NORN WEAVE | FEHUOverview
NORN WEAVE ᚠ FEHU is a trend-following strategy built around one philosophy: survival first, profit second.
The core logic is three filters in sequence — EMA slope, Dow Theory swing structure, and ADX trend confirmation. All three must align before an entry is taken. If the market is ranging, the strategy stands aside.
What defines NORN WEAVE is how it protects what it earns. The Break Even Stop automatically moves the stop to entry price once floating profit reaches a threshold. The Footprint Delta Filter adds a second layer, blocking entries when BTC or ETH order flow contradicts the trade direction. Fewer trades. Fewer unnecessary losses. A drawdown profile that stays flat even across five years of volatile crypto markets.
This is not a strategy designed to make you rich overnight. It is designed to keep you in the game.
Performance Highlights (DOGE / 2H / 2021–2026)
Backtested on DOGE 2H from January 2021 to March 2026, with 0.055% commission included. Net profit +25.4%, max drawdown 1.71%, win rate 70.7%, profit factor 1.80, total trades 557.
Always backtest on your target asset before live trading.
Entry Conditions
Long: EMA rising AND Dow Theory trend up AND ADX above threshold.
Short: EMA falling AND Dow Theory trend down AND ADX above threshold.
Exit Conditions
TP1 triggers at ATR × Factor × 1, closing 30% of the position. TP2 at × 2, closing another 30%. TP3 at × 3, closing a further 30%. The Stop Loss closes the full position at a fixed percentage from entry. The Break Even Stop automatically triggers once floating profit reaches the BE threshold, closing the full position at entry price. A Trend Reversal — when Dow Theory swing flips — also closes the full position.
Footprint Delta Filter (Premium plan required)
Uses BTC or ETH footprint delta (buy volume − sell volume) as a directional confirmation filter. Blocks entries when order flow contradicts the trade direction. Meaningful reduction in false signals during ranging markets.
Parameters
EMA Period defaults to 58, recommended range 30–100. Use shorter values for high-volatility assets, longer for stable ones.
ATR Factor defaults to 3.8, recommended range 2.5–6.0. Controls TP distance — higher means wider targets.
Stop Loss defaults to -5.0%, recommended range -4 to -10%. Wider for volatile assets, tighter for BTC/ETH.
ADX Threshold defaults to 20.5, recommended range 15–28. Higher values produce fewer but cleaner trades.
Swing Length defaults to 13, recommended range 2–20. Larger values reduce sensitivity to minor swings.
BE Trigger defaults to 9.0%, recommended range 3–15%. Set below TP1 distance to protect profits before TP1 is reached.
Footprint Delta SMA defaults to 21, recommended range 1–50. Controls smoothing of the delta signal.
Recommended Settings
For meme coins such as DOGE and SHIB: EMA 44–58, ATR 3.5–5.0, stop loss -5 to -8%, ADX 18–22, BE trigger 7–10%.
For major assets such as BTC and ETH: EMA 55–80, ATR 2.5–4.0, stop loss -4 to -6%, ADX 20–25, BE trigger 5–8%.
For mid-cap alts such as SOL and SUI: EMA 35–55, ATR 4.0–5.5, stop loss -5 to -7%, ADX 18–23, BE trigger 6–10%.
For timeframe selection, an ADX threshold of 15–20 suits 1–5 minute charts. 18–23 suits 15 minutes to 1 hour. 20–25 suits 2–4 hour charts. Default settings are optimized for the 2H timeframe.
Visual Guide
The EMA line uses a 3-layer glow effect — teal when rising, red when falling. Dow Theory zones show a gradient from the current swing level to the current price. TP lines are semi-transparent, with TP1 the faintest and TP3 the most visible. The BE Stop line appears in gold only when the break even stop is active. A gray background indicates ADX is below the threshold — the strategy does not enter trades in this zone. An orange background means the Footprint Delta Filter is blocking entry. The status table shows all entry conditions and current state in real time, with a Japanese/English toggle.
概要
NORN WEAVE ᚠ FEHU は、「まず生き残る、利益はその次」 という一つの哲学から作られたトレンドフォロー型ストラテジーです。
エントリー条件はシンプルな3つのフィルターで構成されています——EMAの傾き、ダウ理論のスイング構造、ADXトレンドフィルター。この3つが同時に揃ったときだけエントリーします。レンジ相場と判断されたときは、何もせずに待ちます。
NORN WEAVEを特徴づけているのは、稼いだ利益をどう守るかという設計です。ブレークイーブンストップは、含み益が一定の閾値に達した瞬間に損切りラインをエントリー価格へ自動移動します。フットプリント・デルタフィルターはBTCまたはETHのオーダーフローを確認し、トレードの方向と逆行している場合はエントリーをブロックします。結果としてトレード数は絞られ、不要な損失が減り、ドローダウンが5年間の荒れた暗号資産市場でも極めて小さく抑えられています。
一夜にして資産を増やすストラテジーではありません。長くゲームに居続けるためのストラテジーです。
バックテスト結果
DOGEの2時間足、2021年1月から2026年3月まで、手数料0.055%を含む条件でバックテストを実施しています。総損益は+25.4%、最大ドローダウンは1.71%、勝率は70.7%、プロフィットファクターは1.80、トレード総数は557件です。
実運用の前に必ずご自身の対象銘柄でバックテストを行ってください。
エントリー条件
ロングエントリーはEMAが上向き、ダウ理論トレンドが上昇、ADXがしきい値以上の3条件が揃ったときに発動します。ショートエントリーはEMAが下向き、ダウ理論トレンドが下降、ADXがしきい値以上の3条件が揃ったときに発動します。
イグジット条件
TP1はエントリーからATR×倍率×1の地点でポジションの30%を決済します。TP2は×2の地点でさらに30%、TP3は×3の地点でさらに30%を決済します。損切りは設定した%を超えた時点でポジションを全決済します。ブレークイーブンストップは含み益がしきい値%に達した瞬間に自動発動し、エントリー価格でポジションを全決済します。ダウ理論のスイングが逆転したトレンド反転時も、ポジションを全決済します。
フットプリント・デルタフィルター（Premiumプラン以上が必要）
BTCまたはETHのフットプリント・デルタ（買い出来高から売り出来高を引いた値）を方向性確認フィルターとして使用します。オーダーフローがトレードの方向と逆行しているときはエントリーをブロックします。横ばい相場でのだましシグナルを大幅に削減します。
パラメーター
EMA期間のデフォルトは58で、推奨範囲は30〜100です。ボラティリティが高い銘柄は短め、安定した銘柄は長めに設定します。
ATR倍率のデフォルトは3.8で、推奨範囲は2.5〜6.0です。TP距離の基準となる値で、大きいほど利確ラインが遠くなります。
損切りのデフォルトは-5.0%で、推奨範囲は-4〜-10%です。ボラティリティが高い銘柄は広め、BTC・ETHなどはタイトに設定します。
ADXしきい値のデフォルトは20.5で、推奨範囲は15〜28です。高いほどトレード数が減り、精度が上がります。
スイング検出期間のデフォルトは13で、推奨範囲は2〜20です。大きいほど小さなスイングに反応しにくくなります。
BE発動しきい値のデフォルトは9.0%で、推奨範囲は3〜15%です。TP1到達距離より低めに設定することで、TP1到達前に元本を保護できます。
フットプリントSMA期間のデフォルトは21で、推奨範囲は1〜50です。デルタシグナルの平滑化期間です。
銘柄タイプ別おすすめ設定
ミーム系銘柄（DOGE・SHIBなど）ではEMAを44〜58、ATR倍率を3.5〜5.0、損切りを-5〜-8%、ADXしきい値を18〜22、BEトリガーを7〜10%に設定することを推奨します。
主要銘柄（BTC・ETH）ではEMAを55〜80、ATR倍率を2.5〜4.0、損切りを-4〜-6%、ADXしきい値を20〜25、BEトリガーを5〜8%に設定することを推奨します。
中堅アルト（SOL・SUIなど）ではEMAを35〜55、ATR倍率を4.0〜5.5、損切りを-5〜-7%、ADXしきい値を18〜23、BEトリガーを6〜10%に設定することを推奨します。
時間足については、1〜5分足ではADXしきい値を15〜20、15分〜1時間足では18〜23、2〜4時間足では20〜25に設定することを推奨します。デフォルト設定はDOGEの2時間足向けに最適化されています。
チャートの見方
EMAラインは3層のグロー効果で描画されます。上向きのときはティール、下向きのときはレッドで表示されます。ダウ理論ゾーンは現在のスイングレベルから現在価格へ向かうグラデーションで表示されます。TPラインは半透明で、TP1が最も薄く、TP3が最も濃く表示されます。BEストップラインはブレークイーブンストップが発動している間のみゴールドのラインで表示されます。グレーの背景はADXがしきい値以下の横ばいゾーンを示しており、このゾーンではエントリーは発生しません。オレンジの背景はフットプリント・デルタフィルターがエントリーをブロックしていることを示します。ステータステーブルは全エントリー条件と現在の状態をリアルタイムで表示し、日本語・英語の切り替えに対応しています。
デフォルト設定はDOGEの2時間足向けに最適化されています。実運用の前に必ずご自身の対象銘柄・時間足でバックテストを行ってください。過去の結果は将来の利益を保証するものではありません。
NORN WEAVEは今後も継続的にアップデートされます。ただし、コアコンセプト——生き残ること——は変わりません。
Strategy
Exponential Hull Momentum [BackQuant]Exponential Hull Momentum
Overview
Exponential Hull Momentum is a normalized momentum oscillator built from an Exponential Hull Moving Average -style transformation. Its purpose is to measure whether smoothed directional pressure is pushing toward the upper or lower end of its own recent range, while keeping the response faster and cleaner than a plain moving-average oscillator.
At a high level, the script does three things:
Builds a fast, low-lag smoothed series using an Exponential Hull-style calculation.
Normalizes that series against its own rolling high-low range so the output fits into a bounded oscillator-style scale centered around zero.
Optionally smooths the oscillator with a selectable moving average so you can use a secondary signal line or regime filter.
The final result is an oscillator that tries to answer:
Is momentum pushing toward the strong positive end of its recent range?
Is momentum collapsing toward the negative end?
Is the current move still expanding, or is it rolling over relative to its own smoothed state?
What this indicator is actually measuring
This indicator is not measuring raw returns, not measuring RSI-style up/down closes, and not measuring volatility. It is measuring the position of a low-lag smoothed price transform within its own recent rolling range .
That distinction matters.
It means:
Positive values indicate the Exponential Hull series is in the upper half of its recent normalized range.
Negative values indicate it is in the lower half of its recent normalized range.
Extreme positive values suggest strong upward momentum persistence.
Extreme negative values suggest strong downward momentum persistence.
Because it is normalized, the oscillator is less about absolute price level and more about relative momentum state .
Where the “Hull” idea comes from
The Hull Moving Average family exists to solve a classic moving-average problem:
If you smooth more, you reduce noise but increase lag.
If you smooth less, you reduce lag but increase noise.
Alan Hull’s core idea was to combine moving averages in a way that compensates for lag before applying a final smoothing stage. The classic HMA uses weighted moving averages. This script uses the same structural idea, but with EMAs instead , producing an Exponential Hull-style moving average .
So instead of a classic HMA, the script constructs:
A fast EMA on half-length input.
A slower EMA on full-length input.
A lag-compensated intermediate value using 2 * fast - slow.
A final EMA smoothing pass using sqrt(length).
This is why it is called Exponential Hull Momentum . The “Hull” part refers to the lag-reduction structure, the “Exponential” part comes from using EMA instead of WMA.
The EHMA calculation step by step
The core function is:
EHMA(_src, _length) =
EMA( 2 * EMA(_src, _length / 2) - EMA(_src, _length), round(sqrt(_length)) )
Let’s break that down.
1) Fast EMA on half length
EMA(_src, _length / 2)
This reacts quickly to recent price changes.
2) Slow EMA on full length
EMA(_src, _length)
This is smoother and more delayed.
3) Lag compensation
2 * fastEMA - slowEMA
This is the critical step. It pushes the result toward the faster average while subtracting part of the slower lagging component. Conceptually, it behaves like a “de-lagged” smoother. It is related in spirit to reduced-lag constructions like DEMA and TEMA, though implemented in a Hull-style framework.
4) Final smoothing
EMA(lag_compensated_series, sqrt(length))
This final pass cleans up the compensated series so it remains usable as a smooth momentum engine rather than a noisy de-lagged line.
So the oscillator’s underlying subject is not raw price, but this EHMA subject series .
Why use EHMA instead of a plain EMA or raw price
A raw price oscillator is often too noisy. A plain EMA oscillator is smoother, but can still lag too much. EHMA tries to balance:
Faster reaction than a standard EMA.
Cleaner shape than a raw de-lagged transform.
More sensitivity to directional bursts.
That makes it useful for momentum work, especially when you want:
Earlier momentum regime shifts.
Cleaner trend-state transitions.
A bounded oscillator rather than an overlay line.
Normalization: turning the EHMA into an oscillator
After computing the EHMA subject, the script normalizes it using its own rolling lowest and highest values over a user-defined normalization period:
lowest = lowest(subject, norm_period)
highest = highest(subject, norm_period)
plotosc = (subject - lowest) / (highest - lowest) - 0.50
This transforms the EHMA series into a bounded range centered around zero.
Interpretation:
If subject is near the rolling highest, plotosc approaches +0.5.
If subject is near the rolling lowest, plotosc approaches -0.5.
If subject is near the middle of the rolling range, plotosc is near 0.
So the oscillator is essentially:
Where is the current EHMA value sitting within its recent high-low envelope?
Why normalization matters
Without normalization, the EHMA value itself would still be in price units, which makes comparison harder across:
Different assets,
Different timeframes,
Different price regimes.
Normalization gives you a common scale:
-0.5 to +0.5, centered at 0
That makes the output much easier to use as a momentum state tool.
What the oscillator values mean
Near +0.5
The EHMA subject is pressing against the upper end of its rolling range. This usually means:
Strong bullish momentum,
Persistent upward movement in the smoothed series,
A possible “stretched” positive momentum condition.
Near -0.5
The EHMA subject is pressing against the lower end of its rolling range. This usually means:
Strong bearish momentum,
Persistent downward movement,
A possible stretched downside state.
Near 0
The EHMA subject is near the midpoint of its recent range. This can mean:
Momentum is neutral,
Momentum is transitioning,
The market is compressing or chopping relative to recent structure.
Important nuance about the oscillator scale
This is not a z-score . It is not measuring “standard deviations from mean.” It is a min-max style range normalization . That means:
The output depends on the recent highest and lowest subject values.
If the rolling range changes sharply, oscillator sensitivity can change too.
The same oscillator value does not imply the same statistical rarity across all contexts.
It is best read as a relative range-position momentum oscillator , not as a probabilistic metric.
Signal line / moving average layer
The script optionally applies a second smoothing layer directly to the oscillator:
sig_ma = MA(plotosc, malen, matype)
You can choose from many MA types:
SMA
EMA
DEMA
TEMA
RMA
WMA
HMA
T3
ALMA
LINREG
VWMA
This signal line is not required for the core oscillator to work. It is a secondary interpretation layer that can be used for:
Momentum confirmation,
Cross-based entry logic,
Smoothing out the oscillator for regime filtering,
Visual comparison between raw momentum and smoothed momentum.
The script note suggests that if you want to use the MA more like a signal histogram, you can change its style to columns in the style menu.
Why a selectable MA matters
Different traders want different signal characteristics:
SMA/EMA for classic smoothing,
DEMA/TEMA for lower lag,
HMA/T3/ALMA for smoother trend-state filtering,
LINREG for slope-sensitive behavior,
VWMA if you want volume-weighted smoothing.
This makes the indicator more flexible without changing the core EHMA oscillator.
Color gradient logic
The oscillator columns are colored using thresholded intensity zones rather than a continuous gradient function. The color changes as the oscillator moves further away from zero.
For positive values:
Weak positive: lighter cyan/green tones.
Moderate positive: stronger green.
Strong positive: bright green.
Extreme positive near +0.5: intense bright green.
For negative values:
Weak negative: orange/red tint.
Moderate negative: deeper red.
Strong negative: bright red.
Extreme negative near -0.5: intense red.
This means the plot does two jobs at once:
Direction from sign,
Relative momentum intensity from color saturation.
So even without reading the value numerically, you can see whether momentum is:
Barely positive,
Strongly positive,
Barely negative,
Or deeply negative.
Static levels and what they mean
The script draws fixed zones:
+0.5 and +0.4
-0.4 and -0.5
0 midline
These create:
An upper “overbought / strong positive momentum” zone from 0.4 to 0.5
A lower “oversold / strong negative momentum” zone from -0.4 to -0.5
A midline at 0 separating positive from negative momentum territory
Important:
These are momentum extreme zones , not traditional RSI overbought/oversold zones.
Strong trends can stay pinned near +0.5 or -0.5 for long periods.
Extreme readings do not automatically mean reversal.
The fill between the upper and lower static boundaries just makes those zones easier to identify visually.
Midline logic
The zero line is the most important structural level in the oscillator:
Above 0 = EHMA is in the upper half of its recent range, positive momentum regime.
Below 0 = EHMA is in the lower half of its recent range, negative momentum regime.
The alert conditions are built on this exact logic:
Long alert on crossover above 0
Short alert on crossunder below 0
So the core directional interpretation is midline-based.
How to interpret the indicator in practice
1) Momentum regime
The cleanest use is as a regime filter:
Above 0: positive momentum bias.
Below 0: negative momentum bias.
This alone can already be useful for:
Filtering entries,
Avoiding countertrend setups,
Aligning with the dominant smoothed momentum state.
2) Momentum intensity
The closer the oscillator moves toward +0.5 or -0.5, the stronger the recent momentum relative to its own normalized range.
This can help distinguish:
Weak trend drift,
Healthy trend continuation,
Momentum surge / expansion,
Potential exhaustion zones.
3) Transition behavior
Watch how the oscillator behaves around 0:
Fast thrust through 0 often signals a fresh momentum shift.
Repeated chop around 0 often signals indecision or sideways conditions.
A flattening oscillator after an extreme reading often shows momentum deterioration before price fully turns.
4) Using the moving average signal
If enabled, the MA of the oscillator can help identify:
When raw momentum is accelerating away from smoothed momentum,
When momentum is rolling over,
Whether the oscillator move is broad and sustained or only a short burst.
A common interpretation:
Oscillator above signal MA and above zero = strong bullish momentum structure.
Oscillator below signal MA and below zero = strong bearish momentum structure.
Divergence between oscillator and signal MA = momentum fading or transitioning.
What makes this different from RSI or stochastic-style oscillators
This script is structurally different from standard oscillators.
Compared to RSI
RSI is based on the ratio of average up closes to down closes. It measures directional internal strength of return behavior.
EHMA Momentum instead:
Starts from a low-lag smoothed price transform,
Then asks where that transform sits in its recent range.
So it is more “structure-relative momentum” than “up/down return balance.”
Compared to Stochastic
Stochastic asks where price closes relative to recent high-low range.
EHMA Momentum asks where the EHMA-smoothed subject sits relative to its own recent subject range.
That means:
It is less raw than stochastic,
More smoothed,
Potentially less noisy,
And more focused on directional structure than candle location.
Parameter behavior
Exponential Hull Calculation Period (len)
Controls how the EHMA subject is built.
Very low values make the subject extremely reactive.
Higher values smooth the subject more and reduce sensitivity.
Since the default is very small, this script is designed to be sharp and responsive by nature.
Normalization Period (norm_period)
Controls the rolling high-low range used to normalize the subject.
Higher values create a broader historical range and smoother normalization.
Lower values make the oscillator adapt faster, but it can become more jumpy and “range-reset” more often.
Signal MA Period and Type
Controls how smooth the optional secondary line is.
Shorter MA = faster cross behavior.
Longer MA = slower, steadier confirmation.
Strengths of this approach
Fast response because of the Exponential Hull construction.
Easy interpretation because of bounded normalized output.
Works well as a regime filter via the zero line.
Intensity is visually clear from both height and color.
Flexible because of optional multi-type signal smoothing.
Limitations and what to watch for
Because the oscillator is min-max normalized, extreme values can persist in strong trends.
A rolling highest/lowest normalization can make the oscillator “reset” as old extremes leave the window.
On very low lengths, the EHMA can become highly reactive and potentially noisy.
Zero-line crosses can whipsaw in sideways markets, especially if normalization is too short.
So this tool is best used with context:
Trend structure,
Market regime,
Higher timeframe bias,
Or combined with the signal MA and price action.
Summary
Exponential Hull Momentum is a normalized momentum oscillator built from an EMA-based Hull-style smoothing engine. It first creates a low-lag Exponential Hull series, then normalizes that series within its own rolling high-low range so the output oscillates around zero between roughly -0.5 and +0.5. Positive values indicate the EHMA subject is pressing into the upper half of its recent range, negative values indicate the lower half, and the distance from zero reflects relative momentum strength. Static zones highlight extreme positive and negative momentum states, while an optional multi-type moving average can be used as a secondary signal or smoothing layer. Indicator
Blanco V3 (PRO MTF System)**Blanco V3 – Advanced Precision Trading System**
Blanco V3 is the next evolution of the Blanco series, designed to deliver **precision entries, stronger confirmations, and cleaner decision-making**. It builds on the foundation of Blanco V1 and V2 by enhancing timing, filtering noise, and introducing smarter multi-timeframe alignment.
At its core, Blanco V3 uses a **Zero Lag EMA (ZLEMA)** to reduce delay and detect trend direction faster than traditional indicators. Combined with advanced filters, it helps traders enter earlier while avoiding weak or late setups.
---
### ⚙️ Intelligent Trading Modes
Blanco V3 features three adaptive modes that dynamically adjust strictness:
* **Aggressive Mode**
Faster signals with more entries. Ideal for scalping and lower timeframes.
* **Balanced Mode (Recommended)**
Optimized for consistency. Balances signal quality and frequency.
* **Conservative Mode**
Focuses only on the strongest setups. Best for swing trading and higher timeframes.
Each mode automatically adjusts:
* Trend strength thresholds (ADX)
* Momentum requirements (RSI)
* Entry precision (pullback sensitivity)
---
### 📊 Signal System
Blanco V3 delivers a refined 3-layer signal structure:
#### 🔺 Entry Signals (Precision Arrows)
Small arrows mark optimized entry points using:
* Pullbacks toward the ZLEMA
* Momentum confirmation (RSI alignment)
* Strong trend validation (ADX filter)
* Candle strength (price action confirmation)
These signals are designed to **improve timing and avoid chasing price**.
---
#### 🟢 BUY / 🔴 SELL Labels (Trend Confirmation)
Larger labels appear when the overall trend shifts direction, helping traders identify:
* Swing entries
* Trend reversals
* Continuation opportunities
---
#### ❗ Elite Signals (Full Alignment)
Blanco V3 introduces enhanced **Elite Signals**, which appear only when:
* A valid entry signal is triggered
* AND all monitored timeframes are aligned
These signals represent the **highest-probability setups**, combining trend, momentum, and full market agreement.
---
### 🧠 Multi-Timeframe Intelligence
Blanco V3 includes a bright, easy-to-read dashboard showing trend direction across:
* 5-minute
* 15-minute
* 30-minute
* 1-hour
* 2-hour
* 4-hour
Each timeframe is color-coded:
* 🟢 Green = Bullish
* 🔴 Red = Bearish
---
### 🔍 Smart Confirmation Logic (NEW)
Blanco V3 improves flexibility and accuracy with:
* **Partial Alignment (4/6 or more)**
Allows earlier entries while maintaining quality
* **Full Alignment (6/6)**
Triggers ❗ Elite Signals for maximum confidence
* **Noise Reduction Filters**
Avoids sideways markets and weak momentum conditions
---
### 🎯 Strategy Philosophy
Blanco V3 is designed around one key principle:
> **Trade with the trend, enter on pullbacks, and confirm with alignment.**
It focuses on:
* Entering **after retracements**, not breakouts
* Trading only in **strong market conditions**
* Aligning with **higher timeframe direction**
---
### ⚠️ Best Use
* Best on **1H and 4H charts**
* Works best in **trending markets**
* Combine with:
* Risk management
* Support & resistance
* Market structure
---
### 📌 Quick Guide
* 🔺 Arrows = precise entries
* 🟢 BUY / 🔴 SELL = trend shifts
* ❗ = elite high-probability trades
* 📊 Dashboard = multi-timeframe confirmation
---
**Blanco V3 is built for traders who want cleaner charts, smarter entries, and higher-quality signals — all in one system.**
Indicator
Hash Auto Fibonacci## Overview
Hash Auto Fibonacci eliminates the most time-consuming part of Fibonacci trading — drawing the levels yourself. Drop it on any chart and it automatically detects the most recent significant swing high and swing low, then instantly draws a complete Fibonacci retracement web anchored to those pivots. No manual drawing, no subjectivity, no missed setups.
Built for active traders who use Fibonacci as a core part of their strategy, this tool is engineered to keep up with fast-moving markets through a volatility-adaptive detection engine, a highlighted Golden Pocket zone, a built-in stop-loss reference, and optional multi-timeframe confirmation.
## Key Features
**Automatic Swing Detection**
The indicator uses a pivot-based algorithm to identify swing highs and lows in real time. A pink dot marks the swing high and a green dot marks the swing low on the chart — always showing only the current active pair, never cluttering your screen with historical markers.
**Dynamic Lookback Engine**
Rather than using a fixed lookback period, Hash Auto Fibonacci automatically adjusts its sensitivity based on current market volatility. During high-volatility conditions (fast trending moves, breakouts), the lookback shortens to detect swings quickly. During low-volatility conditions (consolidation, ranging markets), it lengthens to filter out noise and identify only meaningful pivots. This is calculated using the ratio of a 50-period ATR to a 10-period ATR, scaled by a user-adjustable multiplier. You can also switch to a fixed manual lookback at any time.
**Fibonacci Retracement Levels**
The following retracement levels are drawn automatically:
- 0 (swing high anchor)
- 0.236
- 0.382
- 0.5
- 0.618
- 0.65
- 0.786
- 1.0 (swing low anchor)
Optional extension levels (1.272, 1.618, 2.618) can be enabled for targets beyond the swing low.
**The Golden Pocket Zone**
The 0.618–0.65 confluence zone is highlighted as a gradient-filled amber band directly on the chart. This region — known as the Golden Pocket — is widely regarded as the highest-probability reversal zone within any Fibonacci retracement. The zone enforces an ATR-based minimum thickness so it remains visible even on assets with small absolute price ranges.
**ATR Stop-Loss Reference**
A dashed red line is automatically drawn below the swing low (bullish setup) or above the swing high (bearish setup) at a distance of 2× ATR-10. This gives a data-driven starting point for your stop-loss placement without requiring a separate indicator.
**Multi-Timeframe Confirmation**
When the current chart's swing pivot aligns within 0.5% of a confirmed pivot on a higher timeframe (default: 4H), the entire Fibonacci web is visually upgraded — lines become bolder, a confirmation badge appears, and an alert can be triggered. MTF-confirmed webs represent structurally significant levels that multiple timeframes agree on, which historically carry more weight as support and resistance.
**Direction Detection**
The indicator automatically determines whether the current setup is bullish (retracing upward from a low) or bearish (retracing downward from a high) by comparing which pivot — the high or the low — was confirmed most recently. You can override this manually if needed.
**Info Dashboard**
A clean navy dashboard in the corner of your chart displays:
- Current swing high and swing low prices
- 0.5 and 0.618 Fibonacci levels
- Golden Pocket price range
- Suggested ATR-based stop-loss price
- Active lookback period (and whether it's dynamic or manual)
---
## How To Use
**Basic setup**
Add the indicator to any chart. It works on all timeframes and all assets — crypto, stocks, forex, futures. The Fibonacci web draws automatically. The Golden Pocket zone is the primary area to watch for price reactions.
**Reading the chart**
- Price pulling back into the Golden Pocket (0.618–0.65 zone) in a bullish setup is the classic high-probability long entry zone
- Price rejecting from the Golden Pocket in a bearish setup is a potential short entry or profit-taking zone
- The 0.5 level acts as the midpoint — a close above (bullish) or below (bearish) confirms continuation of the retracement
- The 0.786 level is deep — a sweep past this level often signals the retracement is becoming a full reversal
**Using the stop-loss line**
The dashed red SL line is a reference, not a guaranteed stop placement. Use it as a starting point and adjust to your own risk tolerance. On volatile assets, consider placing your stop slightly beyond it to avoid wicks triggering your exit prematurely.
**Multi-timeframe confirmation**
When the ◆ MTF badge appears, the swing that anchors the current web also exists on the higher timeframe. These setups tend to produce cleaner reactions at Fibonacci levels because they represent areas where both short-term and institutional timeframe participants are watching the same price zone.
**Alerts**
Five alert conditions are available:
- New swing high detected
- New swing low detected
- MTF confirmation active
- Price entering the Golden Pocket
- Price at the 0.382 level
- Price at the 0.786 level
Set these in the Alerts panel to get notified without watching the chart constantly.
---
## Settings Reference
**Swing Detection**
| Setting | Default | Description |
|---|---|---|
| Dynamic lookback | On | Automatically adjusts pivot sensitivity based on volatility |
| Manual lookback | 10 | Fixed lookback used when dynamic mode is off |
| Dynamic multiplier | 9 | Controls the average lookback length in dynamic mode |
| Direction mode | Auto | Auto, Bullish, or Bearish override |
| Show swing markers | On | Displays pivot dots on the chart |
**Multi-Timeframe Confirmation**
| Setting | Default | Description |
|---|---|---|
| MTF confirmation | On | Enables higher timeframe pivot alignment check |
| HTF timeframe | 240 (4H) | The timeframe used for confirmation pivots |
**Fibonacci Levels**
| Setting | Default | Description |
|---|---|---|
| Retracement levels | On | Draws the standard 0–1 retracement web |
| Extension levels | Off | Adds 1.272, 1.618, 2.618 extension targets |
| Ratio labels | On | Shows ratio numbers next to each level |
| Golden Pocket zone | On | Highlights the 0.618–0.65 zone |
| ATR stop-loss line | On | Draws the 2× ATR stop reference |
**Info Table**
| Setting | Default | Description |
|---|---|---|
| Show info table | On | Displays the dashboard |
| Position | Top Right | Corner placement of the dashboard |
---
## Notes
- This indicator is an overlay — it draws directly on the price chart
- Works on all timeframes, all markets, and all asset classes available on PulseWire
- The dynamic lookback is calibrated on BTC/USDT 1H data and performs well across most liquid crypto and equity instruments
- Past Fibonacci levels do not guarantee future price reactions — use this tool as part of a broader trading system, not as a standalone signal
- This indicator does not repaint. Swing pivots are confirmed before being drawn and are not subject to change after confirmation
---
## By Hash Capital Research
Indicator
[ A L P H A X ] Dynamic Liquidity Matrix
AlphaX Dynamic Liquidity Matrix — Volume-Weighted Liquidity Heatmap, Fair Value Gap Overlay, Sweep Detection & Live Bias Dashboard
AlphaX Dynamic Liquidity Matrix is a professional-grade liquidity mapping system that identifies where stop-loss clusters and unfilled liquidity pools accumulate across the recent price range — and tracks them in real time. Unlike a static volume profile that simply measures historical volume at price, this indicator builds a fully dynamic heatmap from volume-weighted pivot extremes, recalculates on every bar, and only displays zones that price has not yet revisited. These are the active pockets that institutions and smart money systematically target for liquidity sweeps.
Built on the AlphaX brand framework, the indicator combines four distinct analytical layers: a dynamic liquidity profile, a Fair Value Gap (imbalance) overlay, a sweep detection engine, and a live market context dashboard — all unified under a single, clean visual system.
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🔬 The Dynamic Liquidity Profile — How It Works
Most volume profiles are passive historical tools. The AlphaX Dynamic Liquidity Matrix is active and forward-looking.
On every bar within your configured lookback window, the indicator identifies swing highs and swing lows and assigns each one a volume weight based on the smoothed cumulative volume at that moment — normalized against the maximum volume within the entire lookback window. This produces a volume score (0–100%) for every extreme, which represents the relative significance of the liquidity pool at that price.
These volume-weighted extremes are then distributed across a configurable number of price bins (resolution levels) spanning the full high-to-low range of the lookback window. Each bin accumulates the total volume from every pivot that maps into it. The result is a real-time heatmap profile showing exactly where liquidity is concentrated — heavier at some levels, lighter at others.
The ATR is used to scale the pivot offset distance dynamically, meaning the profile adapts automatically to the current volatility regime. On high-volatility instruments and timeframes, the pivot offsets expand; on quiet markets, they contract. No manual recalibration is required.
What makes this different from a standard Volume Profile:
Standard volume profiles measure how much volume traded at a price — they are backward-looking and include already-filled orders
AlphaX DLM tracks unmitigated pivot extremes — zones where stops and unfilled orders still exist because price has NOT revisited them since they formed
Every pivot that gets swept by price is automatically removed from the profile — keeping the map clean and relevant at all times
The profile rebuilds every bar, so it reflects the current state of the market's liquidity landscape, not a snapshot from hours or days ago
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📊 Profile Visualization
The profile is displayed as horizontal bars extending to the right of the current price, with each bar representing one price bin. The visual system communicates multiple layers of information simultaneously:
Color Logic
Yellow-green bars — bins where the current close is above the bin midpoint (buy-side liquidity / demand zones)
Red bars — bins where the current close is below the bin midpoint (sell-side liquidity / supply zones)
Orange highlight — the Point of Control (POC) bin, the single highest-volume level in the entire profile
Gradient Depth
Each bar uses a gradient that scales from near-transparent at low volume to fully opaque at high volume. At a glance, the most significant liquidity concentrations stand out immediately — no need to read numbers or hover over elements.
Volume Labels
For bins with above-average volume accumulation, the raw volume figure is displayed inside the bar. A percentage label on the left side of each bar shows what proportion of the maximum bin volume that level represents. This gives you both absolute and relative context for every zone.
POC Line
The Point of Control — the level with the highest accumulated liquidity in the profile — is marked with a full dashed horizontal line that extends across the entire lookback window. This makes it easy to see how price has historically reacted around the dominant liquidity level: rejected it, consolidated around it, or broken through it cleanly. A labeled marker on the right identifies the POC precisely.
Liquidity Level Lines
Each active bin above the noise floor is also represented by a dotted horizontal line on the chart itself. The line starts from the bar where price last tested that level and runs to the current bar, giving you a visual connection between the historical pivot origin and the current profile position. Line width scales with the bin's relative volume weight — heavier lines mean more significant zones.
Buy / Sell Split Mode
An optional split view separates each profile bar into its buy-side and sell-side components, stacked side by side. This lets you see at a single level whether it is dominated by buy-side stop clusters (below price), sell-side stop clusters (above price), or a balanced mix — critical for anticipating which direction a liquidity sweep is more likely to run.
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⚡ Fair Value Gap (Imbalance) Overlay
A Fair Value Gap is a three-candle imbalance where the body of the middle candle is not overlapped by the wicks of the surrounding candles, creating a gap in price delivery. These gaps represent unfilled orders left by rapid, one-sided moves — and price has a strong statistical tendency to return to fill them.
AlphaX DLM detects and displays these gaps directly on the chart as shaded rectangular zones:
Bullish FVG — the low of the current candle is higher than the high of the candle two bars prior. Price moved up so quickly it left an unfilled gap below. Displayed in yellow-green.
Bearish FVG — the high of the current candle is lower than the low of the candle two bars prior. Price moved down so quickly it left an unfilled gap above. Displayed in red.
Mitigation Tracking
Once price returns and closes inside a FVG zone (mitigating it), the box is automatically removed from the chart. Only genuinely unmitigated gaps remain visible at all times — the overlay stays clean and actionable regardless of how many gaps have formed historically.
ATR-Scaled Minimum Size Filter
A configurable minimum FVG size (expressed as a multiple of the current ATR) filters out micro-gaps caused by normal spread or noise. Only structurally significant imbalances that represent real impulsive moves are displayed.
Background Highlight
When the current close is inside an active FVG zone — meaning price is currently sitting inside an unmitigated imbalance — the chart background highlights in a subtle amber tone. This is a real-time alert that price is at a decision point within institutional supply or demand.
How to trade FVGs with the Liquidity Matrix:
When a FVG aligns with a high-volume liquidity bin on the profile, the confluence is significant — two independent reasons for price to react at the same level
Bullish FVG zones near buy-side liquidity clusters are high-priority long re-entry areas
Bearish FVG zones near sell-side liquidity clusters are high-priority short re-entry areas
A sweep into a zone followed by an immediate close back through it (a sweep-and-reverse pattern) is one of the cleanest entry setups the indicator can flag
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🎯 Liquidity Sweep Detection
Liquidity sweeps are the mechanism by which institutional players clear stop-loss orders before reversing price in the opposite direction. Identifying sweeps in real time gives retail traders the opportunity to enter after the stops have been taken — in alignment with the direction the institution is positioning.
AlphaX DLM detects sweeps using the following logic:
Bullish Sweep (⚡ SWEEP LOW)
The current bar's low breaches the lowest low of the configurable sweep lookback window, but the bar closes above that low and closes as a bullish candle. This pattern indicates that sell-side stops below the recent range were triggered, absorbed, and reversed — a classic stop hunt before an upside move.
Bearish Sweep (⚡ SWEEP HIGH)
The current bar's high breaches the highest high of the sweep lookback window, but the bar closes below that high and closes as a bearish candle. Buy-side stops above the recent range were triggered and absorbed — a stop hunt before a downside move.
Visual Presentation
Bullish sweeps are labeled with a cyan "⚡ SWEEP LOW" marker below the sweep candle
Bearish sweeps are labeled with an orange "⚡ SWEEP HIGH" marker above the sweep candle
The sweep candle itself is barcolored in the respective sweep color — immediately visible on the chart without needing to look for the label
The most recent 20 sweep labels are retained on the chart, automatically pruning the oldest when new ones form
How to use Sweep Detection with the Liquidity Profile:
A sweep into a high-volume buy-side liquidity bin followed by a close back above that bin is a high-conviction long entry signal
A sweep into a high-volume sell-side liquidity bin followed by a close back below that bin is a high-conviction short entry signal
When a sweep coincides with a FVG zone AND a high-volume profile bin, the three-way confluence represents the highest quality trade setup the indicator can identify
The sweep lookback can be tightened (lower value) for more sensitive detection on fast-moving instruments, or widened for cleaner, less-frequent signals on slower timeframes
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📋 Live Market Context Dashboard
A compact real-time dashboard displays the current state of all indicator systems at a glance. It is divided into four sections:
Profile Section
Active Pivots — total number of unmitigated pivot extremes currently mapped in the profile. Higher counts indicate a richer, more complex liquidity landscape.
Buy Pivots — number of unmitigated buy-side (demand) extremes
Sell Pivots — number of unmitigated sell-side (supply) extremes
Liquidity Bias — overall directional lean of the liquidity map. BUY SIDE means more unmitigated demand zones exist; SELL SIDE means more supply zones exist; BALANCED means roughly equal. This is not a trade signal on its own, but it tells you where the more significant unfilled orders are positioned.
Sweep Section
Last Sweep — whether the current bar is a bullish or bearish sweep, highlighted in the respective sweep color when active
Sweep Lookback — the currently configured lookback window for sweep detection
Fair Value Gap Section
Active FVGs — total number of unmitigated fair value gaps currently displayed on the chart
FVG Split — the breakdown between active bullish and bearish FVGs. When bullish FVGs dominate, unmitigated demand imbalances outnumber supply imbalances — and vice versa.
Market Context Section
ATR — current ATR value and its percentage of price. Color-coded: green for low volatility, orange for moderate, red for elevated. High ATR readings mean liquidity zones will be wider and stops should be placed further from entry.
Normalized Volume — current volume expressed as a percentage of the maximum volume within the lookback window, labeled VERY HIGH / HIGH / NORMAL / LOW / VERY LOW. Elevated volume on a sweep candle significantly increases the probability of follow-through.
Price in Range — where the current close sits within the full liquidity range as a percentage, labeled as upper zone / mid-range / lower zone. This tells you at a glance whether price is approaching a range extreme (potential sweep target) or sitting in the middle of the distribution.
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🚀 How to Identify Trade Opportunities — Step by Step
Step 1 — Assess the Liquidity Landscape
Load the indicator and check the profile: are liquidity bins densely clustered in a narrow zone, or spread across a wide range?
Check the Liquidity Bias in the dashboard: does the map lean buy-side or sell-side?
Identify the POC line — this is the dominant reference level for the session
Step 2 — Identify High-Value Target Zones
Look for thick profile bars with high volume percentages — these are the zones that price is most likely to revisit for a sweep
Note any FVG boxes that overlap with high-volume bins — these dual-layer confluences are the strongest setups
Mark the POC: if price is approaching from below with buy-side bias, the POC is a likely magnet. If approaching from above with sell-side bias, the same applies.
Step 3 — Wait for a Sweep into a Liquidity Zone
Watch for price to push into a high-volume bin — especially below a cluster of buy pivots or above a cluster of sell pivots
A sweep label (⚡ SWEEP LOW or ⚡ SWEEP HIGH) confirms the stop-hunt pattern has occurred
The sweep candle will be highlighted in cyan (bull sweep) or orange (bear sweep) for instant identification
Step 4 — Confirm the Reversal
The most important confirmation is the close: the sweep candle must close back on the opposite side of the liquidity zone it spiked through
If price is also inside a FVG zone and closes back out of it, the reversal confluence is stronger
Elevated normalized volume on the sweep candle (VERY HIGH or HIGH) significantly increases the conviction of the setup
Step 5 — Enter and Manage
Enter in the direction of the sweep reversal — long after a bullish sweep, short after a bearish sweep
Place your stop loss below the sweep wick low (for longs) or above the sweep wick high (for shorts) — the stop hunt has already occurred, so price should not need to revisit that level
Target the POC level, the next high-volume bin on the profile, or the opposite side of an active FVG zone
If the Liquidity Bias matches your trade direction (e.g., BUY SIDE bias on a long trade), hold with greater conviction — the overall liquidity landscape supports continuation
Step 6 — When NOT to Trade
If the profile is extremely thin (very few active pivots), the liquidity landscape is unclear — wait for the profile to rebuild
If the ATR is very low (quiet, compressed market), FVGs and sweep signals may be less reliable — tighten the FVG minimum size filter
If price is in mid-range with BALANCED bias and no nearby FVGs, there is no clear structural edge — wait for price to approach a zone with confluence
Do not chase a sweep candle — the entry is on the confirmation close, not the spike
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⚙ Settings Reference
Core Settings
Lookback Bars — how many bars back the indicator scans for pivot extremes and builds the liquidity profile (default: 300). Increase for a broader, more historical view; decrease for a tighter, more immediate profile focused on the current session.
Profile Resolution — the number of price bins the range is divided into (default: 50). Higher values give finer granularity; lower values produce a smoother, broader profile. Recommended range: 30–70.
Volume Smoothing — the rolling sum window for volume normalization (default: 10). Higher values reduce the effect of individual volume spikes; lower values make the profile more reactive to each candle's volume.
ATR Length — the lookback period for the ATR calculation used to scale pivot offsets (default: 14). Match this to your typical ATR analysis setting.
Profile Display
Show Profile Bars — toggle the horizontal heatmap bars on/off
Show Volume % Labels — toggle volume figures and percentage labels inside and beside each bar
Show POC Line — toggle the full-width dashed POC level line and label
Show Liquidity Level Lines — toggle the dotted horizontal lines connecting each pivot's origin to the current bar
Split Buy / Sell Bars — splits each profile bar into its buy-side and sell-side volume components displayed side by side
Bar Offset from Price — controls the gap between the current bar and where the profile starts rendering (default: 20 bars). Increase if the profile overlaps with recent candles.
Max Bar Width — controls the maximum horizontal length of the widest profile bar in bars (default: 50). Adjust based on your chart's zoom level.
Fair Value Gaps
Show Fair Value Gaps — toggle the FVG overlay on/off
Min FVG Size (ATR mult) — minimum gap size as a multiple of ATR for a gap to qualify as a valid FVG (default: 0.1×). Increase to filter out minor imbalances; decrease to show all gaps.
Max FVGs to Display — maximum number of unmitigated FVGs shown simultaneously (default: 8). Oldest gaps are pruned first when the limit is reached.
Sweep Detection
Highlight Sweeps — toggle sweep labels and candle barcolor on/off
Sweep Lookback (bars) — the window used to define the recent high/low for sweep detection (default: 5). Lower values detect micro-sweeps on fast instruments; higher values detect only significant structural sweeps.
Colors
Buy Liquidity — color for buy-side profile bars and bullish FVGs (default: yellow-green #c8e624)
Sell Liquidity — color for sell-side profile bars and bearish FVGs (default: red #ff1744)
POC / Max Level — color for the Point of Control bar, POC line, and FVG background highlight (default: orange #ff9800)
Sweep Bull Label — color for bullish sweep labels and barcolor (default: cyan #00e5ff)
Sweep Bear Label — color for bearish sweep labels and barcolor (default: orange #ff9100)
Dashboard Background / Text / Neutral — dashboard theme colors
Dashboard
Show Dashboard — toggle the live context dashboard on/off
Position — choose Top Left, Top Right, Bottom Left, or Bottom Right
Text Size — Tiny, Small, or Normal
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🔔 Alert Conditions
Bullish Liquidity Sweep — fires when a bullish sweep pattern is confirmed on bar close
Bearish Liquidity Sweep — fires when a bearish sweep pattern is confirmed on bar close
Any Liquidity Sweep — fires on either sweep direction — use for a single catch-all alert
Bullish FVG Created — fires when a new unmitigated bullish fair value gap forms
Bearish FVG Created — fires when a new unmitigated bearish fair value gap forms
Price Entered FVG — fires when the current close moves inside any active unmitigated FVG zone
All alert messages include {{ticker}} and {{interval}} placeholders for clean webhook and bot integration.
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⚡ Key Features
🔬 Fully dynamic volume-weighted liquidity heatmap — rebuilds every bar, not a static historical snapshot
🗑 Auto-removal of swept/mitigated pivot levels — the profile always reflects only active, unvisited liquidity
📊 ATR-adaptive pivot offsets — automatically scales to the current volatility regime, no manual recalibration
🟡 Volume-gradient profile bars with buy/sell split mode — see the composition of every liquidity zone
◆ POC full-width level line with label — the dominant liquidity reference level clearly marked at all times
⚡ Fair Value Gap overlay with real-time mitigation tracking — only unmitigated imbalances remain visible
🌐 FVG background highlight — instant visual alert when price is sitting inside an active imbalance
🎯 Liquidity sweep detection with barcolor — cyan for bull sweeps, orange for bear sweeps
📋 Live dashboard — active pivots, buy/sell count, liquidity bias, sweep status, FVG split, ATR, normalized volume, and price-in-range percentage
🎨 Full AlphaX brand theme — yellow-green / red / orange / dark background, consistent with the AlphaX indicator suite
🔔 6 alert conditions — sweep entries and FVG events with clean ticker/interval message formatting
⚙ Fully configurable — all lookback windows, resolution, sensitivity, colors, and display toggles adjustable from the settings panel
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👥 Who This Is For
🥇 Smart Money Concept (SMC) traders — the entire indicator is built around the core SMC concepts of liquidity pools, stop hunts, and fair value gaps. It automates the manual process of mapping where stops are likely clustered and where imbalances need to be filled.
📊 Order flow and volume profile traders — the dynamic heatmap provides a volume-at-price context that updates in real time, giving a live picture of the market's liquidity distribution.
⚡ Intraday scalpers and day traders — the sweep detection and FVG alerts fire on bar close, making them practical for fast timeframe traders on instruments like XAUUSD, indices, and forex majors.
🧠 Traders who struggle with entry timing — the sweep reversal pattern gives a precise, rules-based entry trigger rather than a subjective "it looks good" decision.
📈 Traders who want confluence, not single indicators — when a sweep, a high-volume bin, and a FVG all align at the same level, the three-layer confluence removes ambiguity and provides an objective framework for decision-making.
🎯 Traders building systematic approaches — all signals are rule-based, non-repainting, and confirmed on bar close. The dashboard provides quantitative context — not just visuals — for every condition the indicator monitors.
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📝 Notes
All signals are non-repainting — every sweep label, FVG box, and profile bar is confirmed on bar close and does not move or disappear retroactively
The profile renders only at the last bar (barstate.islast) and redraws on each new bar — this is by design and standard practice for all right-side profile indicators. Historical profile positions are not stored.
On very low timeframes (sub-1-minute) or extended chart history windows, PulseWire's 500-box and 500-line limits apply — the indicator operates within these limits by design. Reducing the lookback or bins will always keep rendering within limits.
The ATR-adaptive offset means the indicator self-adjusts across different instruments and timeframes without requiring separate configurations for each. The same settings work on XAUUSD 1-minute and EURUSD 15-minute with no manual changes needed.
For best results, use in combination with AlphaX Vision (Fusion Trend Engine) — the Liquidity Matrix identifies where to enter within the zones that Vision's trend system defines as directionally favored.
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⚠ Disclaimer
This indicator is a technical analysis and visualization tool intended for educational and informational purposes only. It does not constitute financial advice or a recommendation to buy or sell any financial instrument. All signals are generated from historical and real-time price data using mathematical calculations — their accuracy or profitability is not guaranteed. Past performance of any signal type does not guarantee future results. Always conduct your own analysis, use proper risk management, and consult a licensed financial advisor before making any trading decisions. The author accepts no responsibility for any losses incurred from the use of this indicator.
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Built for traders who read the market at the level where institutions operate.
Indicator
Indicator
Machine Learning: Trend Classifier [identityKa]Overview
The Machine Learning: Trend Classifier is a professional-grade algorithmic momentum and trend analysis tool designed for data-driven traders. Unlike traditional moving averages that inherently lag behind live price action, this script introduces a multi-factor mathematical classification engine that evaluates real-time market behavior to predict the true direction of the trend.
Core Mechanics & Detection
The algorithm uses a continuous data-stream calculation to locate major market shifts:
Bullish Classification (Neon Green): Detected when the underlying momentum, volatility, and trend-flow simultaneously show aggressive upward expansion. The dynamic data ribbon shifts to green, encapsulating the price.
Bearish Classification (Neon Red): Detected when the structural momentum shifts downwards. The dynamic ribbon turns red, acting as algorithmic resistance.
Neutral / Chop Zones (Orange): Detected when the market loses clear direction. The engine recognizes this as a friction zone and shifts to a neutral state, warning the trader of potential whipsaws.
The Algorithmic Classification Engine
A fundamental rule of this indicator is the "AI Confidence Score". The engine normalizes multiple indicators (RSI, CCI, and MACD flows) into a strict 0 to 100 percentage scale.
The script constantly monitors this confidence score. If the score is above 20%, a Bullish state is confirmed. If it is below -20%, a Bearish state is confirmed. Anything in between is classified as market noise.
Upon crossing these algorithmic thresholds, the script instantly updates the on-chart Ribbon, ensuring that only statistically significant trend shifts are highlighted for the trader. This keeps the workspace incredibly clean and mathematically sound.
HUD Dashboard & AI Logic
The on-chart intelligence panel evaluates the live market state and generates actionable data:
Dangerous: Displayed actively whenever the current live price is trading inside the Neutral zone (Confidence Score between -20% and 20%). This serves as a warning that the price is in a high-friction area where sharp rejections and false breakouts are imminent.
LONG / SHORT: The engine tracks the macro bias based on the classification state. If the AI Confidence heavily favors upward momentum, the bias shifts to LONG. If the momentum breaks downwards, the bias shifts to SHORT.
How to Use It
This tool provides exceptional context for trade entries and trend following. When the AI Suggestion reads "LONG," traders should look for pullbacks toward the lower band of the green ribbon. When the state reads "Dangerous," it is highly recommended to stay out of the market or tighten stop losses until a clear trend direction is re-established by the algorithm. Indicator
Pro Levels & Zones [MTE]Pro Levels & Zones
An intraday futures overlay that combines pivot-based supply and demand zones with multi-session key levels and a confluence-based signal filter. The core idea is that zones alone generate too many potential entries — by requiring alignment across multiple independent factors before labeling a zone touch, the indicator filters out low-conviction setups and highlights where several references converge.
HOW IT WORKS
Supply & Demand Zone Detection
Zones are built from 60-minute pivot highs and pivot lows using a 3-bar left / 3-bar right pivot structure. When a pivot high is confirmed, the area between the candle's high and the top of its body becomes a supply zone (red). When a pivot low is confirmed, the area between the candle's low and the bottom of its body becomes a demand zone (green). Zones extend forward in real time and are automatically removed when price closes beyond the zone boundary or when the zone exceeds a configurable age limit (default: 500 bars). Only the 3 most recent zones per side are kept to avoid chart clutter.
Confluence Scoring (signal filter)
When price enters a fresh (unused) zone, the indicator checks up to 5 independent factors before printing a signal:
1. Volume delta direction — estimated from the bar's close position within its range. A buy signal requires positive delta; a sell signal requires negative delta.
2. VWAP proximity — whether price is near the session VWAP (within 0.15% of current price).
3. Key level proximity — whether price is near a relevant prior-session level (PDH, PDL, PMH, PML).
4. POC proximity — whether price is near the intraday volume Point of Control.
5. VWAP trend bias — whether price is on the "right side" of VWAP for the signal direction (buy below VWAP, sell above).
Each matching factor adds 1 to the score. The signal label displays the count (e.g., "Buy 4/5") so traders can see at a glance how many factors aligned. A configurable cooldown (default: 12 bars) prevents repeated signals in the same area. An additional filter requires bearish candle close for sells and bullish candle close for buys.
Note: The confluence score is simply a count of how many factors happen to align at the moment of zone contact. A higher count does not predict or guarantee a successful trade. It is a filtering tool, not a performance metric.
SESSION LEVELS & KEY LEVELS
The indicator tracks and displays levels from multiple sessions:
- London session high/low — plotted as live-updating steplines during the session, then held after session close.
- Asia session high/low — same behavior, off by default.
- Key levels drawn as dashed horizontal lines: Previous Day High/Low/Close (PDH/PDL/PDC), Pre-Market High/Low (PMH/PML), Previous Week High/Low (PWH/PWL), Overnight High/Low (ONH/ONL), and the RTH Opening Print. All are off by default and individually toggleable.
Previous day and week values use request.security() with a offset and lookahead_on, which is the standard method to reference the prior completed period without future data leakage.
ADDITIONAL TOOLS (all off by default)
- VWAP — standard session-anchored VWAP using ohlc4 as source.
- POC — intraday volume Point of Control calculated by distributing each bar's volume into a 100-bin histogram across the RTH price range, then finding the bin with the highest accumulated volume. Resets daily.
- Fair Value Gaps — bullish and bearish imbalances detected when a gap exists between bar 's low and bar 's high (or vice versa), filtered by a minimum percentage size (default: 0.15%). FVGs auto-expire after 40 bars. Maximum 6 active FVGs.
- Opening Range — plots the RTH opening range as a box (15 or 30 minute, configurable). Extends through the session.
WHY THIS COMBINATION
Most zone-based approaches generate signals every time price touches a zone, regardless of context. This indicator addresses that by requiring zone contact AND directional volume AND candle confirmation before printing anything, then layering additional context (VWAP, key levels, POC) as a visible confluence count. The result is fewer signals that occur only at zones where multiple independent references happen to converge.
The session levels (London, Asia, pre-market, overnight) are included because futures often react at session boundaries, and having them as toggleable overlays avoids needing separate indicators cluttering the chart.
HOW TO USE
1. Apply to a 1-15 minute intraday futures chart (defaults tuned for NQ on 5 min).
2. Adjust "Min Zone Size" for your instrument (NQ: 20-50 pts, ES: 5-15 pts).
3. Watch for Buy/Sell labels at zone touches. Higher confluence counts (4/5, 5/5) mean more factors aligned — use your own judgment on whether the context supports a trade.
4. Toggle key levels on/off depending on which session references matter to your trading approach.
5. All features are independently toggleable. Start with zones + signals, then add levels as needed.
DEFAULT SETTINGS
- Zones: ON, min size 20 pts, max age 500 bars
- Signals: ON, cooldown 12 bars, volume delta confirmation ON
- London session levels: ON
- All other levels and tools: OFF
LIMITATIONS
- Volume delta is estimated from bar close position within range — it is not true order flow data.
- POC uses a 100-bin histogram which is an approximation, not tick-level volume profile.
- Confluence scoring counts factor alignment but does not predict outcomes. Past confluence patterns do not guarantee future results.
- Zone detection has a 3-bar lag due to pivot confirmation.
- Designed for futures instruments. Adjust zone size settings for other markets.
Indicator
Performance Comparison (Zeiierman)█ Overview
Performance Comparison (Zeiierman) is a period-mapping comparison engine that shows how the current month, quarter, or year is evolving relative to its historical structure.
It takes completed historical periods, compresses each into a normalized timeline, and overlays them on the active period so you can compare paths, pace, expansion, and finish. Instead of only asking where the price is now, the script asks how this period is behaving relative to past periods at the same stage of development.
The indicator displays all curves in Percentage Accumulated terms, meaning each period starts at the same zero point and then tracks total return from that period start. This makes it easier to compare period structure on an equal footing, regardless of the asset’s raw price level.
█ How It Works
⚪ 1) Period Segmentation
The script groups price into repeating time buckets based on the selected Period:
Monthly
Quarterly
Yearly
Each new month, quarter, or year starts a fresh period, while completed periods are stored for later comparison.
⚪ 2) Timeline Normalization
Because historical periods do not all contain the same number of bars, each is remapped to a shared normalized progress scale from start to end.
This allows the script to compare:
the beginning of one period to the beginning of another
the midpoint of one period to the midpoint of another
the final stage of one period to the final stage of another
So even if one quarter had more bars than another, both can still be compared on the same visual path.
⚪ 3) Value Mapping
The script uses Percentage Accumulated only.
Each period begins at 0% and then tracks cumulative return from that period’s starting price:
Percentage Accumulated = current price/period starting price − 1
This means all periods are anchored to the same starting point, making relative path comparison much cleaner than raw price comparison.
⚪ 4) Historical Curve Engine
Completed periods are collected into comparison buckets across the normalized timeline. From these buckets, the script can draw:
Historical paths
Median path
Average path
This creates a period-based structure model rather than a simple price overlay.
⚪ 5) Current Period Tracking
The active period is plotted on top of the historical framework, so you can see:
whether the current action is stronger or weaker than normal
whether it is tracking near the median path
whether it is diverging from the average or historical range
where the current period sits in time through the timeline bar
⚪ 6) Similarity Table
The table compares the current period against past visible periods using four path metrics:
MAE: Average distance from the current path. Lower is better.
Max Dev: Largest divergence at any point. Lower is better.
Dir Match %: How often did both paths move in the same direction? Higher is better.
End Diff: Difference at the latest comparable point. Closer to zero is better.
This helps identify which historical period most closely resembles the current one.
█ Why It Is Useful
⚪ Structural Context
The script does not just show whether the price is up or down. It shows whether the current period is unfolding in a way that is typical, weak, extended, delayed, or abnormal relative to history.
⚪ Period-Based Comparison
It is especially useful for traders and analysts who think in recurring cycles, such as:
monthly structure
quarterly seasonality
yearly progression
█ How to Use
⚪ Historical Comparison
Use the historical paths to see how prior periods behaved across the full normalized timeline.
⚪ Median Path
Use the median as the most typical historical path. This is often the cleanest benchmark for “normal” behavior.
⚪ Average Path
Use the average to measure the broad mean tendency of past periods.
⚪ Current Period
Use the current path to judge whether the live period is:
leading
lagging
tracking normally
diverging sharply from history
⚪ Similarity Table
Use the table to find the closest historical analog to the current period.
Low MAE and Max Dev suggest close path similarity.
High Dir Match % suggests similar movement behavior.
End Diff near zero suggests similar positioning at the current stage.
█ Settings
Period — groups data into Monthly, Quarterly, or Yearly periods.
Completed Periods to Compare — number of finished historical periods used in the comparison engine.
Chart Resolution — number of normalized steps used to draw each path.
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Indicator
Aura: Adaptive Statistical Smoother [Pineify]Aura: Adaptive Statistical Smoother
The Aura: Adaptive Statistical Smoother is an overlay trend-following indicator that combines a forward-backward zero-lag EMA approximation with an R-Squared trend filter to produce an adaptive moving average that tightly tracks price during trending markets and deliberately diverges during ranging conditions — solving the core problem of traditional moving averages that generate excessive whipsaw signals in sideways price action. Instead of using a fixed smoothing period or a single-pass EMA, the indicator first constructs a bidirectional (zero-phase-shift) EMA baseline that virtually eliminates the lag inherent in standard exponential averages, then modulates how closely the final Aura MA follows this baseline based on the real-time R-Squared coefficient of determination. When R-Squared confirms a strong linear trend, the Aura MA converges toward the zero-lag target proportionally to trend strength; when R-Squared indicates a ranging market, the MA actively pushes away from price in the last known trend direction, creating a natural buffer zone that suppresses false crossovers. Dynamic standard-deviation volatility bands and R-Squared-filtered buy/sell signals complete the system, giving traders a statistically grounded, self-adjusting trend tool with built-in noise rejection.
Key Features
Forward-backward zero-lag EMA approximation — a two-pass EMA computation (forward pass followed by a backward iteration over historical values) that closely approximates a bidirectional filter, virtually eliminating the phase lag that causes standard EMAs to react late to trend changes.
R-Squared adaptive trend filter — the Pearson correlation coefficient squared (R²) between price and bar index measures how well a linear trend fits recent data. Values above 0.5 indicate trending conditions; values below indicate ranging. This statistical metric drives the core adaptive behavior of the Aura MA.
Dual-regime moving average — during trending markets (R² > 0.5), the Aura MA blends toward the zero-lag target proportionally to R², tracking price closely. During ranging markets (R² ≤ 0.5), the MA diverges from price in the last known direction, creating a buffer that prevents whipsaw crossovers.
Dynamic volatility bands — standard deviation of the source price over the statistical window, scaled by a user-defined multiplier, creates upper and lower bands that automatically expand during volatile periods and contract during quiet ones.
R-Squared-filtered buy/sell signals — crossover signals between price and the Aura MA are only generated when R² exceeds 0.3, ensuring signals fire only when there is statistically meaningful trend strength and suppressing noise during flat markets.
Trend-adaptive coloring — the Aura MA line, volatility cloud fill, and bar colors all dynamically switch between bullish and bearish colors based on the current trend state, providing instant visual identification of the prevailing direction.
How It Works
The indicator follows a multi-stage calculation pipeline that transforms raw price data into an adaptive, statistically filtered trend line:
Forward-backward zero-lag baseline: A standard EMA is first computed on the source price. Then a second pass iterates backward over the historical EMA values, applying the same EMA alpha (2 / (smooth + 1)) at each step across the lookback window. This two-pass approach approximates a zero-phase-shift filter — the resulting baseline tracks price turns almost immediately, without the half-period delay of a conventional EMA. This baseline serves as the "target" that the adaptive Aura MA will converge toward when the market is trending.
R-Squared trend detection: The Pearson correlation between closing prices and bar indices over the statistical window is squared to produce R². This coefficient of determination measures the proportion of price variance explained by a linear trend. R² near 1.0 means price is moving in a clean, directional manner; R² near 0.0 means price is oscillating without a clear direction. The 0.5 threshold divides the market into "trending" and "ranging" regimes.
Adaptive MA computation: In trending mode (R² > 0.5), the Aura MA is computed as a weighted blend: R² × target + (1 − R²) × previous Aura MA. Stronger trends (higher R²) pull the MA closer to the zero-lag target; weaker trends allow it to lag slightly, providing natural smoothing. In ranging mode (R² ≤ 0.5), the MA moves away from price by the magnitude of the target's recent change, in the direction of the last known trend bias. This deliberate divergence creates separation between price and the MA, preventing the repeated false crossovers that plague fixed-parameter moving averages in choppy markets.
Volatility bands and signal generation: Standard deviation bands are added around the Aura MA to visualize the current volatility regime. Buy and sell signals are generated on price crossovers of the Aura MA, but only when R² exceeds 0.3 — a secondary filter that ensures even the crossover signals carry minimum statistical trend evidence.
Trading Ideas and Insights
Trend-following entries with lag reduction: The zero-lag baseline allows the Aura MA to respond to trend initiations significantly faster than a standard EMA of equivalent smoothing. When a BUY signal fires (price crosses above the Aura MA with R² > 0.3), the entry is closer to the actual trend start than what a conventional moving average crossover would provide, improving the risk/reward ratio of trend-following trades.
Whipsaw avoidance in ranging markets: The adaptive divergence mechanism during low-R² periods is specifically designed to prevent the most common failure mode of moving average systems — repeated false crossovers during sideways consolidation. Traders can trust that when a signal does fire, the statistical environment supports a directional move.
Volatility band breakout confirmation: When price breaks above the upper band or below the lower band while the Aura MA is already in the corresponding trend state, it confirms a high-volatility directional expansion. These breakouts can be used to add to existing positions or to set trailing stops at the opposite band.
R-Squared as a standalone filter: Even without acting on the buy/sell signals, traders can use the implicit R-Squared regime (visible through the MA's behavior — tight tracking vs. divergence) as a filter for other strategies. Apply your existing entry rules only when the Aura MA is tightly tracking price (trending regime), and stand aside when the MA visibly separates from price (ranging regime).
Multi-timeframe trend alignment: Apply the Aura indicator on both a higher timeframe (e.g., daily) and a lower timeframe (e.g., 1-hour). Take lower-timeframe BUY signals only when the higher-timeframe Aura MA is in bullish state, and SELL signals only when the higher-timeframe is bearish. This multi-timeframe alignment leverages the adaptive nature of the indicator across different time horizons.
How Multiple Indicators Work Together
The Aura indicator integrates three distinct analytical components into a unified adaptive system, each addressing a specific weakness of traditional moving averages:
Forward-backward zero-lag EMA (lag elimination): Standard moving averages inherently lag price by approximately half their lookback period. The bidirectional EMA approximation addresses this by running a second smoothing pass in reverse over historical values, canceling out the phase shift. This gives the Aura MA a responsive baseline to track during trends — without the noise sensitivity that comes from simply using a very short-period EMA.
R-Squared trend filter (regime detection): The R-Squared coefficient provides an objective, statistical answer to the question "is the market trending right now?" This replaces subjective visual assessment or fixed-threshold approaches (like ADX) with a measure rooted in linear regression theory. R² directly controls how the Aura MA behaves — it is not merely a signal filter but the core adaptive mechanism that switches the MA between trend-tracking and range-diverging modes.
Standard deviation volatility bands (context visualization): The bands add a volatility dimension that neither the zero-lag baseline nor the R-Squared filter provides. They show traders the expected range of price movement around the Aura MA, helping to distinguish between normal retracements within a trend (price stays within bands) and genuine trend reversals (price breaks through bands and crosses the MA).
The synergy is structural: zero-lag EMA (responsive baseline) → R-Squared (regime classification) → adaptive blending/divergence (the Aura MA itself) → volatility bands (context envelope) → R²-filtered crossover signals (actionable entries/exits). The zero-lag baseline ensures the MA has a fast, accurate target to track; R-Squared determines whether to track it or diverge; and the volatility bands provide the visual context for interpreting the MA's position relative to price. Each component compensates for a specific weakness — lag, false signals in ranges, and lack of volatility context — that would undermine the system if any single component were used alone.
Unique Aspects
Statistical regime switching: Unlike adaptive moving averages that use volatility or momentum to adjust their speed (e.g., KAMA, VIDYA), the Aura MA uses R-Squared — a measure of trend linearity — to switch between two fundamentally different behaviors: convergence toward a target during trends and deliberate divergence during ranges. This is a qualitatively different approach that directly addresses the root cause of whipsaw (lack of trend) rather than a symptom (high volatility).
Bidirectional EMA approximation in Pine Script: True zero-phase-shift filters require processing the entire dataset in both directions, which is not natively possible in real-time bar-by-bar computation. The forward-backward loop in this indicator approximates this by iterating over historical forward-EMA values within the lookback window, achieving near-zero lag without requiring future data — a practical implementation of signal processing theory within Pine Script's constraints.
Directional divergence mechanism: During ranging markets, the Aura MA does not simply freeze or slow down — it actively moves away from price in the last known trend direction. This creates increasing separation that requires a genuine trend resumption (not just noise) to produce a crossover, providing a self-adjusting buffer proportional to the ranging market's volatility.
Dual-threshold R-Squared filtering: The indicator uses two R-Squared thresholds for different purposes: 0.5 for the MA's adaptive regime switch (trending vs. ranging behavior) and 0.3 for signal generation (minimum trend evidence for crossover signals). This layered approach means the MA adapts its behavior at a stricter threshold while still allowing signals in moderately trending conditions, balancing responsiveness with noise rejection.
How to Use
Add the indicator to your chart. It overlays directly on the price chart, displaying the Aura MA line, upper and lower volatility bands, and a shaded volatility cloud between the bands.
Observe the Aura MA line (thick colored line). When it is green and tightly tracking price, the market is in a statistically confirmed uptrend. When it is red and tracking price closely, the market is in a confirmed downtrend. When the MA visibly separates from price, the R-Squared filter has detected a ranging market and the MA is in divergence mode.
Watch for BUY signals (green "BUY" labels below bars) — these fire when price crosses above the Aura MA and R-Squared exceeds 0.3, indicating a bullish crossover with minimum statistical trend support. Consider entering long positions or closing short positions.
Watch for SELL signals (red "SELL" labels above bars) — these fire when price crosses below the Aura MA and R-Squared exceeds 0.3, indicating a bearish crossover with trend confirmation. Consider entering short positions or closing long positions.
Use the volatility bands (shaded cloud) to gauge the expected price range around the Aura MA. Price touching the upper band in an uptrend suggests extended momentum; price touching the lower band in a downtrend suggests extended selling pressure. Reversals from band extremes back toward the MA can serve as mean-reversion opportunities within the prevailing trend.
Monitor bar colors for a quick visual scan of the current trend state across the chart — green bars indicate bullish trend, red bars indicate bearish trend.
Adjust the Statistical Window to match your trading timeframe. Shorter windows (10–15) make the R-Squared filter more responsive to recent price behavior — suitable for intraday or short-term swing trading. Longer windows (25–50) provide a more stable trend assessment — suitable for position trading on daily or weekly charts.
Customization
Statistical Window (default: 20): The lookback period for both the R-Squared calculation and the standard deviation bands. This is the most impactful parameter. Shorter values make the indicator more responsive — the R-Squared filter reacts faster to regime changes and the volatility bands adjust more quickly. Longer values produce smoother, more stable readings that filter out short-term noise but may delay regime detection. Start with 20 for daily charts and adjust based on your asset's typical trend duration.
Forward-Backward Smoothing (default: 10): Controls the EMA period used in the zero-lag approximation. Lower values (5–7) produce a baseline that tracks price very closely, making the Aura MA highly responsive during trends but potentially more sensitive to noise. Higher values (15–20) produce a smoother baseline with slightly more residual lag but better noise rejection. The interaction between this parameter and the Statistical Window determines the overall character of the indicator.
Volatility Multiplier (default: 1.5): Scales the standard deviation bands around the Aura MA. Higher values (2.0–3.0) produce wider bands that contain more price action — useful for volatile assets or for identifying only extreme deviations. Lower values (0.5–1.0) produce tighter bands that price breaks more frequently — useful for identifying smaller volatility expansions or for more active trading styles.
Bullish / Bearish Colors: Fully customizable colors applied to the Aura MA line, volatility bands, cloud fill, signal labels, and bar coloring. Adjust to match your chart theme or to improve visibility on different background colors.
Conclusion
The Aura: Adaptive Statistical Smoother brings a statistically rigorous approach to trend following by combining a forward-backward zero-lag EMA approximation with an R-Squared-driven adaptive regime filter. The zero-lag baseline eliminates the inherent delay of conventional moving averages, while the R-Squared coefficient provides an objective, real-time assessment of whether the market is trending or ranging. During trends, the Aura MA converges toward the responsive baseline proportionally to trend strength; during ranges, it deliberately diverges to create a whipsaw-resistant buffer zone. Dynamic volatility bands add a contextual envelope, and dual-threshold R-Squared filtering ensures that buy and sell signals carry minimum statistical trend evidence. Whether used as a standalone trend-following system or as an adaptive trend filter for other strategies, the Aura indicator provides a self-adjusting framework that adapts its behavior to the current market regime — tracking trends closely when they exist and stepping aside when they do not.
Indicator
Indicator
Bot Webhook v8.4 [ETH]Bot Webhook v8.4 - Optimized Multi-Timeframe Signal Generator
Data-driven signal generation for ETH/USD with timeframe-specific filters (30S-20m), Keltner Squeeze Detection and Volatility Regime Recognition. Optimized from 136 signals + 9406 1m candles.
Datengetriebene Signalgenerierung fuer ETH/USD mit TF-spezifischen Filtern (30S-20m), Keltner-Squeeze-Detection und Volatility-Regime-Erkennung. Optimiert aus 136 Signalen + 9406 1m-Candles.
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OVERVIEW / UEBERBLICK
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This script is the ETH/USD-specific version of Bot Webhook v8.4. It generates Long and Short signals with a confidence score and sends them as JSON alerts to a webhook endpoint. The symbol "ETHUSD" is hardcoded in the alert - ideal for use with an automated trading bot.
Dieses Script ist die ETH/USD-spezifische Version des Bot Webhook v8.4. Es generiert Long- und Short-Signale mit Confidence-Score und sendet diese als JSON-Alert an einen Webhook-Endpunkt. Das Symbol "ETHUSD" ist fest im Alert eingebettet - ideal fuer den Einsatz mit einem automatisierten Trading-Bot.
Base: v7.3 TF-specific filters (proven) + v8.0 Keltner/Regime (Squeeze SHORT only)
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SIGNAL LOGIC / SIGNAL-LOGIK
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LONG Signals (v7.3 Base):
- RSI < TF-specific threshold (Oversold)
- Stochastic K < TF-specific threshold
- RSI Slope > TF-specific threshold (Momentum reversal / Momentum-Wende)
- ADX < TF-specific threshold (no excessive counter-trend / kein ueberstarker Gegentrend)
- Proven performance: 68.2% $20-rate, R/R 1.48x
SHORT Signals (v7.3 Base + Keltner Squeeze):
- RSI > TF-specific threshold (Overbought)
- Stochastic K > TF-specific threshold
- RSI Slope < TF-specific threshold (Momentum reversal / Momentum-Wende)
- Squeeze SHORT: Bollinger inside Keltner + bearish momentum
- Proven performance: 53.8% $20-rate, R/R 1.39x (Squeeze)
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INDICATORS / INDIKATOREN
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- EMA 20/50/200 (Trend detection + filter / Trend-Erkennung + Filter)
- RSI 14 + RSI Slope (Momentum + direction change / Richtungswechsel)
- Stochastic RSI (Overbought/Oversold conditions)
- MACD 12/26/9 (Momentum confirmation / Momentum-Bestaetigung)
- Bollinger Bands 20/2.0 (Volatility + Squeeze Detection)
- Keltner Channel 20/1.5 (Squeeze Detection)
- ADX 14 (Trend strength / Trendstaerke)
- ATR 14 (Stop Loss / Take Profit calculation)
- Volume SMA 20 (Volume confirmation / Volumen-Bestaetigung)
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REGIME DETECTION / REGIME-ERKENNUNG
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Trend Regime (EMA-based):
- STRONG_TREND_UP / STRONG_TREND_DOWN
- WEAK_TREND_UP (BLOCKED - 0% success rate! / BLOCKIERT - 0% Erfolgsrate!)
- WEAK_TREND_DOWN / NEUTRAL
Volatility Regime (ADX + ATR Percentile):
- TRENDING_HIGH_VOL / TRENDING_LOW_VOL
- SQUEEZE_BUILDING / BREAKOUT_IMMINENT
- RANGING_HIGH_VOL / RANGING_LOW_VOL
- TRANSITIONAL
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CONFIDENCE CALCULATION / CONFIDENCE-BERECHNUNG
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Base confidence from verified win rates per timeframe (0.72-0.92)
Modifiers / Modifikatoren:
+ Extreme RSI/StochK values (+0.03 to +0.05)
+ Trending High Vol Regime (+0.04)
- Ranging High Vol Regime (-0.08)
- Squeeze Building (-0.03)
- Counter-trend / Gegentrend (-0.10)
- Low Volume (-0.05)
Min. confidence for alert: 70% (adjustable / einstellbar)
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STOP LOSS / TAKE PROFIT
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Base trades: ATR x 1.5 (SL) / ATR x 2.5 (TP) = R/R 1:1.67
Squeeze trades: ATR x 1.2 (SL) / ATR x 3.0 (TP) = R/R 1:2.5
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TIMEFRAMES
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Supported / Unterstuetzt: 30S, 45S, 1m-20m (each with individually optimized thresholds / alle mit eigenen optimierten Schwellenwerten)
Best TFs / Beste TFs: 30S (47.1%), 45S (34.8%), 12m+ (33%+)
4m: LONG + SHORT disabled (no data / deaktiviert, keine Daten)
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WEBHOOK ALERT FORMAT (JSON)
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{"signal":"long/short", "symbol":"ETHUSD", "timeframe":"...", "price":..., "source":"Bot_Webhook_v84", "confidence":..., "metadata":{"entry":..., "stop_loss":..., "take_profit":..., "atr":..., "adx":..., "rsi":..., "rsi_slope":..., "stoch_k":..., "signal_type":"...", "strategy":"...", "regime":"...", "vol_regime":"...", "expected_wr":"..."}}
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SETUP
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1. Apply script to ETHUSDT/ETHUSD chart / Script auf ETHUSDT/ETHUSD Chart anwenden
2. Select desired timeframe (30S-20m) / Gewuenschten Timeframe waehlen
3. Create alert and enter webhook URL / Alert erstellen und Webhook-URL eintragen
4. Create a separate alert for each timeframe / Fuer jeden Timeframe einen separaten Alert erstellen
Other versions available / Weitere Versionen verfuegbar: BTC, SOL
DISCLAIMER: This strategy is for educational purposes only. Past performance does not guarantee future results. Always use proper risk management. / Diese Strategie dient zu Bildungszwecken. Vergangene Performance garantiert keine zukuenftigen Ergebnisse. Nutze stets ein angemessenes Risikomanagement.
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AUTOMATED TRADING BOT / AUTOMATISIERTER TRADING-BOT
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Want to automate these signals? A fully automated trading bot is available that processes the webhook alerts from this script and executes trades on Kraken Futures - including risk management, position sizing, regime filtering and smart signal validation.
- Full bot with live trading or paper trading mode
- Processes all signals from this indicator automatically
- Built-in risk management with ATR-based SL/TP
- Multi-timeframe support (30S-20m)
More info: futuresbot.de
Or send me a direct message here on PulseWire!
Du moechtest diese Signale automatisieren? Es gibt einen vollautomatischen Trading-Bot, der die Webhook-Alerts dieses Scripts verarbeitet und Trades auf Kraken Futures ausfuehrt - inklusive Risikomanagement, Positionsgroesse, Regime-Filterung und smarter Signal-Validierung.
- Kompletter Bot mit Live-Trading oder Paper-Trading-Modus
- Verarbeitet alle Signale dieses Indikators automatisch
- Integriertes Risikomanagement mit ATR-basiertem SL/TP
- Multi-Timeframe-Unterstuetzung (30S-20m)
Mehr Infos: futuresbot.de
Oder schreib mir eine persoenliche Nachricht hier auf PulseWire!
Indicator
Indicator
[ A L P H A X ] Range Profile ProAlphaX Range Profile Pro — Volume Profile, POC, Value Area, Delta & HVN Levels
Stop guessing where price wants to go. AlphaX Range Profile Pro builds a full volume profile over any custom bar range, automatically locating the Point of Control, Value Area High, Value Area Low, and High Volume Nodes — so you always know exactly where the market has accepted the most volume and where it is likely to react next. Built for Gold, Forex, Crypto, Indices, and Futures traders on any timeframe.
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🔍 What This Indicator Does
Volume profile is the single most powerful tool for understanding where institutional money has been most active. AlphaX Range Profile Pro scans every candle inside your selected range, distributes volume across price bins using a body-and-wick weighted algorithm, and renders a clean horizontal volume profile directly on your chart — complete with POC, Value Area, and optional HVN lines. Every level updates in real time as new bars form.
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⚡ Key Features
📊 Body & Wick Weighted Volume Distribution
Most volume profile tools split volume equally across the full candle range. AlphaX Range Profile Pro uses a precise body-and-wick weighting model — up volume is assigned to bullish body segments, down volume to bearish body segments, and wick volume is split proportionally. The result is a significantly more accurate representation of where buying and selling pressure actually occurred at each price level.
🎯 Point of Control (POC)
The POC line marks the single price level with the highest traded volume in the entire range — the most accepted price by the market. It acts as a magnet for price and is one of the most reliable reaction levels in any profile. The POC is displayed as a solid line with a clearly labelled price tag and volume percentage.
📦 Value Area (VAH & VAL)
The Value Area represents the price range containing a configurable percentage of total volume (default 70%). VAH and VAL are plotted as dashed lines with labels. The Value Area fill box shades the region across your chart for instant visual reference. Price trading inside the Value Area indicates acceptance. Price outside the Value Area indicates potential for a return or a breakout continuation.
🔵🟠 Up / Down Split Display
Each profile row is rendered in two segments — blue for buy-side volume and orange for sell-side volume — showing the delta composition of every price level at a glance. Three display modes are available: Up/Down Split, Total Only, and Delta Only, so you can view the profile in whichever format suits your analysis style.
📍 High Volume Nodes (HVN)
Optional HVN lines mark the top secondary volume levels outside the POC. These are the next most traded price clusters in the range and often act as strong support, resistance, and target levels. The number of HVN lines displayed is fully configurable.
📐 Flexible Range Selection
Choose between Fixed Bars mode to profile the last N candles, or From Date/Time mode to anchor the profile to a specific session or event start. Profile width, placement, and X offset are all adjustable so the profile sits exactly where you need it on your chart.
🖥 Professional Dark Panel Design
The profile renders inside a clean dark glass panel with an accent edge, subtle backdrop, and optional highlight — keeping the profile readable without cluttering your price action. All colors are individually customisable including up volume, down volume, value area fill, panel tint, border, and accent.
📋 Stats Table
A compact on-chart stats table displays all key metrics in one place: range bar count, POC price and volume percentage, VAH and VAL, total up and down volume, and net delta. Table position is configurable to any corner of the chart.
🔔 4 Built-In Alert Conditions — Webhook Ready
Cross Above POC — price closes above the Point of Control
Cross Below POC — price closes below the Point of Control
Cross Above VAH — price closes above the Value Area High
Cross Below VAL — price closes below the Value Area Low
All alerts fire on confirmed bar close. Connect to Telegram, 3Commas, Alertatron, n8n, or any webhook automation service.
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⚙ Settings Reference
Range
Range Mode — Fixed Bars or From Date/Time anchor
Number of Bars — how many bars back to profile (default 150)
Anchor Time — start timestamp for Date/Time mode
Max Lookback — maximum bars scanned in anchor mode
Profile
Row Size (bins) — number of horizontal price bins (default 24). Higher = more granular profile
Value Area Volume % — percentage of volume defining the Value Area (default 70%)
Display Mode — Up/Down Split, Total Only, or Delta Only
Profile Width — horizontal width of the profile in bars
Placement — Left inside chart or Right (future bars)
X Offset — fine-tune horizontal position
Levels
Shade Value Area — fills the VAH–VAL range across the chart
Show POC — toggle POC line
Show VAH / VAL — toggle Value Area lines
Show Range High / Low — toggle outer range boundary lines
Extend Lines — extend levels to the right or keep contained
Show Level Labels — toggle price labels on all levels
Show HVN Lines — toggle High Volume Node lines
HVN Count — number of HVN lines to display (1–5)
Style
Full color controls for POC, VAH, VAL, up volume, down volume, value area fill, panel background, border, accent edge, labels, and highlight tint
Line width controls for POC, VAH/VAL, HVN, and panel border
Row gap — spacing between profile bins
Stats
Stats Table — toggle the on-chart statistics panel
Table Position — Top Right, Top Left, Bottom Right, or Bottom Left
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🚀 How to Use
Add AlphaX Range Profile Pro to any chart — default settings work well across most markets
Set your Range Mode — use Fixed Bars for a rolling profile or anchor to a specific session open
Focus on the POC first — it is the highest conviction level in the entire profile
Use VAH and VAL as your Value Area boundaries — look for rejections at VAH in downtrends and VAL in uptrends
Watch for price to leave and return to the Value Area — these are high-probability mean reversion setups
Enable HVN lines to identify secondary reaction levels within the range
Set alerts on POC and VAH/VAL crosses for automated entry triggers
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👥 Who This Is For
🥇 Gold (XAUUSD) traders — volume profile is essential for reading institutional order flow in XAU
📈 ICT and Smart Money traders — use POC and Value Area to identify premium, discount, and equilibrium zones
📊 Volume profile traders — a clean, accurate, customisable profile built natively in Pine Script v6
📉 Forex and Index traders — works on all major pairs, US30, NAS100, SPX500, and more
🌍 Crypto traders — ideal for BTC, ETH, and high-volume altcoin analysis
🤖 Algo and bot traders — webhook-ready alerts on all key level crosses
📐 All timeframes — from M1 intraday scalping to Daily and Weekly swing analysis
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📝 Notes
Works on all asset classes — Gold, Forex, Crypto, Futures, Indices, Stocks
Profile recalculates fully on every bar close — always current
No repainting — all levels are based on confirmed historical volume data
Pine Script v6 — built for performance and forward compatibility
All visual elements are individually toggleable
Recommended timeframes: M5, M15, M30, H1, H4, Daily
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Built for traders who trade with the market, not against it. Indicator
Divergence Confirmation System [JOAT]Divergence Confirmation System
Introduction
The Divergence Confirmation System (DCS) is an advanced open-source multi-oscillator divergence detection indicator that combines RSI, MFI, Stochastic, MACD, CCI, and Stochastic RSI analysis to identify high-probability divergence setups through systematic pivot comparison and multi-oscillator confirmation. This indicator reveals when price action diverges from underlying momentum across six independent oscillators, providing traders with early warning signals of potential trend reversals or continuations through rigorous confirmation requirements.
Unlike basic divergence indicators that rely on a single oscillator, DCS employs a sophisticated 6-oscillator confirmation system that detects both regular divergences (trend reversal signals) and hidden divergences (trend continuation signals) across multiple momentum indicators. The indicator requires minimum oscillator confirmation (default 2/6) to filter false signals and provides divergence strength scoring based on oscillator count, volume confirmation, and price momentum.
Why This Indicator Exists
This indicator addresses the challenge of identifying reliable divergence signals in noisy market conditions. Single-oscillator divergences often produce false signals, but when multiple independent oscillators confirm the same divergence pattern, probability of successful reversal increases significantly. DCS systematically reveals:
6-Oscillator Analysis: RSI, MFI, Stochastic, MACD, CCI, Stochastic RSI for comprehensive momentum assessment
Regular Divergence Detection: Price makes new high/low but oscillators don't confirm (reversal signal)
Hidden Divergence Detection: Price makes higher low/lower high but oscillators show opposite (continuation signal)
Multi-Oscillator Confirmation: Requires 2+ oscillators to agree before generating signal
Divergence Strength Scoring: 0-100% score based on oscillator count, volume, and momentum
Multi-Timeframe Divergence: Confirms divergences on higher timeframe for added conviction
Divergence Clustering: Detects multiple divergences in short period indicating strong reversal potential
Each component provides unique intelligence. Multiple oscillators reduce false signals, regular divergences show reversals, hidden divergences show continuations, strength scoring quantifies quality, MTF confirmation adds conviction, and clustering shows intensity.
Core Components Explained
1. Multi-Oscillator Divergence Detection System
DCS calculates six independent oscillators and detects divergences on each:
// RSI
float rsi = ta.rsi(close, rsi_period)
float rsi_high = ta.pivothigh(rsi, pivot_left, pivot_right)
float rsi_low = ta.pivotlow(rsi, pivot_left, pivot_right)
// MFI (Money Flow Index - volume-weighted RSI)
float mfi = ta.mfi(hlc3, mfi_period)
// Stochastic
float stoch_k = ta.stoch(close, high, low, stoch_period)
// MACD Histogram
= ta.macd(close, macd_fast, macd_slow, macd_signal)
// CCI (Commodity Channel Index)
float cci = ta.cci(close, 20)
// Stochastic RSI
float rsi_for_stoch = ta.rsi(close, rsi_period)
float stoch_rsi_k = ta.stoch(rsi_for_stoch, rsi_for_stoch, rsi_for_stoch, stoch_period)
Each oscillator provides independent momentum perspective. RSI shows price momentum, MFI adds volume weighting, Stochastic shows position in range, MACD shows trend momentum, CCI shows deviation from mean, and Stochastic RSI shows RSI momentum.
2. Regular Divergence Detection (Reversal Signals)
Regular bullish divergence occurs when price makes lower low but oscillator makes higher low:
f_detect_bull_regular_div(float osc_val, float osc_pivot) =>
bool detected = false
if not na(osc_pivot) and not na(price_low) and array.size(price_lows) >= 2
float curr_price = array.get(price_lows, last_idx)
float prev_price = array.get(price_lows, prev_idx)
// Price makes lower low, oscillator makes higher low
if curr_price < prev_price and osc_pivot > osc_pivot
if (bar_index - prev_bar) <= max_pivot_distance
detected := true
detected
Regular bearish divergence occurs when price makes higher high but oscillator makes lower high. These signal potential trend reversals.
3. Hidden Divergence Detection (Continuation Signals)
Hidden bullish divergence occurs when price makes higher low but oscillator makes lower low:
f_detect_bull_hidden_div(float osc_val, float osc_pivot) =>
bool detected = false
if detect_hidden and not na(osc_pivot) and not na(price_low)
float curr_price = array.get(price_lows, last_idx)
float prev_price = array.get(price_lows, prev_idx)
// Price makes higher low, oscillator makes lower low
if curr_price > prev_price and osc_pivot < osc_pivot
if (bar_index - prev_bar) <= max_pivot_distance
detected := true
detected
Hidden bearish divergence occurs when price makes lower high but oscillator makes higher high. These signal trend continuation after pullback.
4. Multi-Oscillator Confirmation Aggregation
DCS counts how many oscillators confirm each divergence type:
int bull_reg_count = (rsi_bull_reg ? 1 : 0) + (mfi_bull_reg ? 1 : 0) +
(stoch_bull_reg ? 1 : 0) + (macd_bull_reg ? 1 : 0) +
(cci_bull_reg ? 1 : 0) + (srsi_bull_reg ? 1 : 0)
bool confirmed_bull_regular = bull_reg_count >= min_oscillators
// Optional volume confirmation
float vol_avg = ta.sma(volume, 20)
bool vol_confirm = volume > vol_avg * 1.2
bool final_bull_regular = confirmed_bull_regular and
(not require_volume_confirm or vol_confirm)
Minimum oscillator requirement (default 2/6) filters false signals. Volume confirmation adds additional filter.
5. Divergence Strength Scoring System
Strength score (0-100%) calculated from multiple factors:
f_divergence_strength(int osc_count, bool vol_confirm_param, float price_momentum) =>
float score = 0.0
// Oscillator count (0-50 points)
score += osc_count * 8.33 // 6 oscillators max = 50 points
// Volume confirmation (0-25 points)
score += vol_confirm_param ? 25 : 0
// Price momentum (0-25 points)
float momentum_score = math.min(math.abs(price_momentum) * 5, 25)
score += momentum_score
math.min(score, 100)
Strength classification:
- 75-100%: Very Strong (highest probability)
- 60-74%: Strong (high probability)
- 40-59%: Moderate (medium probability)
- 0-39%: Weak (low probability)
6. Multi-Timeframe Divergence Confirmation
DCS checks for divergences on higher timeframe (default 15m):
f_get_htf_divergence(string tf) =>
= request.security(syminfo.tickerid, tf,
)
float htf_rsi_high = ta.pivothigh(htf_rsi, pivot_left, pivot_right)
float htf_rsi_low = ta.pivotlow(htf_rsi, pivot_left, pivot_right)
bool htf_bull = f_detect_bull_regular_div(htf_rsi, htf_rsi_low)
bool htf_bear = f_detect_bear_regular_div(htf_rsi, htf_rsi_high)
bool mtf_bull_confirmed = final_bull_regular and htf_bull_div
bool mtf_bear_confirmed = final_bear_regular and htf_bear_div
MTF confirmation significantly increases signal reliability.
7. Divergence Clustering Detection
Clustering identifies multiple divergences in short period:
var array div_bars = array.new_int(0)
if final_bull_regular or final_bear_regular
array.push(div_bars, bar_index)
// Count divergences in last 50 bars
int recent_div_count = 0
for i = 0 to array.size(div_bars) - 1
int div_bar = array.get(div_bars, i)
if bar_index - div_bar <= 50
recent_div_count += 1
bool in_div_cluster = recent_div_count >= 3
string cluster_intensity = recent_div_count >= 5 ? "High" :
recent_div_count >= 3 ? "Moderate" : "Low"
Clusters indicate strong reversal pressure building.
Visual Elements
Primary Oscillator Display: User-selectable (RSI/MFI/Stochastic/MACD) with gradient shadow effect
Reference Lines: 70 (overbought), 50 (midline), 30 (oversold)
Oscillator Histogram: Gradient-colored bars showing oscillator deviation from 50
Background Zones: Cyan for bullish divergence, red for bearish divergence
Divergence Labels: "BULL DIV" or "BEAR DIV" with oscillator count (e.g., "4/6")
Hidden Divergence Markers: Small "H" circles for hidden divergences
Elite Signals: Large labels for 4+ oscillator confirmation with strength >75%
MTF Confirmation: Triangle markers when higher timeframe confirms
Multi-Oscillator Confirmation: Labels showing oscillator count (e.g., "3/6 CONF")
Institutional Flow: "INST BUY/SELL" labels when delta confirms divergence
Input Parameters
Oscillator Settings:
RSI Period: RSI calculation period (default: 14)
MFI Period: MFI calculation period (default: 14)
Stochastic Period: Stochastic calculation period (default: 14)
MACD Fast: MACD fast EMA (default: 12)
MACD Slow: MACD slow EMA (default: 26)
MACD Signal: MACD signal line (default: 9)
Divergence Detection:
Pivot Left Bars: Bars to left of pivot (default: 5)
Pivot Right Bars: Bars to right of pivot (default: 2)
Detect Hidden Divergences: Toggle hidden divergence detection (default: true)
Max Pivot Distance: Maximum bars between pivots (default: 60)
Confirmation Rules:
Minimum Oscillator Confirmation: Required oscillators (default: 2/6)
Require Volume Confirmation: Toggle volume filter (default: false)
Visualization:
Show Divergence Lines: Toggle divergence line drawing (default: true)
Show Labels: Toggle divergence labels (default: true)
Primary Display: Select oscillator to display (RSI/MFI/Stochastic/MACD)
How to Use This Indicator
Step 1: Monitor Primary Oscillator
Watch selected oscillator (default RSI) for overbought/oversold conditions.
Step 2: Wait for Divergence Labels
"BULL DIV" or "BEAR DIV" labels appear when 2+ oscillators confirm divergence.
Step 3: Check Oscillator Count
Higher count = higher probability. 4/6 or better is ideal.
Step 4: Assess Divergence Strength
Tooltip shows strength percentage. >75% is very strong, >60% is strong.
Step 5: Confirm with MTF
Triangle markers indicate higher timeframe confirmation - highest probability setups.
Step 6: Watch for Elite Signals
Large "BULL DIV" or "BEAR DIV" labels with 4+ oscillators and >75% strength are highest conviction.
Best Practices
Focus on divergences with 3+ oscillator confirmation for best results
Regular divergences work best at price extremes (support/resistance)
Hidden divergences confirm trend continuation - trade with trend
MTF confirmation adds significant edge - wait when possible
Divergence clustering indicates strong reversal pressure
Volume confirmation reduces false signals but adds lag
Elite signals (4+ oscillators, >75% strength) have highest win rate
Use cooldown system (15 bars minimum) to avoid overtrading
Combine with price action - divergence shows momentum, price shows structure
Indicator Limitations
Divergence detection requires clear pivot formation - lags by pivot_right bars
Multiple oscillators can produce conflicting signals during choppy markets
Hidden divergences are less reliable than regular divergences
Strength scoring is probabilistic, not deterministic
MTF confirmation adds lag but increases reliability
Clustering detection has fixed lookback - may miss longer-term patterns
Volume confirmation may not work well on illiquid instruments
Extreme market conditions can invalidate divergence signals
Technical Implementation
Built with Pine Script v6 using:
6-oscillator system (RSI, MFI, Stochastic, MACD, CCI, Stochastic RSI)
Pivot-based divergence detection with array tracking
Regular and hidden divergence algorithms
Multi-oscillator confirmation aggregation
Divergence strength scoring (oscillator count + volume + momentum)
Multi-timeframe security requests for HTF confirmation
Divergence clustering detection (50-bar lookback)
Signal cooldown system (15 bars minimum)
Gradient visualization with dynamic coloring
Institutional flow integration (CVD delta analysis)
Elite signal filtering (4+ oscillators, >75% strength)
The code is fully open-source and can be modified to suit individual trading styles.
Originality Statement
This indicator is original in its comprehensive multi-oscillator divergence confirmation approach. While individual oscillator divergences are established concepts, this indicator is justified because:
It combines 6 independent oscillators (RSI, MFI, Stochastic, MACD, CCI, Stochastic RSI) for robust confirmation
The multi-oscillator confirmation system (2-6 required) significantly reduces false signals
Divergence strength scoring quantifies setup quality through multi-factor analysis
Multi-timeframe divergence confirmation adds conviction layer
Divergence clustering detection identifies high-probability reversal zones
Integration of institutional flow (CVD delta) with divergence analysis is unique
Elite signal filtering (4+ oscillators, >75% strength) isolates highest probability setups
Signal cooldown system prevents overtrading while maintaining signal quality
Each component contributes unique information: multiple oscillators reduce false signals, regular divergences show reversals, hidden divergences show continuations, strength scoring quantifies quality, MTF confirmation adds conviction, clustering shows intensity, and institutional flow confirms with volume. The indicator's value lies in presenting these complementary perspectives simultaneously with rigorous confirmation requirements.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Divergence signals do not guarantee reversals. Trading involves substantial risk of loss. Past performance does not guarantee future results. Always use proper risk management and never risk more than you can afford to lose.
-Made with passion by officialjackofalltrades Indicator
Institutional Order Flow Shield [MarkitTick]💡 The Institutional Order Flow Shield is an advanced, overlay-based technical indicator designed to peer inside the standard price chart and extract granular order flow dynamics. By utilizing lower timeframe (LTF) intrabar data, this tool reconstructs buying and selling pressure, helping traders identify hidden accumulation, distribution, and manipulative market practices such as order spoofing and iceberg execution. It acts as a comprehensive shield, filtering market noise through volatility and trend alignment to deliver high-probability signals.
✨ Originality and Utility
Standard volume indicators often fail to distinguish between aggressive buying and aggressive selling within a single candle. This script solves that problem by drilling down into intrabar price action to approximate order flow delta.
● Key Differentiators
Intrabar Reconstruction: Rebuilds volume delta without requiring expensive tick data or footprint charts.
Manipulation Detection: Specifically engineered to detect "Spoofing" (pulling large limit orders to fake price direction) and "Icebergs" (large hidden orders executing in smaller clips).
Adaptive Decision Matrix: Does not just fire raw signals; it weights them using a confidence scoring system based on VWAP, EMA trends, and Relative Volume (RVOL).
🔬 Methodology and Concepts
The core engine of this indicator relies on several interconnected mathematical and logical frameworks to process market data.
● Order Flow Approximation
The script requests lower timeframe data (defaulting to 1-minute candles) and calculates where the close occurs relative to the high-low range of that LTF candle. It allocates volume to the "Buy" side or "Sell" side proportionally. Wick rejections are also factored in to adjust the final volume delta, reducing the impact of passive limit orders getting filled at extreme highs or lows.
● Spoof and Iceberg Logic
Spoof Detection: Triggered when a massive volume spike is followed immediately by a sharp volume drop and a price reversal, indicating that the liquidity was pulled (faked) rather than executed.
Iceberg Detection: Identified when volume surges past a smart threshold (based on a multiplier of the volume SMA) while price stalls, indicating a massive hidden limit order absorbing market aggression.
🎨 Visual Guide
The indicator provides a rich, non-intrusive visual experience on the main chart, utilizing color-coded bars, labels, and a comprehensive dashboard.
● Chart Elements
Bar Colors: Candles are painted bright green for confirmed bullish signals (confidence > 50%) and bright red for confirmed bearish signals.
ACM / DST Labels: Green "ACM" labels indicate accumulation (bullish order flow), while Red "DST" labels indicate distribution. Hovering over these labels reveals a tooltip with confidence score, VWAP alignment, and volume impact.
BPL / APL Labels: Orange labels denoting Bid Pulls and Ask Pulls (Spoofing events).
BWL / AWL Labels: Cyan labels highlighting Bid Walls and Ask Walls (Iceberg events).
WBD / WAK Labels: Faded cyan labels indicating massive Whale Bid or Ask entries based purely on relative volume spikes.
● The Sniper Dashboard
Located by default in the top right corner, this table provides a real-time summary.
Net Whale Flow: The cumulative delta of massive order events.
Decision Matrix: Displays the current overall bias (e.g., "STRONG BUY" or "WAIT/NEUTRAL").
Signal Confidence: A percentage score grading the strength of the current setup.
Filters: Real-time status of RVOL, VWAP Position, EMA Trend, and ATR Gates.
Event Counters: Tracks the total number of spoofing and iceberg anomalies detected during the session.
📖 How to Use
This indicator is best used as a confluence tool for day trading and scalping.
● Trade Execution Guidelines
Identify the Trend: Check the dashboard to ensure the EMA 50/200 trend aligns with your directional bias.
Wait for Manipulation: Look for Spoof (BPL/APL) or Iceberg (BWL/AWL) labels. A Bid Pull (Spoof) often precedes a move lower, while a Bid Wall (Iceberg) can act as solid support.
Confirm with Accumulation/Distribution: Enter a long trade when a green "ACM" label appears, confirming that aggressive buyers have stepped in. Ensure the dashboard's "Signal Conf." is high (above 60-70%).
Risk Management: Place stop losses behind identified Iceberg walls. If an Ask Wall (AWL) is broken by price, it often triggers a short squeeze, offering breakout opportunities.
⚙️ Inputs and Settings
The script offers deep customization through its settings menu, divided into functional groups.
● Order Flow Engine
Intrabar Timeframe (LTF): Determines the granularity of the internal volume calculation.
Flow Batch Length (bars): The rolling window used to sum up recent volume delta.
Flow Sensitivity Ratio: Adjusts how much larger the average buy size must be compared to the sell size to trigger an accumulation signal.
● Spoof & Iceberg Detection
Min Spoof Volume Diff: The minimum volume drop required to flag a pulled order.
Spoof Pull Threshold (%): The percentage drop required compared to the previous bar.
Iceberg Avg Multiplier: How many times larger than the average volume a bar must be to trigger an iceberg alert.
● Smart Filters
RVOL Filter: Requires the current bar's volume to be above a specific relative threshold, keeping you out of low-liquidity chop.
ATR Volatility Gate: Suppresses signals on extremely tight, flat candles based on a minimum ATR percentage.
VWAP / Trend Filters: Toggles the alignment checks that feed into the confidence scoring.
🔍 Deconstruction of the Underlying Scientific and Academic Framework
The foundation of this indicator rests heavily on Market Microstructure Theory and Order Book Dynamics.
● Volume Delta Estimation Models
Because trading platforms often do not natively supply bid/ask tick data for all assets, the script utilizes an intrabar price-proportion heuristic. This aligns with academic models like the Lee-Ready algorithm, which infers trade direction based on price movement relative to previous prints. By applying this to LTF data and rolling it up, the script effectively calculates a weighted approximation of order flow toxicity (the imbalance of aggressive market orders).
● Liquidity Illusion and Spoofing
Spoofing is a recognized manipulative practice where liquidity is posted to the limit order book to create a false impression of supply or demand, only to be cancelled before execution. The script attempts to quantify this mathematically by monitoring sudden, severe variance in Relative Volume (RVOL) coupled with strict directional price reversals. When volume drops below the pullback threshold immediately following an injection phase, the algorithm flags the structural anomaly.
● Bayesian-Inspired Confidence Matrix
The Decision Matrix behaves similarly to a naive Bayesian classifier. It starts with a base event (e.g., an accumulation phase) and updates the probability (Confidence Score) of a successful follow-through by checking independent market state variables: Mean Reversion metrics (VWAP), Volatility (ATR), and Momentum (EMA crossover). This multidimensional filtering ensures that order flow anomalies are only traded when the broader statistical environment is favorable.
⚠️ Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion. Indicator
Indicator
Gamma Exposure Levels [BackQuant]Gamma Exposure Levels
This indicator allows you to paste Gamma Exposure (GEX) level data directly into a text input on PulseWire, automatically parsing the values and plotting them as labeled horizontal lines on your chart. It is designed for traders who use options-derived gamma exposure data as part of their technical analysis and want a fast, visual way to overlay those key price levels onto any chart and timeframe.
Rather than manually drawing lines for each level, this script reads a structured block of GEX output text, extracts every relevant dollar value, and draws color-coded, labeled levels across your chart. If two or more levels share the same price, their labels are automatically merged (for example, "Max Pain / Call Res $75,000") so the chart stays clean and readable.
What is Gamma Exposure (GEX)?
Gamma Exposure refers to the aggregate gamma held by options market makers (dealers) at each strike price. Gamma measures how much a dealer's delta (directional hedge) changes as the underlying price moves. When dealers hold large gamma positions, they must continuously hedge by buying or selling the underlying asset, which can either dampen or amplify price movement depending on the sign of that gamma.
When dealers are long gamma (positive GEX), they hedge against the prevailing trend: buying dips and selling rallies. This creates a stabilizing, mean-reverting effect around high-gamma strikes, making those levels act like magnets or support/resistance zones.
When dealers are short gamma (negative GEX), they hedge in the same direction as the move: selling into drops and buying into rallies. This amplifies volatility and can cause sharp, directional moves once a key gamma level breaks.
Understanding where these gamma levels sit gives traders a structural map of where options market makers are likely to add liquidity or accelerate a move.
How to Use This Indicator
Add the indicator to your chart.
Open the indicator settings and find the "Data Input" group at the top.
Paste your full GEX levels output into the text area. The indicator expects a structured text format (see the example format below).
The indicator will automatically parse all dollar values from the text and plot them as horizontal lines with labels.
Use the toggle checkboxes next to each level type to show or hide individual levels.
Customize colors, line style, line width, label size, label offset, and label position from the settings panel.
Expected Input Format
The indicator parses structured GEX output text. Below is an example of the expected format. Copy and paste a block like this directly into the text area input in the indicator settings:
GEX Levels - 04/03/2026, 12:17:19
All-Expiry Levels:
HVL: $72,000 +$1,841 (+2.62%)
Call Resistance: $75,000 +$4,841 (+6.90%)
Put Support: $60,000 $-10,159 (-14.48%)
0DTE Levels:
0DTE HVL: $68,000 $-2,159 (-3.08%)
0DTE Call: $71,000 +$841 (+1.20%)
0DTE Put: $66,000 $-4,159 (-5.93%)
Advanced:
Zero Gamma: $71,819 +$1,660 (+2.37%)
Max Pain: $74,000 +$3,841 (+5.47%)
Expected Move: $64,238 to $76,081
Flip Zones (All): $67,500
All-Expiry GEX Top 10 (by |gamma|):
1. $60,000 $-10,159 (-14.48%) | GEX: -20,711,741.86
2. $75,000 +$4,841 (+6.90%) | GEX: 18,876,578.2
3. $72,000 +$1,841 (+2.62%) | GEX: 17,530,960.01
4. $70,000 $-159 (-0.23%) | GEX: 17,494,795.02
5. $74,000 +$3,841 (+5.47%) | GEX: 13,573,146.08
6. $73,000 +$2,841 (+4.05%) | GEX: 10,380,107.7
7. $69,000 $-1,159 (-1.65%) | GEX: 10,341,883.98
8. $80,000 +$9,841 (+14.03%) | GEX: 8,636,674.83
9. $71,000 +$841 (+1.20%) | GEX: 7,962,084.65
10. $65,000 $-5,159 (-7.35%) | GEX: -7,257,124.01
0DTE GEX Top 10 (by |gamma|):
1. $69,500 $-659 (-0.94%) | GEX: 3,659,702.74
2. $70,500 +$341 (+0.49%) | GEX: 1,152,595.15
3. $69,000 $-1,159 (-1.65%) | GEX: 703,339.82
4. $72,000 +$1,841 (+2.62%) | GEX: 697,625.91
5. $73,000 +$2,841 (+4.05%) | GEX: 419,096.08
6. $68,000 $-2,159 (-3.08%) | GEX: 294,575.89
7. $74,000 +$3,841 (+5.47%) | GEX: 281,083.42
8. $75,000 +$4,841 (+6.90%) | GEX: 183,191.05
9. $66,000 $-4,159 (-5.93%) | GEX: -172,470.38
10. $68,500 $-1,659 (-2.37%) | GEX: 167,135.87
The indicator only extracts the dollar values from this text. The percentage changes, GEX magnitude values, and other metadata are informational context in the source data but are not plotted by this script.
Level Definitions
Below is a detailed explanation of every level this indicator can parse and plot. These are grouped the same way they appear in the indicator settings.
All-Expiry Levels
These levels are derived from gamma exposure aggregated across all option expiration dates.
HVL (High Volume Level) - The price with the highest total gamma exposure across all expirations. This is the strike where dealers hold the most aggregate gamma and therefore where hedging activity is most concentrated. Price tends to gravitate toward the HVL in positive gamma environments because dealer hedging creates a mean-reverting effect around this level. Think of it as the "center of gravity" for options-driven price action.
Call Resistance - The price level where call-side gamma creates overhead resistance. At this strike, the concentration of call gamma means that as price rises toward it, dealers who are long those calls must sell the underlying to stay delta-neutral. This selling pressure acts as a ceiling, making it harder for price to push through. Breaks above call resistance can signal a shift in positioning or the start of a gamma squeeze.
Put Support - The price level where put-side gamma creates downside support. At this strike, the concentration of put gamma means that as price falls toward it, dealers must buy the underlying to hedge. This buying pressure acts as a floor, cushioning the decline. A break below put support can accelerate selling as dealers flip from buying to selling, potentially triggering a sharp move lower.
0DTE Levels
These levels are derived exclusively from same-day (zero days to expiration) options. Because 0DTE options have extremely high gamma due to their proximity to expiration, they can dominate intraday price action even when their notional size is smaller than longer-dated positions.
0DTE HVL - The same-day high volume level. This is the intraday gamma center of gravity derived solely from options expiring today. It represents the strike where 0DTE dealer hedging is most concentrated and where intraday gamma polarity can flip. Particularly relevant for intraday traders, as 0DTE gamma effects intensify throughout the trading session and peak in the final hours before expiration.
0DTE Call - Same-day call resistance. The intraday ceiling created by 0DTE call gamma. Dealer hedging against these expiring calls creates selling pressure as price approaches this level. Because 0DTE gamma decays rapidly, this level can shift during the session and its strength increases as expiration approaches.
0DTE Put - Same-day put support. The intraday floor created by 0DTE put gamma. Dealer hedging against expiring puts creates buying pressure at this level. Like the 0DTE call level, its influence grows as the trading day progresses and gamma effects intensify near the close.
Advanced Levels
These levels provide additional structural context beyond the core support, resistance, and HVL framework.
Zero Gamma - The precise price where cumulative gamma across all strikes and expirations equals zero. This is one of the most important structural levels in gamma analysis. Above the Zero Gamma level, dealers are net long gamma and their hedging stabilizes price (buying dips, selling rallies). Below it, dealers are net short gamma and their hedging amplifies moves (selling into drops, buying into rallies). Crossing the Zero Gamma level often marks a regime change in how the market behaves, shifting from mean-reversion to trend-following dynamics.
Max Pain - The strike price at which the total value of all outstanding options (both calls and puts) would be minimized if the underlying expired at that price. In other words, it is the price where option holders collectively lose the most money. Max Pain theory suggests that there is a gravitational pull toward this level as expiration approaches, driven by dealers and market makers who benefit from options expiring worthless. It is most relevant in the final days before a major expiration.
Expected Move - The 1-sigma (one standard deviation) expected price range, plotted as two levels: Expected Move Upper and Expected Move Lower. This range represents the statistically expected boundaries of price movement based on current implied volatility. Roughly 68% of the time, price is expected to remain within this range. These levels help traders gauge whether the current price action is within normal bounds or represents an unusual move. A break beyond the expected move range can signal a volatility event or a shift in market regime.
Flip Zones - All price levels where gamma polarity changes sign. At these strikes, dealer hedging behavior transitions from stabilizing (long gamma) to destabilizing (short gamma) or vice versa. Flip zones act as transition boundaries. When price crosses a flip zone, the nature of dealer activity changes, which can lead to shifts in volatility, momentum, and the tendency for price to mean-revert or trend. Multiple flip zones in a narrow range can create a "no man's land" where positioning is mixed and price action becomes choppy.
GEX Top 10
The GEX Top 10 are the ten strike prices with the highest absolute gamma exposure, ranked by the magnitude of their gamma (|gamma|). These represent the strikes where dealer hedging activity is most significant, regardless of whether the gamma is positive (call-dominated, stabilizing) or negative (put-dominated, destabilizing).
The indicator provides a dropdown selector with five options for the GEX Top 10:
None - Do not plot any GEX Top 10 levels.
0DTE - Plot the Top 10 from same-day (0DTE) options only. Best for intraday analysis.
All Expiries - Plot the Top 10 from all expiration dates combined. Best for swing or multi-day analysis.
0DTE 1-5 - Plot only the top 5 from 0DTE options. Useful for reducing chart clutter while keeping the most significant intraday levels.
All Expiries 1-5 - Plot only the top 5 from all expiration dates. Useful for a cleaner multi-day view.
Each of the 10 GEX levels (GEX #1 through GEX #10) has its own individual toggle and color picker, so you can show or hide any specific rank and assign distinct colors to differentiate them.
Overlap Handling
It is common for multiple GEX levels to land on the same price. For example, Max Pain and Call Resistance might both be at $75,000, or a GEX Top 10 strike might coincide with the HVL. Rather than drawing overlapping lines and labels that clutter the chart, this indicator automatically detects when two or more levels share the same price (within a $0.50 tolerance). When a match is found, only one line is drawn at that price and the labels are merged with a "/" separator.
For example, if Max Pain is $75,000 and Call Resistance is also $75,000, the chart will show a single line labeled:
Max Pain / Call Res 75000
This keeps the chart clean and makes it immediately obvious when multiple structural levels converge at the same price, which often signals a particularly significant level.
Customization Options
The indicator provides extensive customization through its settings panel:
Per-Level Controls
Each level type has its own color picker and show/hide toggle on the same line.
GEX Top 10 levels (#1 through #10) each have individual color pickers and toggles.
A dropdown selector lets you choose which GEX Top 10 dataset to plot (0DTE, All Expiries, top 5 only, or none).
Line Style
Line Width: 1 to 4 pixels.
Line Style: Solid, Dashed, or Dotted.
Extend Lines: Both directions, Right only, Left only, or None.
Label Settings
Label Size: Tiny, Small, Normal, Large, or Huge.
Label Offset: Position the labels any number of bars to the right or left of the current bar (-200 to 500).
Label Side: Place labels on the Right or Left side of the chart.
Every toggle and input has a descriptive tooltip that appears on hover, explaining what the level represents and how it is used.
How the Parsing Works
The script uses Pine Script v6 string functions to scan the pasted text for known keywords (such as "HVL:", "Call Resistance:", "0DTE Call:", "Zero Gamma:", "Expected Move:", "Flip Zones:", etc.). For each keyword found, it locates the next "$" character and extracts the numeric value that follows, correctly handling both comma-separated thousands (e.g., $72,000) and decimal values (e.g., $71,819.50).
For the Expected Move, it parses both the lower and upper bounds from the "to" separator (e.g., "$64,238 to $76,081").
For Flip Zones, it scans for every "$" on the line and extracts each value, correctly distinguishing thousands-separator commas from delimiter commas between multiple zone values.
For the GEX Top 10 sections, it identifies the section header ("All-Expiry GEX Top 10" or "0DTE GEX Top 10") and parses the first dollar value from each numbered line, stopping when it hits a new section header or separator.
The indicator only draws on the last bar and uses a delete-and-redraw system to ensure that only one clean set of lines and labels exists at any time. Old drawings are removed before new ones are created on each update.
Important Notes
This indicator does not generate or calculate GEX data. It is a visualization tool that plots externally sourced gamma exposure levels onto your PulseWire chart.
The indicator requires you to paste GEX data in the expected structured text format. If the text area is empty, nothing will be plotted.
GEX data is a snapshot in time. Options positioning changes throughout the trading day as new trades are opened and closed. Levels should be updated periodically for the most accurate representation of current dealer positioning.
GEX levels are not guaranteed support or resistance. They represent areas where dealer hedging activity is concentrated, which can influence price behavior but does not determine it. Always use GEX data as one component of a broader analysis framework.
Indicator
Aura Trend Momentum [Pineify]```
Aura Trend Momentum - Advanced Double-Smoothed Oscillator with Gradient Visualization
The Aura Trend Momentum indicator is a sophisticated momentum oscillator that combines double exponential smoothing with normalized momentum calculations to provide clear, noise-filtered trend signals. Unlike traditional momentum oscillators that suffer from erratic movements and false signals, this indicator employs a dual-layer EMA smoothing technique on both the raw momentum and its absolute value, creating a stable, normalized oscillator that ranges between -100 and +100. This approach effectively eliminates market noise while preserving the essential momentum characteristics needed for accurate trend identification.
Key Features
Double-smoothed momentum calculation that significantly reduces false signals and whipsaw trades
Normalized oscillator output (-100 to +100) for consistent interpretation across all market conditions and timeframes
Four-color gradient histogram system that visually distinguishes between strong bullish, weak bullish, strong bearish, and weak bearish momentum states
Signal line with cloud fill visualization showing the relationship between momentum and its smoothed average
Smart crossover detection that filters signals by requiring reversals to occur in optimal zones (negative territory for bullish signals, positive territory for bearish signals)
Built-in alert conditions for automated trading notifications and real-time monitoring
Overbought (+50) and oversold (-50) reference levels with zero-line equilibrium
How It Works
The Aura Trend Momentum indicator utilizes a unique three-stage calculation methodology that sets it apart from conventional momentum oscillators:
Stage 1: Momentum Extraction
The indicator begins by calculating the raw price change (momentum) between consecutive bars using the selected source price (default: close). This represents the basic rate of change in the market.
Stage 2: Double Exponential Smoothing
Rather than using a single smoothing pass, the indicator applies two layers of exponential moving average (EMA) smoothing. The first EMA uses the "Trend Length" parameter (default: 21 periods) to capture the primary trend momentum, while the second EMA applies the "Signal Smoothing" parameter (default: 9 periods) to further refine the signal. This same double-smoothing process is applied to both the raw momentum and its absolute value, creating two parallel smoothed datasets.
Stage 3: Normalization and Signal Generation
The smoothed momentum is divided by the smoothed absolute momentum and multiplied by 100, creating a normalized oscillator that always ranges between -100 and +100. This normalization ensures consistent readings regardless of price levels or volatility conditions. A signal line is then generated by applying another EMA smoothing pass to the oscillator, creating a slower-moving reference line for crossover detection.
Trading Ideas and Insights
Momentum Reversal Strategy:
The indicator excels at identifying momentum reversals in optimal zones. Bullish entry signals (green dots) appear when the oscillator crosses above the signal line while in negative territory (below zero), indicating that downward momentum is exhausting and a reversal is beginning. Conversely, bearish entry signals (red dots) trigger when the oscillator crosses below the signal line while in positive territory, signaling that upward momentum is weakening.
Trend Strength Assessment:
The four-color gradient system provides instant visual feedback on trend strength. Strong bullish momentum (bright green) occurs when the oscillator is positive and rising, indicating accelerating upward movement. Weak bullish momentum (light green) appears when the oscillator is positive but declining, suggesting the uptrend is losing steam. The same logic applies inversely for bearish conditions with red and light red colors.
Overbought/Oversold Trading:
The +50 and -50 reference levels serve as overbought and oversold zones. When the oscillator reaches these extremes, it suggests the current momentum may be overextended, potentially leading to mean reversion opportunities. Traders can watch for the oscillator to retreat from these levels as confirmation of momentum exhaustion.
Divergence Detection:
Like other momentum oscillators, Aura Trend Momentum can be used to identify divergences between price action and momentum. A bullish divergence occurs when price makes lower lows while the oscillator makes higher lows, suggesting weakening bearish momentum. Bearish divergences show the opposite pattern, warning of potential trend reversals.
How Multiple Indicators Work Together
The Aura Trend Momentum indicator integrates three distinct technical analysis components into a unified system:
1. Momentum Oscillator Component: At its core, this is a momentum-based oscillator similar to the Rate of Change (ROC) indicator, measuring the speed and magnitude of price movements.
2. Moving Average Smoothing Component: The double EMA smoothing technique borrows from the concept of DEMA (Double Exponential Moving Average), which reduces lag while maintaining smoothness. This component filters out market noise that would otherwise generate false signals.
3. Normalization Component: By dividing smoothed momentum by smoothed absolute momentum, the indicator incorporates a normalization technique similar to the Percentage Price Oscillator (PPO) or normalized RSI, ensuring readings are comparable across different securities and timeframes.
These components work synergistically: the momentum calculation captures market dynamics, the double smoothing eliminates noise without excessive lag, and the normalization ensures universal applicability. The signal line adds a fourth dimension by providing a smoothed reference for timing entry and exit points, similar to how MACD uses a signal line for crossover detection.
Unique Aspects
What distinguishes Aura Trend Momentum from other momentum oscillators is its sophisticated approach to noise reduction and signal clarity. While indicators like RSI, Stochastic, or standard momentum oscillators either sacrifice responsiveness for smoothness or vice versa, this indicator achieves both through its double-smoothing methodology applied to both numerator and denominator of the normalization formula.
The four-color gradient visualization system is another unique feature that goes beyond simple bullish/bearish coloring. By distinguishing between strong and weak states within each trend direction, traders gain immediate insight into momentum acceleration or deceleration without needing to analyze multiple indicators or chart patterns.
Additionally, the smart signal filtering—requiring bullish crosses to occur below zero and bearish crosses above zero—dramatically reduces false signals that plague many oscillator-based systems. This zone-based filtering ensures that signals align with genuine momentum reversals rather than minor fluctuations within an established trend.
How to Use
Add the Aura Trend Momentum indicator to your chart from the indicators menu
The oscillator will appear in a separate pane below your price chart, displaying the histogram, oscillator line, signal line, and cloud fill
Watch for green dots (bullish entry signals) when the oscillator crosses above the signal line in negative territory—these indicate potential long entry opportunities
Watch for red dots (bearish entry signals) when the oscillator crosses below the signal line in positive territory—these indicate potential short entry opportunities
Monitor the histogram colors: bright green indicates strong bullish momentum, light green shows weakening bullish momentum, bright red indicates strong bearish momentum, and light red shows weakening bearish momentum
Use the +50 level as an overbought reference and -50 as oversold—consider taking profits or tightening stops when these levels are reached
The cloud fill between the oscillator and signal line provides additional context: green cloud suggests bullish control, red cloud suggests bearish control
Set up alerts using the built-in alert conditions to receive notifications when buy or sell signals trigger
Customization
The indicator offers flexible customization options to adapt to different trading styles and market conditions:
Oscillator Settings:
Trend Length (default: 21): Controls the primary lookback period for momentum calculation. Increase for longer-term trend analysis (30-50), decrease for shorter-term trading (10-15)
Signal Smoothing (default: 9): Adjusts the smoothing applied to both the oscillator and signal line. Higher values create smoother signals with fewer crossovers, lower values increase responsiveness
Source (default: close): Select which price data to use for calculations—close, open, high, low, or various price averages like HL2 or HLC3
Visuals & Colors:
Customize all four gradient colors (Bullish Strong, Bullish Weak, Bearish Strong, Bearish Weak) and the Signal Line color to match your chart theme or personal preferences. The color scheme helps with quick visual pattern recognition during live trading.
Conclusion
The Aura Trend Momentum indicator represents a refined approach to momentum analysis, combining proven technical analysis concepts—momentum calculation, exponential smoothing, and normalization—into a cohesive, noise-filtered system. Its double-smoothing methodology addresses the primary weakness of traditional momentum oscillators (excessive noise) while maintaining the responsiveness needed for timely trade entries. The four-color gradient system and smart signal filtering provide clear, actionable insights that help traders identify high-probability momentum reversals and trend continuation opportunities. Whether you're a day trader seeking precise entry points or a swing trader looking for trend confirmation, this indicator offers the clarity and reliability needed for confident decision-making in dynamic market conditions.
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Indicator
Liquidity Sweep Rider Institutional HFT Grabber Liquidity Sweep Rider Strategy (Swing Pivot + Volume Filter)
Publication Description:
This is an open-source Pine Script v6 strategy that identifies potential liquidity sweep patterns around confirmed swing highs and lows.
It uses:
Pivot points (ta.pivothigh / ta.pivotlow) to mark historical swing levels where orders (such as stops or pending entries) often cluster.
A volume filter requiring above-average volume (SMA-based with multiplier) on the sweep candle to highlight stronger moves.
Classic sweep logic: price wicks beyond the level but closes back inside, suggesting a possible reversal after liquidity is taken.
Entry rules:
Long: after a downside sweep below a recent swing low (with volume condition).
Short: after an upside sweep above a recent swing high (with volume condition).
Features include:
Optional toggles to enable/disable long/short directions.
ATR-based stop-loss and take-profit (configurable multipliers and risk-reward ratio).
Visual plots for liquidity levels, entry signals, background highlights, and an info table.
Alert conditions for long/short triggers.
Important notes:
This is an educational/example script for backtesting and learning.
Past performance does not indicate future results. Trading involves significant risk of loss — use proper risk management and never risk more than you can afford to lose.
No guarantees of profitability are made. Always test thoroughly on demo accounts before live use.
Customize parameters (pivot lengths, volume multiplier, ATR settings) based on the instrument and timeframe you trade. Works on various markets/timeframes but performs differently depending on liquidity and volatility.
Feel free to fork/modify the code. Feedback and improvements are welcome!
(≈ 3–4 paragraphs, clear, educational, includes risk disclaimer, explains logic + usage without hype.) Strategy
Auto Support and Resistance with Swing Pivots + Touch StrengthAuto S/R — Swing Pivots with Touch Strength
Automatically detects and plots dynamic support & resistance levels based on swing highs/lows (using pivot detection).
Key features:
Draws horizontal lines for the most recent swing-based S/R zones
Tracks how many times price has touched/tested each level (wick or body close within adjustable tolerance)
Visually strengthens levels with thicker lines & brighter colors as touches increase (2 touches = medium strength, 3+ = strongest conviction)
Includes optional price labels, near-level background highlights, and tiny pivot markers
Merge logic prevents clutter from very close levels
Fully customizable: pivot lookback, max levels shown, touch sensitivity, line style/width
Ideal for day trading (15m–1h), swing setups (1h–4h), and identifying high-probability long-term zones on higher timeframes. Especially powerful in volatile markets like BTC, where multi-touch levels often act as strong magnets or reversal points.
Perfect for spotting confluence, structure breaks, and high-conviction reactions in real time. Indicator
Trend Velocity Channel [BackQuant]Trend Velocity Channel
Overview
Trend Velocity Channel is a trend and momentum-acceleration overlay built around one idea, trend strength is the gap between a fast “lead” average and a slow “lag” average . When the lead line pulls away from the lag line, the market is accelerating in that direction. When that gap collapses, trend energy is fading and reversals become more likely.
Instead of using a single moving average slope or crossover, this indicator measures:
A leading trend line (DEMA) that reacts quickly.
A lagging trend line (slower EMA) that represents slower consensus value.
A normalized “velocity / crush” metric: the distance between them in ATR units .
A trend regime based on the sign of that velocity.
A dynamic channel defined by the lead line on one side and a padded lag boundary on the other.
A reversal level engine that marks flip bars and tracks retests and invalidations.
The result is a channel that visually answers:
Are we accelerating or decelerating?
How strong is the current acceleration relative to recent history?
Where is the “danger edge” where a reversal would be confirmed?
Which flip levels remain relevant and which got invalidated?
Concept: lead vs lag as a proxy for trend velocity
Markets trend when price doesn’t just move, it keeps moving faster than the slow baseline can follow . If a fast estimator (lead) separates from a slow estimator (lag), that separation is a practical proxy for “velocity”:
Lead above lag, bullish acceleration.
Lead below lag, bearish acceleration.
Lead converging back into lag, trend energy compressing.
This script calls that separation Crush , meaning the lead line is “crushing away” from the lag line.
Core components
1) Leading line: DEMA
The lead line is a Double Exponential Moving Average:
dema = DEMA(price, maLen)
Why DEMA:
It reduces lag relative to a standard EMA.
It reacts faster to genuine directional moves.
It still smooths noise enough to act as a structural line.
DEMA is used as the “inner” channel edge and the glow anchor.
2) Lagging line: Slow EMA
The lag line is a slower EMA:
lagMA = EMA(price, round(maLen * 1.5))
Why a slower EMA:
It represents a slower-moving consensus baseline.
It creates a meaningful “gap” against the lead line.
It is less sensitive to micro-chop, so separation signals are cleaner.
The lag line also becomes the basis for the channel’s outer edge.
3) Volatility normalization: ATR
Raw MA distance is not comparable across regimes. A 50-point gap might be huge in a low-vol market and nothing in a high-vol market. So the gap is normalized by ATR:
atr = ATR(14)
rawCrush = (dema - lagMA) / atr
Interpretation:
rawCrush = “how many ATRs the lead line is away from the lag line.”
This standardizes the signal across instruments and volatility states.
4) Crush smoothing
The gap can still jitter, especially in choppy markets. So it is EMA-smoothed:
crush = EMA(rawCrush, crushSmth)
Lower crushSmth:
Faster regime flips, more noise.
Higher crushSmth:
More stable regimes, slower reaction.
Trend regime and flips
Trend direction is derived directly from the sign of the smoothed crush:
trend = crush > 0 ? +1 : -1
flip = trend != trend
Meaning:
Bull regime: lead (DEMA) is above lag baseline in ATR units.
Bear regime: lead is below lag baseline.
Flip: the velocity sign changed, meaning acceleration has switched direction.
This is not a price crossover system, it is a lead-lag separation regime system .
Measuring strength: crushNorm
The script also grades how extreme current crush is relative to recent conditions:
crushAbs = abs(crush)
crushHigh = highest(crushAbs, 80)
crushNorm = crushHigh > 0 ? min(crushAbs / crushHigh, 1) : 0
Interpretation:
crushNorm near 0 means separation is small relative to recent extremes, trend is weak or compressing.
crushNorm near 1 means separation is near the largest seen recently, trend acceleration is strong.
This strength scale drives:
Color intensity (gradient)
Glow width
“Peak Crush” alert condition
Channel construction
Inner edge
The inner edge is the leading line:
inner = dema
This is the “fast structure” of the move.
Outer edge
The outer edge is built from the lag line plus an ATR padding:
outer = (bull) lagMA - atr * chanPad
outer = (bear) lagMA + atr * chanPad
This is important. The lag line sits behind price, so the script offsets it outward by a user-defined fraction of ATR. This creates a more realistic boundary that accounts for volatility.
Interpretation:
In bull regimes, the outer boundary is below lagMA, creating a support-like corridor beneath price.
In bear regimes, the outer boundary is above lagMA, creating a resistance-like corridor above price.
The channel is intentionally asymmetric
This channel is not “± ATR around a mean.” It is directional:
Inner edge hugs price via fast DEMA.
Outer edge is anchored to lagMA and padded outward.
So it behaves like a trend corridor where:
The inner edge shows where the trend is currently “being pulled.”
The outer edge shows the boundary where the trend would be meaningfully compromised if crossed.
Ribbon fill (3-layer depth)
Two midpoints are created between inner and outer:
mid1 = inner + (outer - inner) * 0.33
mid2 = inner + (outer - inner) * 0.66
Then the fill is layered:
inner → mid1 (most opaque)
mid1 → mid2
mid2 → outer (most transparent)
This creates a depth effect that visually communicates where price is sitting within the corridor. When the corridor is tight and strong, the ribbon looks concentrated. When it expands, the ribbon spreads and fades.
Color logic (trend + strength)
The indicator uses a gradient color where direction sets the palette and crushNorm sets intensity:
Bull: faint green → strong green as crushNorm increases
Bear: faint red → strong red as crushNorm increases
This means you can read two things instantly:
Direction (bull vs bear)
Acceleration strength (faded vs intense)
Glow engine on DEMA
Glow width scales with ATR and crushNorm:
glowW = atr * 0.07 * (0.5 + crushNorm)
So:
High acceleration = larger glow, more “energy” around the lead line.
Low acceleration = smaller glow.
Glow is built as multiple invisible plots above and below DEMA with layered fills, forming a halo around the lead line that encodes strength.
Flip-aware band breaking
The outer boundary line is broken on flips:
bandBrk = flip ? na : outer
plot(..., plot.style_linebr)
This prevents a misleading continuous line across regime changes, since the outer edge swaps sides on flip.
Crush reversal levels (flip levels engine)
This script includes a level system that plants a dashed horizontal level on every regime flip, then tracks:
Whether price retests it (first touch marker)
Whether price invalidates it (deletes it)
How long it extends forward
How many levels are kept
1) Level placement
On a flip:
If trend flips bullish, the level is placed at the flip bar’s low.
If trend flips bearish, the level is placed at the flip bar’s high.
That makes sense structurally:
Bull flip low is a “pivot low” candidate.
Bear flip high is a “pivot high” candidate.
Then a dashed line is drawn forward ~60 bars.
2) Level storage and maxLvls
Levels are stored in an array and capped by maxLvls. When the cap is exceeded, the oldest is deleted. This keeps the chart readable.
3) Level invalidation (broken logic)
Each level is monitored:
Bull flip level breaks if price closes far below it: close < level - atr * 2.5
Bear flip level breaks if price closes far above it: close > level + atr * 2.5
This is a volatility-scaled invalidation. If price pushes through a flip level by a large margin in ATR terms, it’s no longer acting like a meaningful reaction point.
4) Retest detection
A “touch” is detected when:
close is within 0.25 ATR of the level,
and close two bars ago was not close (distance > 0.5 ATR),
and the level hasn’t been marked retested yet.
On first retest, an “x” marker is printed and the level’s retested flag is set to true so it won’t spam.
What these levels represent
They are not generic support/resistance. They are regime pivot levels created by a change in lead-lag acceleration. In practice:
Untested flip levels can act like “memory zones” where price may react.
Retested levels become less special, still relevant but not “naked.”
Invalidated levels are removed to reduce noise.
Signals and alerts
The script provides:
Crush Bull: flip into bullish regime (crush crosses above 0 via smoothing logic)
Crush Bear: flip into bearish regime
Peak Crush: crushNorm > 0.85, meaning separation is near recent max, strong acceleration
Important: Peak Crush is not a reversal call. It flags strong trend energy. That can precede continuation or exhaustion, you use it as context, not a standalone trade trigger.
How to use it
Trend following framework
Stay aligned with the regime color.
In bull regime, treat the outer boundary as the “structure floor.”
In bear regime, treat the outer boundary as the “structure ceiling.”
The inner DEMA is your fast guide, the outer edge is your compromise boundary.
Acceleration read
Increasing color intensity and thicker glow imply acceleration is strengthening.
Fading color and shrinking glow imply acceleration is decaying and the move is losing energy.
A regime flip is a clean state change, not a micro-signal.
Using reversal levels
Treat naked flip levels as potential reaction zones.
Watch first retest behavior, clean rejection suggests the flip level is holding.
If the level invalidates by 2.5 ATR, it’s removed because structure has been overwritten.
Key inputs explained
MA Length (maLen)
Sets both the lead line length and the lag line length (scaled by 1.5). Lower values:
More sensitive, more flips.
Higher values:
Smoother, fewer flips, slower response.
Crush Smoothing (crushSmth)
Controls stability of the velocity signal. Lower:
Fast flips, noisier regime.
Higher:
More confirmation, later flips.
Channel Padding (chanPad)
Controls how much extra ATR space is added beyond lagMA. Higher padding:
Wider channel, fewer boundary touches.
Lower padding:
Tighter boundary, more reactive “risk edge.”
Max Levels
Controls how many historical flip levels are retained.
Summary
Trend Velocity Channel treats trend as lead-lag separation expressed in ATR units. A fast DEMA tracks the active move, a slower EMA defines baseline value, and their normalized gap (Crush) defines both direction and acceleration strength . That strength drives an adaptive visual language (gradient color, glow width, ribbon depth). The channel itself is directional, with the lead line as the inner edge and a volatility-padded lag boundary as the outer edge, acting as a structural “compromise line.” On every regime flip the script plants a pivot level, tracks retests, and deletes invalidated levels, giving you a clean map of acceleration-based reversal zones. Indicator
Uptrick: Volatility Aggregation ModelIntroduction
Uptrick: Volatility Aggregation Model (VAM) is a very simple overlay indicator that classifies market direction using a five-speed ensemble of volatility-adaptive range engines. Instead of relying on a single trend filter, VAM evaluates direction across multiple responsiveness settings and converts those states into a normalized score. The script then uses configurable score thresholds to define bullish, bearish, and neutral regimes, and it visualizes those regimes directly on the chart through candle recoloring and optional Up/Down labels.
Overview
VAM is built around an ensemble concept: five independent “speed” layers each determine a directional state by testing whether price breaks above or below a volatility-defined band. The five states are combined into a single score ranging from -1.0 (fully bearish across all speeds) to +1.0 (fully bullish across all speeds). This score is compared to user-defined buy and sell thresholds to determine regime. For visual context, the indicator also plots directional trail layers derived from the middle speed for stability, and can optionally fill the space between trail layers to make regime changes easier to spot at a glance.
Originality and value
This script’s originality comes from how it frames direction as a consensus problem rather than a single-indicator outcome. Each speed layer uses a volatility range defined from true range smoothing and applies a breakout-based state flip using upper and lower bands. Because the layers differ in lookback length, volatility scaling, band width, and smoothing, they respond differently to the same price movement. Aggregating them into a normalized score creates a compact, interpretable measure of directional agreement that can be tuned to be more selective or more permissive using thresholds. The result is a regime tool that is transparent, parameterized, and suitable for traders who want a directional filter that adapts to volatility and avoids treating all market conditions as equally “trendable.”
How it works
Start date gating
The script includes a start date filter that can be used to restrict when labels (and any signal interpretation) begin. Bars before the start date will still plot normally, but Up/Down labels are suppressed until the chart time is greater than or equal to the configured start date.
Five-speed volatility range engines
Each of the five speeds computes:
➜ A volatility measure based on true range (TR), smoothed with an EMA over the speed’s length, then scaled by a speed-specific volatility multiplier.
➜ An internal center line that “snaps” toward price only when price moves beyond the current volatility allowance. When price movement is smaller than the allowance, the center remains unchanged.
➜ Upper and lower bands around the center, spaced by the volatility allowance multiplied by a speed-specific band multiplier, then smoothed.
➜ A directional side state:
━━━━➤ Side flips bullish when source crosses above the upper band.
━━━━➤ Side flips bearish when source crosses below the lower band. This breakout-only flip logic is fixed in the script (no center-cross mode), so direction changes occur only when price breaks out of the band envelope.
Ensemble scoring
The five side states are summed and divided by 5 to produce a normalized ensemble score:
➜ +1.0 means all five speeds are bullish.
➜ -1.0 means all five speeds are bearish.
➜ Values between reflect partial agreement and mixed conditions.
The script then classifies the current regime using your thresholds:
➜ Bullish regime when score is greater than the buy threshold.
➜ Bearish regime when score is less than the sell threshold.
➜ Neutral regime otherwise.
Signals
Signals are generated from score crossing events:
➜ A buy signal occurs when the score crosses over the buy threshold.
➜ A sell signal occurs when the score crosses under the sell threshold.
These signals are used for labels (if enabled) and alert conditions. They are not strategy orders and do not simulate fills.
Visual system: trails, ATR layer, and fill
For stability, the trail structure is derived from the middle speed (Speed 3). The script computes smoothed lower and upper bands from Speed 3 as internal reference levels.
It then plots ATR-offset layers based on true range smoothed over the ATR Layer Length and scaled by the ATR Layer Mult. The bullish ATR layer is positioned below the Speed 3 lower band, and the bearish ATR layer is positioned above the Speed 3 upper band.
These ATR-offset layers are the primary visible trail elements. Optional fill appears between each reference band and its ATR layer only during the active bullish or bearish regime.
The script can optionally fill between the trail and ATR layer lines, but only in the corresponding regime:
➜ Bull fill appears only when the regime is bullish.
➜ Bear fill appears only when the regime is bearish.
Neutral conditions suppress the regime fill emphasis.
Candle recoloring
The indicator uses plotcandle to recolor candles based on the current regime:
➜ Bull color when bullish regime is active.
➜ Bear color when bearish regime is active.
➜ Neutral gray when neither threshold condition is met.
This makes regime identification possible without relying on separate panels.
Inputs and how to use them
Plot group
Start Date
Defines the earliest chart time at which labels and signal annotations are allowed. This is useful for limiting label clutter when reviewing long history or when you only want signals after a certain market regime, contract listing date, or personal testing period.
Ensemble group
Buy Threshold
A score level above which the script considers the market bullish. Higher values make bullish classification more selective because more of the five speeds must agree bullishly. Lower values allow bullish classification with weaker consensus.
Sell Threshold
A score level below which the script considers the market bearish. More negative values make bearish classification more selective. Values closer to zero will classify bearish regimes more readily.
Show Up/Down Labels
Toggles the display of directional labels on threshold cross events. When enabled, labels are only printed on bars at or after the Start Date, and only when score crosses the relevant threshold (not merely when it remains above or below).
Visuals group
Fill Between Trail Layers
Enables or disables the filled region between each trail and its ATR layer. When disabled, trail lines can still be visible (depending on the regime) but the emphasis fill is removed.
Trail Smooth
Controls EMA smoothing applied to the trail lines and their ATR-offset layers. Higher values produce smoother, slower-reacting trails; lower values make trails respond more quickly but can increase visual noise.
ATR Layer Length
Controls the EMA length used to smooth true range for the ATR-style layer. Larger values produce a steadier ATR layer; smaller values track volatility changes more quickly.
ATR Layer Mult
Scales the ATR layer offset distance from the trail. Increasing this value expands the buffer around the trail; decreasing it tightens the buffer.
Colors group
Bull
Sets the color used for bullish candles, bullish trail visuals, and bullish label styling.
Bear
Sets the color used for bearish candles, bearish trail visuals, and bearish label styling.
Neutral Gray
Sets the candle color used when the score is between thresholds (neutral regime).
5 Speeds group
Source
Chooses the price series used for band breakouts and side calculations (default close). Changing the source changes what the engines consider the breakout trigger. For example, using hl2 or ohlc4 can reduce sensitivity to closes alone, while using close keeps breakouts tied to settlement values.
Speed 1 Length, Speed 2 Length, Speed 3 Length, Speed 4 Length, Speed 5 Length
These define the EMA length used to smooth true range for each speed’s volatility allowance. Smaller lengths typically react faster to volatility changes; larger lengths smooth volatility more.
Speed 1 Vol Mult through Speed 5 Vol Mult
These scale the volatility allowance for each speed. Increasing a speed’s volatility multiplier makes its center and bands more tolerant to price movement, which can reduce how often that layer flips direction. Decreasing it tightens the allowance, potentially increasing flip frequency.
Speed 1 Band Mult through Speed 5 Band Mult
These control how far bands are placed from the center relative to the volatility allowance. Higher band multipliers widen bands (requiring larger breakouts to flip side). Lower band multipliers narrow bands (making flips easier to trigger).
Speed 1 Smooth through Speed 5 Smooth
These apply EMA smoothing to the volatility allowance and the band outputs for each speed. Higher smoothing reduces jitter and slows reaction; lower smoothing increases responsiveness.
Alerts
The script provides two alert conditions:
Ensemble Buy: triggers when the score crosses above the buy threshold.
Ensemble Sell: triggers when the score crosses below the sell threshold.
These alerts correspond directly to the label events (when labels are enabled), but alerts can be used independently of label visibility.
Trail
The trail in Uptrick: Volatility Aggregation Model (VAM) acts as a dynamic support and resistance band derived from the middle engine (Speed 3) for stability. In bullish regimes, the lower trail functions as volatility-adjusted support. During a long trade, stops can be positioned below this band, and pullbacks into the trail while the regime remains bullish may be treated as opportunities to add to the position.
In bearish regimes, the upper trail functions as volatility-adjusted resistance. During a short trade, stops can be placed above the band, and rallies back into the trail while the regime remains bearish may be considered potential add-on zones.
The trail is designed for trade management and structural guidance within the ensemble-defined regime, not as a standalone entry signal.
Summary
Uptrick: Volatility Aggregation Model (VAM) is a volatility-adaptive, five-speed ensemble direction indicator that converts multiple breakout-based range states into a single normalized score. You control regime sensitivity using buy/sell score thresholds, and you can visualize regimes through candle recoloring, optional labels, and trail layers derived from the middle speed plus an ATR-based buffer. The indicator is designed to help traders interpret directional agreement across multiple responsiveness settings and to mark regime transitions when score crosses the chosen thresholds.
Disclaimer
This indicator is for informational and educational purposes only and does not constitute financial advice. Trading involves risk, and you are responsible for your own decisions. Past performance and historical signals do not guarantee future results.
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