one direction to the other, centerline crossings with above-average volume suggest genuine directional repositioning within the channel structure.
Disclaimer
Volume Regression Channel is a professional-grade regression-anchored volume flow analysis tool. It uses OLS curve fitting with close-position volume splitting and cumulative profile construction but does not predict future price movements. Results depend on market conditions, instrument volume characteristics, parameter selection, and disciplined execution. BOSWaves recommends deploying this indicator within a broader analytical framework that incorporates momentum context, order flow analysis, and comprehensive risk management. Indicator
Forex Liquidity Map [invincible3]b]Forex Liquidity Glow Map
The Forex Liquidity Glow Map is a visual currency-rotation dashboard designed to estimate where relative strength and trading activity are moving across the major Forex market.
The indicator analyzes all 28 unique currency pairs formed from:
USD, EUR, GBP, JPY, CHF, CAD, AUD, and NZD
Instead of evaluating one pair in isolation, it combines information from every relationship connected to each currency. This produces an aggregated flow score for all eight currencies and helps identify the strongest and weakest areas of the Forex market.
Calculation Model
Each Forex pair is evaluated using:
• ATR-normalized price momentum
• Relative tick-volume activity
• Fast-versus-slow trend structure
• Volatility expansion
• Directional breadth
• Score smoothing
• Flow acceleration
A positive pair score strengthens the base currency and weakens the quote currency. A negative pair score strengthens the quote currency and weakens the base currency.
Each currency’s final score is calculated from its seven connected pair relationships.
Because spot Forex is decentralized, the indicator uses PulseWire broker-feed tick volume as an activity proxy. It does not represent centralized institutional order flow.
Forex Liquidity Map
The circular map displays the eight major currencies as nodes.
• Node value: Aggregated currency-flow score
• Node size: Average relative activity across connected pairs
• River direction: Weaker currency toward stronger currency
• River width: Estimated strength of liquidity rotation
• River color: Leading currency in that relationship
• Arrow: Direction of relative capital rotation
A positive score indicates relative strength or estimated inflow. A negative score indicates relative weakness or estimated outflow.
Water Flow Matrix
The scatter matrix shows each currency according to:
• Horizontal position: Current flow score
• Vertical position: Flow acceleration
• Bubble size: Relative pair activity
• Bubble color: Currency identity
The four matrix conditions are:
• Accelerating inflow: Positive flow with positive acceleration
• Weakening inflow: Positive flow with negative acceleration
• Accelerating outflow: Negative flow with negative acceleration
• Weakening outflow: Negative flow with positive acceleration
This helps distinguish a currency that is merely strong from one whose strength is actively increasing.
Dashboard and Pair Ranking
The dashboard includes:
• Currency strength ranking
• Current flow score
• Relative tick activity
• Momentum condition
• Inflow, outflow, or balanced status
• Ranked breakdown of all 28 Forex pairs
• Strongest and weakest currencies
• Best relative-strength pair
• Market confirmation percentage
• Current Forex-rotation regime
For example, when GBP is the strongest currency and AUD is the weakest, the dashboard may identify GBPAUD as the primary relative-strength opportunity.
Update Modes
Confirmed bars only uses completed calculation-timeframe candles. The rivers, matrix, rankings, and signals remain fixed while the current candle is forming.
Live uses the active candle and updates as price and tick volume change. This provides faster information but may change before candle close.
Confirmed mode is recommended for stable analysis and alerts. Live mode is intended for intrabar monitoring.
Display Features
• Responsive bar-index geometry
• Stable layout across intraday and higher timeframes
• Dark and Bright theme presets
• Fully opaque dashboard cells
• High-contrast currency colors
• Adjustable map and matrix dimensions
• Adjustable river threshold
• Optional arrows, glow, tooltips, tables, and signals
• Configurable PulseWire Forex-feed prefix
Interpretation
The indicator is most useful for:
• Finding strongest-versus-weakest currency combinations
• Confirming directional pair setups
• Monitoring broad Forex rotation
• Detecting strengthening or weakening flows
• Avoiding pairs where both currencies have similar strength
• Comparing pair-level movement with broader currency-level confirmation
The output should be used as a market-structure and relative-strength tool , not as a standalone entry system.
Execution decisions should also consider price structure, volatility, liquidity conditions, risk management, and scheduled economic events. Indicator
Market Structure Trend [QuantAlgo]🟢 Overview
The Market Structure Trend tracks the dominant directional bias of price by detecting confirmed swing highs and lows and maintaining an active structure level that only flips on a genuine break of that level. Rather than reacting to every minor high or low, it waits for a pivot to lock in after a defined number of bars on either side, then holds the resulting structure until price closes beyond it by an optional confirmation buffer. The result is a clean, non-repainting structure line that stays aligned with the prevailing market structure while filtering out stop hunts and marginal pokes through key levels. This makes the prevailing bias readable at a glance across any instrument or timeframe.
🟢 How It Works
The indicator begins by identifying pivot highs and pivot lows using the selected left and right structure bars. These pivots become the swing points that define market structure:
pivot_high = ta.pivothigh(high, left_bars, right_bars)
pivot_low = ta.pivotlow(low, left_bars, right_bars)
When a new pivot is confirmed, the corresponding swing high or swing low is updated. The active structure range is calculated as the absolute distance between the current swing high and swing low, and a confirmation buffer is derived as a percentage of that range:
structure_range = math.abs(swing_high - swing_low)
confirm_buffer = structure_range * buffer_pct / 100.0
Break levels are then offset by this buffer so that a downside break sits below the swing low and an upside break sits above the swing high. On every confirmed bar the script checks whether the chosen source (or the high or low when Break On Wick is enabled) has crossed the relevant break level. A successful cross reverses structure direction and reassigns the structure level to the opposite swing. If no break occurs, the structure level simply continues to track the swing consistent with the current direction.
Structure direction is seeded on the first ready bar by comparing price to the midpoint of the swing range, establishing an initial bias. From that point forward flips are gated strictly by confirmed breaks, so the state never repaints or changes mid-bar.
The structure level is drawn as a continuous line with a soft glow underneath. When radial layering is enabled, four concentric fills are drawn between the structure level and the bar midpoint, with transparency increasing outward. This produces a stepped radial field that visually maps distance from the active structure boundary rather than a single flat zone.
🟢 Signal Interpretation
▶ Bullish Structure (Structure Line at Swing Low with Bullish Color): When structure direction is bullish the line sits at the most recent confirmed swing low. Price is considered to remain in an uptrend structure as long as it stays above the buffered downside break level. The bullish state holds until a confirmed downside break occurs, at which point the line moves to the swing high and the color transitions.
▶ Bearish Structure (Structure Line at Swing High with Bearish Color): When structure direction is bearish the line sits at the most recent confirmed swing high. Price remains in a downtrend structure until a confirmed upside break flips the state. The bearish state persists through subsequent bars until an upside break is registered.
🟢 Features
▶ Preconfigured Presets: Three parameter sets cover a range of trading styles and timeframes. Default uses the manual Left Structure Bars, Right Structure Bars, and Confirmation Buffer values and is balanced for swing trading on 1-hour and daily charts. Fast Response shortens the structure legs for scalping and intraday use on 1-minute to 1-hour charts, registering minor swings so the structure trend flips earlier. Smooth Trend lengthens the legs for position trading on daily and weekly charts, tracking only major swings and holding through pullbacks with the confirmation buffer.
▶ Built-in Alerts: Three alert conditions support automated monitoring of structure flips. Bullish Structure Shift fires on the first bar that structure direction changes from bearish to bullish. Bearish Structure Shift fires on the opposite transition. Any Structure Shift triggers on either flip for traders who prefer a single unified alert. All messages include the exchange, ticker, and timeframe for immediate context.
▶ Visual Customization: Six color presets (Classic, Aqua, Cosmic, Cyber, Neon, and Custom) supply coordinated bullish and bearish color pairings suited to different chart themes. Selecting Custom unlocks independent color pickers for full manual control. Optional bar coloring tints each candle with the active structure color at a configurable transparency, and optional background coloring extends the same tint across the full chart pane. Radial layering, structure shift markers, and the structure line itself all inherit the active color pair so the entire visual system remains consistent.
Indicator
Regression Trend [MiesOnCharts]Regression Trend - Mies
What it does
This indicator fits a linear regression line to price over a rolling window and draws a corridor around it based on the statistical error of that fit. The corridor is what decides the trend state. As long as price stays inside it, nothing changes. When price closes outside one side, the whole thing flips color and a triangle marks the bar.
The result is a trend line that carries its own tolerance band with it, so you can see at a glance both where the fitted trend sits and how much room price has before the state changes.
How it works
A least squares regression is fitted across the lookback window. That gives the center line.
Around it, the script computes the standard error of the estimate, which is the typical distance between actual price and the fitted line. It comes from the correlation between price and time:
r is the correlation of the source with bar index over the window
residual variance is the price variance scaled by (1 - r²)
the standard error is the square root of that, adjusted for the degrees of freedom of the fit.
This is the part that makes the corridor behave differently from a standard deviation band. The width responds to how well price is actually tracking the trend, not just to raw volatility. A strong, clean trend produces a high correlation, small residuals, and a narrow corridor, so the indicator stays sensitive.
Choppy price that wanders around the line produces a weak fit, a wide corridor, and a much higher bar for triggering a state change. The indicator effectively demands more evidence in exactly the conditions where evidence is thin.
The bands sit at the center line plus and minus a multiple of that standard error. A close above the upper band turns the state bullish, a close below the lower band turns it bearish, and everything in between leaves the previous state untouched. That hysteresis is intentional. It is what stops the indicator from flipping every time price crosses its own mean.
On the chart
Regression line, green when the state is bullish, red when bearish, gray before the first breakout
Upper and lower standard error bands with a light fill between them, colored to match the current state Triangle below the bar when the state flips bullish Triangle above the bar when the state flips bearish.
Display controls to hide the fill, or the bands entirely, if you want a bare trend line
Two alert conditions, one for each direction
Settings
Source sets which series gets fitted. Close is the standard choice. HL2 or a smoothed input will give a calmer line and fewer flips.
Regression Window sets how many bars the fit covers. Shorter windows follow recent structure and react fast. Longer windows describe the broader trend and produce fewer, slower signals. This is the main setting for matching the tool to your timeframe.
SE Band Multiplier controls how far price has to move from the fitted line before the state changes. Lower values tighten the corridor and generate more signals. Higher values require a more decisive break and filter more noise, at the cost of entering later.
Display group toggles the bands and the fill, and adjusts band opacity.
How to use it
The most direct use is as a trend filter. Trade only in the direction the line is colored and treat the opposite flip as your exit or your cue to step aside.
The corridor itself gives you two readable things. Its width tells you how well price is respecting the trend, so a corridor that has narrowed over recent bars means the fit is tightening and the move is orderly. A corridor that has ballooned means the fit has broken down and the state you are looking at is stale. The center line works as a dynamic reference within an established regime, since a pullback toward it is price returning to its own fitted mean rather than to an arbitrary level.
It pairs well with a volume or momentum check. A corridor break tells you the move is statistically unusual relative to the current fit, but it says nothing about whether there is participation behind it.
Behavior worth understanding
The regression is recalculated on every bar, and the corridor plotted on each bar is that bar's own fit. This is a running envelope, not a fixed channel anchored to a pivot, so the bands will look wavier than a manually drawn regression channel. The reference moves with price, which is what keeps the state stable through a sustained run.
Signals are evaluated on the live bar, so a flip can appear and then vanish before the bar closes. Wait for bar close if you need signals that hold.
Limitations
Linear regression assumes price is moving in a straight line across the window, which is never fully true. The fit degrades at sharp reversals and around gaps, and the corridor is slow to acknowledge a turn right after a strong move because that extension is still inside the window. Treat this as a description of current trend structure, not a forecast.
Disclaimer
The indicator provided is not financial advice. Always conduct your own research and consider multiple factors before making trading decisions. Trade at your own risk. Indicator
Adaptive Trend Ensemble [BackQuant]Adaptive Trend Ensemble
Overview
Adaptive Trend Ensemble is an online-learning trend filter that combines eight different moving-average methods into one continuously weighted trend estimate.
Instead of selecting one moving average permanently, the indicator treats each method as an independent forecasting expert. Every bar, each expert is evaluated according to whether its previous slope correctly anticipated the direction of the latest price move.
Experts that were directionally correct retain more influence. Experts that were wrong lose influence through a multiplicative penalty. The weights are then normalised and used to blend all eight moving-average values into one adaptive ensemble line.
The indicator therefore attempts to answer two separate questions:
Which smoothing method has recently aligned best with price direction?*
How strongly do the weighted methods currently agree on the direction of trend?
The final output includes:
A dynamically weighted ensemble trend line.
Bullish and bearish trend-state colouring.
A gradient between price and the ensemble.
A consensus-driven glow.
Trend-coloured candles.
A live label showing the leading expert and its current weight.
Alerts when the ensemble trend changes direction.
This is not a fixed moving average and it is not a simple average of several indicators. The contribution of each expert changes over time according to its recent directional performance.
Core idea
Moving averages respond differently to the same market.
A Hull Moving Average may respond quickly during a sharp transition, while an RMA may remain stable through temporary noise. A linear-regression estimate may follow a smooth directional move well, while a conventional EMA may perform better during a more ordinary trend.
No individual smoothing method is consistently superior across every environment.
Markets alternate between:
Persistent trends.
Fast breakouts.
Slow directional drift.
Volatile reversals.
Compressed ranges.
Noisy transitions.
A fixed indicator cannot change its mathematical personality when the environment changes. It continues using the same weighting structure regardless of whether that structure currently suits the market.
Adaptive Trend Ensemble addresses this by maintaining a bank of different smoothing methods and changing their influence through time.
The model does not attempt to decide in advance which method is best. It allows recent realised price action to determine which experts should currently receive more weight.
Prediction with expert advice
The indicator is based on a class of online-learning methods commonly described as:
Prediction with Expert Advice
In this framework:
Several experts produce predictions.
The actual outcome is observed.
Each expert receives a loss based on its prediction.
Expert weights are updated.
The combined model places more influence on better-performing experts.
The term “expert” does not imply that each method is intelligent by itself. An expert is simply an individual forecasting rule.
In this indicator, the eight experts are eight moving-average methods.
The model uses a multiplicative-weights process closely related to the Hedge and Weighted Majority families of online-learning algorithms.
The central principle is:
Do not commit permanently to one model.
Track several models simultaneously.
Reduce the weight of models that make mistakes.
Allow the combined forecast to adapt as relative performance changes.
Online learning
The model learns sequentially, one bar at a time.
It does not train on a separate historical dataset and then freeze its parameters.
At each new bar:
The previous slope of each moving average is treated as that expert's prediction.
The realised close-to-close direction is observed.
Each expert receives a loss.
Weights are updated multiplicatively.
Weights are normalised.
The current expert values are blended using the new weights.
This makes the process online and adaptive.
The weight state is carried forward from bar to bar, meaning the current ensemble reflects the accumulated results of earlier expert decisions.
The expert bank
The ensemble contains eight moving-average experts:
Simple Moving Average - SMA*
Exponential Moving Average - EMA
Weighted Moving Average - WMA*
Hull Moving Average - HMA
Double Exponential Moving Average - DEMA*
Running Moving Average - RMA
Arnaud Legoux Moving Average - ALMA*
Least-Squares Moving Average - LSMA
All experts use the same Base Length.
This is important because it keeps their nominal observation horizon comparable. The ensemble is comparing different mathematical treatments of approximately the same lookback rather than comparing completely unrelated time horizons.
Even with an identical length, the experts behave differently because they assign weight to historical observations in different ways.
Simple Moving Average - SMA
The SMA applies equal weight to every observation inside the selected window.
Its general form is:
SMA = Sum of observations / Number of observations
The SMA is stable and easy to interpret, but every included observation has the same importance.
This can make it slower to react when a new trend begins because older prices continue to influence the average until they leave the window.
Within the ensemble, the SMA acts as a neutral equal-weight baseline.
Exponential Moving Average - EMA
The EMA assigns progressively greater weight to recent observations.
Its recursive form is based on:
EMA = α × Current Price + (1 - α) × Previous EMA
where α is determined by the selected length.
Compared with an SMA of the same length, an EMA generally responds more quickly to recent movement.
Its recursive weighting makes it useful during ordinary directional markets, although it can still turn repeatedly when price oscillates in a range.
Weighted Moving Average - WMA
The WMA assigns linearly increasing weight to more recent observations.
For example, in a simplified four-period WMA, the newest value receives four units of weight, while the oldest receives one.
This makes the WMA more responsive than an equal-weight SMA while retaining a finite lookback window.
Within the ensemble, it provides a direct recency-weighted alternative to the exponential behaviour of the EMA.
Hull Moving Average - HMA
The Hull Moving Average was designed to reduce lag while preserving a relatively smooth output.
Its construction combines weighted moving averages over different horizons, applies a lag-compensation step, and then smooths the result over approximately the square root of the original length.
Conceptually:
Calculate a faster WMA.
Calculate a slower WMA.
Use their difference to compensate for lag.
Smooth the compensated result.
The HMA often reacts quickly to changes in trend direction.
That responsiveness can make it valuable during strong transitions, but it may also make it more sensitive to short-term oscillation.
Double Exponential Moving Average - DEMA
Despite its name, DEMA is not simply an EMA calculated twice.
Its general construction is:
DEMA = 2 × EMA - EMA of EMA
The second EMA estimates some of the lag in the first EMA. Subtracting it attempts to create a smoother with less delay.
DEMA can respond quickly to directional changes, although reduced lag may also increase sensitivity during unstable conditions.
Running Moving Average - RMA
RMA is commonly associated with Wilder-style smoothing.
It uses a slower recursive update than a typical EMA of the same nominal length.
Its general form places substantial influence on the previous RMA value, producing a persistent and stable estimate.
The RMA expert often changes direction less aggressively than the faster methods.
Within the ensemble, it acts as one of the more conservative smoothing models.
Arnaud Legoux Moving Average - ALMA
ALMA applies a Gaussian-style weighting curve across the observation window.
The weighting distribution can be shifted toward more recent observations while maintaining a smooth bell-shaped profile.
The script uses a recent-weighted offset and a fixed Gaussian width.
ALMA attempts to balance:
Smoothness.
Reduced lag.
Controlled weighting of the observation window.
It provides a different weighting structure from the linear, exponential and lag-compensated experts.
Least-Squares Moving Average - LSMA
The LSMA is based on linear regression.
Instead of averaging historical prices directly, it fits a straight line through the selected window and evaluates the regression estimate at the current bar.
The method attempts to represent the local directional path of price.
LSMA can follow smooth trends closely because it models slope explicitly. However, it may respond strongly when the local regression direction changes abruptly.
Within the indicator, the LSMA is produced using the rolling linear-regression output.
Base Length
The Base Length is shared by all eight experts.
Lower values:
Make every expert more responsive.
Increase sensitivity to short-term changes.
Produce faster weight and trend changes.
Increase the possibility of whipsaws.
Higher values:
Create smoother expert outputs.
Focus the ensemble on broader trend structure.
Reduce short-term changes.
Increase lag during sudden reversals.
Because all experts share the same length, changing this setting adjusts the entire ensemble horizon.
It does not change the number of experts or their relative starting weights.
Expert predictions
The model evaluates each expert using the direction of its slope.
For each moving average:
Rising slope is represented as +1.
Falling or non-rising slope is represented as -1.
To evaluate the latest completed move, the script uses the expert's slope from the previous bar.
For example:
If the expert was rising from two bars ago to the previous bar, it predicted a positive current move.
If the expert was falling, it predicted a negative current move.
The realised outcome is determined from the current close relative to the previous close:
Close above previous close = positive realised direction.
Close below previous close = negative realised direction.
Unchanged close = zero realised direction.
The model therefore scores directional slope prediction, not the numerical distance between each moving average and price.
An expert is rewarded for getting direction right, even if its plotted value is relatively far from the market.
Likewise, an expert is penalised for getting direction wrong even if its line remains visually close to price.
Loss functions
The indicator provides two loss functions:
Directional 0/1*
Magnitude-weighted
The selected loss determines how strongly incorrect experts are penalised.
Correct experts receive zero loss under both modes.
Directional 0/1 loss
Directional mode treats every incorrect prediction equally.
The loss is:
0 when the expert predicted the realised direction correctly.
1 when the expert predicted incorrectly.
This means that an incorrect prediction on a very small move receives the same loss as an incorrect prediction on a large move.
Directional mode answers a simple question:
Was the expert right or wrong?
It does not consider how important the move was.
This mode can produce consistent learning because every directional observation is treated equally, but it may respond to small and insignificant price changes as strongly as major moves.
Magnitude-weighted loss
Magnitude-weighted mode scales the penalty according to the size of the realised move.
The move is normalised using ATR:
Move = Absolute close-to-close change / ATR
The ATR uses the shared Base Length.
The incorrect expert's loss becomes:
Loss = Normalised Move
with the magnitude capped at 3.
The cap prevents a single extreme bar from creating an unlimited penalty.
This mode gives greater importance to mistakes during large movements.
For example:
An incorrect expert during a 0.10 ATR move receives a small penalty.
An incorrect expert during a 1.00 ATR move receives a larger penalty.
An incorrect expert during a move above 3 ATR receives the capped penalty of 3.
Magnitude-weighted mode answers:
How costly was the directional mistake relative to current volatility?
This can make the ensemble adapt more strongly after significant movements while paying less attention to small fluctuations.
Flat price bars
If the current close is unchanged from the previous close, the realised direction is zero.
Because expert directions are encoded as either positive or negative, no expert can exactly match a zero realised direction.
Under Directional mode, all experts receive the same incorrect classification.
Because every weight is multiplied by the same penalty factor, their relative weight distribution remains effectively unchanged after normalisation.
Under Magnitude-weighted mode, the realised move is zero, so the resulting penalty is also zero.
In both cases, a completely flat close-to-close bar does not materially change the relative ranking of the experts.
Multiplicative weight update
Each expert begins with an equal weight:
Initial Weight = 1 / 8
After the loss is calculated, the weight is updated using:
New Unnormalised Weight = Old Weight × exp(-η × Loss)
where η is the Learning Rate.
This is the central Hedge or multiplicative-weights update.
Correct experts have zero loss:
exp(-η × 0) = 1
Their unnormalised weight is unchanged.
Incorrect experts have a positive loss, so their weight is multiplied by a value below one.
For example, in Directional mode with a Learning Rate of 2:
Incorrect Weight Multiplier = exp(-2) ≈ 0.135
An incorrect expert retains only about 13.5% of its previous unnormalised weight before the weight set is normalised again.
This does not mean its final displayed weight will necessarily fall by exactly 86.5%, because all expert weights are subsequently rescaled so they sum to one.
Why multiplicative updates are used
An additive system might subtract a fixed quantity from each incorrect expert.
That can create problems:
Weights can become negative.
The same penalty has a different effect on large and small weights.
The model may not adapt proportionally.
A multiplicative update preserves non-negative weights and penalises experts proportionally to their current influence.
It also allows the distribution to become concentrated around consistently successful methods.
Learning Rate - η
The Learning Rate controls how aggressively the ensemble shifts weight after mistakes.
Higher values:
Penalise incorrect experts more strongly.
Move influence rapidly toward recent winners.
Can produce winner-take-all behaviour.
Can make the leader change abruptly after a few important bars.
Lower values:
Produce gradual weight changes.
Keep the expert distribution more diversified.
Reduce sensitivity to short-term performance.
Make the model slower to adapt.
The Learning Rate does not change the moving averages themselves. It changes only how quickly their relative influence evolves.
High Learning Rate behaviour
At high settings, a wrong expert may lose most of its weight after one or two mistakes.
This can be beneficial when one smoothing method is clearly better suited to the current regime.
It can also create instability:
A recent winner can dominate the ensemble.
A temporary performance streak can cause excessive concentration.
The model can switch leaders quickly when conditions reverse.
Low Learning Rate behaviour
At low settings, the ensemble behaves more like a slowly adapting average of the expert bank.
No single observation dramatically changes the distribution.
This produces smoother adaptation, but a poorly suited expert may retain substantial influence for longer.
Weight normalisation
After all expert weights are updated, they are normalised:
Normalised Weight = Expert Weight / Sum of All Expert Weights
This ensures that the complete weight set sums to one.
The weights can then be interpreted as each expert's share of the ensemble.
For example:
A 25% weight means that expert contributes one quarter of the weighted output.
A 5% weight means its current influence is relatively small.
The weights are not probabilities that the experts will be correct on the next bar.
They are adaptive influence coefficients based on accumulated relative loss.
Weight Floor
The optional Weight Floor preserves a minimum allocation for every expert.
After normalisation, the adjusted weight is calculated so that:
Every expert receives at least the selected floor.
The remaining weight is distributed according to the normalised Hedge weights.
The full set continues to sum to one.
For eight experts, a floor of 0.01 reserves at least 1% for each expert.
This assigns:
A minimum combined mass of 8%.
The remaining 92% according to relative performance.
A floor of 0.05 reserves at least 5% for each of the eight experts, using 40% of the total distribution as minimum allocations.
The remaining 60% is distributed according to current performance.
Why use a floor?
Without a floor, repeatedly incorrect experts can approach a weight extremely close to zero.
Because the update only reduces weights after losses, an expert with almost no weight may require a long period of relative outperformance before it becomes influential again.
A positive floor keeps all methods alive.
This allows an expert that performed poorly in the previous regime to recover more quickly when the market environment changes.
Weight Floor set to zero
With a zero floor:
The model is free to concentrate almost entirely in one expert.
Recent winners can dominate strongly.
The ensemble can become highly specialised.
This produces the purest multiplicative-weights behaviour but increases the risk of weight collapse.
Positive Weight Floor
With a positive floor:
The expert bank remains diversified.
Cold experts retain some influence.
The model can recover more easily after regime changes.
The leading expert's maximum possible weight is reduced.
The floor therefore controls the balance between specialisation and diversity.
Ensemble output
After the weight update, the current values of the eight experts are blended:
Ensemble = Sum of Expert Weight × Expert Value
This is a weighted average in which the weights are determined by online directional performance.
If the HMA currently has the greatest weight, the ensemble will behave more like the HMA.
If the RMA and SMA dominate, the output will become smoother and more conservative.
If the weights are distributed evenly, the line represents a broad blend of all eight methods.
The output can therefore change its effective smoothing behaviour without changing the user-selected Base Length.
Line Smoothing
The weighted ensemble may be passed through an optional EMA for visual smoothing.
A setting of 1 effectively disables this additional stage.
Higher settings:
Create a smoother displayed line.
Reduce small slope changes.
Delay bullish and bearish flips.
This smoothing is cosmetic in the sense that it occurs after the online expert weighting.
It does not affect:
Expert predictions.
Expert losses.
Weight updates.
Consensus.
Leader selection.
It does affect the final plotted line and the trend state derived from that line.
Trend state
Trend direction is determined from the slope of the smoothed ensemble line.
If the line is above its previous value, trend becomes bullish.
If the line is below its previous value, trend becomes bearish.
If the line is unchanged, the previous trend persists.
This creates a persistent two-state regime.
A bullish flip occurs when the trend changes from bearish to bullish.
A bearish flip occurs when it changes from bullish to bearish.
The trend state is based on the ensemble's slope, not on price crossing the ensemble.
Price may be above or below the line without immediately changing its direction.
Consensus calculation
The indicator calculates a separate weighted directional vote.
Each expert's current slope direction is multiplied by its current weight:
Weighted Vote = Sum of Weight × Direction
Because each direction is either +1 or -1 and the weights sum to one, the vote lies between -1 and +1.
Examples:
+1 means all meaningful weight is assigned to rising experts.
-1 means all meaningful weight is assigned to falling experts.
0 means bullish and bearish weighted influence is evenly balanced.
The displayed consensus strength is:
Consensus Strength = Absolute Value of Weighted Vote
This converts the result to a range from zero to one.
0% means the weighted expert bank is evenly divided.
100% means the weighted influence is entirely aligned in one direction.
Weighted consensus versus expert count
Consensus is not calculated by simply counting how many of the eight experts are rising.
An expert with a 40% weight contributes more than one with a 2% weight.
For example:
Five low-weight experts may be bullish.
Three high-weight experts may be bearish.
The final weighted vote can still be bearish.
This means consensus measures the agreement of the current weighted model, not the raw number of methods on each side.
With a zero Weight Floor, consensus may become very high when one expert dominates, even if several near-zero-weight experts disagree.
With a positive floor, disagreement from the remaining experts has more influence on the consensus value.
Consensus is not confidence
The consensus percentage should not be interpreted as a probability that the trend will continue.
It measures only the current alignment of weighted expert slopes.
High consensus means:
The influential experts point in the same direction.
It does not guarantee:
Future price continuation.
A profitable entry.
Low reversal risk.
Strong agreement can occur late in a mature trend as well as early in a new one.
Leading method
The live information label identifies the expert with the highest current weight.
It displays:
The expert name.
Its current percentage weight.
The weighted consensus strength.
The current ensemble direction.
For example:
Leading: HMA (34.5%)*
Consensus: 78% ▲
This means the HMA currently has the largest share of the ensemble and the weighted expert bank is strongly aligned upward.
The leader percentage is not a win probability.
It is only the experts share of the current normalised weight distribution.
Leader changes
The leading method can change when:
The current leader makes directional mistakes.
Another expert remains correct while competitors are penalised.
A large magnitude-weighted move strongly changes relative weights.
The market transitions into a regime better suited to another smoother.
Leader changes can help reveal how the ensemble is adapting.
For example:
A shift toward HMA or DEMA may reflect stronger preference for responsive methods.
A shift toward SMA or RMA may reflect better recent performance from slower methods.
A shift toward LSMA may occur during a smooth local directional path.
These interpretations are contextual and should not be treated as fixed rules.
Gradient fill
The indicator fills the area between price and the ensemble line.
When price is above the line:
A bullish gradient is displayed.
When price is below the line:
A bearish gradient is displayed.
The gradient visually separates price from the adaptive trend estimate.
The fill reflects price location, while the line colour reflects the slope-derived ensemble trend.
These can temporarily disagree.
For example:
Price may fall below a still-rising ensemble during a pullback.
Price may rise above a still-falling ensemble during a counter-trend rally.
This disagreement can provide useful context.
Consensus glow
A glow is drawn around the ensemble line.
Its brightness changes according to weighted consensus.
When consensus is high:
The glow becomes brighter and more visible.
When the experts are divided:
The glow becomes more transparent.
The glow width is scaled using ATR based on the Base Length, helping the effect remain proportional across instruments and volatility environments.
The glow is a visual representation of model agreement. It does not modify the line or trend calculation.
Candle colouring
Candles can be coloured according to the current ensemble trend:
Bullish trend uses the selected bullish colour.
Bearish trend uses the selected bearish colour.
Candle colouring is based on the direction of the ensemble line, not the direction of each individual candle.
A bearish candle can therefore remain green during a bullish ensemble regime, and a bullish candle can remain red during a bearish regime.
How to interpret the indicator
Bullish ensemble trend
A bullish state means the final ensemble line is rising.
This indicates that the current weighted combination of experts is moving upward.
It does not require all individual experts to be bullish.
Bearish ensemble trend
A bearish state means the final ensemble line is falling.
The weighted combination is moving downward, even if one or more individual experts remain bullish.
High bullish consensus
A strongly positive vote means most influential expert weight is assigned to rising methods.
This can indicate broad directional alignment.
High bearish consensus
A strongly negative vote means the influential experts are predominantly falling.
Low consensus
A consensus near zero means weighted expert directions are divided.
This can occur during:
Trend transitions.
Sideways ranges.
Pullbacks.
Disagreement between faster and slower methods.
Low consensus does not automatically mean price will remain sideways. It means the ensemble's components are not currently aligned.
High leader weight and high consensus
This indicates that:
One method currently dominates.
The broader weighted bank is aligned with it.
The model is highly concentrated and directionally unified.
This can produce a responsive and decisive ensemble, but it also means the output depends heavily on the current leader.
Distributed weights and high consensus
This means several experts maintain meaningful weights while pointing in the same direction.
The trend is supported by a more diversified group of methods.
Leader weight high but consensus low
This can occur when the dominant expert points one way while several remaining experts point the other way.
The ensemble may still follow the leader, but internal disagreement is present.
How to use the indicator
1. Trend regime filter
Use the ensemble slope as directional context:
Prioritise long setups during bullish regimes.
Prioritise short setups during bearish regimes.
The indicator does not define entry price, stop placement or profit targets.
2. Consensus filter
A user may require stronger consensus before acting on the trend state.
For example:
A bullish flip with low consensus may represent an early or uncertain transition.
A bullish regime with high consensus indicates broader weighted alignment.
No universal consensus threshold is appropriate for every market.
3. Pullback analysis
During a bullish ensemble regime:
Price moving toward or below the line may represent a pullback.
The ensemble remaining bullish suggests its trend estimate has not yet reversed.
During a bearish regime:
Price moving toward or above the line may represent a counter-trend rally.
Price interaction with the line should be combined with structure and risk management.
4. Regime adaptation observation
The Leading Method label can be used to study how different smoothers perform through changing environments.
Rather than assuming one moving average is always best, the user can observe:
Which expert gains weight during trends.
Which expert takes over during transitions.
How concentrated the model becomes.
How quickly weights change under different Learning Rates.
5. Bullish and bearish flips
Trend flips can be used as:
Regime-change alerts.
Confirmation for another setup.
Potential exit conditions.
A directional filter for discretionary trades.
Because flips are based on line slope, responsive settings can generate repeated changes during ranges.
Suggested configurations
Balanced adaptive configuration
Moderate Base Length.
Moderate Learning Rate.
Directional loss.
Small positive Weight Floor.
Minimal Line Smoothing.
This keeps the model adaptive while preserving some expert diversity.
Fast adaptation configuration
Shorter Base Length.
Higher Learning Rate.
Magnitude-weighted loss.
Zero or very small Weight Floor.
Line Smoothing of 1 or 2.
This allows rapid concentration around recent winners but can create unstable leader changes.
Conservative diversified configuration
Longer Base Length.
Lower Learning Rate.
Directional loss.
Positive Weight Floor.
Additional Line Smoothing.
This creates slower and more diversified adaptation.
Large-move-focused configuration
Magnitude-weighted loss can be used when mistakes during large ATR-normalised moves should matter more than errors during minor fluctuations.
This may reduce the influence of small alternating bars on the weight distribution.
Pure directional configuration
Directional loss is useful when every close-to-close directional observation should be treated equally.
It creates a straightforward right-or-wrong scoring process.
How this differs from averaging moving averages
A normal moving-average ribbon or composite may calculate:
Average of SMA, EMA, HMA and other methods.
If every method receives equal weight permanently, its influence never changes.
Adaptive Trend Ensemble instead calculates:
Performance-dependent weights.
Sequential loss updates.
A dynamically changing weighted output.
Two bars with the same expert values can produce different ensemble values if the weight distributions differ.
How this differs from selecting the current fastest average
The indicator does not select whichever moving average is currently closest to price or whichever has moved the most.
Weights are based on whether previous expert slopes correctly anticipated realised price direction.
An expert can therefore lead even if it is not the fastest or closest line.
How this differs from an optimisation
The model does not search historical data for one set of parameters with the best backtest result.
It does not change the shared length of each expert.
Instead, it performs continuous online adaptation of the expert weights.
This avoids permanently selecting one historical winner, but it also means recent performance can strongly influence the current model.
How this differs from a machine-learning forecast
The indicator uses a genuine online-learning algorithm, but it is not a neural network or a price-target forecasting model.
It does not estimate the size of the next move.
The experts make binary directional predictions derived from their slopes.
The learning system then adjusts how much influence each moving-average value receives.
It is therefore best understood as an adaptive model-selection and blending process.
Causality and real-time behaviour
The learning update uses:
The prior-bar slope of each expert.
The current close-to-close realised direction.
It does not use future bars.
On historical completed candles, the update is fully causal.
On the current live candle:
The close can continue changing.
The realised direction can change.
Expert values can change.
Weights and consensus can update intrabar.
A bullish or bearish flip may appear before the candle closes.
Users requiring confirmed signals should evaluate the indicator at bar close.
Strengths
Combines eight distinct smoothing methods.
Adapts expert influence through online learning.
Supports directional and magnitude-sensitive losses.
Uses multiplicative updates rather than fixed weighting.
Provides optional protection against permanent weight collapse.
Separates ensemble direction from expert consensus.
Displays the currently leading method.
Uses one shared horizon for a fairer expert comparison.
Requires no offline training process.
Provides transparent open-source calculations.
Summary
Adaptive Trend Ensemble combines eight moving-average experts using a multiplicative online-learning model.
Each expert uses the same Base Length but applies a different smoothing method. The previous slope of each expert acts as its directional prediction for the latest close-to-close move.
After the realised direction is observed, incorrect experts receive either a fixed directional loss or an ATR-normalised magnitude-weighted loss. Their weights are reduced using an exponential Hedge update, then normalised and optionally adjusted using a minimum Weight Floor.
The current expert values are blended according to these adaptive weights, producing one ensemble line whose effective behaviour changes as different methods gain or lose influence.
A separate weighted vote measures current directional agreement. This consensus controls the visual glow and is displayed beside the current leading expert.
The result is a transparent adaptive trend model that does not assume one moving average will remain optimal. Instead, it continuously redistributes influence toward the methods that have recently aligned better with realised price direction while retaining configurable control over responsiveness, diversity and visual smoothing.
Indicator
Leg Anatomy - Measured Retracement and ExtensionEvery trader draws the same three numbers on every chart: 38.2, 50 and 61.8. Those numbers were not derived from this market, this timeframe, or this instrument. They were not derived from any market. They are a convention that spread because it spread.
This script measures the real thing instead.
WHAT IT MEASURES
Price is broken into confirmed swing legs. A running extreme is tracked, and when price closes back from that extreme by more than a configurable multiple of ATR, the extreme is confirmed as a swing and a new leg begins.
Every completed leg is measured as a ratio of the leg immediately before it. A leg that travelled 60 percent of the previous leg records 0.60. A leg that went 140 percent past it records 1.40. That single number, the leg-to-leg ratio, is the entire dataset.
From the last N legs on the chart you have open, the panel reports:
The median leg, expressed as a multiple of the one before it.
The interquartile range, the middle half of the distribution.
The share of legs that were shallow, under 0.62.
The share that were deep, between 0.62 and 1.00.
The share that were extensions, past 1.00.
On some symbols and timeframes the conventional levels sit close to the measured centre. On many they do not, and the gap between what a chart actually does and what the convention assumes is visible in one row of the panel.
THE PROJECTION
The distribution is not left as a table. It is applied forward.
The leg currently forming starts from the last confirmed swing, and the leg before it has a known size. Multiplying that size by the measured median, upper quartile and ninetieth percentile gives three projected endpoints, drawn as a shaded zone in front of price with a dashed median line and a price label.
The panel shows how far the forming leg has travelled as a percentage of its median expectation. Below 100 percent the leg is still inside its normal range. Above it, the leg has already outrun the typical case for this chart, which is information whether you are holding it or fading it.
The zone is not a forecast. It is where the middle of the distribution sits, and roughly half of past legs fell short of it.
THE SKELETON
Confirmed legs are drawn as a thick zigzag across the chart, each one labelled with its own ratio, so the distribution in the panel can be read directly off the price action that produced it. Candles are tinted by the direction of the leg currently forming.
Because swings only confirm on closed bars and a confirmed swing is never revisited, the skeleton behind price is final. Only the leg at the right edge is still forming, and the projection zone updates only when a new leg is confirmed.
SETUPS
When a swing confirms, a new leg begins, and the script produces a complete setup at that close.
The stop sits just beyond the swing that was just confirmed, plus an ATR buffer. That swing is the level the leg depends on. If it goes, the leg reading was wrong.
The three targets are the lower quartile, the median and the upper quartile of the measured distribution, projected from the swing. They are not multiples of risk and they are not conventional ratios. They are the shape of this chart's own legs.
Only one setup is tracked at a time. The panel records whether the first target or the stop was reached first, and prints collecting until the sample is large enough to mean anything. That number measures one mechanical rule and is not a backtest.
SETTINGS
Reversal Threshold is the only structural dial. It decides what counts as a leg. A low value produces many small legs and a distribution dominated by noise. A high value produces few large legs and a distribution with a small sample. The default sits between the two, and changing it changes the entire analysis, which is the point: a leg on a scalping horizon is not a leg on a swing horizon, and the measured distribution should differ between them.
Volatility Length sets the ATR lookback used for the reversal threshold and the stop buffer.
Legs Kept In Sample bounds the history, so the distribution tracks the current regime instead of averaging in a market from years ago.
REPAINTING
Swing confirmation, leg measurement, the distribution, setups and alerts all evaluate on confirmed bars. A confirmed swing is never moved and a drawn leg is never redrawn. The projection zone in front of price is recomputed only when a new leg begins. The script requests no higher timeframe data.
HOW TO READ IT
Start with the three share rows. If a chart shows most of its legs under 0.62, it is a market that retraces shallowly and continuation is the base case. If most legs sit between 0.62 and 1.00, it is a market that gives deep pullbacks and entering early is expensive. A high share above 1.00 is a trending regime where each leg outruns the last.
Then look at the forming leg's progress. A leg at 40 percent of median with a distribution that favours extension is a different situation from a leg at 130 percent in a market that rarely extends.
The ratios printed on the skeleton let you check the panel against your own eyes rather than trusting it.
This is an analysis tool, not financial advice, and not a trading system. A measured distribution describes what happened, not what will. Sample sizes are small by the standards of statistics and regimes change. Use it with your own risk management and position sizing. Indicator
Volatility Corridor - Quantized Equilibrium LevelsMost range and channel tools slide. The midline is a moving average, so it moves on every bar, and the levels drawn from it move with it. That makes them fine as a trend read and close to useless as levels, because the level you looked at ten bars ago is no longer where you left it.
Volatility Corridor does the opposite. It holds still, and then it jumps.
HOW THE CORRIDOR IS BUILT
An equilibrium anchor sits at the centre of the corridor. Once placed, it is frozen. It does not drift, it does not smooth, it does not respond to anything at all until price closes more than one volatility step away from it.
When that happens, the anchor jumps by a whole number of steps in the direction of the breach, lands at the new location, re-measures its step size from ATR at that exact moment, and freezes again.
Three bands are drawn one step apart above the anchor and three below, giving seven horizontal levels: S3, S2, S1, EQ, R1, R2, R3. Because the anchor and the step are both frozen between jumps, every one of those levels is a genuine flat horizontal line for the entire life of the corridor. Across a chart the result is a staircase of stable shelves rather than a wave, and the jump bars are marked so the history of the structure is readable at a glance.
The quantization matters. The anchor moves by whole steps, never by fractions, so successive corridors line up on a common grid instead of drifting off it. When price returns to an area it traded weeks ago, the corridor tends to rebuild on the same shelves rather than near them.
WHAT IS ON THE CHART
Seven stepline levels, thickest at the equilibrium.
Six filled bands between them, darkening toward the outer edges, so the corridor reads instantly without inspecting a single number.
Candles tinted by their position inside the corridor, running from the lower colour at the bottom edge through neutral at equilibrium to the upper colour at the top.
Background tint whenever price is trading fully outside the corridor.
Price labels on every level at the right edge, in four selectable sizes.
Jump markers at the top and bottom of the pane showing every bar the corridor re-anchored, and in which direction.
SETUPS
Two setups are defined, and either can be switched off.
Reversion. Price has pushed into the outer band and closes back inside it while still on its own side of equilibrium. The stop is the far outer level, and the targets are the levels above: equilibrium first, then the next band, then the one after that. The reasoning is that a corridor that is holding will pull price back toward its centre, and the level structure already provides the map for that journey.
Breakout. Price closes fully beyond the outer level of the corridor. The stop is the first level back inside, and the targets are projected one, two and three steps beyond the corridor edge, on the same grid the corridor itself uses.
In both cases the stop and the targets are structural levels, not multiples of risk. Nothing is placed at an arbitrary distance. The stop is where the structure would be wrong, and the targets are the next shelves on the grid.
Only one setup is tracked at a time. A new signal cannot silently replace an unresolved one.
The panel keeps a record of whether the first target or the stop was reached first, and prints collecting rather than a percentage until the sample is large enough to mean anything. That number is a narrow measurement of one mechanical rule, not a backtest, and it says nothing about what a trader who moved a stop or scaled out would have achieved.
SETTINGS
Step Size is the one dial that matters. It sets the width of a single band in ATR terms, and therefore how far price must travel to force a jump. Larger values give wider, rarer, more significant corridors. Smaller values give a tighter grid that re-anchors often.
Volatility Length sets the ATR lookback used to measure a step at each anchor. Longer is more stable.
Everything else is cosmetic: fills, candle painting, label size, level thickness, background tint.
REPAINTING
The anchor, the step size, the jumps, the setups and the alerts all evaluate on confirmed bars only. A level that is drawn is final for the life of the corridor and is never moved retroactively. The script requests no higher timeframe data.
READING IT
Equilibrium is the fair value the corridor is currently defending. Price oscillating around it is a market with no directional decision.
The outer bands are where the current corridor stops being an adequate description of price. Price reaching them means one of two things is about to happen: it is rejected and the corridor holds, or it closes through and the whole structure jumps to a new shelf. Both are tradable and both have a setup defined for them.
A corridor that survives many bars is a market that has agreed on value. A rapid sequence of jumps in one direction is a trend, and the jump markers make that sequence obvious even when the candles do not.
This is an analysis tool, not financial advice, and not a trading system. The setups are two mechanically defined patterns, and no pattern has an edge on its own. Use it with your own risk management and position sizing. Indicator
EVA Ai+ Radar v25.2 Screener - Crypto & Stock LONG SHORT Si🧬 EVA Ai+ Radar — профессиональный рыночный скринер и индикатор для PulseWire, созданный для быстрого поиска перспективных торговых инструментов среди российских акций и популярных криптовалют.
Система одновременно анализирует до 20 активов, рассчитывает приоритет каждого инструмента и автоматически сортирует рынок по силе текущего движения. Вместо ручного переключения между графиками трейдер получает компактную премиальную панель с готовым рейтингом активов.
🔎 Что анализирует EVA Ai+ Radar
Для каждого инструмента рассчитываются:
направление краткосрочного и среднесрочного тренда;
положение цены относительно EMA;
сила тренда через ADX и DMI;
состояние RSI;
относительный торговый объём;
направленный рыночный поток Flow;
изменение цены;
итоговая сила и приоритет сигнала.
📊 Сигналы скринера
🟢 LONG — подтверждённое преимущество покупателей и восходящее направление.
🔴 SHORT — подтверждённое преимущество продавцов и нисходящее направление.
🟡 РАНО ↑ / РАНО ↓ — раннее формирование движения до достижения строгого порога основного сигнала.
⚪ НАБЛ. — инструмент пока не имеет достаточного преимущества для подтверждённого входа.
⚡ Два режима работы
RADAR — строгий режим для поиска подтверждённых сигналов LONG и SHORT.
РАНО — расширенный режим, дополнительно показывающий инструменты, в которых движение только начинает формироваться.
🛡️ Защита от перерисовки
По умолчанию скринер использует данные только закрытых свечей выбранного таймфрейма:
без lookahead_on;
без смещения сигналов в прошлое;
без перерисовки подтверждённых значений;
с безопасной обработкой недоступных торговых инструментов
🌍 Поддерживаемые рынки
🇷🇺 Российские акции Московской биржи:
Сбербанк;
Газпром;
Лукойл;
Роснефть;
Новатэк;
Норникель;
Полюс;
Татнефть;
ВТБ;
Яндекс.
₿ Криптовалюты:
Bitcoin;
Ethereum;
Solana;
BNB;
XRP;
Dogecoin;
Cardano;
Avalanche;
Chainlink;
Toncoin.
Все тикеры можно изменить в настройках индикатора.
⚙️ Основные возможности
✅ Скринер акций и криптовалют
✅ Одновременный анализ 20 инструментов
✅ Торговые сигналы LONG и SHORT
✅ Раннее обнаружение движения
✅ Автоматический рейтинг активов
✅ Анализ тренда, объёма, RSI, ADX и DMI
✅ Относительный объём и Flow
✅ Индикатор без перерисовки
✅ Настраиваемый таймфрейм
✅ Алерты PulseWire
✅ Премиальный интерфейс EVA
✅ Безопасная обработка недоступных тикеров
⚠️ Важная информация
EVA Ai+ Radar является аналитическим инструментом и не представляет собой инвестиционную рекомендацию. Сигналы индикатора необходимо оценивать совместно с рыночным контекстом, управлением капиталом и контролем риска.
🧬 EVA Ai+ Radar is a professional PulseWire market scanner designed to help traders quickly identify strong opportunities across major cryptocurrencies and Russian stocks.
The screener analyzes up to 20 markets simultaneously, calculates a priority score for every symbol, and automatically ranks instruments according to current trend strength and market momentum. Instead of manually switching between multiple charts, traders receive a compact premium dashboard with a structured market overview.
🔎 What EVA Ai+ Radar analyzes
For every selected symbol, the system evaluates:
short-term and medium-term trend direction;
price position relative to exponential moving averages;
trend strength using ADX and DMI;
RSI momentum;
relative trading volume;
directional market Flow;
price change;
final signal strength and priority score.
📊 Screener signals
🟢 LONG — confirmed bullish advantage and positive market direction.
🔴 SHORT — confirmed bearish advantage and negative market direction.
🟡 EARLY ↑ / EARLY ↓ — an emerging directional setup detected before the strict signal threshold is reached.
⚪ WATCH — the asset does not currently have enough directional advantage for a confirmed signal.
⚡ Two scanning modes
RADAR — strict mode designed to identify confirmed LONG and SHORT signals.
EARLY — expanded mode that also identifies assets where a new directional move may be starting.
🛡️ Non-repainting calculation
By default, the screener uses confirmed data from closed candles on the selected timeframe:
no lookahead_on;
no historical signal backfilling;
no repainting of confirmed values;
safe processing of unavailable or unsupported symbols.
If one selected ticker is temporarily unavailable, the remaining markets continue to be calculated normally.
💎 Premium EVA dashboard
The dashboard displays:
market ranking;
symbol;
LONG, SHORT, or EARLY signal;
signal strength;
percentage price change;
RSI and relative volume;
directional Flow;
number of active LONG, SHORT, and EARLY signals;
selected timeframe and calculation mode.
The visible list can be adjusted from 5 to 20 rows, while all enabled markets continue to be analyzed.
🔔 PulseWire alerts
The screener includes three alert conditions:
confirmed LONG signal detected;
confirmed SHORT signal detected;
EARLY directional setup detected.
Alerts can be configured using the standard PulseWire alert system.
🌍 Supported markets
🇷🇺 Russian stocks:
Sberbank;
Gazprom;
Lukoil;
Rosneft;
Novatek;
Norilsk Nickel;
Polyus;
Tatneft;
VTB;
Yandex.
₿ Cryptocurrencies:
Bitcoin;
Ethereum;
Solana;
BNB;
XRP;
Dogecoin;
Cardano;
Avalanche;
Chainlink;
Toncoin.
Every symbol can be changed through the indicator settings.
⚙️ Main features
✅ PulseWire stock and crypto screener
✅ Simultaneous analysis of 20 symbols
✅ LONG and SHORT trading signals
✅ Early trend detection
✅ Automatic market ranking
✅ Trend, volume, RSI, ADX, and DMI analysis
✅ Relative volume and directional Flow
✅ Non-repainting indicator
✅ Custom scanning timeframe
✅ PulseWire alerts
✅ Premium EVA interface
✅ Safe invalid-symbol handling
⚠️ Disclaimer
EVA Ai+ Radar is an analytical and educational tool. It does not provide financial or investment advice. Every signal should be evaluated together with market context, position sizing, risk management, and independent analysis. Indicator
Squeeze Breakout Signals [TBalgo]Squeeze Breakout Signals spots when volatility compresses, then flags breakout long and short signals when price escapes the band after a tight zone.
Overview
This overlay indicator maps volatility compression and breakout direction on your chart. It builds dynamic SMA bands, detects when band width ranks in the lowest part of recent history (squeeze / tight zone), and fires signals only when price breaks the upper or lower band after compression.
Built for traders who want a clean squeeze → breakout workflow without clutter.
How it works
1. Bands — SMA midline + standard-deviation upper/lower bands
2. Tight zone — band width percentile rank vs lookback; when rank is low, market is in a squeeze
3. Signals — long when price crosses above the upper band after a tight bar; short when price crosses below the lower band after a tight bar
4. Guide lines — optional entry, risk (opposite band), and reward level based on band width
Features
- Green/red squeeze bands with tight-zone background wash
- Diamond markers on breakout signals
- Optional entry labels (`TB Long` / `TB Short`)
- HUD chip showing **TIGHT** or **LIVE** state
- Full display toggles — turn bands, signals, tags, guides, or HUD on/off
- Custom colors for bull, bear, and neutral states
- Built-in alerts for long, short, squeeze start, and expansion
Settings
Display — Bands · Tight Zone · Signals · Tags · Guide Lines · HUD
Engine
- **Length** — SMA / band period (default 50)
- **Std Mult** — band width multiplier (default 2.0)
- **Rank Lookback** — history for squeeze detection (default 100)
- **Tight Rank ≤** — max percentile to count as tight (default 20)
- **Reward × Width** — target distance as multiple of band width (default 1.5)
| Alert | When it fires |
|---|---|
| TB Squeeze Long | Bullish breakout after tight zone |
| TB Squeeze Short | Bearish breakout after tight zone |
| TB Squeeze Tight | Compression / squeeze begins |
| TB Squeeze Expand | Compression ends |
---
Suggested use
- **Higher timeframes (1H–1D):** default settings often work well for swing context
- **Lower timeframes (1–15m):** try shorter Length (20–35) and lower Tight Rank (10–15)
- Wait for **TIGHT** on the HUD, then trade only confirmed diamond signals
- Use guide lines as reference — not automatic trade execution
Pairs well with volume, structure, or liquidity tools on the same chart.
---
License
Original TBalgo indicator.
Licensed under Mozilla Public License 2.0 — free to use and modify with attribution.
Disclaimer
For education and research only. Not financial advice. Past signals do not guarantee future results. Always manage risk and do your own analysis before trading.
Indicator
AlgoForex PULSE Momentum & Volatility CompassAlgoForex PULSE is a single-pane trend, momentum and volatility read-out. It replaces the usual stack of three separate indicators — a moving average, an oscillator and a volatility gauge — with one adaptive framework drawn directly on price.
WHY IT EXISTS
A fixed-period moving average has one setting and two problems: it lags in a trend and whipsaws in a range. Most traders answer this by adding an oscillator in a lower pane and a volatility filter somewhere else, then spend the session moving their eyes between three places. PULSE folds those three jobs into one object on the chart.
HOW THE BASELINE WORKS
The baseline is an adaptive average driven by an efficiency ratio. For the chosen lookback it measures:
• net directional travel = |price now − price N bars ago|
• total travel = the sum of every bar-to-bar move over the same N bars
The ratio of the two is the efficiency ratio. Near 1, almost all movement went one way, so the average is allowed to accelerate toward price. Near 0, price covered a lot of distance and ended up nowhere, so the average slows down and flattens. The smoothing constant is squared, which makes the transition between the two states sharper than a linear blend.
The practical effect: the line tracks trends closely, then stops reacting to noise when the market goes sideways.
AURORA BANDS
Three ATR-scaled layers are drawn on each side of the baseline and filled with the live trend colour. They serve two purposes at once:
• the WIDTH shows current volatility — the cloud breathes as ATR expands and contracts
• the POSITION of price inside the cloud shows how stretched the move is
A close hugging the outer band is an extended move. A close oscillating around the baseline is a market with no commitment.
TREND STATE (with hysteresis)
The trend does not flip the moment price touches the baseline. It requires a close beyond baseline ± (Trend Trigger × ATR), default 0.5× ATR. This buffer is the difference between a handful of meaningful flips per session and dozens of meaningless ones. Raise it for fewer, slower signals; lower it for a more reactive read.
Flips are marked with and labels.
MOMENTUM SCORE (0-100)
Rather than a second pane, momentum is reduced to one number:
Momentum = 55 × normalised position inside the bands + 45 × RSI
The position component is clamped to ±1 so a single spike bar cannot dominate the reading. The result drives three things: the gauge in the dashboard, the candle colour gradient, and the surge markers (small dots) fired when the score crosses the bullish or bearish levels.
CONVICTION
The dashboard shows the raw efficiency ratio as a percentage. This is deliberately kept separate from the momentum score because the two answer different questions:
• Momentum = which direction, how strongly
• Conviction = how clean that movement was
A high momentum score with low conviction is a move fighting through chop. High on both is the condition worth acting on.
SQUEEZE RADAR
Current ATR is compared against its own percentile over a lookback window (default: bottom 25% of the last 100 bars). While ATR sits in that bottom band the background is tinted, marking compression. The bar where ATR climbs back out is marked with a the expansion point.
Compression tells you nothing about direction, only that the range is unusually tight. Pair it with the trend state for a directional bias.
HOW TO USE IT
1. Read the trend colour first — it sets your bias for the session.
2. Check Conviction. Below roughly 20% the market is not paying trend-followers.
3. Wait for price to pull back toward the baseline rather than chasing the outer band.
4. Treat a squeeze release in the direction of the trend as a timing cue, not a signal on its own.
5. Momentum surge dots confirm strength — they are not standalone entries.
SETTINGS THAT MATTER MOST
• Adaptive Length — the responsiveness of the whole system. Lower = faster.
• Trend Trigger ( ATR) — signal frequency. The single most useful dial here.
• Squeeze Percentile — how rare a "squeeze" should be. Lower = stricter.
ALERTS
Bullish trend flip Bearish trend flip Bullish momentum surge Bearish momentum surge Squeeze started Squeeze release.
NOTES
Works on any symbol and any timeframe. The dashboard is bilingual (English) and can be switched in the settings.
This indicator is an analysis tool. It does not predict price and it is not financial advice. No indicator has an edge on its own — use it inside a plan that includes risk management and position sizing. Past behaviour of any tool does not guarantee future results. Indicator
Adaptive Cycle Momentum Oscillator [ZurvanEG]⯁ Adaptive Cycle Momentum Oscillator
◇ Overview
MOM is a cycle-adaptive momentum oscillator built to present market direction, strength, fatigue, volatility compression and saturation within one coherent framework.
Unlike conventional momentum oscillators that apply the same lookback to every market condition, MOM can adjust its momentum window to the market’s active rhythm. This allows its response to become faster or slower as market behaviour changes, while a fixed-length mode remains available for users who require consistent settings.
Beyond measuring momentum, MOM adds context to the reading. It distinguishes strengthening movement from fading pressure, reduces the influence of momentum formed during volatility compression, identifies statistically unusual momentum zones, and detects confirmed divergence structures.
The objective is not to produce more signals or predict every reversal. It is to provide a cleaner and more informative view of momentum—showing not only its direction, but also the conditions under which it is developing.
◈ Key Features
◇ Adaptive Momentum
Automatically adjusts the momentum lookback as market rhythm changes. Fixed mode can be selected whenever a constant length is preferred.
◇ Momentum Regime
Classifies momentum as bullish, bearish or neutral. Separate entry and exit levels reduce unstable regime switching around the dead zone.
◇ Strength & Fatigue
The line gradient shows direction and magnitude, while color strength distinguishes expanding momentum from momentum fading toward zero.
◇ Volatility Squeeze
Detects compressed volatility and reduces momentum produced inside quiet conditions. Squeeze intensity can also be displayed as a variable background.
◇ Saturation Bands
Adaptive upper and lower bands identify momentum readings that are extreme relative to the oscillator’s own recent behavior. They should be treated as saturation zones, not automatic reversal signals.
◇ Divergence
Detects confirmed regular and hidden bullish or bearish divergence. Signals can optionally be restricted to pivots occurring beyond the saturation bands to filter weaker mid-range structures.
◇ Visuals & Information
Optional candle coloring transfers the oscillator’s momentum gradient to the main chart. A compact table displays the current regime, momentum value and slope state, with optional cycle, length, squeeze and divergence diagnostics.
◇ Alerts
Independent alerts are available for:
⬦ Bullish and bearish regime shifts
⬦ Upper and lower saturation contacts
⬦ Squeeze entry and release
⬦ Confirmed bullish and bearish divergence
◈ Interpretation
Adaptive Cycle Momentum Oscillator helps answer:
⬦ Is momentum bullish, bearish or neutral?
⬦ Is the current move strengthening or fading?
⬦ Was momentum produced during expansion or compression?
⬦ Is the reading unusually saturated for this market?
⬦ Has a meaningful divergence been confirmed?
◈ Notes
⬦ Adaptive mode requires sufficient historical data for cycle estimation.
⬦ Divergences appear after pivot confirmation and are therefore delayed by design.
⬦ Saturation does not guarantee reversal, especially during strong trends.
⬦ Squeeze attenuation provides context; it does not predict breakout direction.
◈ Conclusion
Adaptive Cycle Momentum Oscillator is designed as a complete momentum-analysis framework rather than a simple oscillator or signal generator. It combines adaptive measurement, stable directional regimes, strength and fatigue colouring, volatility context, dynamic saturation bands and confirmed divergence in a single visual system.
By adapting to market rhythm and evaluating momentum within its surrounding conditions, MOM helps separate meaningful directional pressure from weak movement produced inside noise or compression. Its visual structure is intended to make changes in direction, intensity and exhaustion recognizable without requiring several overlapping indicators.
MOM does not attempt to replace price structure, risk management or trading confirmation. Its role is to provide a clearer and more consistent momentum perspective that can support trend analysis, pullback evaluation, saturation monitoring and divergence assessment across different instruments and timeframes.
Indicator
True Strength Index Ribbon
True Strength Index Ribbon: A new way to visualize momentum
Most TSI indicators answer a simple question:
"Is momentum bullish or bearish?"
The True Strength Index Gradient Ribbon was designed to answer a much more useful question:
"How committed is momentum to that direction?"
Instead of displaying two ordinary oscillator lines that constantly cross and overlap, this indicator transforms the relationship between the TSI and its signal line into a continuously expanding and contracting gradient ribbon.
The result is an oscillator that allows traders to recognize momentum shifts almost instantly while dramatically reducing the visual clutter common to traditional TSI implementations.
Why a ribbon?
Momentum isn't simply bullish or bearish.
It has strength.
It has conviction.
It accelerates.
It weakens.
It compresses before expanding again.
The width of the ribbon naturally visualizes the distance between the TSI and its signal line.
A widening ribbon suggests increasing directional commitment.
A narrowing ribbon often indicates weakening momentum or an approaching transition.
Instead of mentally measuring the distance between two moving lines, your eyes recognize it immediately.
Designed for mean reversion and trend trading
While the indicator performs well as a traditional trend-following oscillator, it was specifically developed with mean reversion trading in mind.
Markets spend surprisingly little time at statistically stretched levels.
By combining directional momentum with configurable extension zones, traders can quickly identify when momentum is beginning to reverse after reaching unusually extended conditions.
The indicator intentionally avoids telling traders what to buy or sell.
Instead, it provides objective information that can be combined with price action, structure, moving averages, VWAP, volume, or any existing trading methodology.
Key Features
• Innovative gradient ribbon visualization
• Multiple signal moving average options:
EMA
SMA
WMA
RMA
HMA
VWMA
ALMA
• Higher-timeframe smoothing without changing your chart timeframe
• Four display modes:
Ribbon Only
Signal Line Only
Solid Signal Line Only
Ribbon + Signal Line
• Customizable bullish, bearish, neutral, and extreme colors
• Configurable extension levels for progressively stretched market conditions
• Optional extension-zone shading
• Live Extension Grade panel showing:
Direction
Degree of extension
Current TSI value
• Bullish and bearish crossover alerts
• Extension alerts for every major threshold
Timeframe smoothing
One of the more unique capabilities of this indicator is timeframe-based smoothing.
Instead of requiring traders to constantly switch chart timeframes, the script can internally scale its smoothing calculations to approximate the behavior of a higher timeframe while remaining on the current chart.
This produces cleaner momentum structure while preserving the convenience of lower-timeframe execution.
Extension Grades
Rather than treating all overbought and oversold conditions equally, this indicator classifies momentum into progressively stronger extension levels.
Examples include:
• Moderately Extended
• Extended
• Very Extended
• Extremely Extended
The goal isn't to predict reversals simply because a market reaches an extreme.
Instead, these classifications provide context so traders can better judge when momentum has become unusually stretched.
Built for customization
Every trader sees momentum differently.
Nearly every visual element can be customized, including:
Colors
Signal moving average
Signal smoothing
Ribbon visibility
Timeframe smoothing
Extension thresholds
Zone shading
Signal line appearance
This allows the indicator to adapt to different markets, different trading styles, and different visual preferences.
Design Philosophy
The best indicators don't make trading decisions.
They improve the trader's ability to understand market behavior.
The True Strength Index Ribbon was built around one simple objective:
Transform momentum from something you calculate...
into something you can immediately see.
If this script helps your trading, consider leaving a Like and sharing your feedback. Suggestions for future improvements are always welcome.
Disclaimer
This indicator is provided for educational and informational purposes only. It is designed to assist with market analysis and should not be considered financial or investment advice. No indicator can predict future market movements or guarantee profitable trades. Always conduct your own research, use appropriate risk management, and consider multiple factors before making any trading decisions. Indicator
AlphaVault - Regime FilterTwo long-term trend filters and one rule: price above both is a bull regime, below both is
a bear regime, anything in between is neutral. It plots the filters, tints the background
by state, marks each change, and shows how long the current state has held.
NO REPAINTING. Both filters are read from the previous COMPLETED daily and weekly bar
(lookahead_off plus a one-bar offset), so the regime shown for a closed bar never changes
afterwards. This is worth verifying yourself on any indicator you did not write: scroll
back, note the state on an old bar, reload the chart, and check it is the same.
What it is for: deciding whether to be doing anything at all. Most trend systems lose the
majority of their money trying to trade against a long-term downtrend, and a neutral state
is genuinely common — roughly a fifth of all bars on BTC since 2018. Treating "no clear
regime" as a valid answer rather than a gap to be filled is most of the value here.
What it is not: an entry signal. It tells you which direction is permitted, not when to
act, and it will keep you out of some large moves that begin before the filters confirm.
It is deliberately slow. On BTC it changes state a handful of times a year.
Defaults are a 200-period SMA on daily closes and a 20-period EMA on weekly closes. Both
lengths are configurable, though the defaults are the ones worth arguing about — a filter
you re-tune until it looks good on the chart in front of you has stopped being a filter.
Alerts fire on a turn to bull, a turn to bear, or any change. Regime changes are rare by
construction; an alert that fires constantly is one you learn to ignore.
Open source. Read it, change it, take it apart. Indicator
3D Trend Vortex [BOSWaves]3D Trend Vortex - Slope-Adaptive Gradient Bands with Polyline 3D Extrusion and Zone Entry Signal Detection
Overview
3D Trend Vortex is a slope-driven trend band system that constructs a pair of eight-layer gradient bands positioned above and below price using ATR-scaled offsets from a configurable moving average baseline, where band width breathes inversely with slope magnitude, candle gradient intensity reflects normalized slope strength, and a polyline-based three-dimensional extrusion renders the outer and inner band edges as volumetric ribbon geometry that follows the bands across the configured display length.
Instead of relying on static symmetric bands or fixed volatility channels, the band width contracts when trend slope is strong and expands when slope is flat or weakening, producing a visual breathing effect that communicates momentum intensity through band geometry rather than through a separate indicator. The eight gradient fill layers within each band progress from near-transparent at the inner edge to full opacity at the outer edge, creating a visual depth effect that reinforces the three-dimensional extrusion rendered at the current bar.
This creates a trend framework where every visual layer simultaneously communicates the same underlying information from a different angle. The gradient bands reveal momentum intensity through their width. The candle gradient communicates slope conviction through brightness. The 3D extrusion at the band edges provides spatial depth cues that make the band structure immediately readable across varying zoom levels. Signal labels fire when price first enters either band after the cooldown period, identifying the specific bars where price has moved into the zone of interest defined by the ATR-offset band boundary.
Price is therefore tracked not just for its directional relationship to the basis MA but for its position within or outside a dynamically breathing gradient band system whose visual geometry encodes slope strength and momentum quality on every bar.
Conceptual Framework
3D Trend Vortex is founded on the principle that trend band visualization should communicate momentum quality through the geometric properties of the bands themselves rather than requiring separate momentum indicators, and that introducing three-dimensional spatial depth into the band rendering provides immediate structural legibility that flat two-dimensional bands cannot achieve regardless of color or transparency settings.
Traditional band indicators apply fixed widths or static volatility multiples that remain visually identical whether momentum is surging or stalling, requiring traders to consult separate oscillators for conviction context. This framework embeds conviction directly into band geometry through the breathing width mechanism, where strong slope produces tighter, more concentrated bands reflecting focused directional commitment and weak slope produces wider, more diffuse bands reflecting reduced momentum quality. The three-dimensional extrusion layer adds spatial depth cues that reinforce the structural separation between the supply zone above price and the demand zone below.
Three core principles guide the design:
Band width should adapt to slope magnitude, contracting during strong momentum and expanding during low-conviction conditions, encoding trend health directly into the geometric properties of the bands without requiring a separate momentum indicator.
The gradient fill system across eight layers within each band should provide visual depth that reinforces the three-dimensional extrusion, creating a consistent spatial reading between the flat fill and the extruded geometry at the current bar edge.
Signals should fire on first entry into band territory after the cooldown period rather than on crossover of a single line, capturing the structural significance of price reaching the offset zone while preventing signal clustering during extended band interactions.
This shifts trend band analysis from static channel monitoring into a momentum-adaptive visual system where band breathing, candle intensity, and three-dimensional geometry collectively communicate trend conviction across every bar of the display window.
Theoretical Foundation
The indicator combines configurable moving average baseline selection, ATR-based band offset and width calculation with slope-driven breathing modulation, eight-level gradient fill construction across inner-to-outer band subdivisions, polyline-based three-dimensional extrusion geometry using depth offset coordinates, and slope-normalized candle gradient coloring.
The basis MA is computed in the selected type over the configured length and the three-bar slope is measured as the difference between current and three-bar-lagged values. The slope magnitude is normalized against its highest value over an eighty-bar window, producing a 0-1 score that drives the breathing multiplier applied to the band width. ATR is smoothed over fifty bars to reduce sensitivity to individual volatility spikes, providing a stable scaling unit for both band offset and width calculations. The eight gradient fill layers divide the inner-to-outer band distance into equal steps with progressively increasing opacity, connecting smoothly to the polyline faces of the 3D extrusion that render the outer edge face, top face, and inner top face as separate filled polygon regions at configurable depth offsets.
Four internal systems operate in tandem:
Slope-Adaptive Band Engine : Calculates ATR-smoothed band offset and width, applies EMA smoothing to all four band edges, and modulates total band width by a breathing factor derived from normalized slope magnitude so that bands contract proportionally during high-momentum conditions.
Eight-Layer Gradient Fill System : Subdivides the inner-to-outer band width into eight equal steps and fills each interval with progressively decreasing transparency, producing a continuous opacity gradient from the near-transparent inner edge to the full-opacity outer edge across both the top and bottom bands.
Three-Dimensional Extrusion Engine : On the last bar, constructs polyline polygon arrays for the outer face, top face, and inner top face of each band by combining current bar coordinates with depth-offset coordinates at the configured bar and ATR depth, rendering six filled polyline regions that create the illusion of volumetric band geometry extending from the current bar edge into the chart space.
Zone Entry Signal System : Monitors price crossing into the top or bottom band on each bar, applying independent cooldown tracking for each side to prevent signal clustering during extended band interactions.
This design allows band geometry, candle coloring, and 3D extrusion to all derive from the same underlying slope and ATR measurements, ensuring visual consistency across every layer of the indicator.
How It Works
3D Trend Vortex evaluates price through a sequence of slope-aware band construction and visualization processes:
Basis MA Calculation : The selected moving average type is calculated over the configured length, providing the directional baseline from which all band positions and slope measurements are derived.
ATR Smoothing : Raw ATR over fourteen bars is smoothed with a fifty-bar SMA to produce a stable volatility unit that prevents individual spike bars from distorting band positioning across the display window.
Slope Measurement and Normalization : The three-bar change in basis MA is measured and its absolute value is normalized against the highest absolute slope over eighty bars, producing a 0-1 score reflecting how strong the current slope is relative to recent momentum history.
Breathing Width Calculation : The normalized slope score is scaled and subtracted from 1.0 to produce a breathing multiplier that reduces band width proportionally during high-slope conditions, causing bands to contract during strong momentum and expand during low-conviction flat conditions.
Band Edge Calculation and Smoothing : Inner and outer edges for both the top and bottom bands are calculated by adding and subtracting ATR-scaled offset and width values from the basis MA, then smoothed with the configured EMA length to prevent jagged edge movement.
Eight-Layer Gradient Fill Rendering : The inner-to-outer distance of each band is divided into eight equal steps and plot-fill pairs are rendered at each subdivision with transparency increasing from outer to inner, producing a smooth opacity gradient across the band depth.
Candle Gradient Coloring : The normalized slope score is power-transformed and mapped to a gradient from a dimmed version of the trend color at low slope to full saturation at high slope, coloring chart candles proportionally to current momentum conviction.
Zone Entry Detection : Price crossing into the top band from below or the bottom band from above is detected with independent cooldown tracking for each side. When entry is confirmed and cooldown is satisfied, a signal label is placed at the bar high or low respectively.
3D Extrusion Construction : On the last bar, polyline arrays are constructed for each of the six extruded faces using combinations of current and depth-offset bar indices and price coordinates, rendering the outer face, top face, and inner top face for both the top and bottom bands as filled polygon regions.
Together, these elements form a continuously updating slope-adaptive band system where gradient geometry, candle brightness, and three-dimensional extrusion simultaneously communicate trend direction, momentum conviction, and structural band positioning across the full display window.
Interpretation
3D Trend Vortex should be interpreted as a slope-driven momentum band system with spatial depth visualization and zone entry monitoring:
Bullish Trend State (Green) : Active when the basis MA slope is positive, with the bottom gradient band rendered in green and candles coloring green with intensity proportional to slope strength.
Bearish Trend State (Red) : Active when the basis MA slope is negative, with the top gradient band rendered in red and candles coloring red with intensity proportional to slope strength.
Band Width Dynamics : Narrow bands indicate strong slope momentum with high directional conviction. Wide bands indicate weak slope with reduced momentum quality. Monitoring band width evolution provides real-time conviction context without requiring a separate momentum oscillator.
Eight-Layer Gradient Fill : The opacity gradient from inner to outer edge provides visual depth within each band, with the near-transparent inner boundary representing the threshold where price enters the zone of interest and the fully opaque outer boundary representing the extreme of the ATR-scaled offset distance.
3D Extrusion : The three-dimensional polyline faces rendered at the current bar edge provide spatial depth cues that reinforce the structural separation between the top supply zone and bottom demand zone, making band positioning immediately readable across varying chart zoom levels.
▲ Buy Signals : Green upward triangles mark the first bar where price enters the bottom band after the cooldown period, identifying price reaching the lower ATR-offset zone of interest.
▼ Sell Signals : Red downward triangles mark the first bar where price enters the top band after the cooldown period, identifying price reaching the upper ATR-offset zone of interest.
Candle Gradient : Price candles brighten toward full trend color saturation as slope strengthens and dim toward a muted version of the trend color as slope weakens, providing bar-level momentum conviction readings directly on the candlestick display.
Band width dynamics, candle gradient intensity, signal zone entry, and 3D extrusion depth collectively provide more momentum and structural context than any element in isolation.
Signal Logic & Visual Cues
3D Trend Vortex presents two zone entry signal types with independent cooldown enforcement:
Buy Signal (▲) : Green triangle placed below the bar when price first closes below the bottom band inner edge after the configured cooldown period has elapsed since the previous buy signal, identifying price entry into the lower ATR-offset demand zone.
Sell Signal (▼) : Red triangle placed above the bar when price first closes above the top band inner edge after the configured cooldown period has elapsed since the previous sell signal, identifying price entry into the upper ATR-offset supply zone.
Independent per-side cooldown tracking prevents consecutive signals on the same side while allowing the opposite side to signal freely, ensuring that transitions between upper and lower zone interactions are captured without artificial suppression.
Alert generation covers buy and sell zone entry events for systematic monitoring workflows.
Strategy Integration
3D Trend Vortex fits within momentum-informed band interaction and zone-based directional approaches:
Band Width Conviction Reading : Use band width as a continuous momentum quality gauge. Entering a position during a narrow-band high-slope period indicates stronger directional conviction than entries during wide-band low-slope conditions where momentum quality is reduced.
Zone Entry Signal Framework : Use buy and sell signals as structural alerts that price has reached the ATR-offset zone of interest rather than as standalone entry triggers. Evaluate slope direction and band width at the signal bar to assess whether the zone entry occurs during supporting or deteriorating momentum conditions.
Candle Gradient Momentum Monitoring : Use the brightness of trend-colored candles as a bar-level momentum reading throughout the trend. Progressively brightening candles indicate strengthening slope. Dimming candles within an established trend suggest momentum deterioration before band width changes confirm it visually.
3D Extrusion Spatial Reference : Use the three-dimensional band faces at the current bar edge as a visual anchor for where the current supply and demand zones sit relative to price, with the depth extending into future chart space providing an intuitive structural reference for the zone boundaries.
Basis Type Selection : Use EMA for standard responsive trend tracking. Use HMA for lower-lag applications requiring faster slope detection with minimal smoothing delay. Use WMA for weighted recent-bar emphasis. Use SMA for a simpler unweighted baseline reference.
Multi-Timeframe Band Alignment : Apply higher-timeframe slope direction and band positioning as a directional bias filter, engaging with lower-timeframe zone entry signals only when they align with the established higher-timeframe momentum state.
Technical Implementation Details
Basis Engine : Configurable EMA, SMA, WMA, or HMA with slope measurement and normalization against eighty-bar highest absolute slope
Band Construction : Smoothed ATR offset and width with slope-derived breathing modulation across four band edges
Gradient System : Eight equal subdivisions between inner and outer band edges with plot-fill pairs at progressively increasing transparency
3D Extrusion : Polyline polygon arrays for outer face, top face, and inner top face of each band using depth-offset bar index and ATR height coordinates
Signal Logic : Zone entry detection with independent per-side cooldown bar tracking
Candle Coloring : Power-transformed slope normalization mapped to trend-color gradient
Performance Profile : 3D extrusion triggered only on last bar with full polyline rebuild and cleanup each render cycle, configurable display length cap for object management
Optimal Application Parameters
Timeframe Guidance:
1 - 5 min : Intraday zone monitoring for scalping with shorter basis length and tighter band offset for responsive zone positioning on fast intraday momentum
15 - 60 min : Session-level momentum band tracking with balanced basis length and moderate offset for meaningful zone separation across typical intraday swings
4H - Daily : Swing-level momentum band analysis with longer basis length for sustained slope readings and wider offset reflecting larger price excursions from trend
Suggested Baseline Configuration:
Basis Length : 21
Basis Type : EMA
Band Offset (ATR×) : 3.0
Band Width (ATR×) : 0.9
Band Smoothing : 65
3D Display Length : 400
3D Depth (Bars) : 8
3D Height (ATR×) : 0.5
Show Signals : Enabled
Signal Cooldown : 20
Color Candles : Enabled (requires disabling original chart candles in chart settings)
These suggested parameters should be used as a baseline; their effectiveness depends on the instrument's volatility characteristics, typical ATR range, and preferred band sensitivity, so fine-tuning is expected for optimal performance.
Parameter Calibration Notes
Use the following adjustments to refine behavior without altering the core logic:
Bands too far from price : Decrease Band Offset to bring the inner band edge closer to price, reducing the ATR distance required for price to reach the signal zone.
Bands too close to price : Increase Band Offset to push bands further from price, requiring more significant price extension before zone entry signals fire.
Band width breathing too pronounced : The breathing effect scales with slope normalization. On instruments with highly variable slope the breathing range may appear extreme. Reduce Band Width to compress the overall width range and make breathing less visually dramatic.
Bands too jagged or smooth : Adjust Band Smoothing to control EMA smoothing on band edges. Higher values produce smoother, more gradual band curves. Lower values produce more responsive edges that track price structure changes faster.
Too many signals : Increase Signal Cooldown to enforce greater bar separation between consecutive zone entry signals on the same side, focusing attention on less frequent but more structurally spaced entries.
3D extrusion too deep or shallow : Adjust 3D Depth (Bars) to change the horizontal extent of the extruded faces and 3D Height (ATR×) to change the vertical depth of the extrusion, calibrating the spatial effect to the chart's aspect ratio and zoom level.
3D extrusion covers too many or too few bars : Adjust 3D Display Length to control how many recent bars receive the polyline extrusion rendering, reducing for performance on slower systems or increasing to extend the visual depth effect further back into price history.
Adjustments should be incremental and evaluated across multiple session types rather than isolated market conditions.
Performance Characteristics
High Effectiveness:
Trending markets with clear directional momentum where slope normalization produces meaningful band breathing dynamics and candle gradient provides reliable conviction context throughout the trend
Instruments with consistent ATR behavior where the volatility-scaled band offset positions zones at structurally meaningful distances from price across varying market conditions
Zone interaction strategies where price reaching the ATR-offset band boundary identifies structurally significant extension events worth monitoring for reversal or continuation behavior
Visualization-focused workflows where the three-dimensional band geometry provides spatial chart reading advantages that improve structural awareness relative to flat two-dimensional bands
Reduced Effectiveness:
Choppy, trendless markets where slope alternates rapidly in direction, causing frequent trend color flips and band breathing that produces no sustained directional momentum context
Extremely high-volatility instruments where ATR spikes push band offsets to distances so large that price rarely reaches the zone boundaries and signals become infrequent regardless of cooldown settings
Low-ATR instruments where the extrusion height and band width produce visually imperceptible geometry requiring significant parameter adjustment to produce meaningful spatial depth
Markets with highly irregular slope profiles where the eighty-bar normalization window consistently registers outlier slope readings that compress the breathing range for typical bars
Consolidation environments where flat slope produces maximum band width expansion and near-neutral candle coloring simultaneously, reducing the visual differentiation that makes momentum context readable
Integration Guidelines
Confluence : Combine with BOSWaves order flow tools, structural analysis, or momentum oscillators to validate zone entry signals with broader analytical context before acting on band boundary interactions
Band Breathing Awareness : Monitor band width evolution throughout established trends as a continuous slope health indicator. Progressively widening bands during a trend suggest slope is weakening and conviction is diminishing before price structure confirms the change.
Candle Gradient Divergence : Watch for price extending toward the outer band while candles are simultaneously dimming, indicating momentum deterioration during price extension that may precede reversal toward the basis MA.
3D Depth Calibration : Adjust 3D Depth and Height parameters until the extrusion provides clear spatial depth without obscuring price action. The extrusion is a visualization aid and should complement rather than dominate the chart reading experience.
State Discipline : Maintain directional bias aligned with current slope direction until slope reverses. Zone entry signals within the same trend direction represent extension events rather than reversal triggers and should be interpreted as monitoring alerts rather than directional change signals.
Disclaimer
3D Trend Vortex is a professional-grade slope-adaptive trend visualization and zone monitoring tool. It uses moving average slope normalization with ATR-scaled breathing band construction and polyline three-dimensional extrusion but does not predict future price movements. Results depend on market conditions, instrument momentum characteristics, parameter selection, and disciplined execution. BOSWaves recommends deploying this indicator within a broader analytical framework that incorporates order flow context, structural analysis, and comprehensive risk management. Indicator
Macro Trend Split Profile [ChartPrime]Macro Trend Split Profile
🔶 OVERVIEW
Traders often lose focus during long trends, failing to realize where the true market value is being built. The Macro Trend Split Profile bridges the gap between directional trend-following and volume-profile structure. It anchors a profile analysis at the start of every macro trend leg, splitting the histogram into Bullish and Bearish components.
Instead of seeing a combined profile, this script visually separates where bulls were aggressive versus where bears attempted to defend, providing a clear map of which price levels represent the highest conviction for either side.
🔶 HOW IT WORKS
The indicator executes its structural analysis through a three-stage engine:
Noise-Filtered Macro Trend Detection: At its core, the script utilizes a Supertrend engine with a noise-filter multiplier. This provides a clean, macro-directional baseline that ignores minor retracements and identifies high-conviction trend legs.
Trend-Start Profile Anchoring: Once a trend begins, the indicator initializes a memory array. It captures every candle in that trend leg and categorizes them as either Bullish (Close > Open) or Bearish (Close < Open).
Split-Histogram Mapping: Once the trend leg hits your minimum bar requirement, the indicator generates a dual-sided histogram at the start point of the trend. The Bullish profile expands to the right, while the Bearish profile expands to the left, allowing for an immediate visual comparison of institutional interest.
Dual Point of Control (POC) Tracking: The script calculates the Point of Control for both bulls and bears independently, drawing extended dashed lines across your chart that mark the exact price levels where each side has deposited the most structural weight.
🔶 KEY FEATURES
Independent POC Projection: Independently identifies the strongest bullish and bearish structural walls, helping you identify where the current trend will likely find support or resistance.
Automated Dashboard: A sleek, top-right status table provides the live macro trend direction and the exact price coordinates for the active Bullish and Bearish POC levels.
Dynamic Rescaling: The profile histogram automatically rescales based on the number of bars in a trend and the intensity of the volume distribution, ensuring the visual footprint always fits your chart perfectly.
Trend-Leg Sanitization: When a trend flips (e.g., from bullish to bearish), the script automatically purges the old data arrays and resets the profile engine, ensuring you are never analyzing "stale" historical order blocks.
🔶 TRADING APPLICATIONS
Trend-Leg Retracement Entries: During a strong trend, monitor the Point of Control line that matches your trend direction. A dip back into the Bullish POC (during a Bullish trend) represents a high-probability zone to reload positions at a institutional fair-value level.
Confluence for Reversals: If price approaches an opposing POC (e.g., Bearish POC during a Bullish trend), this marks a high-friction zone. These levels are prime candidates for taking partial profits, as they represent the most "defended" territory for the counter-trend side.
Macro Structure Shifts: If price closes consistently beyond the most recent POC projection, it indicates that the current trend has exhausted its structural support, often serving as a signal to tighten stop-losses or prepare for a potential macro trend flip.
🔶 SETTINGS
Macro Trend Length & Multiplier: Controls the sensitivity of the Supertrend. Higher values filter out aggressive noise and capture only the most significant primary trend legs.
Minimum Bars for Profile: Sets the threshold for how long a trend must persist before the profile begins to render, preventing false signals during short-lived, volatile consolidations.
Profile Resolution (Bins/Width): Customize the granularity of the histogram segments and the horizontal space the indicator occupies on your chart to suit your workspace preference.
🔶 CONCLUSION
The Macro Trend Split Profile is a surgical tool for trend traders. By splitting the volume profile into Bullish and Bearish components, it stops you from guessing where the "other side" is positioned and shows you exactly where the institutional battle lines are drawn. Indicator
