ZynAlgo S&R ProZynAlgo S&R Pro identifies confirmed swing highs and swing lows, marks them on the chart, and draws single horizontal liquidity lines that extend from each confirmed swing until the next swing of the same type occurs. The tool can optionally recolor candles based on whether the current close is above or below the previous close. It also exposes alert conditions for new swing points and for when price reaches the most recent buy-side or sell-side liquidity line.
Important: This is a visual analysis tool. It does not open, manage, or close positions. It is provided for educational and informational purposes only.
How it works (under the hood)
Swing detection (confirmed):
The script uses ta.pivothigh/ta.pivotlow with symmetric left/right bars defined by Left bar & Right bar. A swing is considered only after the bar is confirmed.
Swing markers:
When enabled, confirmed swing highs/lows are marked with small circles above/below bars. The offset equals the left/right length to align with the confirmed pivot location.
Liquidity lines:
On each swing high, the script ends (anchors) the previous buy-side line at the pivot’s bar, then creates a new dotted/dashed/solid horizontal line at that swing price and extends it forward.
On each swing low, it does the same for sell-side lines.
Between swing events, the most recent buy-side and sell-side lines continue extending to the current bar.
Alerts:
Swing High / Swing Low Created — fires on confirmation of a new swing.
Buy Side Liquidity Raid — when price crosses over the most recent swing-high line.
Sell Side Liquidity Raid — when price crosses under the most recent swing-low line.
Optional candle coloring:
If enabled, candles can be recolored by comparing current close to the previous close, with independent toggles for body, borders, and wicks.
Inputs & recommended tooltips (copy-friendly)
Swing High/Low Setting
Left bar & Right bar (len_l)
Tooltip: “Bars to the left/right required to confirm a pivot. Larger values = fewer but stronger swing points (default: 20).”
Show Swing High Swing Low (flg_shsl)
Tooltip: “Plot small circles at confirmed swing highs (red) and swing lows (blue).”
(Note: i_labelcolor_price is present but unused in visible drawings—safe to ignore or reserve for future use.)
Liquidity Pools Settings
Show Liquidity Pools (flg_lq)
Tooltip: “Draw a horizontal line at each confirmed swing. The line extends forward until the next swing of the same type appears.”
Line Width (i_width)
Tooltip: “Thickness of liquidity lines (1–6).”
Line Style (i_linestyle)
Tooltip: “Choose solid, dashed, or dotted style for liquidity lines.”
Buy Side Liquidity Color (i_linecolor_bs)
Tooltip: “Color for swing-high liquidity lines (default: red).”
Sell Side Liquidity Color (i_linecolor_ss)
Tooltip: “Color for swing-low liquidity lines (default: blue).”
Candles
Color bars based on previous close (use_prev_close)
Tooltip: “If enabled, candle colors are based on whether close > previous close (Up) or not (Down).”
Up Color / Down Color
Tooltip: “Colors used for up vs. down determination.”
Body / Borders / Wick (apply toggles)
Tooltip: “Choose which candle parts to recolor.”
Alerts available (names as shown in the Create Alert dialog)
Swing High
Triggers when a new swing high is confirmed. Select this condition to be notified about newly formed swing highs.
Swing Low
Triggers when a new swing low is confirmed.
Buy Side Liquidity Raid
Triggers when price crosses above the most recent swing-high liquidity line (crossover(high, LSH)).
Sell Side Liquidity Raid
Triggers when price crosses below the most recent swing-low liquidity line (crossunder(low, LSL)).
Quick start (suggested workflow)
Add to chart: Apply ZynAlgo S&R Pro to your symbol and timeframe.
Choose sensitivity: Adjust Left bar & Right bar. Higher values focus on more significant swing points; lower values react faster.
Toggle visuals:
Enable Show Swing High Swing Low to see swing markers.
Enable Show Liquidity Pools to draw/extend liquidity lines. Pick the line style, width, and colors you prefer.
(Optional) Candle colors: Turn on Color bars based on previous close and choose which parts to color.
Set alerts:
Open Create Alert → Condition: ZynAlgo S&R Pro → choose Swing High, Swing Low, Buy Side Liquidity Raid, or Sell Side Liquidity Raid as needed.
Practical notes & limitations
Confirmed swings only: Pivots are plotted after confirmation (i.e., once the required left/right bars are complete). This avoids repainting the pivot location.
One active line per side: Only the most recent buy-side and sell-side liquidity lines extend to the right; prior lines are ended when a new swing of the same side appears.
Timeframes & instruments: Parameter sensitivity can vary across markets/timeframes. Consider tuning Left bar & Right bar to match volatility.
No orders are placed: This indicator does not execute trades or manage positions.
Compliance & fair-use guidance
No performance promises: This tool does not guarantee profitable results and should not be described as “signals,” “guaranteed,” “best,” or similar claims. It is an analysis aid that visualizes historical swing points, liquidity levels, and optional candle coloring.
Educational intent: Use it to support your chart review and alerting workflow; combine with your own judgment and risk controls.
Alerts are informational: Alerts reflect the conditions described above and do not constitute financial advice.
Change log (summary of core features)
Swing detection with configurable left/right bars; optional swing markers.
Auto-extending buy-side/sell-side liquidity lines with customizable style/width/colors.
Four alert conditions (new swing highs/lows and liquidity raids).
Optional candle recoloring with separate toggles for body/borders/wicks.
Dynamic Line Management
Unlike static support/resistance tools, ZynAlgo S&R Pro automatically manages the lifecycle of each liquidity line — removing outdated levels the moment new structure forms.
This ensures the chart always reflects the most relevant active zones.
Structure + Liquidity Integration
By combining price structure (swing points) with liquidity visualization, it bridges the gap between classic S&R and modern liquidity-based interpretation — a fusion rarely found in lightweight indicators.
Noise-Free Design
The script plots only the most essential elements: confirmed swings, active liquidity lines, and optional candle color context.
It avoids overlapping labels, text clutter, or unnecessary metrics — ideal for traders who prefer clarity and precision.
Non-Repainting Logic
All pivots are confirmed only after the required right-side bars are closed, ensuring all swing points and lines remain fixed once plotted.
This gives confidence in backtesting and visual analysis without misleading signals.
Lightweight & Efficient
Despite tracking multiple dynamic lines, the algorithm is optimized for performance (using arrays and efficient bar updates), making it suitable for both high- and low-timeframe analysis.
Adaptable Across Market Types
Equally applicable to forex, crypto, indices, and commodities, the algorithm’s sensitivity parameter lets users adjust to volatility differences between instruments.
Purely Analytical
The tool does not provide trade signals or predictions.
Its design supports price-action interpretation, liquidity mapping, and structure confirmation — helping traders read context rather than react to noise.
🔶 RISK DISCLAIMER
Trading is risky & most day traders lose money. All content, tools, scripts, articles, & education provided by ZynAlgo are purely for informational & educational purposes only. Past performance does not guarantee future results.
In den Scripts nach "profitable" suchen
Ultimate MACD Suite [BigBeluga]🔵 OVERVIEW
The Ultimate MACD Suite is an advanced momentum-based system that enhances the classic MACD with modern features tailored for professional traders.
It transforms MACD into a full market-decision engine — offering multi-timeframe confluence, adaptive histogram behavior, divergence detection, heatmap trend visualization, and actionable reversal signals.
This toolkit goes far beyond standard MACD, helping traders identify trend momentum shifts, exhaustion zones, high-probability reversal areas, and breakout confirmation signals across multiple timeframes simultaneously. It's to be used as part of a major trading system and to simplify usage of the MACD.
⚠️ Note:
This is not a traditional MACD — it uses normalized values , enhanced visual feedback, and a multi-timeframe dashboard engine for superior signal quality and clarity.
🔵 CONCEPTS
Combines MACD momentum, signal-line crossovers, and histogram reversals into one system
Uses normalized scaling to detect extreme momentum levels and exhaustion zones
Multi-timeframe dashboard displays consensus signal alignment across several timeframes
Divergence engine identifies bullish & bearish trend weakening early
Heatmap mode visually distinguishes strong trend phases from neutral or fading momentum
Reversal arrows & crosses highlight actionable turning points on chart
🔵 FEATURES
Normalized MACD Engine — improves signal clarity across all assets/timeframes
MACD Heatmap Mode — color-coded slope intensity for trend strength monitoring
MACD Rising and Falling Mode — color-coded rising and falling MACD regimes
Histogram Reversal Detection — early momentum fade signal before price turns
Signal-Line Momentum Shifts — bullish ▲ & bearish ▼ alerts on cross-confirmation
Overbought/Oversold Bands — enhanced visual thresholds at ±80 levels
Smart Divergence Detection (Non-Lag) — confirms regular bullish & bearish divergences
Multi-Timeframe Dashboard — MACD, signal, histogram & divergence signals across 5+ TFs
Reversal Push-Filter — ensures only clean signals after confirmed momentum inflection
On-Chart Reversal Labels — optional compact signal markers for clean visual execution
Histogram Color Logic — rising/falling or heatmap mode for deeper momentum reading
🔵 HOW TO USE
Look for MACD crossing above signal + green histogram to confirm bullish momentum
Use ▼ and ▲ arrows to catch confirmed momentum reversals
Monitor the dashboard — the more timeframes align, the stronger the setup
Watch divergences for trend exhaustion or reversal setups
Treat histogram trend shifts as early momentum clues before price reacts
Use ±80 levels to identify overheated conditions & fade opportunities
Combine with structure, volume, or BigBeluga liquidity tools for higher accuracy
🔵 ALERTS
The indicator includes a full alert suite for automation and real-time trade readiness:
MACD crossovers (Bullish / Bearish)
Histogram reversals & zero-line shifts
Bullish / Bearish divergence detection
Overbought / Oversold MACD alerts
Bullish ▲ and bearish ▼ reversal triggers
Use these alerts to automate signal monitoring or feed algorithmic systems.
🔵 CONCLUSION
The Ultimate MACD Suite transforms a classic indicator into a powerful trading engine.
With multi-timeframe alignment, heatmapping, divergence logic, normalized scaling and automated signals, it becomes an elite momentum-confirmation and reversal-timing system built for serious traders.
Whether scalping intraday or managing swing positions, this MACD engine helps identify the most profitable phases of trend movement — while warning early when a trend is weakening.
Bezahltes Script
Binary Options Gold Scalping [TradingFinder] 1 & 5 Min Strategy🔵 Introduction
In binary options trading, price movements are often driven by the market’s tendency to reach key liquidity zones. These areas include Liquidity, Fair Value Gaps (FVGs), and Order Blocks (OBs), zones where a large number of pending orders are concentrated.
When price reaches one of these zones, it typically enters a Liquidity Sweep phase to collect available liquidity. After this process, the market often reacts sharply, either reversing direction or continuing its move with renewed momentum. Understanding this cycle forms the foundation of most smart money-based binary options strategies.
In this analytical approach, a Liquidity Sweep is usually seen as a False Breakout, often recognized through a distinctive candle confirmation pattern. The pattern appears when price briefly breaks a level to trigger stops, then quickly returns within range. This formation is one of the most reliable reversal signals for short-term trades and plays a central role in many binary options strategies.
After a liquidity sweep, price often returns to Fair Value Gap (FVG) or Order Block (OB) areas to restore balance in the market. These are zones where institutional orders are typically placed, and reactions around them can create high-probability trade setups. In binary options trading, this quick reaction following a sweep and retrace into an FVG or OB provides one of the best entry opportunities for short-term trades.
By combining the concepts of Liquidity Sweep, Fair Value Gap, and Order Block, traders can build a precise binary options strategy based on smart money behavior, allowing them to identify market reversals with greater confidence and enter at the optimal moment.
Bullish Setup :
Bearish Setup :
🔵 How to Use
This indicator is built on the Smart Money Concept (SMC) framework and serves as a core tool for accurately detecting Liquidity Sweeps, Order Blocks, and Fair Value Gaps in binary options trading.
Its logic is simple yet powerful : when price reaches high-interest liquidity zones and shows reversal signs, the indicator issues an entry signal immediately after a Candle Confirmation is complete.
Signals only activate when both the market structure and the candle confirmation pattern align, ensuring high accuracy in spotting genuine reversals.
🟣 Long Position
A bullish signal appears when the market, after a downward move, reaches sell-side liquidity zones where liquidity has built up below previous lows. In such conditions, a bullish Order Block or Fair Value Gap often exists in the same region, acting as a potential reversal point.
When the indicator detects the presence of liquidity, an imbalance zone (FVG), and a valid candle confirmation simultaneously, it triggers a green Call signal.
In a binary options strategy, the best entry moment is immediately after the candle confirmation closes, as this is when the probability of reversal is highest and the market tends to react strongly within the next few candles.
In the example below, after the liquidity sweep and candle confirmation, price quickly rallied, resulting in a Binary Win setup.
🟣 Short Position
A bearish signal occurs when price, after an upward move, reaches an area of buy-side liquidity and collects liquidity above recent highs. At this stage, the market is typically overbought and ready to reverse. If a bearish Order Block or Fair Value Gap exists in the same area and a candle confirmation pattern forms, the indicator displays a red Put signal.
This setup is highly accurate because multiple structural confirmations occur simultaneously : liquidity has been absorbed, price is rebalancing, and the confirmation candle has closed.
In binary options trading, this is the ideal moment to enter a Put (Sell) position, as the price reaction to the downside is usually quick and decisive.
In the example chart, the indicator generated a bearish signal right after the candle confirmation and completion of the liquidity sweep, price then dropped within minutes, resulting in another Binary Win.
🔵 Settings
Time Frame : Select the desired timeframe for analysis. If left blank, the indicator uses the chart’s current timeframe.
Swing Period : Defines how many candles are used to detect structural pivots (swing highs and lows). A higher value increases accuracy but reduces the number of signals.
Candle Pattern : Enables candle-based confirmation logic. When turned on, the indicator issues signals only if a valid reversal pattern is detected. You can also choose the confirmation filter strength, tighter filters show fewer but more precise signals.
🔵 Conclusion
A deep understanding of Liquidity Sweeps, Order Blocks, and Fair Value Gaps can make a decisive difference between ordinary and professional traders in the binary options market.
This indicator, combining smart money logic with candle confirmation, is one of the most precise tools for detecting true market reversals. When liquidity is collected and structural reversal signs emerge, the indicator automatically recognizes the price reaction and generates a reliable Call or Put signal.
Using this tool alongside market structure analysis and FVG detection allows traders to enter high-probability setups while filtering out false breakouts. For that reason, this binary options strategy is not only suitable for short-term trading but also valuable for understanding deeper smart-money behavior across timeframes.
Ultimately, success with this system comes down to two key principles: understanding the logic of the liquidity sweep and waiting for the candle confirmation to close. When these two conditions align, the indicator can pinpoint the best entry points with remarkable precision, helping you build a structured, intelligent, and profitable binary options strategy.
CipherThis indicator identifies potential reversal points through volume exhaustion analysis combined with multi-factor confirmation, volume distribution patterns at price extremes, market state classification based on volatility characteristics, and time-weighted probability calculations. Each component reduces false signals that single-factor indicators typically produce.
METHODOLOGY:
The system continuously monitors market conditions across multiple dimensions. When volume patterns indicate potential exhaustion at significant price levels, it checks for alignment with favorable market conditions and statistical probabilities. Signals only generate when multiple factors confirm, with entry triggered on momentum continuation beyond the exhaustion point.
COMPLETE USAGE GUIDE:
Signal Identification:
- "EXH L+2" = Long exhaustion with 2 confirmations
- "EXH S+3" = Short exhaustion with 3 confirmations
- Higher confirmation numbers indicate stronger setups
Entry Execution:
- Dashed lines mark entry trigger levels
- Entry activates when price breaks trigger within specified bar window
- Buffer setting controls distance from exhaustion bar (ticks)
Position Management:
- Automatic stop loss and target levels display on entry
- Green lines = profit targets
- Red lines = stop loss levels
- Info panel shows real-time position status
CONFIGURABLE PARAMETERS:
Timing Controls:
- Entry Buffer: 0-5 ticks (momentum confirmation distance)
- Max Bars to Wait: 3-10 bars (entry window duration)
- Session Times: Separate London/New York parameters
Sensitivity Settings:
- Volume Multiplier: 1.5-3.0 (vs 20-bar average)
- Lambda Values: Setup frequency expectations per session
- Stop Distances: Session-specific risk parameters
Risk Controls:
- Daily Win Limit: Stops after profitable day
- Daily Loss Limit: Prevents excessive drawdown
- Maximum Daily Trades: Controls overtrading
PERFORMANCE OPTIMIZATION:
Best Trading Windows:
- 10:00 AM EST: Primary reversal window
- 9:30-9:45 AM EST: Opening range exhaustion
- 3:00-4:00 AM EST: European session setups
- 2:30 PM EST: Afternoon reversal potential
Session Characteristics:
- London (2-9 AM EST): Lower frequency, cleaner setups
- New York (9 AM-4 PM EST): Higher frequency, requires filtering
- Background colors indicate active sessions
RISK PARAMETERS:
- Default Stops: 30-40 ticks (session-dependent)
- Risk:Reward Ratios: 1:1.5 to 1:3 (configurable)
- Trade Frequency: 2-4 quality setups weekly
VISUAL REFERENCE:
- Orange Background: London session active
- Blue Background: New York session active
- Yellow Markers: Exhaustion points identified
- Dashed Lines: Pending entry levels
- Solid Lines: Active trade levels
- Info Table: Statistics and system status
IMPORTANT CONSIDERATIONS:
This tool identifies potential setups based on rule-based analysis. Traders should understand that no system guarantees profits and should use appropriate risk management. The indicator works best on 3-minute and 5-minute timeframes in liquid markets. Combine with market context and price action understanding for optimal results.
TECHNICAL REQUIREMENTS:
- Best suited for index and commodites
- Optimized for 3M and 5M
- Requires volume data for proper function
- Best results with consistent market participation
Lot Size Calculator for FX(JPY Base)-By Jason v1.1 ロッド自動計算ツール🧭概要
このインジケーターは、日本円口座で取引するFXトレーダー専用に設計されたロットサイズ自動計算ツールです。
クロス円だけでなく、ドルストレート通貨ペア（EURUSD・GBPUSD・など）も自動換算に対応。
リアルなJPY換算ベースで、リスクとロットを正確に可視化します。
🎯 主な特徴
✅ JPY自動換算対応
ドルストレート・クロス円ペアを問わず、リアルタイムでJPYベースに換算。
✅ リスク/リワード自動計算
口座残高・ストップロス・リスク割合・固定損失額からロットサイズを即時算出。
✅ 証拠金維持率 / 実効レバレッジ表示
過剰エントリーを防ぎ、リスクを数値で管理。
✅ パネル表示を自由カスタマイズ
* 表示項目を個別にON/OFF可能
* 項目名（ラベル）を自分の言葉に変更可能
* パネル位置・文字サイズ・色・背景も自由設定
✅ 日本口座仕様に最適化
DMM、GMO、外為どっとコムなどJPY建て口座での取引計算に完全対応。
💡 推奨リスク管理ルール（プロトレーダー実践例）
プロ仕様のトレードは、「勝つこと」より「失わないこと」を最優先に行われます。
安定して利益を積み上げるトレーダーは、常に明確なリスク基準をもって行動します。
以下は、その代表的なリスク管理ルールです。
📉 連敗時のリスクコントロール（防御モード）
* 1トレードあたり口座残高の1%以下に抑える
* 連続2～3敗でリスクを半分（例：1%→0.5%）に下げる
* 1日の最大損失率を 3〜5%以内に制限（到達したらその日は終了）
* 「メンタルドローダウン」を避けるために連敗日翌日は休むことも多い
📘 目的：生き残ること。資金を守ることが最大の攻撃。
📈 連勝時のリスクコントロール（拡張モード）
* 2連勝以上の場合、**リスクを段階的に拡大（例：1%→1.5%）**
* ただし、最大でも3%以内
* リワードが積み上がっている時にのみ増加させる（利益分をリスクに再投資）
📘 目的：勝っている時にリスクを“複利的”に活かすが、ルール内にとどめる。
🧠 デイリーマネジメントルール（プロ基準）
1トレードリスク ： 1〜2%以内
1日最大損失 ：3〜5%以内
1週間最大損失 ： 10%以内
リスクリワード比 ：最低 1 : 2（理想は 1 : 3 以上）
勝率の目安 ： 40〜50%でもRR管理で黒字維持可能
⚙️ このツールを使う理由
このロット計算機を使えば、
「感覚的なロット設定」から「数値的なリスク管理」へ進化できます。
✅ 過剰ロット防止
✅ 損失率の明確化
✅ 勝ち負けのバランス最適化
✅ 冷静なトレード継続が可能に
🧩 使い方
1️⃣ チャートにインジケーターを追加
2️⃣ 「口座残高」「リスク割合」「ストップロス(pips)」を設定
3️⃣ 「ロットサイズ」欄の数値が、**最適ロットサイズ**
4️⃣ リスク指標（証拠金維持率・実効レバレッジ）をチェック
⚠️ 免責事項
このインジケーターは教育目的の補助ツールです。
最終的な売買判断はご自身の責任で行ってください。
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🧾 クレジット
Developed for Japanese Traders 🇯🇵
Optimized for FX Based Risk Control
Created by
💬 まとめ
資金を守ることは「守り」ではなく、次のチャンスに立ち続けるための最強の戦略です。
リスクを管理できる者だけが、長期的に勝ち続けることができます。
🧩 今後について
このインジケーターは、今後も使いやすさと精度を追求しながら改善を続けていきます。
もちろんです。以下は、あなたの日本語説明文を**自然でプロフェッショナルな英語**に翻訳したものです。
TradingViewのインジケーター説明欄にそのまま使えるトーン（ややフォーマル＋分かりやすい）で整えています👇
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🧭 Overview
This indicator is a **lot size auto-calculator** designed specifically for **FX traders using Japanese Yen (JPY) accounts**.
It automatically converts values not only for JPY crosses but also for **USD-based pairs (e.g., EURUSD, GBPUSD, etc.)**,
providing precise **risk and lot visualization in real JPY terms**.
🎯 Key Features
✅ **Automatic JPY Conversion**
Real-time JPY-based conversion for both USD and JPY pairs.
✅ **Risk / Reward Auto Calculation**
Instantly calculates the optimal lot size based on account balance, stop loss, and defined risk percentage or fixed loss.
✅ **Margin Maintenance Rate / Effective Leverage Display**
Prevents over-leveraging and allows you to monitor your risk numerically.
✅ **Fully Customizable Panel Display**
* Enable or disable each display item individually
* Rename labels freely to your preferred wording
* Adjust panel position, font size, colors, and background
✅ **Optimized for Japanese Brokerage Accounts**
Fully compatible with major JPY-based brokers such as **DMM, GMO, and Gaitame.com**.
💡 Recommended Risk Management Rules (Professional Trader Practices)
Professional trading prioritizes **“not losing” over “winning.”**
Consistent traders operate with a clear and disciplined risk framework.
Here are the most common examples of professional risk management rules:
📉 Loss Streak Risk Control (Defensive Mode)
* Keep risk per trade below **1% of account balance**
* After **2–3 consecutive losses**, reduce risk by half (e.g., 1% → 0.5%)
* Limit daily loss to **3–5%** — stop trading once reached
* Take a break after a losing streak to avoid **mental drawdown**
📘 **Objective:** Survival first. Protecting capital is the strongest form of offense.
📈 Win Streak Risk Control (Expansion Mode)
* After 2 consecutive wins, **gradually increase risk (e.g., 1% → 1.5%)**
* Never exceed **3% total risk per trade**
* Only scale up when trading with accumulated profit — reinvest from gains, not from capital
📘 **Objective:** Use profits to grow risk *compoundedly*, but always within defined limits.
🧠 Daily Risk Management (Professional Standards)
Risk per trade : 1–2% of account balance
Max daily loss : 3–5%
Max weekly loss :10%
Minimum R:R ratio : 1 : 2 (Ideal: 1 : 3 or higher)
Profitability baseline : 40–50% win rate can still stay profitable with proper R:R control
⚙️ Why Use This Tool?
This calculator helps you shift from **“emotional lot sizing” to “numerical risk control.”**
✅ Prevents over-lotting
✅ Clarifies risk exposure
✅ Balances wins and losses
✅ Enables calm, consistent execution
🧩 How to Use
1️⃣ Add the indicator to your chart
2️⃣ Set your **account balance**, **risk percentage**, and **stop loss (pips)**
3️⃣ The **“Lot Size”** value automatically displays the optimal lot size
4️⃣ Check risk indicators such as **Margin Maintenance** and **Effective Leverage**
⚠️ Disclaimer
This indicator is a **support tool for educational purposes only**.
All final trading decisions are the sole responsibility of the user.
🧾 Credits
Developed for **Japanese Traders 🇯🇵**
Optimized for **FX-Based Risk Control**
Created by ** **
💬 Summary
Protecting your capital isn’t a defensive move —
it’s the **strongest strategy to stay in the game and seize the next opportunity**.
Only those who manage risk properly can sustain consistent long-term success.
🧩 Future Updates
This indicator will continue to evolve with improvements in usability and accuracy.
Stay tuned for upcoming updates and refinements.
Manifold Singularity EngineManifold Singularity Engine: Catastrophe Theory Detection Through Multi-Dimensional Topology Analysis
The Manifold Singularity Engine applies catastrophe theory from mathematical topology to multi-dimensional price space analysis, identifying potential reversal conditions by measuring manifold curvature, topological complexity, and fractal regime states. Unlike traditional reversal indicators that rely on price pattern recognition or momentum oscillators, this system reconstructs the underlying geometric surface (manifold) that price evolves upon and detects points where this topology undergoes catastrophic folding—mathematical singularities that correspond to forced directional changes in price dynamics.
The indicator combines three analytical frameworks: phase space reconstruction that embeds price data into a multi-dimensional coordinate system, catastrophe detection that measures when this embedded manifold reaches critical curvature thresholds indicating topology breaks, and Hurst exponent calculation that classifies the current fractal regime to adaptively weight detection sensitivity. This creates a geometry-based reversal detection system with visual feedback showing topology state, manifold distortion fields, and directional probability projections.
What Makes This Approach Different
Phase Space Embedding Construction
The core analytical method reconstructs price evolution as movement through a three-dimensional coordinate system rather than analyzing price as a one-dimensional time series. The system calculates normalized embedding coordinates: X = normalize(price_velocity, window) , Y = normalize(momentum_acceleration, window) , and Z = normalize(volume_weighted_returns, window) . These coordinates create a trajectory through phase space where price movement traces a path across a geometric surface—the market manifold.
This embedding approach differs fundamentally from traditional technical analysis by treating price not as a sequential data stream but as a dynamical system evolving on a curved surface in multi-dimensional space. The trajectory's geometric properties (curvature, complexity, folding) contain information about impending directional changes that single-dimension analysis cannot capture. When this manifold undergoes rapid topological deformation, price must respond with directional change—this is the mathematical basis for catastrophe detection.
Statistical normalization using z-score transformation (subtracting mean, dividing by standard deviation over a rolling window) ensures the coordinate system remains scale-invariant across different instruments and volatility regimes, allowing identical detection logic to function on forex, crypto, stocks, or indices without recalibration.
Catastrophe Score Calculation
The catastrophe detection formula implements a composite anomaly measurement combining multiple topology metrics: Catastrophe_Score = 0.45×Curvature_Percentile + 0.25×Complexity_Ratio + 0.20×Condition_Percentile + 0.10×Gradient_Percentile . Each component measures a distinct aspect of manifold distortion:
Curvature (κ) is computed using the discrete Laplacian operator: κ = √ , which measures how sharply the manifold surface bends at the current point. High curvature values indicate the surface is folding or developing a sharp corner—geometric precursors to catastrophic topology breaks. The Laplacian measures second derivatives (rate of change of rate of change), capturing acceleration in the trajectory's path through phase space.
Topological Complexity counts sign changes in the curvature field over the embedding window, measuring how chaotically the manifold twists and oscillates. A smooth, stable surface produces low complexity; a highly contorted, unstable surface produces high complexity. This metric detects when the geometric structure becomes informationally dense with multiple local extrema, suggesting an imminent topology simplification event (catastrophe).
Condition Number measures the Jacobian matrix's sensitivity: Condition = |Trace| / |Determinant|, where the Jacobian describes how small changes in price produce changes in the embedding coordinates. High condition numbers indicate numerical instability—points where the coordinate transformation becomes ill-conditioned, suggesting the manifold mapping is approaching a singularity.
Each metric is converted to percentile rank within a rolling window, then combined using weighted sum. The percentile transformation creates adaptive thresholds that automatically adjust to each instrument's characteristic topology without manual recalibration. The resulting 0-100% catastrophe score represents the current bar's position in the distribution of historical manifold distortion—values above the threshold (default 65%) indicate statistically extreme topology states where reversals become geometrically probable.
This multi-metric ensemble approach prevents false signals from isolated anomalies: all four geometric features must simultaneously indicate distortion for a high catastrophe score, ensuring only true manifold breaks trigger detection.
Hurst Exponent Regime Classification
The Hurst exponent calculation implements rescaled range (R/S) analysis to measure the fractal dimension of price returns: H = log(R/S) / log(n) , where R is the range of cumulative deviations from mean and S is the standard deviation. The resulting value classifies market behavior into three fractal regimes:
Trending Regime (H > 0.55) : Persistent price movement where future changes are positively correlated with past changes. The manifold exhibits directional momentum with smooth topology evolution. In this regime, catastrophe signals receive 1.2× confidence multiplier because manifold breaks in trending conditions produce high-magnitude directional changes.
Mean-Reverting Regime (H < 0.45) : Anti-persistent price movement where future changes tend to oppose past changes. The manifold exhibits oscillatory topology with frequent small-scale distortions. Catastrophe signals receive 0.8× confidence multiplier because reversal significance is diminished in choppy conditions where the manifold constantly folds at minor scales.
Random Walk Regime (H ≈ 0.50) : No statistical correlation in returns. The manifold evolution is geometrically neutral with moderate topology stability. Standard 1.0× confidence multiplier applies.
This adaptive weighting system solves a critical problem in reversal detection: the same geometric catastrophe has different trading implications depending on the fractal regime. A manifold fold in a strong trend suggests a significant reversal opportunity; the same fold in mean-reversion suggests a minor oscillation. The Hurst-based regime filter ensures detection sensitivity automatically adjusts to market character without requiring trader intervention.
The implementation uses logarithmic price returns rather than raw prices to ensure
stationarity, and applies the calculation over a configurable window (default 5 bars) to balance responsiveness with statistical validity. The Hurst value is then smoothed using exponential moving average to reduce noise while maintaining regime transition detection.
Multi-Layer Confirmation Architecture
The system implements five independent confirmation filters that must simultaneously validate
before any singularity signal generates:
1. Catastrophe Threshold : The composite anomaly score must exceed the configured threshold (default 0.65 on 0-1 scale), ensuring the manifold distortion is statistically extreme relative to recent history.
2. Pivot Structure Confirmation : Traditional swing high/low patterns (using ta.pivothigh and ta.pivotlow with configurable lookback) must form at the catastrophe bar. This ensures the geometric singularity coincides with observable price structure rather than occurring mid-swing where interpretation is ambiguous.
3. Swing Size Validation : The pivot magnitude must exceed a minimum threshold measured in ATR units (default 1.5× Average True Range). This filter prevents signals on insignificant price jiggles that lack meaningful reversal potential, ensuring only substantial swings with adequate risk/reward ratios generate signals.
4. Volume Confirmation : Current volume must exceed 1.3× the 20-period moving average, confirming genuine market participation rather than low-liquidity price noise. Manifold catastrophes without volume support often represent false topology breaks that don't translate to sustained directional change.
5. Regime Validity : The market must be classified as either trending (ADX > configured threshold, default 30) or volatile (ATR expansion > configured threshold, default 40% above 30-bar average), and must NOT be in choppy/ranging state. This critical filter prevents trading during geometrically unfavorable conditions where edge deteriorates.
All five conditions must evaluate true simultaneously for a signal to generate. This conjunction-based logic (AND not OR) dramatically reduces false positives while preserving true reversal detection. The architecture recognizes that geometric catastrophes occur frequently in noisy data, but only those catastrophes that align with confirming evidence across price structure, participation, and regime characteristics represent tradable opportunities.
A cooldown mechanism (default 8 bars between signals) prevents signal clustering at extended pivot zones where the manifold may undergo multiple small catastrophes during a single reversal process.
Direction Classification System
Unlike binary bull/bear systems, the indicator implements a voting mechanism combining four
directional indicators to classify each catastrophe:
Pivot Vote : +1 if pivot low, -1 if pivot high, 0 otherwise
Trend Vote : Based on slow frequency (55-period EMA) slope—+1 if rising, -1 if falling, 0 if flat
Flow Vote : Based on Y-gradient (momentum acceleration)—+1 if positive, -1 if negative, 0 if neutral
Mid-Band Vote : Based on price position relative to medium frequency (21-period EMA)—+1 if above, -1 if below, 0 if at
The total vote sum classifies the singularity: ≥2 votes = Bullish , ≤-2 votes = Bearish , -1 to +1 votes = Neutral (skip) . This majority-consensus approach ensures directional classification requires alignment across multiple timeframes and analysis dimensions rather than relying on a single indicator. Neutral signals (mixed voting) are displayed but should not be traded, as they represent geometric catastrophes without clear directional resolution.
Core Calculation Methodology
Embedding Coordinate Generation
Three normalized phase space coordinates are constructed from price data:
X-Dimension (Velocity Space):
price_velocity = close - close
X = (price_velocity - mean) / stdev over hurstWindow
Y-Dimension (Acceleration Space):
momentum = close - close
momentum_accel = momentum - momentum
Y = (momentum_accel - mean) / stdev over hurstWindow
Z-Dimension (Volume-Weighted Space):
vol_normalized = (volume - mean) / stdev over embedLength
roc = (close - close ) / close
Z = (roc × vol_normalized - mean) / stdev over hurstWindow
These coordinates define a point in 3D phase space for each bar. The trajectory connecting these points is the reconstructed manifold.
Gradient Field Calculation
First derivatives measure local manifold slope:
dX/dt = X - X
dY/dt = Y - Y
Gradient_Magnitude = √
The gradient direction indicates where the manifold is "pushing" price. Positive Y-gradient suggests upward topological pressure; negative Y-gradient suggests downward pressure.
Curvature Tensor Components
Second derivatives measure manifold bending using discrete Laplacian:
Laplacian_X = X - 2×X + X
Laplacian_Y = Y - 2×Y + Y
Laplacian_Magnitude = √
This is then normalized:
Curvature_Normalized = (Laplacian_Magnitude - mean) / stdev over embedLength
High normalized curvature (>1.5) indicates sharp manifold folding.
Complexity Accumulation
Sign changes in curvature field are counted:
Sign_Flip = 1 if sign(Curvature ) ≠ sign(Curvature ), else 0
Topological_Complexity = sum(Sign_Flip) over embedLength window
This measures oscillation frequency in the geometry. Complexity >5 indicates chaotic topology.
Condition Number Stability Analysis
Jacobian matrix sensitivity is approximated:
dX/dp = dX/dt / (price_change + epsilon)
dY/dp = dY/dt / (price_change + epsilon)
Jacobian_Determinant = (dX/dt × dY/dp) - (dX/dp × dY/dt)
Jacobian_Trace = dX/dt + dY/dp
Condition_Number = |Trace| / (|Determinant| + epsilon)
High condition numbers indicate numerical instability near singularities.
Catastrophe Score Assembly
Each metric is converted to percentile rank over embedLength window, then combined:
Curvature_Percentile = percentrank(abs(Curvature_Normalized), embedLength)
Gradient_Percentile = percentrank(Gradient_Magnitude, embedLength)
Condition_Percentile = percentrank(abs(Condition_Z_Score), embedLength)
Complexity_Ratio = clamp(Topological_Complexity / embedLength, 0, 1)
Final score:
Raw_Anomaly = 0.45×Curvature_P + 0.25×Complexity_R + 0.20×Condition_P + 0.10×Gradient_P
Catastrophe_Score = Raw_Anomaly × Hurst_Multiplier
Values are clamped to range.
Hurst Exponent Calculation
Rescaled range analysis on log returns:
Calculate log returns: r = log(close) - log(close )
Compute cumulative deviations from mean
Find range: R = max(cumulative_dev) - min(cumulative_dev)
Calculate standard deviation: S = stdev(r, hurstWindow)
Compute R/S ratio
Hurst = log(R/S) / log(hurstWindow)
Clamp to and smooth with 5-period EMA
Regime Classification Logic
Volatility Regime:
ATR_MA = SMA(ATR(14), 30)
Vol_Expansion = ATR / ATR_MA
Is_Volatile = Vol_Expansion > (1.0 + minVolExpansion)
Trend Regime (Corrected ADX):
Calculate directional movement (DM+, DM-)
Smooth with Wilder's RMA(14)
Compute DI+ and DI- as percentages
Calculate DX = |DI+ - DI-| / (DI+ + DI-) × 100
ADX = RMA(DX, 14)
Is_Trending = ADX > (trendStrength × 100)
Chop Detection:
Is_Chopping = NOT Is_Trending AND NOT Is_Volatile
Regime Validity:
Regime_Valid = (Is_Trending OR Is_Volatile) AND NOT Is_Chopping
Signal Generation Logic
For each bar:
Check if catastrophe score > topologyStrength threshold
Verify regime is valid
Confirm Hurst alignment (trending or mean-reverting with pivot)
Validate pivot quality (price extended outside spectral bands then re-entered)
Confirm volume/volatility participation
Check cooldown period has elapsed
If all true: compute directional vote
If vote ≥2: Bullish Singularity
If vote ≤-2: Bearish Singularity
If -1 to +1: Neutral (display but skip)
All conditions must be true for signal generation.
Visual System Architecture
Spectral Decomposition Layers
Three harmonic frequency bands visualize entropy state:
Layer 1 (Surface Frequency):
Center: EMA(8)
Width: ±0.3 × 0.5 × ATR
Transparency: 75% (most visible)
Represents fast oscillations
Layer 2 (Mid Frequency):
Center: EMA(21)
Width: ±0.5 × 0.5 × ATR
Transparency: 85%
Represents medium cycles
Layer 3 (Deep Frequency):
Center: EMA(55)
Width: ±0.7 × 0.5 × ATR
Transparency: 92% (most transparent)
Represents slow baseline
Convergence of layers indicates low entropy (stable topology). Divergence indicates high entropy (catastrophe building). This decomposition reveals how different frequency components of price movement interact—when all three align, the manifold is in equilibrium; when they separate, topology is unstable.
Energy Radiance Fields
Concentric boxes emanate from each singularity bar:
For each singularity, 5 layers are generated:
Layer n: bar_index ± (n × 1.5 bars), close ± (n × 0.4 × ATR)
Transparency gradient: inner 75% → outer 95%
Color matches signal direction
These fields visualize the "energy well" of the catastrophe—wider fields indicate stronger topology distortion. The exponential expansion creates a natural radiance effect.
Singularity Node Geometry
N-sided polygon (default hexagon) at each signal bar:
Vertices calculated using polar coordinates
Rotation angle: bar_index × 0.1 (creates animation)
Radius: ATR × singularity_strength × 2
Connects vertices with colored lines
The rotating geometric primitive marks the exact catastrophe bar with visual prominence.
Gradient Flow Field
Directional arrows display manifold slope:
Spawns every 3 bars when gradient_magnitude > 0.1
Symbol: "↗" if dY/dt > 0.1, "↘" if dY/dt < -0.1, "→" if neutral
Color: Bull/bear/neutral based on direction
Density limited to flowDensity parameter
Arrows cluster when gradient is strong, creating intuitive topology visualization.
Probability Projection Cones
Forward trajectory from each singularity:
Projects 10 bars forward
Direction based on vote classification
Center line: close + (direction × ATR × 3)
Uncertainty width: ATR × singularity_strength × 2
Dashed boundaries, solid center
These are mathematical projections based on current gradient, not price targets. They visualize expected manifold evolution if topology continues current trajectory.
Dashboard Metrics Explanation
The real-time control panel displays six core metrics plus regime status:
H (Hurst Exponent):
Value: Current Hurst (0-1 scale)
Label: TREND (>0.55), REVERT (<0.45), or RANDOM (0.45-0.55)
Icon: Direction arrow based on regime
Purpose: Shows fractal character—only trade when favorable
Σ (Catastrophe Score):
Value: Current composite anomaly (0-100%)
Bar gauge shows relative strength
Icon: ◆ if above threshold, ○ if below
Purpose: Primary signal strength indicator
κ (Curvature):
Value: Normalized Laplacian magnitude
Direction arrow shows sign
Color codes severity (green<0.8, yellow<1.5, red≥1.5)
Purpose: Shows manifold bending intensity
⟳ (Topology Complexity):
Value: Count of sign flips in curvature
Icon: ◆ if >3, ○ otherwise
Color codes chaos level
Purpose: Indicates geometric instability
V (Volatility Expansion):
Value: ATR expansion percentage above 30-bar average
Icon: ● if volatile, ○ otherwise
Purpose: Confirms energy present for reversal
T (Trend Strength):
Value: ADX reading (0-100)
Icon: ● if trending, ○ otherwise
Purpose: Shows directional bias strength
R (Regime):
Label: EXPLOSIVE / TREND / VOLATILE / CHOP / NEUTRAL
Icon: ✓ if valid, ✗ if invalid
Purpose: Go/no-go filter for trading
STATE (Bottom Display):
Shows: "◆ BULL SINGULARITY" (green), "◆ BEAR SINGULARITY" (red), "◆ WEAK/NEUTRAL" (orange), or "— Monitoring —" (gray)
Purpose: Current signal status at a glance
How to Use This Indicator
Initial Setup and Configuration
Apply the indicator to your chart with default settings as a starting point. The default parameters (21-bar embedding, 5-bar Hurst window, 2.5σ singularity threshold, 0.65 topology confirmation) are optimized for balanced detection across most instruments and timeframes. For very fast markets (scalping crypto, 1-5min charts), consider reducing embedding depth to 13-15 bars and Hurst window to 3 bars for more responsive detection. For slower markets (swing trading stocks, 4H-Daily charts), increase embedding depth to 34-55 bars and Hurst window to 8-10 bars for more stable topology measurement.
Enable the dashboard (top right recommended) to monitor real-time metrics. The control panel is your primary decision interface—glancing at the dashboard should instantly communicate whether conditions favor trading and what the current topology state is. Position and size the dashboard to remain visible but not obscure price action.
Enable regime filtering (strongly recommended) to prevent trading during choppy/ranging conditions where geometric edge deteriorates. This single setting can dramatically improve overall performance by eliminating low-probability environments.
Reading Dashboard Metrics for Trade Readiness
Before considering any trade, verify the dashboard shows favorable conditions:
Hurst (H) Check:
The Hurst Exponent reading is your first filter. Only consider trades when H > 0.50 . Ideal conditions show H > 0.60 with "TREND" label—this indicates persistent directional price movement where manifold catastrophes produce significant reversals. When H < 0.45 (REVERT label), the market is mean-reverting and catastrophes represent minor oscillations rather than substantial pivots. Do not trade in mean-reverting regimes unless you're explicitly using range-bound strategies (which this indicator is not optimized for). When H ≈ 0.50 (RANDOM label), edge is neutral—acceptable but not ideal.
Catastrophe (Σ) Monitoring:
Watch the Σ percentage build over time. Readings consistently below 50% indicate stable topology with no imminent reversals. When Σ rises above 60-65%, manifold distortion is approaching critical levels. Signals only fire when Σ exceeds the configured threshold (default 65%), so this metric pre-warns you of potential upcoming catastrophes. High-conviction setups show Σ > 75%.
Regime (R) Validation:
The regime classification must read TREND, VOLATILE, or EXPLOSIVE—never trade when it reads CHOP or NEUTRAL. The checkmark (✓) must be present in the regime cell for trading conditions to be valid. If you see an X (✗), skip all signals until regime improves. This filter alone eliminates most losing trades by avoiding geometrically unfavorable environments.
Combined High-Conviction Profile:
The strongest trading opportunities show simultaneously:
H > 0.60 (strong trending regime)
Σ > 75% (extreme topology distortion)
R = EXPLOSIVE or TREND with ✓
κ (Curvature) > 1.5 (sharp manifold fold)
⟳ (Complexity) > 4 (chaotic geometry)
V (Volatility) showing elevated ATR expansion
When all metrics align in this configuration, the manifold is undergoing severe distortion in a favorable fractal regime—these represent maximum-conviction reversal opportunities.
Signal Interpretation and Entry Logic
Bullish Singularity (▲ Green Triangle Below Bar):
This marker appears when the system detects a manifold catastrophe at a price low with bullish directional consensus. All five confirmation filters have aligned: topology score exceeded threshold, pivot low structure formed, swing size was significant, volume/volatility confirmed participation, and regime was valid. The green color indicates the directional vote totaled +2 or higher (majority bullish).
Trading Approach: Consider long entry on the bar immediately following the signal (bar after the triangle). The singularity bar itself is where the geometric catastrophe occurred—entering after allows you to see if price confirms the reversal. Place stop loss below the singularity bar's low (with buffer of 0.5-1.0 ATR for volatility). Initial target can be the previous swing high, or use the probability cone projection as a guide (though not a guarantee). Monitor the dashboard STATE—if it flips to "◆ BEAR SINGULARITY" or Hurst drops significantly, consider exiting even if target not reached.
Bearish Singularity (▼ Red Triangle Above Bar):
This marker appears when the system detects a manifold catastrophe at a price high with bearish directional consensus. Same five-filter confirmation process as bullish signals. The red color indicates directional vote totaled -2 or lower (majority bearish).
Trading Approach: Consider short entry on the bar following the signal. Place stop loss above the singularity bar's high (with buffer). Target previous swing low or use cone projection as reference. Exit if opposite signal fires or Hurst deteriorates.
Neutral Signal (● Orange Circle at Price Level):
This marker indicates the catastrophe detection system identified a topology break that passed catastrophe threshold and regime filters, but the directional voting system produced a mixed result (vote between -1 and +1). This means the four directional components (pivot, trend, flow, mid-band) are not in agreement about which way the reversal should resolve.
Trading Approach: Skip these signals. Neutral markers are displayed for analytical completeness but should not be traded. They represent geometric catastrophes without clear directional resolution—essentially, the manifold is breaking but the direction of the break is ambiguous. Trading neutral signals dramatically increases false signal rate. Only trade green (bullish) or red (bearish) singularities.
Visual Confirmation Using Spectral Layers
The three colored ribbons (spectral decomposition layers) provide entropy visualization that helps confirm signal quality:
Divergent Layers (High Entropy State):
When the three frequency bands (fast 8-period, medium 21-period, slow 55-period) are separated with significant gaps between them, the manifold is in high entropy state—different frequency components of price movement are pulling in different directions. This geometric tension precedes catastrophes. Strong signals often occur when layers are divergent before the signal, then begin reconverging immediately after.
Convergent Layers (Low Entropy State):
When all three ribbons are tightly clustered or overlapping, the manifold is in equilibrium—all frequency components agree. This stable geometry makes catastrophe detection more reliable because topology breaks clearly stand out against the baseline stability. If you see layers converge, then a singularity fires, then layers diverge, this pattern suggests a genuine regime transition.
Signal Quality Assessment:
High-quality singularity signals should show:
Divergent layers (high entropy) in the 5-10 bars before signal
Singularity bar occurs when price has extended outside at least one of the spectral bands (shows pivot extended beyond equilibrium)
Close of singularity bar re-enters the spectral band zone (shows mean reversion starting)
Layers begin reconverging in 3-5 bars after signal (shows new equilibrium forming)
This pattern visually confirms the geometric narrative: manifold became unstable (divergence), reached critical distortion (extended outside equilibrium), broke catastrophically (singularity), and is now stabilizing in new direction (reconvergence).
Using Energy Fields for Trade Management
The concentric glowing boxes around each singularity visualize the topology distortion
magnitude:
Wide Energy Fields (5+ Layers Visible):
Large radiance indicates strong catastrophe with high manifold curvature. These represent significant topology breaks and typically precede larger price moves. Wide fields justify wider profit targets and longer hold times. The outer edge of the largest box can serve as a dynamic support/resistance zone—price often respects these geometric boundaries.
Narrow Energy Fields (2-3 Layers):
Smaller radiance indicates moderate catastrophe. While still valid signals (all filters passed), expect smaller follow-through. Use tighter profit targets and be prepared for quicker exit if momentum doesn't develop. These are valid but lower-conviction trades.
Field Interaction Zones:
When energy fields from consecutive signals overlap or touch, this indicates a prolonged topology distortion region—often corresponds to consolidation zones or complex reversal patterns (head-and-shoulders, double tops/bottoms). Be more cautious in these areas as the manifold is undergoing extended restructuring rather than a clean catastrophe.
Probability Cone Projections
The dashed cone extending forward from each singularity is a mathematical projection, not a
price target:
Cone Direction:
The center line direction (upward for bullish, downward for bearish, flat for neutral) shows the expected trajectory based on current manifold gradient and singularity direction. This is where the topology suggests price "should" go if the catastrophe completes normally.
Cone Width:
The uncertainty band (upper and lower dashed boundaries) represents the range of outcomes given current volatility (ATR-based). Wider cones indicate higher uncertainty—expect more price volatility even if direction is correct. Narrower cones suggest more constrained movement.
Price-Cone Interaction:
Price following near the center line = catastrophe resolving as expected, geometric projection accurate
Price breaking above upper cone = stronger-than-expected reversal, consider holding for larger targets
Price breaking below lower cone (for bullish signal) = catastrophe failing, manifold may be re-folding in opposite direction, consider exit
Price oscillating within cone = normal reversal process, hold position
The 10-bar projection length means cones show expected behavior over the next ~10 bars. Don't confuse this with longer-term price targets.
Gradient Flow Field Interpretation
The directional arrows (↗, ↘, →) scattered across the chart show the manifold's Y-gradient (vertical acceleration dimension):
Upward Arrows (↗):
Positive Y-gradient indicates the momentum acceleration dimension is pushing upward—the manifold topology has upward "slope" at this location. Clusters of upward arrows suggest bullish topological pressure building. These often appear before bullish singularities fire.
Downward Arrows (↘):
Negative Y-gradient indicates downward topological pressure. Clusters precede bearish singularities.
Horizontal Arrows (→):
Neutral gradient indicates balanced topology with no strong directional pressure.
Using Flow Field:
The arrows provide real-time topology state information even between singularity signals. If you're in a long position from a bullish singularity and begin seeing increasing downward arrows appearing, this suggests manifold gradient is shifting—consider tightening stops. Conversely, if arrows remain upward or neutral, topology supports continuation.
Don't confuse arrow direction with immediate price direction—arrows show geometric slope, not price prediction. They're confirmatory context, not entry signals themselves.
Parameter Optimization for Your Trading Style
For Scalping / Fast Trading (1m-15m charts):
Embedding Depth: 13-15 bars (faster topology reconstruction)
Hurst Window: 3 bars (responsive fractal detection)
Singularity Threshold: 2.0-2.3σ (more sensitive)
Topology Confirmation: 0.55-0.60 (lower barrier)
Min Swing Size: 0.8-1.2 ATR (accepts smaller moves)
Pivot Lookback: 3-4 bars (quick pivot detection)
This configuration increases signal frequency for active trading but requires diligent monitoring as false signal rate increases. Use tighter stops.
For Day Trading / Standard Approach (15m-4H charts):
Keep default settings (21 embed, 5 Hurst, 2.5σ, 0.65 confirmation, 1.5 ATR, 5 pivot)
These are balanced for quality over quantity
Best win rate and risk/reward ratio
Recommended for most traders
For Swing Trading / Position Trading (4H-Daily charts):
Embedding Depth: 34-55 bars (stable long-term topology)
Hurst Window: 8-10 bars (smooth fractal measurement)
Singularity Threshold: 3.0-3.5σ (only extreme catastrophes)
Topology Confirmation: 0.75-0.85 (high conviction only)
Min Swing Size: 2.5-4.0 ATR (major moves only)
Pivot Lookback: 8-13 bars (confirmed swings)
This configuration produces infrequent but highly reliable signals suitable for position sizing and longer hold times.
Volatility Adaptation:
In extremely volatile instruments (crypto, penny stocks), increase Min Volatility Expansion to 0.6-0.8 to avoid over-signaling during "always volatile" conditions. In stable instruments (major forex pairs, blue-chip stocks), decrease to 0.3 to allow signals during moderate volatility spikes.
Trend vs Range Preference:
If you prefer trading only strong trends, increase Min Trend Strength to 0.5-0.6 (ADX > 50-60). If you're comfortable with volatility-based trading in weaker trends, decrease to 0.2 (ADX > 20). The default 0.3 balances both approaches.
Complete Trading Workflow Example
Step 1 - Pre-Session Setup:
Load chart with MSE indicator. Check dashboard position is visible. Verify regime filter is enabled. Review recent signals to gauge current instrument behavior.
Step 2 - Market Assessment:
Observe dashboard Hurst reading. If H < 0.45 (mean-reverting), consider skipping this session or using other strategies. If H > 0.50, proceed. Check regime shows TREND, VOLATILE, or EXPLOSIVE with checkmark—if CHOP, wait for regime shift alert.
Step 3 - Signal Wait:
Monitor catastrophe score (Σ). Watch for it climbing above 60%. Observe spectral layers—look for divergence building. If you see curvature (κ) rising above 1.0 and complexity (⟳) increasing, catastrophe is building. Do not anticipate—wait for the actual signal marker.
Step 4 - Signal Recognition:
▲ Bullish or ▼ Bearish triangle appears at a bar. Dashboard STATE changes to "◆ BULL/BEAR SINGULARITY". Energy field appears around the signal bar. Check signal quality:
Was Σ > 70% at signal? (Higher quality)
Are energy fields wide? (Stronger catastrophe)
Did layers diverge before and reconverge after? (Clean break)
Is Hurst still > 0.55? (Good regime)
Step 5 - Entry Decision:
If signal is green/red (not orange neutral), all confirmations look strong, and no immediate contradicting factors appear, prepare entry on next bar open. Wait for confirmation bar to form—ideally it should close in the signal direction (bullish signal → bar closes higher, bearish signal → bar closes lower).
Step 6 - Position Entry:
Enter at open or shortly after open of bar following signal bar. Set stop loss: for bullish signals, place stop at singularity_bar_low - (0.75 × ATR); for bearish signals, place stop at singularity_bar_high + (0.75 × ATR). The buffer accommodates volatility while protecting against catastrophe failure.
Step 7 - Trade Management:
Monitor dashboard continuously:
If Hurst drops below 0.45, consider reducing position
If opposite singularity fires, exit immediately (manifold has re-folded)
If catastrophe score drops below 40% and stays there, topology has stabilized—consider partial profit taking
Watch gradient flow arrows—if they shift to opposite direction persistently, tighten stops
Step 8 - Profit Taking:
Use probability cone as a guide—if price reaches outer cone boundary, consider taking partial profits. If price follows center line cleanly, hold for larger target. Traditional technical targets work well: previous swing high/low, round numbers, Fibonacci extensions. Don't expect precision—manifold projections give direction and magnitude estimates, not exact prices.
Step 9 - Exit:
Exit on: (a) opposite signal appears, (b) dashboard shows regime became invalid (checkmark changes to X), (c) technical target reached, (d) Hurst deteriorates significantly, (e) stop loss hit, or (f) time-based exit if using session limits. Never hold through opposite singularity signals—the manifold has broken in the other direction and your trade thesis is invalidated.
Step 10 - Post-Trade Review:
After exit, review: Did the probability cone projection align with actual price movement? Were the energy fields proportional to move size? Did spectral layers show expected reconvergence? Use these observations to calibrate your interpretation of signal quality over time.
Best Performance Conditions
This topology-based approach performs optimally in specific market environments:
Favorable Conditions:
Well-Developed Swing Structure: Markets with clear rhythm of advances and declines where pivots form at regular intervals. The manifold reconstruction depends on swing formation, so instruments that trend in clear waves work best. Stocks, major forex pairs during active sessions, and established crypto assets typically exhibit this characteristic.
Sufficient Volatility for Topology Development: The embedding process requires meaningful price movement to construct multi-dimensional coordinates. Extremely quiet markets (tight consolidations, holiday trading, after-hours) lack the volatility needed for manifold differentiation. Look for ATR expansion above average—when volatility is present, geometry becomes meaningful.
Trending with Periodic Reversals: The ideal environment is not pure trend (which rarely reverses) nor pure range (which reverses constantly at small scale), but rather trending behavior punctuated by occasional significant counter-trend reversals. This creates the catastrophe conditions the system is designed to detect: manifold building directional momentum, then undergoing sharp topology break at extremes.
Liquid Instruments Where EMAs Reflect True Flow: The spectral layers and frequency decomposition require that moving averages genuinely represent market consensus. Thinly traded instruments with sporadic orders don't create smooth manifold topology. Prefer instruments with consistent volume where EMA calculations reflect actual capital flow rather than random tick sequences.
Challenging Conditions:
Extremely Choppy / Whipsaw Markets: When price oscillates rapidly with no directional persistence (Hurst < 0.40), the manifold undergoes constant micro-catastrophes that don't translate to tradable reversals. The regime filter helps avoid these, but awareness is important. If you see multiple neutral signals clustering with no follow-through, market is too chaotic for this approach.
Very Low Volatility Consolidation: Tight ranges with ATR below average cause the embedding coordinates to compress into a small region of phase space, reducing geometric differentiation. The manifold becomes nearly flat, and catastrophe detection loses sensitivity. The regime filter's volatility component addresses this, but manually avoiding dead markets improves results.
Gap-Heavy Instruments: Stocks that gap frequently (opening outside previous close) create discontinuities in the manifold trajectory. The embedding process assumes continuous evolution, so gaps introduce artifacts. Most gaps don't invalidate the approach, but instruments with daily gaps >2% regularly may show degraded performance. Consider using higher timeframes (4H, Daily) where gaps are less proportionally significant.
Parabolic Moves / Blowoff Tops: When price enters an exponential acceleration phase (vertical rally or crash), the manifold evolves too rapidly for the standard embedding window to track. Catastrophe detection may lag or produce false signals mid-move. These conditions are rare but identifiable by Hurst > 0.75 combined with ATR expansion >2.0× average. If detected, consider sitting out or using very tight stops as geometry is in extreme distortion.
The system adapts by reducing signal frequency in poor conditions—if you notice long periods with no signals, the topology likely lacks the geometric structure needed for reliable catastrophe detection. This is a feature, not a bug: it prevents forced trading during unfavorable environments.
Theoretical Justification for Approach
Why Manifold Embedding?
Traditional technical analysis treats price as a one-dimensional time series: current price is predicted from past prices in sequential order. This approach ignores the structure of price dynamics—the relationships between velocity, acceleration, and participation that govern how price actually evolves.
Dynamical systems theory (from physics and mathematics) provides an alternative framework: treat price as a state variable in a multi-dimensional phase space. In this view, each market condition corresponds to a point in N-dimensional space, and market evolution is a trajectory through this space. The geometry of this space (its topology) constrains what trajectories are possible.
Manifold embedding reconstructs this hidden geometric structure from observable price data. By creating coordinates from velocity, momentum acceleration, and volume-weighted returns, we map price evolution onto a 3D surface. This surface—the manifold—reveals geometric relationships that aren't visible in price charts alone.
The mathematical theorem underlying this approach (Takens' Embedding Theorem from dynamical systems theory) proves that for deterministic or weakly stochastic systems, a state space reconstruction from time-delayed observations of a single variable captures the essential dynamics of the full system. We apply this principle: even though we only observe price, the embedded coordinates (derivatives of price) reconstruct the underlying dynamical structure.
Why Catastrophe Theory?
Catastrophe theory, developed by mathematician René Thom (Fields Medal 1958), describes how continuous systems can undergo sudden discontinuous changes when control parameters reach critical values. A classic example: gradually increasing force on a beam causes smooth bending, then sudden catastrophic buckling. The beam's geometry reaches a critical curvature where topology must break.
Markets exhibit analogous behavior: gradual price changes build tension in the manifold topology until critical distortion is reached, then abrupt directional change occurs (reversal). Catastrophes aren't random—they're mathematically necessary when geometric constraints are violated.
The indicator detects these geometric precursors: high curvature (manifold bending sharply), high complexity (topology oscillating chaotically), high condition number (coordinate mapping becoming singular). These metrics quantify how close the manifold is to a catastrophic fold. When all simultaneously reach extreme values, topology break is imminent.
This provides a logical foundation for reversal detection that doesn't rely on pattern recognition or historical correlation. We're measuring geometric properties that mathematically must change when systems reach critical states. This is why the approach works across different instruments and timeframes—the underlying geometry is universal.
Why Hurst Exponent?
Markets exhibit fractal behavior: patterns at different time scales show statistical self-similarity. The Hurst exponent quantifies this fractal structure by measuring long-range dependence in returns.
Critically for trading, Hurst determines whether recent price movement predicts future direction (H > 0.5) or predicts the opposite (H < 0.5). This is regime detection: trending vs mean-reverting behavior.
The same manifold catastrophe has different trading implications depending on regime. In trending regime (high Hurst), catastrophes represent significant reversal opportunities because the manifold has been building directional momentum that suddenly breaks. In mean-reverting regime (low Hurst), catastrophes represent minor oscillations because the manifold constantly folds at small scales.
By weighting catastrophe signals based on Hurst, the system adapts detection sensitivity to the current fractal regime. This is a form of meta-analysis: not just detecting geometric breaks, but evaluating whether those breaks are meaningful in the current fractal context.
Why Multi-Layer Confirmation?
Geometric anomalies occur frequently in noisy market data. Not every high-curvature point represents a tradable reversal—many are artifacts of microstructure noise, order flow imbalances, or low-liquidity ticks.
The five-filter confirmation system (catastrophe threshold, pivot structure, swing size, volume, regime) addresses this by requiring geometric anomalies to align with observable market evidence. This conjunction-based logic implements the principle: extraordinary claims require extraordinary evidence .
A manifold catastrophe (extraordinary geometric event) alone is not sufficient. We additionally require: price formed a pivot (visible structure), swing was significant (adequate magnitude), volume confirmed participation (capital backed the move), and regime was favorable (trending or volatile, not chopping). Only when all five dimensions agree do we have sufficient evidence that the geometric anomaly represents a genuine reversal opportunity rather than noise.
This multi-dimensional approach is analogous to medical diagnosis: no single test is conclusive, but when multiple independent tests all suggest the same condition, confidence increases dramatically. Each filter removes a different category of false signals, and their combination creates a robust detection system.
The result is a signal set with dramatically improved reliability compared to any single metric alone. This is the power of ensemble methods applied to geometric analysis.
Important Disclaimers
This indicator applies mathematical topology and catastrophe theory to multi-dimensional price space reconstruction. It identifies geometric conditions where manifold curvature, topological complexity, and coordinate singularities suggest potential reversal zones based on phase space analysis. It should not be used as a standalone trading system.
The embedding coordinates, catastrophe scores, and Hurst calculations are deterministic mathematical formulas applied to historical price data. These measurements describe current and recent geometric relationships in the reconstructed manifold but do not predict future price movements. Past geometric patterns and singularity markers do not guarantee future market behavior will follow similar topology evolution.
The manifold reconstruction assumes certain mathematical properties (sufficient embedding dimension, quasi-stationarity, continuous dynamics) that may not hold in all market conditions. Gaps, flash crashes, circuit breakers, news events, and other discontinuities can violate these assumptions. The system attempts to filter problematic conditions through regime classification, but cannot eliminate all edge cases.
The spectral decomposition, energy fields, and probability cones are visualization aids that represent mathematical constructs, not price predictions. The probability cone projects current gradient forward assuming topology continues current trajectory—this is a mathematical "if-then" statement, not a forecast. Market topology can and does change unexpectedly.
All trading involves substantial risk. The singularity markers represent analytical conditions where geometric mathematics align with threshold criteria, not certainty of directional change. Use appropriate risk management for every trade: position sizing based on account risk tolerance (typically 1-2% maximum risk per trade), stop losses placed beyond recent structure plus volatility buffer, and never risk capital needed for living expenses.
The confirmation filters (pivot, swing size, volume, regime) are designed to reduce false signals but cannot eliminate them entirely. Markets can produce geometric anomalies that pass all filters yet fail to develop into sustained reversals. This is inherent to probabilistic systems operating on noisy real-world data.
No indicator can guarantee profitable trades or eliminate losses. The catastrophe detection provides an analytical framework for identifying potential reversal conditions, but actual trading outcomes depend on numerous factors including execution, slippage, spreads, position sizing, risk management, psychological discipline, and market conditions that may change after signal generation.
Use this tool as one component of a comprehensive trading plan that includes multiple forms of analysis, proper risk management, emotional discipline, and realistic expectations about win rates and drawdowns. Combine catastrophe signals with additional confirmation methods such as support/resistance analysis, volume patterns, multi-timeframe alignment, and broader market context.
The spacing filter, cooldown mechanism, and regime validation are designed to reduce noise and over-signaling, but market conditions can change rapidly and render any analytical signal invalid. Always use stop losses and never risk capital you cannot afford to lose. Past performance of detection accuracy does not guarantee future results.
Technical Implementation Notes
All calculations execute on closed bars only—signals and metric values do not repaint after bar close. The indicator does not use any lookahead bias in its calculations. However, the pivot detection mechanism (ta.pivothigh and ta.pivotlow) inherently identifies pivots with a lag equal to the lookback parameter, meaning the actual pivot occurred at bar but is recognized at bar . This is standard behavior for pivot functions and is not repainting—once recognized, the pivot bar never changes.
The normalization system (z-score transformation over rolling windows) requires approximately 30-50 bars of historical data to establish stable statistics. Values in the first 30-50 bars after adding the indicator may show instability as the rolling means and standard deviations converge. Allow adequate warmup period before relying on signals.
The spectral layer arrays, energy field boxes, gradient flow labels, and node geometry lines are subject to TradingView drawing object limits (500 lines, 500 boxes, 500 labels per indicator as specified in settings). The system implements automatic cleanup by deleting oldest objects when limits approach, but on very long charts with many signals, some historical visual elements may be removed to stay within limits. This does not affect signal generation or dashboard metrics—only historical visual artifacts.
Dashboard and visual rendering update only on the last bar to minimize computational overhead. The catastrophe detection logic executes on every bar, but table cells and drawing objects refresh conditionally to optimize performance. If experiencing chart lag, reduce visual complexity: disable spectral layers, energy fields, or flow field to improve rendering speed. Core signal detection continues to function with all visual elements disabled.
The Hurst calculation uses logarithmic returns rather than raw price to ensure stationarity, and implements clipping to range to handle edge cases where R/S analysis produces invalid values (which can occur during extended periods of identical prices or numerical overflow). The 5-period EMA smoothing reduces noise while maintaining responsiveness to regime transitions.
The condition number calculation adds epsilon (1e-10) to denominators to prevent division by zero when Jacobian determinant approaches zero—which is precisely the singularity condition we're detecting. This numerical stability measure ensures the indicator doesn't crash when detecting the very phenomena it's designed to identify.
The indicator has been tested across multiple timeframes (5-minute through daily) and multiple asset classes (forex majors, stock indices, individual equities, cryptocurrencies, commodities, futures). It functions identically across all instruments due to the adaptive normalization approach and percentage-based metrics. No instrument-specific code or parameter sets are required.
The color scheme system implements seven preset themes plus custom mode. Color assignments are applied globally and affect all visual elements simultaneously. The opacity calculation system multiplies component-specific transparency with master opacity to create hierarchical control—adjusting master opacity affects all visuals proportionally while maintaining their relative transparency relationships.
All alert conditions trigger only on bar close to prevent false alerts from intrabar fluctuations. The regime transition alerts (VALID/INVALID) are particularly useful for knowing when trading edge appears or disappears, allowing traders to adjust activity levels accordingly.
— Dskyz, Trade with insight. Trade with anticipation.
Volumetric Spectrogram [by Oberlunar]Volumetric Spectrogram
A two-pole, price-relative volume profiler that turns regional buy/sell pressure into clean oscillators and actionable regimes in a multi-broker setup.
What it measures
The indicator divides the recent price span into bins and accumulates buy vs. sell volume in each bin, then summarises two regions with respect to the current price:
Upper (↑) — volume that traded above the current price (overhead supply/demand).
Lower (↓) — volume that traded below the current price (underfoot bid/pressure).
Per region, it computes BUY% and SELL%, then forms two normalised oscillators in :
Upper Osc = Upper(BUY%) − Upper(SELL%) → positive when overhead offers are being lifted (breakout acceptance), negative when overhead sell pressure dominates (resistance).
Lower Osc = Lower(BUY%) − Lower(SELL%) → positive when sub-price bids strengthen (support/absorption), negative when selling persists beneath price (weak underbelly).
Both oscillators are optionally smoothed with EMA and can be filled to zero or between curves for quick polarity/strength reading.
Candle-fill modes across brokers
The indicator supports multiple candle-fill policies tied to cross-broker volumetric agreement (e.g., spectral/range-only fills when ≥N brokers align above 70% bullish or below 20% bearish Buy%). This makes regime and pressure shifts visually explicit while filtering out unconfirmed noise.
How it works (core algorithm)
Over a lookback window, find the high/low and split the range into N bins .
For each historical bar, approximate “buy” vs “sell” volume using candle direction and the close relative to each bin’s midprice; update left/right profiles per bin.
Aggregate bins above the current price into the Upper region and bins below into the Lower region; compute regional totals and percentages.
Convert to signed oscillators and smooth (EMA length per input).
Scenario engine (table, every bar)
A compact table reports, for Upper/Lower: BUY Vol, SELL Vol, BUY%, SELL%, and Net%. A classifier labels 8 regimes based on oscillator sign and recent expansion/decay: Sync Long/Short (Expanding/Decaying), Opposite Signs (Widening/Converging), and Tilts (Upper/Lower). This helps distinguish trend continuation, fade risk, compression before break, and asymmetric pressure (e.g., “Tilt Lower — bid/support strengthening”).
# Example strategies and annotated cases:
There are different operational strategies:
1) Bottle-neck Strategy with multi-broker confirmation
When both oscillators are red and they compress toward the zero line (a bottle-neck [/i>), if the squeeze does not flip into the opposite trend but instead resolves in the same direction, you have a continuation setup that can be exploited:
• Pattern: both oscillators red → short, visible contraction (narrow, low-variance cluster) → break of the cluster lows → background shadow bars align bearish (multi-broker agreement).
Example:
This sequence often supports a 1.5–2.5 R/R trade, as in:
Bullish mirror
If both oscillators are teal and compress, then expand upward with multi-broker agreement, the scenario becomes bullish after several bars; the position can be profitable with a reasonable risk setup:
Example:
Follow-through:
Here are the additional, English “playbook” examples you can append to the previous description.
2) Dual-confirmation on volume spikes + multi-broker checks
When pronounced volumetric spikes appear (up or down), trend often reverses sharply. In the figure, the circles highlight the spikes; once the spike subsides (reversion toward baseline), the oscillator turns bullish. The double confirmation of two consecutive minimum spikes acts as support for an ensuing up-move, with fill colors confirming direction.
Chart:
Even with a single spike confirmation, the reversion from an extreme often provides actionable long setups.
3) Volume-pressure + regime-change (multi-broker)
A prospective long configuration emerges when bullish volumetric pressure dominates and bearish pressure fades, especially if this occurs after a lateral phase, followed by a bullish volume spike and multi-broker confirmation .
Chart:
Shadow bars subsequently confirm continuation in a bullish regime; however, a possible regime change is flagged by the scenario classifier and by a color flip in the volumetric borders ( “Possible regime change, but without multi-broker confirmation.” is an appropriate label when applicable).
Chart:
After a verified mean-reversion, price transitions into a bearish configuration: both oscillators turn red. One can wait for a pullback and seek short entries.
Chart:
As shown here, the regime change is anticipated well in advance by the oscillators and multi-broker pressure:
Chart:
4) Contrastive regime-shift with multi-broker validation
In a contrastive trading phase, the lower volumetric oscillator flips color first—buyers start attacking. The first set of background shadow bars does not agree with the regime flip; the second set does. This sequence (oscillator flip → later multi-broker agreement) is a robust early sign of a potential long setup.
Chart:
At the multi-broker level, all shadow bars turn fully green and the setup becomes unambiguously bullish.
Chart:
Note that bearish pressure can still be non-trivial on the volumetric scale—even if it does not reach prior extreme minima—so risk controls should reflect the residual supply.
Delta-bar coloring (optional)
Bars (or candle overlays) can be tinted by a multi-venue weighted bias:
Choose venues (OKX, Coinbase, Bybit, Binance, BlackBull…).
Weight by Equal / Last Volume / SMA Volume.
Apply deadband to suppress flicker around neutrality and a gamma curve to modulate opacity with |bias|.
This layer is independent of the spectrogram core but provides immediate market-wide flow context, consistent with the table and fills.
Inputs (essentials)
Calculation Period and Bins — resolution and depth of the price-range histogram.
EMA length — smoothing per oscillator (optional)
Fill options — to zero / between curves, gradual opacity by |osc|, min/max alpha.
Delta Bar — enable tinting, gamma, neutral band; venue list and weighting mode.
Reading guide
Upper > 0 & expanding : overhead supply is being lifted → breakout acceptance risk rises.
Lower > 0 & expanding : sub-price bids strengthen → pullbacks more likely to absorb.
Opposite signs widening : tug-of-war; avoid late entries.
Converging : compression → prepare for break.
Use the table’s regime label to keep the narrative honest bar-by-bar.
Notes & limits
Buy/Sell attribution uses candle direction and range partitioning (no L2/tick tape).
Venue aggregation relies on per-exchange volume and your chosen weighting; symbols must align (e.g., BTCUSDT pairs).
Oscillators are relative to the current price (regional) by design; they complement, not replace, classical volume profile.
— Oberlunar 👁 ★
XT Buy Sell v1.0 Lite: Non-Repainting Signal Indicator🚀 XT Buy Sell v1.0 Lite: Non-Repainting Signal Indicator
The XT Buy Sell v1.0 Lite indicator is a streamlined version of our flagship tool, designed for traders who need a reliable, ready-to-use source of signals for market entry and exit.
✨ Key Advantages
Non-Repainting Signals: BUY/SELL signals remain permanently on the chart, providing reliability and easy verification on historical data.
High Accuracy: Developed as one of the most accurate tools for identifying entry points.
Ready "Out of the Box": The indicator comes with optimal default settings. All additional and advanced settings are available in the PRO version.
Versatility: Suitable for both Spot and Futures/Leveraged trading.
🔔 Convenience Features
Alerts: Set up alerts for BUY/SELL signals so you don't have to constantly monitor the chart.
Optimization: Configure alerts on the specific coins (tickers) where the indicator shows the best setups (most accurate and profitable).
🧠 Recommendations for Professional Trading (Risk Management)
To achieve maximum results and safety, follow these guidelines:
Historical Backtesting: Always verify the indicator's performance on the history of the selected trading pair before deployment.
Multi-Timeframe Analysis: Utilize the principle of "Signal on Lower TF, Confirmation on Higher TF" to increase your trading confidence.
Entry Confirmation: For maximum entry precision, it is recommended to use it in conjunction with our additional tool "X Trend Dashboard (Lite)".
Sequential Signals: The consecutive appearance of signals in the same direction (e.g., two or more consecutive BUYS) can be interpreted as a signal for re-entry/averaging down the position.
Risk Management:
Always set Stop-Losses.
Move the trade to Break-Even as soon as possible.
Carefully consider the risks and the leverage being used.
Happy trading and profits to all! 📈💰
Squeeze Momentum ProSQUEEZE MOMENTUM PRO - Enhanced Visual Dashboard
A modernized version of the TTM Squeeze Momentum indicator, designed for cleaner visual interpretation and faster decision-making.
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📊 WHAT IS THE SQUEEZE?
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The "squeeze" occurs when Bollinger Bands contract inside Keltner Channels, indicating extremely low volatility. This compression typically precedes explosive directional moves - the tighter the squeeze, the bigger the potential breakout.
John Carter's TTM Squeeze concept (from "Mastering the Trade") combines this volatility compression with momentum direction to identify high-probability setups.
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✨ WHAT'S NEW IN THIS VERSION
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🎯 VISUAL STATUS BAR
- Real-time squeeze state with clear labels
- Color-coded backgrounds (Red = Building, Green = Fired Bullish, Orange = Fired Bearish)
- Squeeze duration counter to gauge compression time
📊 ENHANCED HISTOGRAM
- 4-color momentum gradient (Strong Bull/Weak Bull/Weak Bear/Strong Bear)
- Instantly shows both direction AND strength
- Background shading for current market state
🔥 SQUEEZE INTENSITY GAUGE
- 5-dot pressure indicator showing compression tightness
- Percentage display of squeeze strength
- Only appears during active squeezes
📈 REAL-TIME METRICS PANEL
- Current momentum value
- Direction indicator (increasing/decreasing)
- Strength assessment (strong/weak)
🔔 COMPREHENSIVE ALERTS
- Squeeze started
- Squeeze fired (bullish/bearish)
- Momentum crossovers
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🎮 HOW TO USE
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1. WAIT FOR SQUEEZE
• Red status bar appears
• Intensity dots show compression level
• Longer duration = potentially bigger move
2. WATCH FOR RELEASE
• Status changes to "FIRED - BULLISH" or "FIRED - BEARISH"
• Histogram color confirms momentum direction
• Background highlights the event
3. MANAGE POSITION
• Monitor momentum strength in metrics panel
• Exit when histogram changes color (momentum reversal)
• Use with trend/volume confirmation
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⚙️ CUSTOMIZATION
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- Toggle status bar, metrics, intensity dots independently
- Adjustable BB/KC parameters
- Custom color schemes
- Show/hide squeeze duration
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🙏 CREDITS
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Original TTM Squeeze concept: John F. Carter
Original indicator code: LazyBear (@LazyBear)
This builds on LazyBear's excellent implementation of the TTM Squeeze Momentum indicator, adding modern visual elements and real-time dashboards for improved usability.
Original indicator: "Squeeze Momentum Indicator "
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⚠️ DISCLAIMER
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This indicator is for educational purposes. Always use proper risk management and combine with other forms of analysis. No indicator guarantees profitable trades.
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Best used on: Day trading timeframes (1m-15m) for momentum plays
Combine with: Volume analysis, trend filters, support/resistance levels
Wave Conflict DetectorWave Conflict Detector
Wave Conflict Detector: Identifying Pivot Conditions Through Wave Interference Analysis
Wave Conflict Detector applies wave interference principles from physics to dual-EMA analysis, identifying potential pivot conditions by measuring phase relationships and amplitude states between two moving average waves. Unlike traditional EMA crossover systems that signal on wave intersection, this indicator measures the directional alignment (phase) and interaction strength (interference amplitude) between wave states to identify conditions where wave mechanics suggest potential reversal zones.
The indicator combines two analytical components: velocity-based phase difference calculation that measures whether waves are moving in the same or opposite directions, and normalized interference amplitude that quantifies the degree of wave reinforcement or cancellation. This creates a regime-classification system with visual feedback showing when waves are aligned (constructive state) versus opposed (destructive state).
What Makes This Approach Different
Phase Relationship Measurement
The core analytical method is extracting phase alignment from wave velocities rather than simply measuring EMA separation. The system calculates the first derivative (bar-to-bar change) of each EMA, creating velocity measurements: v₁ = ψ₁ - ψ₁ and v₂ = ψ₂ - ψ₂ . These velocities are combined through normalized correlation: Φ = (v₁ × v₂) / |v|², producing an alignment value ranging from -1 (perfect opposition) to +1 (perfect alignment).
This alignment value is smoothed using EMA and converted to angular degrees: Δφ = (1 - Φ) × 90°, creating a phase difference measurement from 0° to 180°. This quantifies how much the waves are "fighting" each other directionally, independent of their separation distance. Two EMAs can be far apart yet moving in harmony (low phase difference), or close together yet moving in opposition (high phase difference).
This directional correlation approach differs from standard dual-EMA analysis by focusing on velocity alignment rather than positional crossovers.
Interference Amplitude Calculation
The interference formula implements wave superposition principles: I = (|ψ₁ + ψ₂|² - |ψ₁ - ψ₂|²) × Gain, which mathematically simplifies to I = 4 × ψ₁ × ψ₂ × Gain. This measures the product of both waves—when both are positive and large, interference is maximally constructive; when they have opposite signs or differing magnitudes, interference weakens.
The raw interference value is then normalized using adaptive statistical bounds calculated over a rolling window (default 100 bars). The system computes mean (μ) and standard deviation (σ) of raw interference, then applies bounds of μ ± 2σ, and normalizes to a 0-1 range. This creates a scale-invariant measurement that adapts automatically to different instruments and volatility regimes without requiring manual recalibration.
The combination of phase measurement and normalized amplitude creates a two-dimensional state space for classifying market conditions.
Dual-Mode Detection Architecture
The system offers two detection approaches that can be selected based on market conditions:
Interference Mode: Detects pivot conditions when normalized interference amplitude forms local peaks or troughs (current bar is higher/lower than both adjacent bars) AND exceeds the configured threshold. This identifies extremes in wave interaction strength.
Phase Mode: Detects pivot conditions when phase alignment reverses (crosses from positive to negative or vice versa) AND absolute phase difference exceeds the threshold. This identifies directional relationship changes between waves.
Both modes require price structure confirmation (traditional pivot high/low patterns) and minimum bar spacing to prevent over-signaling. This architecture allows traders to match detection sensitivity to market character—interference mode for amplitude-driven markets, phase mode for directional trend shifts.
Multi-Layer Visual System
The visualization approach uses hierarchical layers to display wave state information:
Foundation Layer: The two EMA waves (ψ₁ and ψ₂) plotted directly on the price chart, showing the underlying wave states being analyzed.
Background Layer: Color-coded zones showing regime state—green tint when phase alignment is positive (constructive interference), red tint when phase alignment is negative below -0.3 (destructive interference).
Dynamic Ribbon: A band centered on the wave average with width proportional to |ψ₁ - ψ₂| × (0.5 + interference_norm). This creates an adaptive channel that expands with interference strength and contracts during low-energy states.
Phase Field: Multi-frequency harmonic oscillations generated using three phase accumulators driven by interference amplitude, phase alignment, and accumulated phase rotation. Multiple sine-wave layers create visual texture that becomes erratic during wave conflict conditions and smooth during aligned states.
Particle System: Floating symbols whose density is proportional to interference amplitude, creating a visual intensity indicator.
Each visual component displays non-redundant information about the wave state system.
Core Calculation Methodology
Wave State Generation
Two exponential moving averages are calculated using configurable lengths (default 8 and 21 bars):
- ψ₁ = EMA(close, fastLen) — fast wave component
- ψ₂ = EMA(close, slowLen) — slow wave component
These serve as the base wave functions for all subsequent analysis.
Velocity Extraction
First derivatives are computed as simple bar-to-bar differences:
- psi1_velocity = ψ₁ - ψ₁
- psi2_velocity = ψ₂ - ψ₂
These represent the "motion" of each wave through price-time space.
Phase Alignment Calculation
The velocity product and magnitude are calculated:
- velocity_product = v₁ × v₂
- velocity_magnitude = √(v₁² + v₂²)
Phase alignment is computed as:
- phase_alignment = velocity_product / (velocity_magnitude²)
This is smoothed using EMA of configurable length (default 5) and converted to degrees:
- phase_degrees = (1 - phase_alignment_smooth) × 90
Interference Amplitude Processing
Raw interference is calculated:
- interference_raw = (constructive_amplitude - destructive_amplitude) × gain
- where constructive_amplitude = (ψ₁ + ψ₂)²
- and destructive_amplitude = (ψ₁ - ψ₂)²
Statistical normalization is applied:
- interference_mean = SMA(interference_raw, normalizationLen)
- interference_std = StdDev(interference_raw, normalizationLen)
- upper_bound = mean + 2 × std
- lower_bound = mean - 2 × std
- interference_norm = (interference_raw - lower_bound) / (upper_bound - lower_bound), clamped to
State Classification
Three regime states are identified:
- Constructive: phase_alignment_smooth > 0 (waves moving in same direction)
- Destructive: phase_alignment_smooth < -0.3 (waves moving in opposite directions)
- Neutral: phase_alignment between -0.3 and 0 (weak directional correlation)
Pivot Detection Logic
In Interference Mode:
- High pivots: interference_norm > interference_norm AND interference_norm > interference_norm AND interference_norm > threshold AND price forms pivot high AND spacing requirement met
- Low pivots: interference_norm shows local trough using opposite conditions
In Phase Mode:
- Pivots: phase alignment reverses sign AND absolute phase_degrees > threshold AND price forms pivot high/low AND spacing requirement met
All conditions must be true for a signal to generate.
Dashboard Metrics System
The dashboard displays real-time calculations:
- I (Interference): Normalized amplitude shown as bar gauge and percentage
- Δφ (Phase): Phase difference shown as bar gauge and degrees
- ψ₁ and ψ₂: Current wave values in price units
- Wave Separation: |ψ₁ - ψ₂| with directional indicator
- STATE: Current regime classification (CONSTRUCTIVE/DESTRUCTIVE/NEUTRAL)
- PIVOT Probability: Composite score calculated as interference_norm × (phase_degrees/180) × 100
The interference matrix shows historical heatmap data across four metrics (interference amplitude, phase difference, constructive flags, destructive flags) over the configurable number of bars.
How to Use This Indicator
Initial Configuration
Apply the indicator to your chart with default settings. The fast wave length (default 8) should be adjusted to match short-term price swings for your instrument and timeframe. The slow wave length (default 21) should be 2-4 times the fast length to create adequate wave separation. Enable the dashboard (recommended position: top right) to monitor regime state and metrics in real-time.
Signal Interpretation
High Pivot Marker (▼ Red Triangle): Appears above price bars when a bearish pivot condition is detected. This indicates that price formed a swing high, the selected detection criteria were met (interference peak or phase reversal depending on mode), threshold requirements were satisfied, and the minimum spacing filter passed. This represents a potential reversal zone where wave mechanics suggest downward directional change conditions.
Low Pivot Marker (▲ Green Triangle): Appears below price bars when a bullish pivot condition is detected. This indicates that price formed a swing low and all detection criteria aligned. This represents a potential reversal zone where wave mechanics suggest upward directional change conditions.
Dashboard STATE Reading
The STATE field shows current wave relationship:
- "🟢 CONSTRUCTIVE": Waves are moving in the same direction (phase alignment positive). This suggests trend continuation conditions where waves are reinforcing each other.
- "🔴 DESTRUCTIVE": Waves are moving in opposite directions (phase alignment below -0.3). This suggests reversal-prone conditions where waves are conflicting.
- "🟡 NEUTRAL": Weak directional correlation between waves. This suggests ranging or transitional conditions.
Use STATE for regime awareness rather than specific entry signals.
Interference and Phase Metrics
Monitor the I (Interference) percentage:
- Above 70%: High amplitude state, significant wave interaction
- 40-70%: Moderate amplitude state
- Below 40%: Low amplitude state, weak interaction
Monitor the Δφ (Phase) degrees:
- Above 120°: Significant wave opposition (destructive conditions)
- 60-120°: Transitional phase relationship
- Below 60°: Wave alignment (constructive conditions)
The PIVOT probability metric combines both: high values (>70%) indicate conditions where both amplitude and phase suggest elevated pivot formation potential.
Trading Workflow Example
Step 1 - Regime Check: Observe dashboard STATE to understand current wave relationship. CONSTRUCTIVE states favor trend-following approaches, DESTRUCTIVE states suggest reversal-prone conditions.
Step 2 - Metric Monitoring: Watch I% and Δφ values. Rising interference with high phase difference indicates building wave conflict.
Step 3 - Visual Confirmation: Observe amplitude ribbon width (expanding = active state) and phase field texture (chaotic = conflict conditions, smooth = aligned conditions).
Step 4 - Signal Wait: Wait for confirmed pivot marker (▼ or ▲) rather than anticipating based on metrics alone. The marker indicates all detection criteria have aligned.
Step 5 - Entry Decision: Use pivot markers as potential reversal zones. Combine with other analysis methods such as support/resistance levels, volume confirmation, and higher timeframe bias for entry decisions.
Step 6 - Risk Management: Place stops beyond recent swing structure or ribbon edges. Monitor dashboard STATE—if it flips to CONSTRUCTIVE in trade direction, the reversal may be confirmed; if PIVOT% drops significantly, conditions may be weakening.
Step 7 - Exit Criteria: Consider exits when opposite pivot marker appears, STATE changes unfavorably, or standard technical targets are reached.
Parameter Optimization Guidelines
Fast Wave Length: Adjust to match short-term swing frequency. Shorter values (5-8) for active trading on lower timeframes, longer values (13-20) for swing trading on higher timeframes.
Slow Wave Length: Should maintain 2-4x ratio with fast length. Shorter values create more interference cycles, longer values create more stable baseline.
Phase Detection Length: Smoothing for phase alignment. Lower values (3-5) for responsive detection, higher values (8-12) for stable readings with less sensitivity.
Interference Gain: Amplification multiplier. Lower values (0.5-1.0) for conservative detection, higher values (1.5-2.5) for more sensitive detection.
Normalization Period: Rolling window for statistical bounds. Shorter periods (50-100) adapt quickly to volatility changes, longer periods (150-300) provide more stable normalization.
Interference Threshold: Minimum amplitude to trigger signals. Lower values (0.50-0.60) generate more signals, higher values (0.70-0.85) are more selective.
Phase Threshold: Minimum phase difference in degrees. Lower values (90-110) are more permissive, higher values (140-170) require stronger opposition.
Min Pivot Spacing: Bars between signals. Match to average swing duration on your timeframe—tighter spacing (3-8 bars) for scalping, wider spacing (15-30 bars) for swing trading.
Best Performance Conditions
This approach works better in markets with:
- Clear swing structure where EMA-based wave analysis is meaningful
- Sufficient volatility for wave separation to develop
- Periodic oscillation between trending and ranging states
- Liquid instruments where EMAs reflect true price flow
This approach may be less effective in:
- Extremely choppy conditions with no directional persistence
- Very low volatility environments where wave separation is minimal
- Gap-heavy instruments where price discontinuities disrupt wave continuity
- Parabolic moves where waves cannot keep pace with price velocity
The system adapts by reducing signal frequency in poor conditions—when interference stays below threshold or phase alignment remains neutral, pivot markers will not appear.
Visual Performance Optimization
The phase field and particle systems are computationally intensive. If experiencing chart lag:
- Reduce Phase Field Layers from 5 to 2-3 (significant performance improvement)
- Lower Particle Density from 3 to 1 (reduces label creation overhead)
- Disable Phase Field entirely (removes most intensive calculations)
- Decrease Matrix History Bars to 15-20 (reduces table computation load)
The core wave analysis and pivot detection continue to function with all visual elements disabled.
Important Disclaimers
This indicator is an analytical tool that measures phase relationships and interference amplitude between two exponential moving averages. It identifies conditions where these wave mechanics suggest potential pivot zones based on historical price data analysis. It should not be used as a standalone trading system.
The phase and interference calculations are deterministic mathematical formulas applied to EMA values. These measurements describe current and historical wave relationships but do not predict future price movements. Past wave patterns and pivot markers do not guarantee future market behavior will follow similar patterns.
All trading involves risk. The pivot markers represent analytical conditions where wave mechanics align with specific thresholds, not certainty of directional change. Use appropriate risk management, position sizing, and combine with additional confirmation methods such as support/resistance analysis, volume patterns, and multi-timeframe alignment. No indicator can eliminate false signals or guarantee profitable trades.
The spacing filter and threshold requirements are designed to reduce noise and over-signaling, but market conditions can change rapidly and render any analytical signal invalid. Always use stop losses and never risk capital you cannot afford to lose.
Technical Implementation Notes
All calculations execute on closed bars only—there is no repainting of signals or values. The normalization system requires approximately 100 bars of historical data to establish stable statistical bounds; values in the first 50-100 bars may be unstable as the rolling statistics converge.
Phase field arrays are fixed-size based on the complexity setting. Particle labels are capped at 80 total to prevent excessive memory usage. Dashboard and matrix tables update only on the last bar to minimize computational overhead. Particle generation is throttled to every 2 bars for performance. Phase accumulators use modulo arithmetic (% 2π) to prevent numerical overflow during extended operation.
The indicator has been tested across multiple timeframes (5-minute through daily) and multiple asset classes (forex, stocks, crypto, indices). It functions identically across all instruments due to the adaptive normalization approach.
Quantum Rotational Field MappingQuantum Rotational Field Mapping (QRFM):
Phase Coherence Detection Through Complex-Plane Oscillator Analysis
Quantum Rotational Field Mapping applies complex-plane mathematics and phase-space analysis to oscillator ensembles, identifying high-probability trend ignition points by measuring when multiple independent oscillators achieve phase coherence. Unlike traditional multi-oscillator approaches that simply stack indicators or use boolean AND/OR logic, this system converts each oscillator into a rotating phasor (vector) in the complex plane and calculates the Coherence Index (CI) —a mathematical measure of how tightly aligned the ensemble has become—then generates signals only when alignment, phase direction, and pairwise entanglement all converge.
The indicator combines three mathematical frameworks: phasor representation using analytic signal theory to extract phase and amplitude from each oscillator, coherence measurement using vector summation in the complex plane to quantify group alignment, and entanglement analysis that calculates pairwise phase agreement across all oscillator combinations. This creates a multi-dimensional confirmation system that distinguishes between random oscillator noise and genuine regime transitions.
What Makes This Original
Complex-Plane Phasor Framework
This indicator implements classical signal processing mathematics adapted for market oscillators. Each oscillator—whether RSI, MACD, Stochastic, CCI, Williams %R, MFI, ROC, or TSI—is first normalized to a common scale, then converted into a complex-plane representation using an in-phase (I) and quadrature (Q) component. The in-phase component is the oscillator value itself, while the quadrature component is calculated as the first difference (derivative proxy), creating a velocity-aware representation.
From these components, the system extracts:
Phase (φ) : Calculated as φ = atan2(Q, I), representing the oscillator's position in its cycle (mapped to -180° to +180°)
Amplitude (A) : Calculated as A = √(I² + Q²), representing the oscillator's strength or conviction
This mathematical approach is fundamentally different from simply reading oscillator values. A phasor captures both where an oscillator is in its cycle (phase angle) and how strongly it's expressing that position (amplitude). Two oscillators can have the same value but be in opposite phases of their cycles—traditional analysis would see them as identical, while QRFM sees them as 180° out of phase (contradictory).
Coherence Index Calculation
The core innovation is the Coherence Index (CI) , borrowed from physics and signal processing. When you have N oscillators, each with phase φₙ, you can represent each as a unit vector in the complex plane: e^(iφₙ) = cos(φₙ) + i·sin(φₙ).
The CI measures what happens when you sum all these vectors:
Resultant Vector : R = Σ e^(iφₙ) = Σ cos(φₙ) + i·Σ sin(φₙ)
Coherence Index : CI = |R| / N
Where |R| is the magnitude of the resultant vector and N is the number of active oscillators.
The CI ranges from 0 to 1:
CI = 1.0 : Perfect coherence—all oscillators have identical phase angles, vectors point in the same direction, creating maximum constructive interference
CI = 0.0 : Complete decoherence—oscillators are randomly distributed around the circle, vectors cancel out through destructive interference
0 < CI < 1 : Partial alignment—some clustering with some scatter
This is not a simple average or correlation. The CI captures phase synchronization across the entire ensemble simultaneously. When oscillators phase-lock (align their cycles), the CI spikes regardless of their individual values. This makes it sensitive to regime transitions that traditional indicators miss.
Dominant Phase and Direction Detection
Beyond measuring alignment strength, the system calculates the dominant phase of the ensemble—the direction the resultant vector points:
Dominant Phase : φ_dom = atan2(Σ sin(φₙ), Σ cos(φₙ))
This gives the "average direction" of all oscillator phases, mapped to -180° to +180°:
+90° to -90° (right half-plane): Bullish phase dominance
+90° to +180° or -90° to -180° (left half-plane): Bearish phase dominance
The combination of CI magnitude (coherence strength) and dominant phase angle (directional bias) creates a two-dimensional signal space. High CI alone is insufficient—you need high CI plus dominant phase pointing in a tradeable direction. This dual requirement is what separates QRFM from simple oscillator averaging.
Entanglement Matrix and Pairwise Coherence
While the CI measures global alignment, the entanglement matrix measures local pairwise relationships. For every pair of oscillators (i, j), the system calculates:
E(i,j) = |cos(φᵢ - φⱼ)|
This represents the phase agreement between oscillators i and j:
E = 1.0 : Oscillators are in-phase (0° or 360° apart)
E = 0.0 : Oscillators are in quadrature (90° apart, orthogonal)
E between 0 and 1 : Varying degrees of alignment
The system counts how many oscillator pairs exceed a user-defined entanglement threshold (e.g., 0.7). This entangled pairs count serves as a confirmation filter: signals require not just high global CI, but also a minimum number of strong pairwise agreements. This prevents false ignitions where CI is high but driven by only two oscillators while the rest remain scattered.
The entanglement matrix creates an N×N symmetric matrix that can be visualized as a web—when many cells are bright (high E values), the ensemble is highly interconnected. When cells are dark, oscillators are moving independently.
Phase-Lock Tolerance Mechanism
A complementary confirmation layer is the phase-lock detector . This calculates the maximum phase spread across all oscillators:
For all pairs (i,j), compute angular distance: Δφ = |φᵢ - φⱼ|, wrapping at 180°
Max Spread = maximum Δφ across all pairs
If max spread < user threshold (e.g., 35°), the ensemble is considered phase-locked —all oscillators are within a narrow angular band.
This differs from entanglement: entanglement measures pairwise cosine similarity (magnitude of alignment), while phase-lock measures maximum angular deviation (tightness of clustering). Both must be satisfied for the highest-conviction signals.
Multi-Layer Visual Architecture
QRFM includes six visual components that represent the same underlying mathematics from different perspectives:
Circular Orbit Plot : A polar coordinate grid showing each oscillator as a vector from origin to perimeter. Angle = phase, radius = amplitude. This is a real-time snapshot of the complex plane. When vectors converge (point in similar directions), coherence is high. When scattered randomly, coherence is low. Users can see phase alignment forming before CI numerically confirms it.
Phase-Time Heat Map : A 2D matrix with rows = oscillators and columns = time bins. Each cell is colored by the oscillator's phase at that time (using a gradient where color hue maps to angle). Horizontal color bands indicate sustained phase alignment over time. Vertical color bands show moments when all oscillators shared the same phase (ignition points). This provides historical pattern recognition.
Entanglement Web Matrix : An N×N grid showing E(i,j) for all pairs. Cells are colored by entanglement strength—bright yellow/gold for high E, dark gray for low E. This reveals which oscillators are driving coherence and which are lagging. For example, if RSI and MACD show high E but Stochastic shows low E with everything, Stochastic is the outlier.
Quantum Field Cloud : A background color overlay on the price chart. Color (green = bullish, red = bearish) is determined by dominant phase. Opacity is determined by CI—high CI creates dense, opaque cloud; low CI creates faint, nearly invisible cloud. This gives an atmospheric "feel" for regime strength without looking at numbers.
Phase Spiral : A smoothed plot of dominant phase over recent history, displayed as a curve that wraps around price. When the spiral is tight and rotating steadily, the ensemble is in coherent rotation (trending). When the spiral is loose or erratic, coherence is breaking down.
Dashboard : A table showing real-time metrics: CI (as percentage), dominant phase (in degrees with directional arrow), field strength (CI × average amplitude), entangled pairs count, phase-lock status (locked/unlocked), quantum state classification ("Ignition", "Coherent", "Collapse", "Chaos"), and collapse risk (recent CI change normalized to 0-100%).
Each component is independently toggleable, allowing users to customize their workspace. The orbit plot is the most essential—it provides intuitive, visual feedback on phase alignment that no numerical dashboard can match.
Core Components and How They Work Together
1. Oscillator Normalization Engine
The foundation is creating a common measurement scale. QRFM supports eight oscillators:
RSI : Normalized from to using overbought/oversold levels (70, 30) as anchors
MACD Histogram : Normalized by dividing by rolling standard deviation, then clamped to
Stochastic %K : Normalized from using (80, 20) anchors
CCI : Divided by 200 (typical extreme level), clamped to
Williams %R : Normalized from using (-20, -80) anchors
MFI : Normalized from using (80, 20) anchors
ROC : Divided by 10, clamped to
TSI : Divided by 50, clamped to
Each oscillator can be individually enabled/disabled. Only active oscillators contribute to phase calculations. The normalization removes scale differences—a reading of +0.8 means "strongly bullish" regardless of whether it came from RSI or TSI.
2. Analytic Signal Construction
For each active oscillator at each bar, the system constructs the analytic signal:
In-Phase (I) : The normalized oscillator value itself
Quadrature (Q) : The bar-to-bar change in the normalized value (first derivative approximation)
This creates a 2D representation: (I, Q). The phase is extracted as:
φ = atan2(Q, I) × (180 / π)
This maps the oscillator to a point on the unit circle. An oscillator at the same value but rising (positive Q) will have a different phase than one that is falling (negative Q). This velocity-awareness is critical—it distinguishes between "at resistance and stalling" versus "at resistance and breaking through."
The amplitude is extracted as:
A = √(I² + Q²)
This represents the distance from origin in the (I, Q) plane. High amplitude means the oscillator is far from neutral (strong conviction). Low amplitude means it's near zero (weak/transitional state).
3. Coherence Calculation Pipeline
For each bar (or every Nth bar if phase sample rate > 1 for performance):
Step 1 : Extract phase φₙ for each of the N active oscillators
Step 2 : Compute complex exponentials: Zₙ = e^(i·φₙ·π/180) = cos(φₙ·π/180) + i·sin(φₙ·π/180)
Step 3 : Sum the complex exponentials: R = Σ Zₙ = (Σ cos φₙ) + i·(Σ sin φₙ)
Step 4 : Calculate magnitude: |R| = √
Step 5 : Normalize by count: CI_raw = |R| / N
Step 6 : Smooth the CI: CI = SMA(CI_raw, smoothing_window)
The smoothing step (default 2 bars) removes single-bar noise spikes while preserving structural coherence changes. Users can adjust this to control reactivity versus stability.
The dominant phase is calculated as:
φ_dom = atan2(Σ sin φₙ, Σ cos φₙ) × (180 / π)
This is the angle of the resultant vector R in the complex plane.
4. Entanglement Matrix Construction
For all unique pairs of oscillators (i, j) where i < j:
Step 1 : Get phases φᵢ and φⱼ
Step 2 : Compute phase difference: Δφ = φᵢ - φⱼ (in radians)
Step 3 : Calculate entanglement: E(i,j) = |cos(Δφ)|
Step 4 : Store in symmetric matrix: matrix = matrix = E(i,j)
The matrix is then scanned: count how many E(i,j) values exceed the user-defined threshold (default 0.7). This count is the entangled pairs metric.
For visualization, the matrix is rendered as an N×N table where cell brightness maps to E(i,j) intensity.
5. Phase-Lock Detection
Step 1 : For all unique pairs (i, j), compute angular distance: Δφ = |φᵢ - φⱼ|
Step 2 : Wrap angles: if Δφ > 180°, set Δφ = 360° - Δφ
Step 3 : Find maximum: max_spread = max(Δφ) across all pairs
Step 4 : Compare to tolerance: phase_locked = (max_spread < tolerance)
If phase_locked is true, all oscillators are within the specified angular cone (e.g., 35°). This is a boolean confirmation filter.
6. Signal Generation Logic
Signals are generated through multi-layer confirmation:
Long Ignition Signal :
CI crosses above ignition threshold (e.g., 0.80)
AND dominant phase is in bullish range (-90° < φ_dom < +90°)
AND phase_locked = true
AND entangled_pairs >= minimum threshold (e.g., 4)
Short Ignition Signal :
CI crosses above ignition threshold
AND dominant phase is in bearish range (φ_dom < -90° OR φ_dom > +90°)
AND phase_locked = true
AND entangled_pairs >= minimum threshold
Collapse Signal :
CI at bar minus CI at current bar > collapse threshold (e.g., 0.55)
AND CI at bar was above 0.6 (must collapse from coherent state, not from already-low state)
These are strict conditions. A high CI alone does not generate a signal—dominant phase must align with direction, oscillators must be phase-locked, and sufficient pairwise entanglement must exist. This multi-factor gating dramatically reduces false signals compared to single-condition triggers.
Calculation Methodology
Phase 1: Oscillator Computation and Normalization
On each bar, the system calculates the raw values for all enabled oscillators using standard Pine Script functions:
RSI: ta.rsi(close, length)
MACD: ta.macd() returning histogram component
Stochastic: ta.stoch() smoothed with ta.sma()
CCI: ta.cci(close, length)
Williams %R: ta.wpr(length)
MFI: ta.mfi(hlc3, length)
ROC: ta.roc(close, length)
TSI: ta.tsi(close, short, long)
Each raw value is then passed through a normalization function:
normalize(value, overbought_level, oversold_level) = 2 × (value - oversold) / (overbought - oversold) - 1
This maps the oscillator's typical range to , where -1 represents extreme bearish, 0 represents neutral, and +1 represents extreme bullish.
For oscillators without fixed ranges (MACD, ROC, TSI), statistical normalization is used: divide by a rolling standard deviation or fixed divisor, then clamp to .
Phase 2: Phasor Extraction
For each normalized oscillator value val:
I = val (in-phase component)
Q = val - val (quadrature component, first difference)
Phase calculation:
phi_rad = atan2(Q, I)
phi_deg = phi_rad × (180 / π)
Amplitude calculation:
A = √(I² + Q²)
These values are stored in arrays: osc_phases and osc_amps for each oscillator n.
Phase 3: Complex Summation and Coherence
Initialize accumulators:
sum_cos = 0
sum_sin = 0
For each oscillator n = 0 to N-1:
phi_rad = osc_phases × (π / 180)
sum_cos += cos(phi_rad)
sum_sin += sin(phi_rad)
Resultant magnitude:
resultant_mag = √(sum_cos² + sum_sin²)
Coherence Index (raw):
CI_raw = resultant_mag / N
Smoothed CI:
CI = SMA(CI_raw, smoothing_window)
Dominant phase:
phi_dom_rad = atan2(sum_sin, sum_cos)
phi_dom_deg = phi_dom_rad × (180 / π)
Phase 4: Entanglement Matrix Population
For i = 0 to N-2:
For j = i+1 to N-1:
phi_i = osc_phases × (π / 180)
phi_j = osc_phases × (π / 180)
delta_phi = phi_i - phi_j
E = |cos(delta_phi)|
matrix_index_ij = i × N + j
matrix_index_ji = j × N + i
entangle_matrix = E
entangle_matrix = E
if E >= threshold:
entangled_pairs += 1
The matrix uses flat array storage with index mapping: index(row, col) = row × N + col.
Phase 5: Phase-Lock Check
max_spread = 0
For i = 0 to N-2:
For j = i+1 to N-1:
delta = |osc_phases - osc_phases |
if delta > 180:
delta = 360 - delta
max_spread = max(max_spread, delta)
phase_locked = (max_spread < tolerance)
Phase 6: Signal Evaluation
Ignition Long :
ignition_long = (CI crosses above threshold) AND
(phi_dom > -90 AND phi_dom < 90) AND
phase_locked AND
(entangled_pairs >= minimum)
Ignition Short :
ignition_short = (CI crosses above threshold) AND
(phi_dom < -90 OR phi_dom > 90) AND
phase_locked AND
(entangled_pairs >= minimum)
Collapse :
CI_prev = CI
collapse = (CI_prev - CI > collapse_threshold) AND (CI_prev > 0.6)
All signals are evaluated on bar close. The crossover and crossunder functions ensure signals fire only once when conditions transition from false to true.
Phase 7: Field Strength and Visualization Metrics
Average Amplitude :
avg_amp = (Σ osc_amps ) / N
Field Strength :
field_strength = CI × avg_amp
Collapse Risk (for dashboard):
collapse_risk = (CI - CI) / max(CI , 0.1)
collapse_risk_pct = clamp(collapse_risk × 100, 0, 100)
Quantum State Classification :
if (CI > threshold AND phase_locked):
state = "Ignition"
else if (CI > 0.6):
state = "Coherent"
else if (collapse):
state = "Collapse"
else:
state = "Chaos"
Phase 8: Visual Rendering
Orbit Plot : For each oscillator, convert polar (phase, amplitude) to Cartesian (x, y) for grid placement:
radius = amplitude × grid_center × 0.8
x = radius × cos(phase × π/180)
y = radius × sin(phase × π/180)
col = center + x (mapped to grid coordinates)
row = center - y
Heat Map : For each oscillator row and time column, retrieve historical phase value at lookback = (columns - col) × sample_rate, then map phase to color using a hue gradient.
Entanglement Web : Render matrix as table cell with background color opacity = E(i,j).
Field Cloud : Background color = (phi_dom > -90 AND phi_dom < 90) ? green : red, with opacity = mix(min_opacity, max_opacity, CI).
All visual components render only on the last bar (barstate.islast) to minimize computational overhead.
How to Use This Indicator
Step 1 : Apply QRFM to your chart. It works on all timeframes and asset classes, though 15-minute to 4-hour timeframes provide the best balance of responsiveness and noise reduction.
Step 2 : Enable the dashboard (default: top right) and the circular orbit plot (default: middle left). These are your primary visual feedback tools.
Step 3 : Optionally enable the heat map, entanglement web, and field cloud based on your preference. New users may find all visuals overwhelming; start with dashboard + orbit plot.
Step 4 : Observe for 50-100 bars to let the indicator establish baseline coherence patterns. Markets have different "normal" CI ranges—some instruments naturally run higher or lower coherence.
Understanding the Circular Orbit Plot
The orbit plot is a polar grid showing oscillator vectors in real-time:
Center point : Neutral (zero phase and amplitude)
Each vector : A line from center to a point on the grid
Vector angle : The oscillator's phase (0° = right/east, 90° = up/north, 180° = left/west, -90° = down/south)
Vector length : The oscillator's amplitude (short = weak signal, long = strong signal)
Vector label : First letter of oscillator name (R = RSI, M = MACD, etc.)
What to watch :
Convergence : When all vectors cluster in one quadrant or sector, CI is rising and coherence is forming. This is your pre-signal warning.
Scatter : When vectors point in random directions (360° spread), CI is low and the market is in a non-trending or transitional regime.
Rotation : When the cluster rotates smoothly around the circle, the ensemble is in coherent oscillation—typically seen during steady trends.
Sudden flips : When the cluster rapidly jumps from one side to the opposite (e.g., +90° to -90°), a phase reversal has occurred—often coinciding with trend reversals.
Example: If you see RSI, MACD, and Stochastic all pointing toward 45° (northeast) with long vectors, while CCI, TSI, and ROC point toward 40-50° as well, coherence is high and dominant phase is bullish. Expect an ignition signal if CI crosses threshold.
Reading Dashboard Metrics
The dashboard provides numerical confirmation of what the orbit plot shows visually:
CI : Displays as 0-100%. Above 70% = high coherence (strong regime), 40-70% = moderate, below 40% = low (poor conditions for trend entries).
Dom Phase : Angle in degrees with directional arrow. ⬆ = bullish bias, ⬇ = bearish bias, ⬌ = neutral.
Field Strength : CI weighted by amplitude. High values (> 0.6) indicate not just alignment but strong alignment.
Entangled Pairs : Count of oscillator pairs with E > threshold. Higher = more confirmation. If minimum is set to 4, you need at least 4 pairs entangled for signals.
Phase Lock : 🔒 YES (all oscillators within tolerance) or 🔓 NO (spread too wide).
State : Real-time classification:
🚀 IGNITION: CI just crossed threshold with phase-lock
⚡ COHERENT: CI is high and stable
💥 COLLAPSE: CI has dropped sharply
🌀 CHAOS: Low CI, scattered phases
Collapse Risk : 0-100% scale based on recent CI change. Above 50% warns of imminent breakdown.
Interpreting Signals
Long Ignition (Blue Triangle Below Price) :
Occurs when CI crosses above threshold (e.g., 0.80)
Dominant phase is in bullish range (-90° to +90°)
All oscillators are phase-locked (within tolerance)
Minimum entangled pairs requirement met
Interpretation : The oscillator ensemble has transitioned from disorder to coherent bullish alignment. This is a high-probability long entry point. The multi-layer confirmation (CI + phase direction + lock + entanglement) ensures this is not a single-oscillator whipsaw.
Short Ignition (Red Triangle Above Price) :
Same conditions as long, but dominant phase is in bearish range (< -90° or > +90°)
Interpretation : Coherent bearish alignment has formed. High-probability short entry.
Collapse (Circles Above and Below Price) :
CI has dropped by more than the collapse threshold (e.g., 0.55) over a 5-bar window
CI was previously above 0.6 (collapsing from coherent state)
Interpretation : Phase coherence has broken down. If you are in a position, this is an exit warning. If looking to enter, stand aside—regime is transitioning.
Phase-Time Heat Map Patterns
Enable the heat map and position it at bottom right. The rows represent individual oscillators, columns represent time bins (most recent on left).
Pattern: Horizontal Color Bands
If a row (e.g., RSI) shows consistent color across columns (say, green for several bins), that oscillator has maintained stable phase over time. If all rows show horizontal bands of similar color, the entire ensemble has been phase-locked for an extended period—this is a strong trending regime.
Pattern: Vertical Color Bands
If a column (single time bin) shows all cells with the same or very similar color, that moment in time had high coherence. These vertical bands often align with ignition signals or major price pivots.
Pattern: Rainbow Chaos
If cells are random colors (red, green, yellow mixed with no pattern), coherence is low. The ensemble is scattered. Avoid trading during these periods unless you have external confirmation.
Pattern: Color Transition
If you see a row transition from red to green (or vice versa) sharply, that oscillator has phase-flipped. If multiple rows do this simultaneously, a regime change is underway.
Entanglement Web Analysis
Enable the web matrix (default: opposite corner from heat map). It shows an N×N grid where N = number of active oscillators.
Bright Yellow/Gold Cells : High pairwise entanglement. For example, if the RSI-MACD cell is bright gold, those two oscillators are moving in phase. If the RSI-Stochastic cell is bright, they are entangled as well.
Dark Gray Cells : Low entanglement. Oscillators are decorrelated or in quadrature.
Diagonal : Always marked with "—" because an oscillator is always perfectly entangled with itself.
How to use :
Scan for clustering: If most cells are bright, coherence is high across the board. If only a few cells are bright, coherence is driven by a subset (e.g., RSI and MACD are aligned, but nothing else is—weak signal).
Identify laggards: If one row/column is entirely dark, that oscillator is the outlier. You may choose to disable it or monitor for when it joins the group (late confirmation).
Watch for web formation: During low-coherence periods, the matrix is mostly dark. As coherence builds, cells begin lighting up. A sudden "web" of connections forming visually precedes ignition signals.
Trading Workflow
Step 1: Monitor Coherence Level
Check the dashboard CI metric or observe the orbit plot. If CI is below 40% and vectors are scattered, conditions are poor for trend entries. Wait.
Step 2: Detect Coherence Building
When CI begins rising (say, from 30% to 50-60%) and you notice vectors on the orbit plot starting to cluster, coherence is forming. This is your alert phase—do not enter yet, but prepare.
Step 3: Confirm Phase Direction
Check the dominant phase angle and the orbit plot quadrant where clustering is occurring:
Clustering in right half (0° to ±90°): Bullish bias forming
Clustering in left half (±90° to 180°): Bearish bias forming
Verify the dashboard shows the corresponding directional arrow (⬆ or ⬇).
Step 4: Wait for Signal Confirmation
Do not enter based on rising CI alone. Wait for the full ignition signal:
CI crosses above threshold
Phase-lock indicator shows 🔒 YES
Entangled pairs count >= minimum
Directional triangle appears on chart
This ensures all layers have aligned.
Step 5: Execute Entry
Long : Blue triangle below price appears → enter long
Short : Red triangle above price appears → enter short
Step 6: Position Management
Initial Stop : Place stop loss based on your risk management rules (e.g., recent swing low/high, ATR-based buffer).
Monitoring :
Watch the field cloud density. If it remains opaque and colored in your direction, the regime is intact.
Check dashboard collapse risk. If it rises above 50%, prepare for exit.
Monitor the orbit plot. If vectors begin scattering or the cluster flips to the opposite side, coherence is breaking.
Exit Triggers :
Collapse signal fires (circles appear)
Dominant phase flips to opposite half-plane
CI drops below 40% (coherence lost)
Price hits your profit target or trailing stop
Step 7: Post-Exit Analysis
After exiting, observe whether a new ignition forms in the opposite direction (reversal) or if CI remains low (transition to range). Use this to decide whether to re-enter, reverse, or stand aside.
Best Practices
Use Price Structure as Context
QRFM identifies when coherence forms but does not specify where price will go. Combine ignition signals with support/resistance levels, trendlines, or chart patterns. For example:
Long ignition near a major support level after a pullback: high-probability bounce
Long ignition in the middle of a range with no structure: lower probability
Multi-Timeframe Confirmation
Open QRFM on two timeframes simultaneously:
Higher timeframe (e.g., 4-hour): Use CI level to determine regime bias. If 4H CI is above 60% and dominant phase is bullish, the market is in a bullish regime.
Lower timeframe (e.g., 15-minute): Execute entries on ignition signals that align with the higher timeframe bias.
This prevents counter-trend trades and increases win rate.
Distinguish Between Regime Types
High CI, stable dominant phase (State: Coherent) : Trending market. Ignitions are continuation signals; collapses are profit-taking or reversal warnings.
Low CI, erratic dominant phase (State: Chaos) : Ranging or choppy market. Avoid ignition signals or reduce position size. Wait for coherence to establish.
Moderate CI with frequent collapses : Whipsaw environment. Use wider stops or stand aside.
Adjust Parameters to Instrument and Timeframe
Crypto/Forex (high volatility) : Lower ignition threshold (0.65-0.75), lower CI smoothing (2-3), shorter oscillator lengths (7-10).
Stocks/Indices (moderate volatility) : Standard settings (threshold 0.75-0.85, smoothing 5-7, oscillator lengths 14).
Lower timeframes (5-15 min) : Reduce phase sample rate to 1-2 for responsiveness.
Higher timeframes (daily+) : Increase CI smoothing and oscillator lengths for noise reduction.
Use Entanglement Count as Conviction Filter
The minimum entangled pairs setting controls signal strictness:
Low (1-2) : More signals, lower quality (acceptable if you have other confirmation)
Medium (3-5) : Balanced (recommended for most traders)
High (6+) : Very strict, fewer signals, highest quality
Adjust based on your trade frequency preference and risk tolerance.
Monitor Oscillator Contribution
Use the entanglement web to see which oscillators are driving coherence. If certain oscillators are consistently dark (low E with all others), they may be adding noise. Consider disabling them. For example:
On low-volume instruments, MFI may be unreliable → disable MFI
On strongly trending instruments, mean-reversion oscillators (Stochastic, RSI) may lag → reduce weight or disable
Respect the Collapse Signal
Collapse events are early warnings. Price may continue in the original direction for several bars after collapse fires, but the underlying regime has weakened. Best practice:
If in profit: Take partial or full profit on collapse
If at breakeven/small loss: Exit immediately
If collapse occurs shortly after entry: Likely a false ignition; exit to avoid drawdown
Collapses do not guarantee immediate reversals—they signal uncertainty .
Combine with Volume Analysis
If your instrument has reliable volume:
Ignitions with expanding volume: Higher conviction
Ignitions with declining volume: Weaker, possibly false
Collapses with volume spikes: Strong reversal signal
Collapses with low volume: May just be consolidation
Volume is not built into QRFM (except via MFI), so add it as external confirmation.
Observe the Phase Spiral
The spiral provides a quick visual cue for rotation consistency:
Tight, smooth spiral : Ensemble is rotating coherently (trending)
Loose, erratic spiral : Phase is jumping around (ranging or transitional)
If the spiral tightens, coherence is building. If it loosens, coherence is dissolving.
Do Not Overtrade Low-Coherence Periods
When CI is persistently below 40% and the state is "Chaos," the market is not in a regime where phase analysis is predictive. During these times:
Reduce position size
Widen stops
Wait for coherence to return
QRFM's strength is regime detection. If there is no regime, the tool correctly signals "stand aside."
Use Alerts Strategically
Set alerts for:
Long Ignition
Short Ignition
Collapse
Phase Lock (optional)
Configure alerts to "Once per bar close" to avoid intrabar repainting and noise. When an alert fires, manually verify:
Orbit plot shows clustering
Dashboard confirms all conditions
Price structure supports the trade
Do not blindly trade alerts—use them as prompts for analysis.
Ideal Market Conditions
Best Performance
Instruments :
Liquid, actively traded markets (major forex pairs, large-cap stocks, major indices, top-tier crypto)
Instruments with clear cyclical oscillator behavior (avoid extremely illiquid or manipulated markets)
Timeframes :
15-minute to 4-hour: Optimal balance of noise reduction and responsiveness
1-hour to daily: Slower, higher-conviction signals; good for swing trading
5-minute: Acceptable for scalping if parameters are tightened and you accept more noise
Market Regimes :
Trending markets with periodic retracements (where oscillators cycle through phases predictably)
Breakout environments (coherence forms before/during breakout; collapse occurs at exhaustion)
Rotational markets with clear swings (oscillators phase-lock at turning points)
Volatility :
Moderate to high volatility (oscillators have room to move through their ranges)
Stable volatility regimes (sudden VIX spikes or flash crashes may create false collapses)
Challenging Conditions
Instruments :
Very low liquidity markets (erratic price action creates unstable oscillator phases)
Heavily news-driven instruments (fundamentals may override technical coherence)
Highly correlated instruments (oscillators may all reflect the same underlying factor, reducing independence)
Market Regimes :
Deep, prolonged consolidation (oscillators remain near neutral, CI is chronically low, few signals fire)
Extreme chop with no directional bias (oscillators whipsaw, coherence never establishes)
Gap-driven markets (large overnight gaps create phase discontinuities)
Timeframes :
Sub-5-minute charts: Noise dominates; oscillators flip rapidly; coherence is fleeting and unreliable
Weekly/monthly: Oscillators move extremely slowly; signals are rare; better suited for long-term positioning than active trading
Special Cases :
During major economic releases or earnings: Oscillators may lag price or become decorrelated as fundamentals overwhelm technicals. Reduce position size or stand aside.
In extremely low-volatility environments (e.g., holiday periods): Oscillators compress to neutral, CI may be artificially high due to lack of movement, but signals lack follow-through.
Adaptive Behavior
QRFM is designed to self-adapt to poor conditions:
When coherence is genuinely absent, CI remains low and signals do not fire
When only a subset of oscillators aligns, entangled pairs count stays below threshold and signals are filtered out
When phase-lock cannot be achieved (oscillators too scattered), the lock filter prevents signals
This means the indicator will naturally produce fewer (or zero) signals during unfavorable conditions, rather than generating false signals. This is a feature —it keeps you out of low-probability trades.
Parameter Optimization by Trading Style
Scalping (5-15 Minute Charts)
Goal : Maximum responsiveness, accept higher noise
Oscillator Lengths :
RSI: 7-10
MACD: 8/17/6
Stochastic: 8-10, smooth 2-3
CCI: 14-16
Others: 8-12
Coherence Settings :
CI Smoothing Window: 2-3 bars (fast reaction)
Phase Sample Rate: 1 (every bar)
Ignition Threshold: 0.65-0.75 (lower for more signals)
Collapse Threshold: 0.40-0.50 (earlier exit warnings)
Confirmation :
Phase Lock Tolerance: 40-50° (looser, easier to achieve)
Min Entangled Pairs: 2-3 (fewer oscillators required)
Visuals :
Orbit Plot + Dashboard only (reduce screen clutter for fast decisions)
Disable heavy visuals (heat map, web) for performance
Alerts :
Enable all ignition and collapse alerts
Set to "Once per bar close"
Day Trading (15-Minute to 1-Hour Charts)
Goal : Balance between responsiveness and reliability
Oscillator Lengths :
RSI: 14 (standard)
MACD: 12/26/9 (standard)
Stochastic: 14, smooth 3
CCI: 20
Others: 10-14
Coherence Settings :
CI Smoothing Window: 3-5 bars (balanced)
Phase Sample Rate: 2-3
Ignition Threshold: 0.75-0.85 (moderate selectivity)
Collapse Threshold: 0.50-0.55 (balanced exit timing)
Confirmation :
Phase Lock Tolerance: 30-40° (moderate tightness)
Min Entangled Pairs: 4-5 (reasonable confirmation)
Visuals :
Orbit Plot + Dashboard + Heat Map or Web (choose one)
Field Cloud for regime backdrop
Alerts :
Ignition and collapse alerts
Optional phase-lock alert for advance warning
Swing Trading (4-Hour to Daily Charts)
Goal : High-conviction signals, minimal noise, fewer trades
Oscillator Lengths :
RSI: 14-21
MACD: 12/26/9 or 19/39/9 (longer variant)
Stochastic: 14-21, smooth 3-5
CCI: 20-30
Others: 14-20
Coherence Settings :
CI Smoothing Window: 5-10 bars (very smooth)
Phase Sample Rate: 3-5
Ignition Threshold: 0.80-0.90 (high bar for entry)
Collapse Threshold: 0.55-0.65 (only significant breakdowns)
Confirmation :
Phase Lock Tolerance: 20-30° (tight clustering required)
Min Entangled Pairs: 5-7 (strong confirmation)
Visuals :
All modules enabled (you have time to analyze)
Heat Map for multi-bar pattern recognition
Web for deep confirmation analysis
Alerts :
Ignition and collapse
Review manually before entering (no rush)
Position/Long-Term Trading (Daily to Weekly Charts)
Goal : Rare, very high-conviction regime shifts
Oscillator Lengths :
RSI: 21-30
MACD: 19/39/9 or 26/52/12
Stochastic: 21, smooth 5
CCI: 30-50
Others: 20-30
Coherence Settings :
CI Smoothing Window: 10-14 bars
Phase Sample Rate: 5 (every 5th bar to reduce computation)
Ignition Threshold: 0.85-0.95 (only extreme alignment)
Collapse Threshold: 0.60-0.70 (major regime breaks only)
Confirmation :
Phase Lock Tolerance: 15-25° (very tight)
Min Entangled Pairs: 6+ (broad consensus required)
Visuals :
Dashboard + Orbit Plot for quick checks
Heat Map to study historical coherence patterns
Web to verify deep entanglement
Alerts :
Ignition only (collapses are less critical on long timeframes)
Manual review with fundamental analysis overlay
Performance Optimization (Low-End Systems)
If you experience lag or slow rendering:
Reduce Visual Load :
Orbit Grid Size: 8-10 (instead of 12+)
Heat Map Time Bins: 5-8 (instead of 10+)
Disable Web Matrix entirely if not needed
Disable Field Cloud and Phase Spiral
Reduce Calculation Frequency :
Phase Sample Rate: 5-10 (calculate every 5-10 bars)
Max History Depth: 100-200 (instead of 500+)
Disable Unused Oscillators :
If you only want RSI, MACD, and Stochastic, disable the other five. Fewer oscillators = smaller matrices, faster loops.
Simplify Dashboard :
Choose "Small" dashboard size
Reduce number of metrics displayed
These settings will not significantly degrade signal quality (signals are based on bar-close calculations, which remain accurate), but will improve chart responsiveness.
Important Disclaimers
This indicator is a technical analysis tool designed to identify periods of phase coherence across an ensemble of oscillators. It is not a standalone trading system and does not guarantee profitable trades. The Coherence Index, dominant phase, and entanglement metrics are mathematical calculations applied to historical price data—they measure past oscillator behavior and do not predict future price movements with certainty.
No Predictive Guarantee : High coherence indicates that oscillators are currently aligned, which historically has coincided with trending or directional price movement. However, past alignment does not guarantee future trends. Markets can remain coherent while prices consolidate, or lose coherence suddenly due to news, liquidity changes, or other factors not captured by oscillator mathematics.
Signal Confirmation is Probabilistic : The multi-layer confirmation system (CI threshold + dominant phase + phase-lock + entanglement) is designed to filter out low-probability setups. This increases the proportion of valid signals relative to false signals, but does not eliminate false signals entirely. Users should combine QRFM with additional analysis—support and resistance levels, volume confirmation, multi-timeframe alignment, and fundamental context—before executing trades.
Collapse Signals are Warnings, Not Reversals : A coherence collapse indicates that the oscillator ensemble has lost alignment. This often precedes trend exhaustion or reversals, but can also occur during healthy pullbacks or consolidations. Price may continue in the original direction after a collapse. Use collapses as risk management cues (tighten stops, take partial profits) rather than automatic reversal entries.
Market Regime Dependency : QRFM performs best in markets where oscillators exhibit cyclical, mean-reverting behavior and where trends are punctuated by retracements. In markets dominated by fundamental shocks, gap openings, or extreme low-liquidity conditions, oscillator coherence may be less reliable. During such periods, reduce position size or stand aside.
Risk Management is Essential : All trading involves risk of loss. Use appropriate stop losses, position sizing, and risk-per-trade limits. The indicator does not specify stop loss or take profit levels—these must be determined by the user based on their risk tolerance and account size. Never risk more than you can afford to lose.
Parameter Sensitivity : The indicator's behavior changes with input parameters. Aggressive settings (low thresholds, loose tolerances) produce more signals with lower average quality. Conservative settings (high thresholds, tight tolerances) produce fewer signals with higher average quality. Users should backtest and forward-test parameter sets on their specific instruments and timeframes before committing real capital.
No Repainting by Design : All signal conditions are evaluated on bar close using bar-close values. However, the visual components (orbit plot, heat map, dashboard) update in real-time during bar formation for monitoring purposes. For trade execution, rely on the confirmed signals (triangles and circles) that appear only after the bar closes.
Computational Load : QRFM performs extensive calculations, including nested loops for entanglement matrices and real-time table rendering. On lower-powered devices or when running multiple indicators simultaneously, users may experience lag. Use the performance optimization settings (reduce visual complexity, increase phase sample rate, disable unused oscillators) to improve responsiveness.
This system is most effective when used as one component within a broader trading methodology that includes sound risk management, multi-timeframe analysis, market context awareness, and disciplined execution. It is a tool for regime detection and signal confirmation, not a substitute for comprehensive trade planning.
Technical Notes
Calculation Timing : All signal logic (ignition, collapse) is evaluated using bar-close values. The barstate.isconfirmed or implicit bar-close behavior ensures signals do not repaint. Visual components (tables, plots) render on every tick for real-time feedback but do not affect signal generation.
Phase Wrapping : Phase angles are calculated in the range -180° to +180° using atan2. Angular distance calculations account for wrapping (e.g., the distance between +170° and -170° is 20°, not 340°). This ensures phase-lock detection works correctly across the ±180° boundary.
Array Management : The indicator uses fixed-size arrays for oscillator phases, amplitudes, and the entanglement matrix. The maximum number of oscillators is 8. If fewer oscillators are enabled, array sizes shrink accordingly (only active oscillators are processed).
Matrix Indexing : The entanglement matrix is stored as a flat array with size N×N, where N is the number of active oscillators. Index mapping: index(row, col) = row × N + col. Symmetric pairs (i,j) and (j,i) are stored identically.
Normalization Stability : Oscillators are normalized to using fixed reference levels (e.g., RSI overbought/oversold at 70/30). For unbounded oscillators (MACD, ROC, TSI), statistical normalization (division by rolling standard deviation) is used, with clamping to prevent extreme outliers from distorting phase calculations.
Smoothing and Lag : The CI smoothing window (SMA) introduces lag proportional to the window size. This is intentional—it filters out single-bar noise spikes in coherence. Users requiring faster reaction can reduce the smoothing window to 1-2 bars, at the cost of increased sensitivity to noise.
Complex Number Representation : Pine Script does not have native complex number types. Complex arithmetic is implemented using separate real and imaginary accumulators (sum_cos, sum_sin) and manual calculation of magnitude (sqrt(real² + imag²)) and argument (atan2(imag, real)).
Lookback Limits : The indicator respects Pine Script's maximum lookback constraints. Historical phase and amplitude values are accessed using the operator, with lookback limited to the chart's available bar history (max_bars_back=5000 declared).
Visual Rendering Performance : Tables (orbit plot, heat map, web, dashboard) are conditionally deleted and recreated on each update using table.delete() and table.new(). This prevents memory leaks but incurs redraw overhead. Rendering is restricted to barstate.islast (last bar) to minimize computational load—historical bars do not render visuals.
Alert Condition Triggers : alertcondition() functions evaluate on bar close when their boolean conditions transition from false to true. Alerts do not fire repeatedly while a condition remains true (e.g., CI stays above threshold for 10 bars fires only once on the initial cross).
Color Gradient Functions : The phaseColor() function maps phase angles to RGB hues using sine waves offset by 120° (red, green, blue channels). This creates a continuous spectrum where -180° to +180° spans the full color wheel. The amplitudeColor() function maps amplitude to grayscale intensity. The coherenceColor() function uses cos(phase) to map contribution to CI (positive = green, negative = red).
No External Data Requests : QRFM operates entirely on the chart's symbol and timeframe. It does not use request.security() or access external data sources. All calculations are self-contained, avoiding lookahead bias from higher-timeframe requests.
Deterministic Behavior : Given identical input parameters and price data, QRFM produces identical outputs. There are no random elements, probabilistic sampling, or time-of-day dependencies.
— Dskyz, Engineering precision. Trading coherence.
EV/FCFThis script in the 6 version of Pine brings you the most accurate multiple of "fundamental valuation" in my opinion. EV/FCF gives you a real metric of how profitable is the company in this exact moment and also if the company is overvaluated or undervaluated.
Luxy BIG beautiful Dynamic ORBThis is an advanced Opening Range Breakout (ORB) indicator that tracks price breakouts from the first 5, 15, 30, and 60 minutes of the trading session. It provides complete trade management including entry signals, stop-loss placement, take-profit targets, and position sizing calculations.
The ORB strategy is based on the concept that the opening range of a trading session often acts as support/resistance, and breakouts from this range tend to lead to significant moves.
What Makes This Different?
Most ORB indicators simply draw horizontal lines and leave you to figure out the rest. This indicator goes several steps further:
Multi-Stage Tracking
Instead of just one ORB timeframe, this tracks FOUR simultaneously (5min, 15min, 30min, 60min). Each stage builds on the previous one, giving you multiple trading opportunities throughout the session.
Active Trade Management
When a breakout occurs, the indicator automatically calculates and displays entry price, stop-loss, and multiple take-profit targets. These lines extend forward and update in real-time until the trade completes.
Cycle Detection
Unlike indicators that only show the first breakout, this tracks the complete cycle: Breakout → Retest → Re-breakout. You can see when price returns to test the ORB level after breaking out (potential re-entry).
Failed Breakout Warning
If price breaks out but quickly returns inside the range (within a few bars), the label changes to "FAILED BREAK" - warning you to exit or avoid the trade.
Position Sizing Calculator
Built-in risk management that tells you exactly how many shares to buy based on your account size and risk tolerance. No more guessing or manual calculations.
Advanced Filtering
Optional filters for volume confirmation, trend alignment, and Fair Value Gaps (FVG) to reduce false signals and improve win rate.
Core Features Explained
### 1. Multi-Stage ORB Levels
The indicator builds four separate Opening Range levels:
ORB 5 - First 5 minutes (fastest signals, most volatile)
ORB 15 - First 15 minutes (balanced, most popular)
ORB 30 - First 30 minutes (slower, more reliable)
ORB 60 - First 60 minutes (slowest, most confirmed)
Each level is drawn as a horizontal range on your chart. As time progresses, the ranges expand to include more price action. You can enable or disable any stage and assign custom colors to each.
How it works: During the opening minutes, the indicator tracks the highest high and lowest low. Once the time period completes, those levels become your ORB high and low for that stage.
### 2. Breakout Detection
When price closes outside the ORB range, a label appears:
BREAK UP (green label above price) - Price closed above ORB High
BREAK DOWN (red label below price) - Price closed below ORB Low
The label shows which ORB stage triggered (ORB5, ORB15, etc.) and the cycle number if tracking multiple breakouts.
Important: Signals appear on bar close only - no repainting. What you see is what you get.
### 3. Retest Detection
After price breaks out and moves away, if it returns to test the ORB level, a "RETEST" label appears (orange). This indicates:
The original breakout level is now acting as support/resistance
Potential re-entry opportunity if you missed the first breakout
Confirmation that the level is significant
The indicator requires price to move a minimum distance away before considering it a valid retest (configurable in settings).
### 4. Failed Breakout Detection
If price breaks out but returns inside the ORB range within a few bars (before the breakout is "committed"), the original label changes to "FAILED BREAK" in orange.
This warns you:
The breakout lacked conviction
Consider exiting if already in the trade
Wait for better setup
Committed Breakout: The indicator tracks how many bars price stays outside the range. Only after staying outside for the minimum number of bars does it become a committed breakout that can be retested.
### 5. TP/SL Lines (Trade Management)
When a breakout occurs, colored horizontal lines appear showing:
Entry Line (cyan for long, orange for short) - Your entry price (the ORB level)
Stop Loss Line (red) - Where to exit if trade goes against you
TP1, TP2, TP3 Lines (same color as entry) - Profit targets at 1R, 2R, 3R
These lines extend forward as new bars form, making it easy to track your trade. When a target is hit, the line turns green and the label shows a checkmark.
Lines freeze (stop updating) when:
Stop loss is hit
The final enabled take-profit is hit
End of trading session (optional setting)
### 6. Position Sizing Dashboard
The dashboard (bottom-left corner by default) shows real-time information:
Current ORB stage and range size
Breakout status (Inside Range / Break Up / Break Down)
Volume confirmation (if filter enabled)
Trend alignment (if filter enabled)
Entry and Stop Loss prices
All enabled Take Profit levels with percentages
Risk/Reward ratio
Position sizing: Max shares to buy and total risk amount
Position Sizing Example:
If your account is $25,000 and you risk 1% per trade ($250), and the distance from entry to stop loss is $0.50, the calculator shows you can buy 500 shares (250 / 0.50 = 500).
### 7. FVG Filter (Fair Value Gap)
Fair Value Gaps are price inefficiencies - gaps left by strong momentum where one candle's high doesn't overlap with a previous candle's low (or vice versa).
When enabled, this filter:
Detects bullish and bearish FVGs
Draws semi-transparent boxes around these gaps
Only allows breakout signals if there's an FVG near the breakout level
Why this helps: FVGs indicate institutional activity. Breakouts through FVGs tend to be stronger and more reliable.
Proximity setting: Controls how close the FVG must be to the ORB level. 2.0x means the breakout can be within 2 times the FVG size - a reasonable default.
### 8. Volume & Trend Filters
Volume Filter:
Requires current volume to be above average (customizable multiplier). High volume breakouts are more likely to sustain.
Set minimum multiplier (e.g., 1.5x = 50% above average)
Set "strong volume" multiplier (e.g., 2.5x) that bypasses other filters
Dashboard shows current volume ratio
Trend Filter:
Only shows breakouts aligned with a higher timeframe trend. Choose from:
VWAP - Price above/below volume-weighted average
EMA - Price above/below exponential moving average
SuperTrend - ATR-based trend indicator
Combined modes (VWAP+EMA, VWAP+SuperTrend) for stricter filtering
### 9. Pullback Filter (Advanced)
Purpose:
Waits for price to pull back slightly after initial breakout before confirming the signal.
This reduces false breakouts from immediate reversals.
How it works:
- After breakout is detected, indicator waits for a small pullback (default 2%)
- Once pullback occurs AND price breaks out again, signal is confirmed
- If no pullback within timeout period (5 bars), signal is issued anyway
Settings:
Enable Pullback Filter: Turn this filter on/off
Pullback %: How much price must pull back (2% is balanced)
Timeout (bars): Max bars to wait for pullback (5 is standard)
When to use:
- Choppy markets with many fake breakouts
- When you want higher quality signals
- Combine with Volume filter for maximum confirmation
Trade-off:
- Better signal quality
- May miss some valid fast moves
- Slight entry delay
How to Use This Indicator
### For Beginners - Simple Setup
Add the indicator to your chart (5-minute or 15-minute timeframe recommended)
Leave all default settings - they work well for most stocks
Watch for BREAK UP or BREAK DOWN labels to appear
Check the dashboard for entry, stop loss, and targets
Use the position sizing to determine how many shares to buy
Basic Trading Plan:
Wait for a clear breakout label
Enter at the ORB level (or next candle open if you're late)
Place stop loss where the red line indicates
Take profit at TP1 (50% of position) and TP2 (remaining 50%)
### For Advanced Traders - Customized Setup
Choose which ORB stages to track (you might only want ORB15 and ORB30)
Enable filters: Volume (stocks) or Trend (trending markets)
Enable FVG filter for institutional confirmation
Set "Track Cycles" mode to catch retests and re-breakouts
Customize stop loss method (ATR for volatile stocks, ORB% for stable ones)
Adjust risk per trade and account size for accurate position sizing
Advanced Strategy Example:
Enable ORB15 only (disable others for cleaner chart)
Turn on Volume filter at 1.5x with Strong at 2.5x
Enable Trend filter using VWAP
Set Signal Mode to "Track Cycles" with Max 3 cycles
Wait for aligned breakouts (Volume + Trend + Direction)
Enter on retest if you missed the initial break
### Timeframe Recommendations
5-minute chart: Scalping, very active trading, crypto
15-minute chart: Day trading, balanced approach (most popular)
30-minute chart: Swing entries, less screen time
60-minute chart: Position trading, longer holds
The indicator works on any intraday timeframe, but ORB is fundamentally a day trading strategy. Daily charts don't make sense for ORB.
DEFAULT CONFIGURATION
ON by Default:
• All 4 ORB stages (5/15/30/60)
• Breakout Detection
• Retest Labels
• All TP levels (1/1.5/2/3)
• TP/SL Lines (Detailed mode)
• Dashboard (Bottom Left, Dark theme)
• Position Size Calculator
OFF by Default (Optional Filters):
• FVG Filter
• Pullback Filter
• Volume Filter
• Trend Filter
• HTF Bias Check
• Alerts
Recommended for Beginners:
• Leave all defaults
• Session Mode: Auto-Detect
• Signal Mode: Track Cycles
• Stop Method: ATR
• Add Volume Filter if trading stocks
Recommended for Advanced:
• Enable ORB15 + ORB30 only (disable 5 & 60)
• Enable: Volume + Trend + FVG
• Signal Mode: Track Cycles, Max 3
• Stop Method: ATR or Safer
• Enable HTF Daily bias check
## Settings Guide
The settings are organized into logical groups. Here's what each section controls:
### ORB COLORS Section
Show Edge Labels: Display "ORB 5", "ORB 15" labels at the right edge of the levels
Background: Fill the area between ORB high/low with color
Transparency: How see-through the background is (95% is nearly invisible)
Enable ORB 5/15/30/60: Turn each stage on or off individually
Colors: Assign colors to each ORB stage for easy identification
### SESSION SETTINGS Section
Session Mode: Choose trading session (Auto-Detect works for most instruments)
Custom Session Hours: Define your own hours if needed (format: HHMM-HHMM)
Auto-Detect uses the instrument's natural hours (stocks use exchange hours, crypto uses 24/7).
### BREAKOUT DETECTION Section
Enable Breakout Detection: Master switch for signals
Show Retest Labels: Display retest signals
Label Size: Visual size for all labels (Small recommended)
Enable FVG Filter: Require Fair Value Gap confirmation
Show FVG Boxes: Display the gap boxes on chart
Signal Mode: "First Only" = one signal per direction per day, "Track Cycles" = multiple signals
Max Cycles: How many breakout-retest cycles to track (6 is balanced)
Breakout Buffer: Extra distance required beyond ORB level (0.1-0.2% recommended)
Min Distance for Retest: How far price must move away before retest is valid (2% recommended)
Min Bars Outside ORB: Bars price must stay outside for committed breakout (2 is balanced)
### TARGETS & RISK Section
Enable Targets & Stop-Loss: Calculate and show trade management
TP1/TP2/TP3 checkboxes: Select which profit targets to display
Stop Method: How to calculate stop loss placement
- ATR: Based on volatility (best for most cases)
- ORB %: Fixed % of ORB range
- Swing: Recent swing high/low
- Safer: Widest of all methods
ATR Length & Multiplier: Controls ATR stop distance (14 period, 1.5x is standard)
ORB Stop %: Percentage beyond ORB for stop (20% is balanced)
Swing Bars: Lookback period for swing high/low (3 is recent)
### TP/SL LINES Section
Show TP/SL Lines: Display horizontal lines on chart
Label Format: "Short" = minimal text, "Detailed" = shows prices
Freeze Lines at EOD: Stop extending lines at session close
### DASHBOARD Section
Show Info Panel: Display the metrics dashboard
Theme: Dark or Light colors
Position: Where to place dashboard on chart
Toggle rows: Show/hide specific information rows
Calculate Position Size: Enable the position sizing calculator
Risk Mode: Risk fixed $ amount or % of account
Account Size: Your total trading capital
Risk %: Percentage to risk per trade (0.5-1% recommended)
### VOLUME FILTER Section
Enable Volume Filter: Require volume confirmation
MA Length: Average period (20 is standard)
Min Volume: Required multiplier (1.5x = 50% above average)
Strong Volume: Multiplier that bypasses other filters (2.5x)
### TREND FILTER Section
Enable Trend Filter: Require trend alignment
Trend Mode: Method to determine trend (VWAP is simple and effective)
Custom EMA Length: If using EMA mode (50 for swing, 20 for day trading)
SuperTrend settings: Period and Multiplier if using SuperTrend mode
### HIGHER TIMEFRAME Section
Check Daily Trend: Display higher timeframe bias in dashboard
Timeframe: What TF to check (D = daily, recommended)
Method: Price vs MA (stable) or Candle Direction (reactive)
MA Period: EMA length for Price vs MA method (20 is balanced)
Min Strength %: Minimum strength threshold for HTF bias to be considered
- For "Price vs MA": Minimum distance (%) from moving average
- For "Candle Direction": Minimum candle body size (%)
- 0.5% is balanced - increase for stricter filtering
- Lower values = more signals, higher values = only strong trends
### ALERTS Section
Enable Alerts: Master switch (must be ON to use any alerts)
Breakout Alerts: Notify on ORB breakouts
Retest Alerts: Notify when price retests after breakout
Failed Break Alerts: Notify on failed breakouts
Stage Complete Alerts: Notify when each ORB stage finishes forming
After enabling desired alert types, click "Create Alert" button, select this indicator, choose "Any alert() function call".
## Tips & Best Practices
### General Trading Tips
ORB works best on liquid instruments (stocks with good volume, major crypto pairs)
First hour of the session is most important - that's when ORB is forming
Breakouts WITH the trend have higher success rates - use the trend filter
Failed breakouts are common - use the "Min Bars Outside" setting to filter weak moves
Not every day produces good ORB setups - be patient and selective
### Position Sizing Best Practices
Never risk more than 1-2% of your account on a single trade
Use the built-in calculator - don't guess your position size
Update your account size monthly as it grows
Smaller accounts: use $ Amount mode for simplicity
Larger accounts: use % of Account mode for scaling
### Take Profit Strategy
Most traders use: 50% at TP1, 50% at TP2
Aggressive: Hold through TP1 for TP2 or TP3
Conservative: Full exit at TP1 (1:1 risk/reward)
After TP1 hits, consider moving stop to breakeven
TP3 rarely hits - only on strong trending days
### Filter Combinations
Maximum Quality: Volume + Trend + FVG (fewest signals, highest quality)
Balanced: Volume + Trend (good quality, reasonable frequency)
Active Trading: No filters or Volume only (many signals, lower quality)
Trending Markets: Trend filter essential (indices, crypto)
Range-Bound: Volume + FVG (avoid trend filter)
### Common Mistakes to Avoid
Chasing breakouts - wait for the bar to close, don't FOMO into wicks
Ignoring the stop loss - always use it, move it manually if needed
Over-leveraging - the calculator shows MAX shares, you can buy less
Trading every signal - quality > quantity, use filters
Not tracking results - keep a journal to see what works for YOU
## Pros and Cons
### Advantages
Complete all-in-one solution - from signal to position sizing
Multiple timeframes tracked simultaneously
Visual clarity - easy to see what's happening
Cycle tracking catches opportunities others miss
Built-in risk management eliminates guesswork
Customizable filters for different trading styles
No repainting - what you see is locked in
Works across multiple markets (stocks, forex, crypto)
### Limitations
Intraday strategy only - doesn't work on daily charts
Requires active monitoring during first 1-2 hours of session
Not suitable for after-hours or extended sessions by default
Can produce many signals in choppy markets (use filters)
Dashboard can be overwhelming for complete beginners
Performance depends on market conditions (trends vs ranges)
Requires understanding of risk management concepts
### Best For
Day traders who can watch the first 1-2 hours of market open
Traders who want systematic entry/exit rules
Those learning proper position sizing and risk management
Active traders comfortable with multiple signals per day
Anyone trading liquid instruments with clear sessions
### Not Ideal For
Swing traders holding multi-day positions
Set-and-forget / passive investors
Traders who can't watch market open
Complete beginners unfamiliar with trading concepts
Low volume / illiquid instruments
## Frequently Asked Questions
Q: Why are no signals appearing?
A: Check that you're on an intraday timeframe (5min, 15min, etc.) and that the current time is within your session hours. Also verify that "Enable Breakout Detection" is ON and at least one ORB stage is enabled. If using filters, they might be blocking signals - try disabling them temporarily.
Q: What's the best ORB stage to use?
A: ORB15 (15 minutes) is most popular and balanced. ORB5 gives faster signals but more noise. ORB30 and ORB60 are slower but more reliable. Many traders use ORB15 + ORB30 together.
Q: Should I enable all the filters?
A: Start with no filters to see all signals. If too many false signals, add Volume filter first (stocks) or Trend filter (trending markets). FVG filter is most restrictive - use for maximum quality but fewer signals.
Q: How do I know which stop loss method to use?
A: ATR works for most cases - it adapts to volatility. Use ORB% if you want predictable stop placement. Swing is for respecting chart structure. Safer gives you the most room but largest risk.
Q: Can I use this for swing trading?
A: Not really - ORB is fundamentally an intraday strategy. The ranges reset each day. For swing trading, look at weekly support/resistance or moving averages instead.
Q: Why do TP/SL lines disappear sometimes?
A: Lines freeze (stop extending) when: stop loss is hit, the last enabled take-profit is hit, or end of session arrives (if "Freeze at EOD" is enabled). This is intentional - the trade is complete.
Q: What's the difference between "First Only" and "Track Cycles"?
A: "First Only" shows one breakout UP and one DOWN per day maximum - clean but might miss opportunities. "Track Cycles" shows breakout-retest-rebreak sequences - more signals but busier chart.
Q: Is position sizing accurate for options/forex?
A: The calculator is designed for shares (stocks). For options, ignore the share count and use the risk amount. For forex, you'll need to adapt the lot size calculation manually.
Q: How much capital do I need to use this?
A: The indicator works for any account size, but practical day trading typically requires $25,000 in the US due to Pattern Day Trader rules. Adjust the "Account Size" setting to match your capital.
Q: Can I backtest this strategy?
A: This is an indicator, not a strategy script, so it doesn't have built-in backtesting. You can visually review historical signals or code a strategy script using similar logic.
Q: Why does the dashboard show different entry price than the breakout label?
A: If you're looking at an old breakout, the ORB levels may have changed when the next stage completed. The dashboard always shows the CURRENT active range and trade setup.
Q: What's a good win rate to expect?
A: ORB strategies typically see 40-60% win rate depending on market conditions and filters used. The strategy relies on positive risk/reward ratios (2:1 or better) to be profitable even with moderate win rates.
Q: Does this work on crypto?
A: Yes, but crypto trades 24/7 so you need to define what "session start" means. Use Session Mode = Custom and set your preferred daily reset time (e.g., 0000-2359 UTC).
## Credits & Transparency
### Development
This indicator was developed with the assistance of AI technology to implement complex ORB trading logic.
The strategy concept, feature specifications, and trading logic were designed by the publisher. The implementation leverages modern development tools to ensure:
Clean, efficient, and maintainable code
Comprehensive error handling and input validation
Detailed documentation and user guidance
Performance optimization
### Trading Concepts
This indicator implements several public domain trading concepts:
Opening Range Breakout (ORB): Trading strategy popularized by Toby Crabel, Mark Fisher and many more talanted traders.
Fair Value Gap (FVG): Price imbalance concept from ICT methodology
SuperTrend: ATR-based trend indicator using public formula
Risk/Reward Ratio: Standard risk management principle
All mathematical formulas and technical concepts used are in the public domain.
### Pine Script
Uses standard TradingView built-in functions:
ta.ema(), ta.atr(), ta.vwap(), ta.highest(), ta.lowest(), request.security()
No external libraries or proprietary code from other authors.
## Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice.
Trading involves substantial risk of loss and is not suitable for every investor. Past performance shown in examples is not indicative of future results.
The indicator provides signals and calculations, but trading decisions are solely your responsibility. Always:
Test strategies on paper before using real money
Never risk more than you can afford to lose
Understand that all trading involves risk
Consider seeking advice from a licensed financial advisor
The publisher makes no guarantees regarding accuracy, profitability, or performance. Use at your own risk.
---
Version: 3.0
Pine Script Version: v6
Last Updated: October 2024
For support, questions, or suggestions, please comment below or send a private message.
---
Happy trading, and remember: consistent risk management beats perfect entry timing every time.
Adaptive Trend SelectorThe Adaptive Trend Selector is a comprehensive trend-following tool designed to automatically identify the optimal moving average crossover strategy. It features adjustable parameters and an integrated backtester that delivers institutional-grade insights into the recommended strategy. The model continuously adapts to new data in real time by evaluating multiple moving average combinations, determining the best performing lengths, and presenting the backtest results in a clear, color-coded table that benchmarks performance against the buy-and-hold strategy.
At its core, the model systematically backtests a wide range of moving average combinations to identify the configuration that maximizes the selected optimization metric. Users can choose to optimize for absolute returns or risk-adjusted returns using the Sharpe, Sortino, or Calmar ratios. Alternatively, users can enable manual optimization to test custom fast and slow moving average lengths and view the corresponding backtest results. The label displays the Compounded Annual Growth Rate (CAGR) of the strategy, with the buy-and-hold CAGR in parentheses for comparison. The table presents the backtest results based on the fast and slow lengths displayed at the top:
Sharpe = CAGR per unit of standard deviation.
Sortino = CAGR per unit of downside deviation.
Calmar = CAGR relative to maximum drawdown.
Max DD = Largest peak-to-trough decline in value.
Beta (β) = Return sensitivity relative to buy-and-hold.
Alpha (α) = Excess annualized risk-adjusted returns.
Win Rate = Ratio of profitable trades to total trades.
Profit Factor = Total gross profit per unit of losses.
Expectancy = Average expected return per trade.
Trades/Year = Average number of trades per year.
This indicator is designed with flexibility in mind, enabling users to specify the start date of the backtesting period and the preferred moving average strategy. Supported strategies include the Exponential Moving Average (EMA), Simple Moving Average (SMA), Wilder’s Moving Average (RMA), Weighted Moving Average (WMA), and Volume-Weighted Moving Average (VWMA). To minimize overfitting, users can define constraints such as a minimum and maximum number of trades per year, as well as an optional optimization margin that prioritizes longer, more robust combinations by requiring shorter-length strategies to exceed this threshold. The table follows an intuitive color logic that enables quick performance comparison against buy-and-hold (B&H):
Sharpe = Green indicates better than B&H, while red indicates worse.
Sortino = Green indicates better than B&H, while red indicates worse.
Calmar = Green indicates better than B&H, while red indicates worse.
Max DD = Green indicates better than B&H, while red indicates worse.
Beta (β) = Green indicates better than B&H, while red indicates worse.
Alpha (α) = Green indicates above 0%, while red indicates below 0%.
Win Rate = Green indicates above 50%, while red indicates below 50%.
Profit Factor = Green indicates above 2, while red indicates below 1.
Expectancy = Green indicates above 0%, while red indicates below 0%.
In summary, the Adaptive Trend Selector is a powerful tool designed to help investors make data-driven decisions when selecting moving average crossover strategies. By optimizing for risk-adjusted returns, investors can confidently identify the best lengths using institutional-grade metrics. While results are based on the selected historical period, users should be mindful of potential overfitting, as past results may not persist under future market conditions. Since the model recalibrates to incorporate new data, the recommended lengths may evolve over time.
Multi-Timeframe Granville Signal──────────────────────────────────────────
OVERVIEW
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MTF Granville Signal is an invite-only Pine Script indicator that assists traders in identifying high-probability entry points based on Granville's Law principles, enhanced with Multi-Timeframe (MTF) structural analysis and dynamic Moving Average Deviation Rate (MADR) filtering.
This indicator is NOT investment advice. It is a technical analysis tool. All trading decisions and outcomes are the sole responsibility of the user.
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WHAT MAKES THIS INDICATOR ORIGINAL
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While many indicators implement basic Granville's Law or simple moving average crosses, this indicator distinguishes itself through two mathematically rigorous enhancements:
1. Dynamic MADR Filtering with Statistical Foundation
Unlike fixed percentage bands used in conventional overbought/oversold indicators, this system employs adaptive threshold calculation based on rolling standard deviation :
Mathematical Approach:
Calculates price deviation from the reference Simple Moving Average(SMA) as a percentage
Computes standard deviation (σ) over an extended lookback period
Default: 1σ threshold = 68.26% probability zone under normal distribution
User-configurable sigma multiplier (1σ, 2σ, 3σ)
Operational Logic:
Trend-following signals (Granville Rules 1, 2, 3, 5, 6, 7) : Fire only when MADR is within normal range (< threshold), indicating healthy trend conditions
Counter-trend signals (Granville Rules 4, 8) : Fire only when MADR exceeds threshold, indicating statistical over-extension and mean-reversion probability
Why This Matters:
Traditional indicators use arbitrary fixed thresholds (e.g., "overbought above +3%"). Market volatility varies dramatically across assets and time periods. A 3% deviation in EUR/USD may be extreme, while in Bitcoin it's noise. Dynamic MADR automatically adapts to each market's volatility characteristics, maintaining consistent statistical validity across diverse trading instruments.
2. MTF Structural Verification for Cycle-Phase Filtering
This is not merely displaying multiple timeframe SMAs on a chart. The indicator performs structural analysis to determine trend cycle phase :
Verification Mechanism:
Checks if price has recently touched/crossed the higher timeframe SMA within a configurable lookback period
Confirms SMA hierarchy alignment (short-term > mid-term > long-term for uptrends)
Distinguishes between early-cycle trend initiation and late-cycle exhaustion
Why This Matters:
Granville's Law signals can appear throughout a trend cycle, but probability varies significantly:
Early cycle (price recently interacted with higher TF SMA): High probability - catching trend initiation or deep retracements
Late cycle (price extended far from higher TF SMA): Low probability - entering during exhaustion phase
By requiring recent structural interaction with higher timeframe SMAs, the indicator filters out low-probability late-cycle entries, dramatically improving signal quality.
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GRANVILLE'S LAW IMPLEMENTATION
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This indicator implements all eight of Joseph Granville's classic rules, with a focus on Rules 1, 2, 3,4, 5, 6, 7, and 8 for primary signal generation. Rules 3 and 7 are operationalized through touch-based approximation (see explanation below):
Trend-Following Signals (Rules 1, 2, 3, 5, 6, 7)
Buy Signals:
Short-term SMA crosses above (or touches and bounces off) mid/long-term SMAs
SMA hierarchy confirms uptrend structure
MADR indicates price is NOT over-extended
Price recently interacted with higher timeframe SMA (MTF verification)
Sell Signals:
Mirror logic for downtrends
Counter-Trend Mean-Reversion Signals (Rules 4, 8)
Sell Signals:
Price shows extreme deviation from reference SMA (MADR exceeds threshold)
Price begins reverting toward SMA
Short-term SMA crosses below (or touches and bounces off) mid/long-term SMAs
Recent structural interaction with higher timeframe SMA confirms reversal setup
Buy Signals:
Mirror logic for oversold reversals
How Rules 3 and 7 Are Handled:
Rules 3 and 7 describe "price approaches the SMA." Rather than excluding these rules, this indicator approximates "approaches" as "touches the SMA" to eliminate ambiguity. In practice, defining "approaches" is subjective and adds complexity. By operationalizing "approaches" as "touches/crosses," the indicator maintains mechanical objectivity while still capturing the intent of Rules 3 and 7.
──────────────────────────────────────────
WHY GRANVILLE'S LAW?
──────────────────────────────────────────
Universality: Functions across all markets (forex, stocks, crypto, commodities) and timeframes
Simplicity: Based solely on price-to-moving-average relationships—no complex calculations
Reproducibility: Mechanical rules eliminate emotional bias
60+ Year Track Record: Proven principle since Joseph Granville's 1960 publication
──────────────────────────────────────────
TECHNICAL ARCHITECTURE
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Signal Generation Process
Calculate SMAs across multiple timeframes (short/mid/long-term periods)
Compute MADR : Measure price deviation from reference SMA and its statistical significance
Verify MTF Structure : Check recent price interaction with higher timeframe SMA
Evaluate SMA Hierarchy : Confirm trend direction via SMA alignment
Apply Granville Logic : Detect specific Rule patterns (crosses, touches, bounces)
Determining deviation from SMA :
• Trend-following: MADR < threshold (healthy trend)
• Counter-trend: MADR > threshold (over-extension)
Signal Interval Control : Cooldown period prevents alert spam during noise
Why This Combination Works
The synthesis of these three components creates a robust filtering system:
Granville's Law provides the fundamental signal logic (proven over decades)
Dynamic MADR prevents entries at dangerous price extremes (volatility-adaptive risk management)
MTF Structural Verification ensures signals occur at optimal cycle phases (timing optimization)
No single element alone produces high-quality signals. Their integration may generate edge in trending market conditions.
──────────────────────────────────────────
WHAT THIS INDICATOR DOES NOT DO
──────────────────────────────────────────
To set realistic expectations:
❌ Does not predict future price direction with certainty
❌ Does not guarantee profitable trades
❌ Does not work equally well in all market conditions (see below for limitations)
❌ Does not replace risk management, position sizing, or trading discipline
❌ Does not provide trade exit signals (focus is on entry timing)
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PARAMETER CONFIGURATION
──────────────────────────────────────────
Mid Term Trend Check Enabled (Default: true)
Activates SMA hierarchy verification for mid-term trend confirmation.
When enabled: Signals require short-term SMA > mid-term SMA (uptrend) or vice versa (downtrend)
When disabled: Only short-term SMA behavior is evaluated
Recommendation : Keep enabled for most use cases to filter weak trends
Long Term Trend Check Enabled (Default: true)
Adds long-term SMA to hierarchy verification for additional trend strength confirmation.
Requires Mid Term Trend Check to be enabled
When enabled: Signals require short-term SMA > mid-term SMA > long-term SMA alignment
Recommendation : Enable on lower timeframes (15m or below) for stronger filtering. Disable on higher timeframes (1h or above) as the additional filter becomes redundant and overly restrictive
Require Touch Higher Timeframe SMA Enabled (Default: true)
Enforces recent price interaction with higher timeframe SMA to filter late-cycle entries.
When enabled: Signals fire only if price touched/crossed mid-term or long-term SMA within lookback period
When disabled: Signals can fire regardless of recent SMA interaction (more signals, lower quality)
Recommendation : Keep enabled. This is a core filter for cycle-phase discrimination
Touch Higher Timeframe SMA Lookback Period (Default: 24 bars)
Defines how far back to search for price-SMA interaction.
Lower values (12-18): Stricter filtering, fewer signals, earlier cycle detection
Higher values (24-36): More lenient filtering, more signals, includes some mid-cycle entries
Recommendation : Adjust based on market volatility. Trending markets: use lower values. Choppy markets: use higher values to capture valid retracements
SMA Short Term Period (Default: 20)
Primary SMA for Granville's Law pattern detection.
Lower values (10-15): More responsive, more signals, higher noise
Higher values (25-40): Smoother, fewer signals, delayed entries
Recommendation : 20 is standard across most markets. Adjust ±5 based on your timeframe preference
SMA Mid Term Period (Default: 80)
Reference SMA for trend hierarchy and MTF verification.
Typically 3-5x the short-term period
Recommendation : 80 works well for intraday (15m, 1h) and swing trading (4h, daily). Maintain ratio relationship with short-term SMA
SMA Long Term Period (Default: 320)
Optional trend strength filter (requires Long Term Trend Check enabled).
Typically 4x the mid-term period
Recommendation : 320 is appropriate for multi-day trend analysis. Not critical for intraday scalping
SMA Period for Divergence (Default: 1920)
Lookback period for calculating MADR standard deviation. Two approaches:
Approach 1: Chart Timeframe SMA (Simple)
Use 20 periods matching your chart timeframe for straightforward deviation measurement.
Example: 20 periods on any timeframe
Approach 2: Higher Timeframe SMA (MTF Analysis)
Use period equivalent to higher timeframe's 20-period SMA for multi-timeframe structural analysis.
Recommendation for day trading :
• 15m chart: 1920 periods (≈ daily 20-SMA: 20 days × 96 bars/day)
• 1h chart: 480 periods (≈ daily 20-SMA: 20 days × 24 bars/day)
• 4h chart: 120 periods (≈ daily 20-SMA: 20 days × 6 bars/day)
Both approaches are valid. Approach 2 incorporates higher timeframe context into MADR filtering.
MADR Standard Deviation Band (Sigma) (Default: 1.00)
Statistical threshold for determining trend overheating vs. healthy conditions.
1.0σ = 68.26% probability zone (default, balanced)
2.0σ = 95.44% probability zone (stricter, fewer counter-trend signals)
3.0σ = 99.74% probability zone (very strict, rare extreme reversals only)
Recommendation : Start with 1.0σ. Increase to 2.0σ if you want to trade only extreme mean-reversion opportunities. Decrease to 0.5σ-0.8σ for more aggressive trend-following
Signal Minimum Interval (Default: 4 hours)
Cooldown period between signals to prevent alert spam during consolidation.
Measured in hours regardless of chart timeframe
0 = no cooldown (all valid signals fire)
2-4 = typical for day trading
8-12 = typical for swing trading
Recommendation : Match to your trading frequency. Day traders: 2-4 hours. Swing traders: 8-12 hours
Buy/Sell Signal Text Color (Default: Blue)
Reversal Buy/Sell Signal Text Color (Default: Purple)
Customize label colors for visual distinction between trend-following and counter-trend signals.
Alert Display Prefix (Default: Auto-detected from chart timeframe)
Prefix for alert messages (e.g., "1h", "15m"). Auto-filled if left blank.
──────────────────────────────────────────
RECOMMENDED CONFIGURATIONS
──────────────────────────────────────────
Configuration 1: Aggressive Day Trading (15m Chart)
SMA Short: 20
SMA Mid: 80
SMA Long: 320
MADR SMA Period: 1920
MADR Sigma: 1.0
Signal Interval: 4 hours
Touch Lookback: 24 bars
Long Term Trend Check: Enabled
Use case: Active day trading, multiple signals per session
Configuration 2: Balanced Day Trading (1h Chart)
SMA Short: 20
SMA Mid: 80
MADR SMA Period: 480
MADR Sigma: 1.0
Signal Interval: 4 hours
Touch Lookback: 24 bars
Long Term Trend Check: Disabled
Use case: Standard day trading, moderate signal frequency
──────────────────────────────────────────
TECHNICAL LIMITATIONS AND UNSUITABLE CONDITIONS
──────────────────────────────────────────
This indicator has known limitations:
1. Range/Choppy Markets
Extended consolidation generates false signals and whipsaw entries. Wait for clear breakout or use higher timeframe trend filters.
2. Low Liquidity Instruments
In exotic pairs, microcap stocks, or illiquid assets, wide spreads and slippage erode edge. Stick to major high-volume instruments.
3. News-Driven Volatility
Fundamental shocks invalidate technical patterns. Avoid trading around scheduled high-impact news events.
4. Algorithmic Regime Changes
Market microstructure evolves over time. Review performance periodically and adjust parameters if edge deteriorates.
5. Extreme Market Regimes
Black swan events and unprecedented volatility cause all technical systems to fail simultaneously. Use circuit breakers and position size limits.
6. Gap Openings
Price gaps over weekends or between sessions invalidate some signals. Reduce position sizing accordingly.
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OPEN-SOURCE CODE TRANSPARENCY
──────────────────────────────────────────
While the source code is proprietary and protected, the fundamentals are fully explainable:
SMA calculation : Standard Pine Script ta.sma() function
MADR calculation : (close - sma) / sma * 100 and ta.stdev() for threshold
MTF data retrieval : request.security() for higher timeframe values
Granville pattern detection : Logical comparison of price/SMA positions and crosses
No "black box" algorithms. No hidden magic. Only rigorous application of proven technical principles.
──────────────────────────────────────────
OPEN-SOURCE CODE REUSE
──────────────────────────────────────────
This indicator does NOT reuse code from other TradingView scripts. All logic is proprietary.
Standard Pine Script functions (ta.sma, ta.stdev, request.security, etc.) used per documented API
No third-party libraries or external dependencies
No license conflicts
──────────────────────────────────────────
VERSION INFORMATION
──────────────────────────────────────────
Current Version : 6 (Pine Script v6)
Author : © 2025 mmntmr369. All rights reserved.
Publication Type : Invite-only (Proprietary source code)
──────────────────────────────────────────
DISCLAIMER : This indicator is provided for educational and informational purposes only. It does not constitute investment advice, financial advice, trading advice, or any other type of advice. You should not make any investment decisions based solely on this indicator. Always conduct your own research and consult with a licensed financial professional before making investment decisions. Past performance does not indicate future results. Trading carries substantial risk of loss and is not suitable for all investors.
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日本語版 / JAPANESE VERSION
══════════════════════════════════════════
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概要
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MTF Granville Signalは、グランビルの法則の原則に基づいた高確率エントリーポイントの特定を支援する招待制Pine Scriptインジケーターです。マルチタイムフレーム（MTF）構造分析と動的移動平均線乖離率（MADR）フィルタリングにより強化されています。
本インジケーターは投資助言ではありません。 これはテクニカル分析ツールです。すべての取引判断と結果は、ユーザーの単独責任となります。
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本インジケーターの独自性
──────────────────────────────────────────
多くのインジケーターが基本的なグランビルの法則または単純な移動平均クロスを実装していますが、本インジケーターは2つの数学的に厳密な拡張機能によって差別化されます：
1. 統計的基盤を持つ動的MADRフィルタリング
従来の買われ過ぎ/売られ過ぎインジケーターで使用される固定パーセンテージバンドとは異なり、本システムは ローリング標準偏差に基づく適応的閾値計算 を採用しています：
数学的アプローチ:
参照SMAからの価格偏差をパーセンテージとして計算
拡張ルックバック期間にわたって標準偏差（σ）を計算
デフォルト：1σ閾値 = 正規分布下の68.26%確率ゾーン
ユーザー設定可能なシグマ乗数（1σ、2σ、3σ）
操作ロジック:
順張りシグナル（グランビル法則1、2、3、5、6、7） ：MADRが正常範囲内（<閾値）にある場合のみ発火し、健全なトレンド状態を示します
逆張りシグナル（グランビル法則4、8） ：MADRが閾値を超える場合のみ発火し、統計的過度の拡張と平均回帰確率を示します
重要な理由:
従来のインジケーターは任意の固定閾値（例：「+3%以上で買われ過ぎ」）を使用します。市場のボラティリティは資産と期間によって劇的に変化します。EUR/USDでの3%偏差は極端かもしれませんが、ビットコインではノイズです。動的MADRは各市場のボラティリティ特性に自動的に適応し、多様な取引商品全体で一貫した統計的妥当性を維持します。
2. サイクルフェーズフィルタリングのためのMTF構造検証
これは単にチャート上に複数の時間足SMAを表示するだけではありません。インジケーターは トレンドサイクルフェーズを決定するための構造分析 を実行します：
検証メカニズム:
設定可能なルックバック期間内に価格が上位時間足SMAに最近タッチ/クロスしたかどうかを確認
SMA階層の整列を確認（上昇トレンドでは短期>中期>長期）
初期サイクルトレンド開始と後期サイクル疲弊を区別
重要な理由:
グランビルの法則シグナルはトレンドサイクル全体で出現できますが、確率は大きく異なります：
初期サイクル （価格が最近上位TF SMAと相互作用）：高確率 - トレンド開始または深い調整を捕捉
後期サイクル （価格が上位TF SMAから遠く離れている）：低確率 - 疲弊フェーズ中のエントリー
上位時間足SMAとの最近の構造的相互作用を要求することで、インジケーターは低確率の後期サイクルエントリーを除外し、シグナル品質を劇的に向上させます。
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グランビルの法則実装
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本インジケーターはジョセフ・グランビルの古典的な8つの法則すべてを実装しており、 法則1、2、3、4、5、6、7、8 に焦点を当てた主要シグナル生成を行います。法則3と7はタッチベースの近似で運用されます（以下の説明を参照）：
順張りシグナル（法則1、2、3、5、6、7）
買いシグナル:
短期SMAが中期/長期SMAを上回って交差する（またはタッチしてバウンス）
SMA階層が上昇トレンド構造を確認
MADRが価格が過度に拡張されていないことを示す
価格が最近上位時間足SMAと相互作用した（MTF検証）
売りシグナル:
下降トレンドの場合は反対のロジック
逆張り平均回帰シグナル（法則4、8）
売りシグナル:
価格が参照SMAから極端に乖離（MADRが閾値を超える）
価格がSMAに向かって反転を開始
短期SMAが中期/長期SMAを下回って交差する（またはタッチしてバウンス）
上位時間足SMAとの最近の構造的相互作用が反転セットアップを確認
買いシグナル:
売られ過ぎ反転の場合は反対のロジック
法則3と7の取り扱い:
法則3と7は「価格がSMAに接近する」と説明しています。これらの法則を除外するのではなく、本インジケーターは曖昧さを排除するために「接近」を「SMAにタッチ」として近似します。実際には、「接近」の定義は主観的で複雑さを追加します。「接近」を「タッチ/クロス」として運用することで、インジケーターは法則3と7の意図を捕捉しながら機械的客観性を維持します。
──────────────────────────────────────────
なぜグランビルの法則？
──────────────────────────────────────────
普遍性: すべての市場（外国為替、株式、暗号、商品）および時間足で機能
シンプルさ: 価格対移動平均の関係のみに基づく - 複雑な計算なし
再現性: 機械的ルールが感情的バイアスを排除
60年以上の実績: ジョセフ・グランビルの1960年の出版以来実証された原則
──────────────────────────────────────────
技術アーキテクチャ
──────────────────────────────────────────
シグナル生成プロセス
SMAを計算 複数の時間足にわたって（短期/中期/長期期間）
MADRを計算 ：参照SMAからの価格偏差とその統計的有意性を測定
MTF構造を検証 ：上位時間足SMAとの最近の価格相互作用を確認
SMA階層を評価 ：SMA整列によってトレンド方向を確認
グランビルロジックを適用 ：特定の法則パターンを検出（クロス、タッチ、バウンス）
SMAからの乖離を判定 ：
• 順張り：MADR < 閾値（健全なトレンド）
• 逆張り：MADR > 閾値（過度の拡張）
シグナル間隔制御 ：クールダウン期間がノイズ中のアラートスパムを防止
なぜこの組み合わせが機能するか
これら3つのコンポーネントの統合が堅牢なフィルタリングシステムを生成します：
グランビルの法則 が基本的なシグナルロジックを提供（数十年にわたって実証）
動的MADR が危険な価格極値でのエントリーを防止（ボラティリティ適応的リスク管理）
MTF構造検証 がシグナルを最適なサイクルフェーズで発生させる（タイミング最適化）
単一の要素だけでは高品質のシグナルは生成されません。それらの統合はトレンド相場環境においてエッジを生み出す可能性があります。
──────────────────────────────────────────
本インジケーターが行わないこと
──────────────────────────────────────────
現実的な期待を設定するために：
❌ 将来の価格方向を確実に予測しない
❌ 収益性のある取引を保証しない
❌ すべての市場環境で等しく機能しない（限界については下記参照）
❌ リスク管理、ポジションサイジング、または取引規律を置き換えない
❌ 取引の手仕舞いシグナルを提供しない（焦点はエントリータイミング）
──────────────────────────────────────────
パラメータ設定
──────────────────────────────────────────
Mid Term Trend Check Enabled（中期トレンドチェック有効） (デフォルト: true)
中期トレンド確認のためのSMA階層検証を有効化。
有効時：シグナルは短期SMA > 中期SMA（上昇トレンド）またはその逆（下降トレンド）を要求
無効時：短期SMAの動作のみを評価
推奨 ：弱いトレンドをフィルタリングするため、ほとんどの用途で有効を維持
Long Term Trend Check Enabled（長期トレンドチェック有効） (デフォルト: true)
追加のトレンド強度確認のため、長期SMAをSMA階層検証に追加。
中期トレンドチェックの有効化が必要
有効時：シグナルは短期SMA > 中期SMA > 長期SMAの整列を要求
推奨 ：低時間足（15分足以下）でより強力なフィルタリングのため有効化。高時間足（1時間足以上）では追加フィルターが冗長かつ過度に制限的になるため無効化
Require Touch Higher Timeframe SMA Enabled（上位足SMAタッチ要求有効） (デフォルト: true)
後期サイクルエントリーをフィルタリングするため、上位時間足SMAとの最近の価格相互作用を強制。
有効時：シグナルはルックバック期間内に価格が中期または長期SMAにタッチ/クロスした場合のみ発火
無効時：最近のSMA相互作用に関係なくシグナル発火（多くのシグナル、低品質）
推奨 ：有効を維持。これはサイクルフェーズ識別のコアフィルター
Touch Higher Timeframe SMA Lookback Period（上位足SMAタッチルックバック期間） (デフォルト: 24バー)
価格-SMA相互作用を検索する遡及期間を定義。
低い値（12-18）：厳格なフィルタリング、少ないシグナル、初期サイクル検出
高い値（24-36）：寛容なフィルタリング、多くのシグナル、中期サイクルエントリーを含む
推奨 ：市場ボラティリティに基づいて調整。トレンド市場：低い値を使用。荒れた市場：有効な調整を捉えるため高い値を使用
SMA Short Term Period（SMA短期期間） (デフォルト: 20)
グランビルの法則パターン検出のための主要SMA。
低い値（10-15）：反応的、多くのシグナル、高いノイズ
高い値（25-40）：滑らか、少ないシグナル、遅延エントリー
推奨 ：20はほとんどの市場で標準。時間足の好みに基づいて±5調整
SMA Mid Term Period（SMA中期期間） (デフォルト: 80)
トレンド階層とMTF検証のための基準SMA。
通常、短期期間の3-5倍
推奨 ：80はデイトレ（15m、1h）とスイングトレード（4h、日足）に適している。短期SMAとの比率関係を維持
SMA Long Term Period（SMA長期期間） (デフォルト: 320)
オプションのトレンド強度フィルター（長期トレンドチェック有効時必要）。
通常、中期期間の4倍
推奨 ：320は数日間のトレンド分析に適している。デイトレ、スイングには重要でない
SMA Period for Divergence（乖離のためのSMA期間） (デフォルト: 1920)
MADR標準偏差計算のためのルックバック期間。2つのアプローチがあります：
アプローチ1：チャート時間足SMA（シンプル）
チャート時間足と同じ20期間を使用し、シンプルに乖離を測定。
例：どの時間足でも20期間
アプローチ2：上位時間足SMA（MTF分析）
上位時間足の20期間SMA相当の期間を設定し、マルチタイムフレーム構造分析として利用。
デイトレーディング推奨設定 :
• 15分足チャート：1920期間（≈ 日足20-SMA：20日 × 96本/日）
• 1時間足チャート：480期間（≈ 日足20-SMA：20日 × 24本/日）
• 4時間足チャート：120期間（≈ 日足20-SMA：20日 × 6本/日）
両アプローチとも有効。アプローチ2は上位時間足のコンテクストをMADRフィルタリングに組み込む。
MADR Standard Deviation Band (Sigma)（MADR標準偏差バンド（シグマ）） (デフォルト: 1.00)
トレンド過熱と健全状態を判定するための統計的閾値。
1.0σ = 68.26%確率ゾーン（デフォルト、バランス型）
2.0σ = 95.44%確率ゾーン（厳格、少ない逆張りシグナル）
3.0σ = 99.74%確率ゾーン（非常に厳格、稀な極端反転のみ）
推奨 ：1.0σから開始。極端な平均回帰機会のみを取引したい場合は2.0σに増加。より積極的な順張りのため0.5σ-0.8σに減少
Signal Minimum Interval（シグナル最小間隔） (デフォルト: 4時間)
保ち合い中のアラートスパムを防ぐためのシグナル間のクールダウン期間。
チャート時間足に関係なく時間で測定
0 = クールダウンなし（すべての有効なシグナルが発火）
2-4 = デイトレード取引の典型
8-12 = スイング取引の典型
推奨 ：取引頻度に合わせる。デイトレーダー：2-4時間。スイングトレーダー：8-12時間
Buy/Sell Signal Text Color（買い/売りシグナルテキスト色） (デフォルト: 青)
Reversal Buy/Sell Signal Text Color（反転買い/売りシグナルテキスト色） (デフォルト: 紫)
順張りシグナルと逆張りシグナルの視覚的区別のためのラベル色をカスタマイズ。
Alert Display Prefix（アラート表示プレフィックス） (デフォルト: チャート時間足から自動検出)
アラートメッセージのプレフィックス（例：「1h」、「15m」）。空白の場合自動入力。
──────────────────────────────────────────
推奨設定例
──────────────────────────────────────────
設定1：積極的デイトレ（15分足チャート）
SMA Short: 20
SMA Mid: 80
SMA Long: 320
MADR SMA Period: 1920
MADR Sigma: 1.0
Signal Interval: 4時間
Touch Lookback: 24バー
Long Term Trend Check: 有効
用途: アクティブなデイトレード、セッションあたり複数のシグナル
設定2：バランス型デイトレ（1時間足チャート）
SMA Short: 20
SMA Mid: 80
MADR SMA Period: 480
MADR Sigma: 1.0
Signal Interval: 4時間
Touch Lookback: 24バー
Long Term Trend Check: 無効
用途: 標準的デイトレード、適度なシグナル頻度
──────────────────────────────────────────
技術的限界と不適切な条件
──────────────────────────────────────────
本インジケーターには既知の限界があります：
1. レンジ/荒れた市場
長期の保ち合いが偽シグナルとウィップソーエントリーを生成。明確なブレイクアウトまで待つか、高時間足トレンドフィルターを使用。
2. 流動性の低い銘柄
エキゾチックペア、マイクロキャップ株、流動性の低い資産では、広いスプレッドとスリッページがエッジを侵食。主要な高出来高銘柄に固執。
3. ニュース主導のボラティリティ
ファンダメンタルショックがテクニカルパターンを無効化。予定されている高インパクトニュースイベント前後の取引を避ける。
4. アルゴリズム的レジーム変化
市場マイクロ構造は時間とともに進化。定期的にパフォーマンスをレビューし、エッジが劣化した場合はパラメータを調整。
5. 極端な市場レジーム
ブラックスワンイベントと前例のないボラティリティは、すべてのテクニカルシステムを同時に失敗させる。サーキットブレーカーとポジションサイズ制限を使用。
6. ギャップオープニング
週末またはセッション間の価格ギャップが一部のシグナルを無効化。それに応じてポジションサイジングを削減。
──────────────────────────────────────────
オープンソースコードの透明性
──────────────────────────────────────────
ソースコードはプロプライエタリで保護されていますが、基本は以下で完全に説明できます：
SMA計算 ：標準Pine Script ta.sma()関数
MADR計算 ：(close - sma) / sma * 100と閾値のためのta.stdev()
MTFデータ取得 ：上位時間足値のためのrequest.security()
グランビルパターン検出 ：価格/SMAポジションとクロスの論理比較
「ブラックボックス」アルゴリズムなし。隠された魔法なし。実証された技術原則の厳密な適用のみ。
──────────────────────────────────────────
オープンソースコードの再利用
──────────────────────────────────────────
本インジケーターは他のTradingViewスクリプトのコードを 再利用していません 。すべてのロジックは独自です。
標準Pine Script関数（ta.sma、ta.stdev、request.securityなど）は文書化されたAPIに従って使用
サードパーティライブラリや外部依存関係なし
ライセンス競合なし
──────────────────────────────────────────
バージョン情報
現在のバージョン ：6（Pine Script v6）
作成者 ：© 2025 mmntmr369. 無断転載禁止。
公開タイプ ：招待制（プロプライエタリソースコード）
──────────────────────────────────────────
免責事項 ：本インジケーターは教育および情報提供目的のみで提供されています。投資助言、金融助言、取引助言、その他いかなる種類の助言も構成しません。本インジケーターのみに基づいて投資判断を行うべきではありません。投資判断を行う前に、必ずご自身で調査を行い、認可された金融専門家に相談してください。過去のパフォーマンスは将来の結果を示すものではありません。取引には多大な損失リスクがあり、すべての投資家に適しているわけではありません。
The Slick Strategy ReadinessThe Slick Strategy Readiness
Purpose
This is a readiness checklist, not an auto-trader. It supports the method from “The Slick Strategy: A Unique Profitable Options Trading Method.” The idea: each Monday, if conditions are READY, sell a 10-point wide SPX put credit spread with the short strike ~30 points below Monday’s open and hold to Friday’s close.
How the decision works
• Timing mode (choose one):
– Strict: Monday OPEN vs Friday SMAs (non-repainting on daily)
– Mid: Monday OPEN vs Monday SMAs (uses same day; repaints on daily)
• Core rules (always applied):
1) Price ≥ 200-SMA
2) 10-SMA ≥ 20-SMA
3) Core pause: if price is below both 10 & 20 while still above 200 → PAUSE
• Optional context pauses (only if “Apply context pauses” = ON):
– September: Price > 200 and (10 or 20 above price) → PAUSE
– Short week: Price > 200 and Price > 20 and (10 above price) → PAUSE
– Short week + Mon/Fri holiday + late-week major event and price above both 10 & 20 → PAUSE
If “Apply context pauses” is OFF, context rows are informational only and do not change the decision.
What you see on the chart
• Background tint: green = READY, red = PAUSED (by default, only on Mondays).
• Status bubble (last bar): shows “GOOD TO GO” or “PAUSED” on Mondays.
• PCS weekly reference line (strike helper):
– Level = Monday open − offset (default 30 pts; adjustable; optional rounding).
– Current week: orange = GOOD TO GO, gray = PAUSED; appears at start of Monday’s bar and extends through the week.
– Past weeks: green = win (Friday close ≥ that week’s level), red = loss, purple = skipped by core rules.
• SMA plots: optional 10/20/200 with fill between 10 & 20.
Readiness table (top-right by default)
Two columns: Check / Now (✓ or ✗). Rows: Price ≥ 200-SMA; 10-SMA ≥ 20-SMA; Price ≥ 10-SMA; Price ≥ 20-SMA; any enabled context rows; Core READY; Core PAUSE (price < 10 & 20 while >200); Final decision; optional Weekly PCS level.
Inputs (what to tweak)
• Source, SMA 10/20/200 lengths
• Plot SMAs, Fill between 10 & 20
• Only evaluate/tint on Mondays (on by default)
• Decision timing (Strict or Mid)
• Apply context pauses (and individual context flags)
• Table position/size/padding/border
• PCS helper: show current week’s line, show previous weeks’ lines, offset (pts), rounding increment & method, start only on Mondays, show Weekly PCS level in table
How to use (quick steps)
1) Add to SPX on Daily.
2) Pick timing: Strict (no repaint) or Mid (uses Monday SMAs).
3) Optionally enable Apply context pauses and relevant context flags.
4) On Monday’s open:
– If bubble says GOOD TO GO, consider selling a 10-wide SPX PCS with short strike ~30 pts below Monday’s open (adjust offset/rounding as desired).
– If PAUSED, skip this week.
5) Hold to Friday’s close; past weeks color green/red by result; purple indicates skipped.
Notes
This indicator does not place orders. Results depend on fills, fees, slippage, and risk management. Options trading involves risk; trade responsibly.
🔥 ANDINO Risk Ultimate 🔥Indicator for profitable trading, allowing buy, sell, stop-loss, and 3 take-profit entries, providing profitability and simplifying your trading.
Advanced Multi-Timeframe Trend & Signal System═══════════════════════════════════════════════════════════════
ADVANCED MULTI-TIMEFRAME TREND & SIGNAL SYSTEM v1.0
═══════════════════════════════════════════════════════════════
Created by: Zakaria Safri
License: Mozilla Public License 2.0
A comprehensive technical analysis tool designed for traders seeking
multi-dimensional market insights. This indicator combines proven
technical analysis methods with modern visualization techniques.
═══════════════════════════════════════════════════════════════
KEY FEATURES
═══════════════════════════════════════════════════════════════
✓ SUPERTREND SIGNAL GENERATION
- Customizable sensitivity settings
- Clear long/short entry signals
- Automatic trend direction detection
- ATR-based dynamic calculations
✓ MULTI-TIMEFRAME DASHBOARD
- Real-time trend analysis across 6 timeframes
- Synchronized trend confirmation
- Customizable table position and size
- Current: 1M, 5M, 15M, 1H, 1D coverage
✓ QQE REVERSAL DETECTION
- Quantitative Qualitative Estimation algorithm
- Early reversal signal identification
- Adjustable RSI and smoothing parameters
- Confirmation-based plotting
✓ DYNAMIC SUPPORT & RESISTANCE
- Pivot-based level calculation
- Quick and standard pivot detection
- Color-coded zones (8 levels)
- Automatic level updates
✓ MOMENTUM BREAKOUT SIGNALS
- Ichimoku-inspired calculations
- Bullish and bearish breakout detection
- Visual zone highlighting
- Trend confirmation filters
✓ RISK MANAGEMENT SYSTEM
- ATR-based stop loss calculation
- Multiple take profit targets (TP1, TP2, TP3)
- Customizable risk-to-reward ratios
- Dynamic price level tracking
- Hit detection markers
✓ VOLATILITY BANDS
- Keltner Channel implementation
- Multiple band layers (3 levels)
- EMA-based calculations
- Adaptive to market conditions
✓ TREND CLOUD VISUALIZATION
- Dual moving average cloud
- Clear trend direction indication
- Customizable color scheme
- Trend bar coloring
═══════════════════════════════════════════════════════════════
HOW TO USE
═══════════════════════════════════════════════════════════════
SETUP:
1. Add indicator to your chart
2. Configure sensitivity in Core Signals section
3. Enable desired features (signals, reversals, breakouts)
4. Set up risk management levels if trading
5. Position MTF dashboard to preference
SIGNAL INTERPRETATION:
• LONG Signal: Price crosses above Supertrend
• SHORT Signal: Price crosses below Supertrend
• REV (Reversal): QQE indicates potential trend change
• Diamond Breakouts: Momentum shift confirmation
• T1/T2/T3: Take profit level hits
MULTI-TIMEFRAME ANALYSIS:
• Green (BULL): Higher timeframe supports uptrend
• Red (BEAR): Higher timeframe supports downtrend
• Use for trend alignment and confirmation
• Best results when multiple timeframes align
RISK MANAGEMENT:
• Enable Stop Loss for automatic SL calculation
• Activate TP levels based on trading style
• Adjust Risk-to-Reward ratio (1:1 to 1:10)
• Monitor hit detection circles for exits
═══════════════════════════════════════════════════════════════
TECHNICAL SPECIFICATIONS
═══════════════════════════════════════════════════════════════
CALCULATIONS:
• Supertrend: ATR-based with customizable multiplier
• QQE: Modified RSI with Wilders smoothing
• Keltner Channels: EMA basis with ATR bands
• Pivots: Standard left/right bar methodology
• Support/Resistance: Multi-level pivot analysis
PARAMETERS:
• Supertrend Sensitivity: 0.5 to 10.0 (default: 2.0)
• RSI Period: 5 to 50 (default: 14)
• QQE Multiplier: 1.0 to 10.0 (default: 4.238)
• Risk-to-Reward: 1 to 10 (default: 4)
TIMEFRAMES:
Compatible with all timeframes. MTF dashboard displays:
• 1 Minute (1M)
• 5 Minutes (5M)
• 15 Minutes (15M)
• 1 Hour (1H)
• 1 Day (1D)
• Current chart timeframe
═══════════════════════════════════════════════════════════════
CUSTOMIZATION OPTIONS
═══════════════════════════════════════════════════════════════
VISUAL:
• Professional color scheme (Cyan/Orange)
• Adjustable table position (9 positions)
• Table size options (tiny/small/normal/large)
• Transparent zone highlighting
• Clean, modern label design
TOGGLES:
• Enable/disable any feature independently
• Show/hide signals, reversals, breakouts
• Toggle S/R levels and zones
• Control trend cloud and bands
• Master trend line optional
ALERTS:
The indicator provides visual signals that can be used with
TradingView's alert system by setting alerts on the indicator.
═══════════════════════════════════════════════════════════════
BEST PRACTICES
═══════════════════════════════════════════════════════════════
✓ Combine signals for higher probability setups
✓ Use MTF dashboard for trend confirmation
✓ Respect S/R levels for entry/exit planning
✓ Monitor QQE reversals at key price levels
✓ Adjust sensitivity based on asset volatility
✓ Test on demo/paper trading first
✓ Use proper risk management always
═══════════════════════════════════════════════════════════════
IMPORTANT DISCLAIMER
═══════════════════════════════════════════════════════════════
This indicator is a technical analysis tool and does NOT:
• Guarantee profitable trades
• Provide financial advice
• Predict future price movements with certainty
• Replace proper risk management
• Substitute for personal due diligence
Past performance does not indicate future results. All trading
involves risk. Users should:
- Understand the indicator's logic
- Test thoroughly before live trading
- Use appropriate position sizing
- Never risk more than they can afford to lose
- Consult financial advisors if needed
═══════════════════════════════════════════════════════════════
CODING STANDARDS
═══════════════════════════════════════════════════════════════
This indicator follows PineCoders Coding Conventions:
✓ Proper variable naming (prefixes: i_, f_, c_)
✓ Clear function documentation
✓ Organized code structure
✓ Type declarations
✓ Efficient calculations
✓ No repainting (confirmed signals)
✓ Proper use of request.security
═══════════════════════════════════════════════════════════════
SUPPORT & UPDATES
═══════════════════════════════════════════════════════════════
Version: 1.0
Author: Zakaria Safri
License: MPL 2.0
Last Updated: 2024
For questions, feedback, or suggestions, please comment below.
═══════════════════════════════════════════════════════════════
#trading #signals #supertrend #multiTimeframe #QQE #reversals
#supportResistance #riskManagement #trendAnalysis #momentum
Smart MACD Volume Trader# Smart MACD Volume Trader
## Overview
Smart MACD Volume Trader is an enhanced momentum indicator that combines the classic MACD (Moving Average Convergence Divergence) oscillator with an intelligent high-volume filter. This combination significantly reduces false signals by ensuring that trading signals are only generated when price momentum is confirmed by substantial volume activity.
The indicator supports over 24 different instruments including major and exotic forex pairs, precious metals (gold and silver), energy commodities (crude oil, natural gas), and industrial metals (copper). For forex and commodity traders, the indicator automatically maps to CME and COMEX futures contracts to provide accurate institutional-grade volume data.
## Originality and Core Concept
Traditional MACD indicators generate signals based solely on price momentum, which can result in numerous false signals during low-activity periods or ranging markets. This indicator addresses this critical weakness by introducing a volume confirmation layer with automatic institutional volume integration.
**What makes this approach original:**
- Signals are triggered only when MACD crossovers coincide with elevated volume activity
- Implements a lookback mechanism to detect volume spikes within recent bars
- Automatically detects and maps 24+ forex pairs and commodities to their corresponding CME and COMEX futures contracts
- Provides real institutional volume data for forex pairs where spot volume is unreliable
- Combines two independent market dimensions (price momentum and volume) into a single, actionable signal
- Includes intelligent asset detection that works across multiple exchanges and ticker formats
**The underlying principle:** Volume validates price movement. When institutional money enters the market, it creates volume signatures. By requiring high volume confirmation and using actual institutional volume data from futures markets, this indicator filters out weak price movements and focuses on trades backed by genuine market participation. The automatic futures mapping ensures that forex and commodity traders always have access to the most accurate volume data available, without manual configuration.
## How It Works
### MACD Component
The indicator calculates MACD using standard methodology:
1. **Fast EMA (default: 12 periods)** - Tracks short-term price momentum
2. **Slow EMA (default: 26 periods)** - Tracks longer-term price momentum
3. **MACD Line** - Difference between Fast EMA and Slow EMA
4. **Signal Line (default: 9-period SMA)** - Smoothed average of MACD line
**Crossover signals:**
- **Bullish:** MACD line crosses above Signal line (momentum turning positive)
- **Bearish:** MACD line crosses below Signal line (momentum turning negative)
### Volume Filter Component
The volume filter adds an essential confirmation layer:
1. **Volume Moving Average** - Calculates exponential MA of volume (default: 20 periods)
2. **High Volume Threshold** - Multiplies MA by ratio (default: 2.0x or 200%)
3. **Volume Detection** - Identifies bars where current volume exceeds threshold
4. **Lookback Period** - Checks if high volume occurred in recent bars (default: 5 bars)
**Signal logic:**
- Buy/Sell signals only trigger when BOTH conditions are met:
- MACD crossover/crossunder occurs
- High volume detected within lookback period
### Automatic CME Futures Integration
For forex traders, spot FX volume data can be unreliable or non-existent. This indicator solves this problem by automatically detecting forex pairs and mapping them to corresponding CME futures contracts with real institutional volume data.
**Supported Major Forex Pairs (7):**
- EURUSD → CME:6E1! (Euro FX Futures)
- GBPUSD → CME:6B1! (British Pound Futures)
- AUDUSD → CME:6A1! (Australian Dollar Futures)
- USDJPY → CME:6J1! (Japanese Yen Futures)
- USDCAD → CME:6C1! (Canadian Dollar Futures)
- USDCHF → CME:6S1! (Swiss Franc Futures)
- NZDUSD → CME:6N1! (New Zealand Dollar Futures)
**Supported Exotic Forex Pairs (4):**
- USDMXN → CME:6M1! (Mexican Peso Futures)
- USDRUB → CME:6R1! (Russian Ruble Futures)
- USDBRL → CME:6L1! (Brazilian Real Futures)
- USDZAR → CME:6Z1! (South African Rand Futures)
**Supported Cross Pairs (6):**
- EURJPY → CME:6E1! (Uses Euro Futures)
- GBPJPY → CME:6B1! (Uses British Pound Futures)
- EURGBP → CME:6E1! (Uses Euro Futures)
- AUDJPY → CME:6A1! (Uses Australian Dollar Futures)
- EURAUD → CME:6E1! (Uses Euro Futures)
- GBPAUD → CME:6B1! (Uses British Pound Futures)
**Supported Precious Metals (2):**
- Gold (XAUUSD, GOLD) → COMEX:GC1! (Gold Futures)
- Silver (XAGUSD, SILVER) → COMEX:SI1! (Silver Futures)
**Supported Energy Commodities (3):**
- WTI Crude Oil (USOIL, WTIUSD) → NYMEX:CL1! (Crude Oil Futures)
- Brent Oil (UKOIL) → NYMEX:BZ1! (Brent Crude Futures)
- Natural Gas (NATGAS) → NYMEX:NG1! (Natural Gas Futures)
**Supported Industrial Metals (1):**
- Copper (COPPER) → COMEX:HG1! (Copper Futures)
**How the automatic detection works:**
The indicator intelligently identifies the asset type by analyzing:
1. Exchange name (FX, OANDA, TVC, COMEX, NYMEX, etc.)
2. Currency pair pattern (6-letter codes like EURUSD, GBPUSD)
3. Commodity identifiers (XAU for gold, XAG for silver, OIL for crude)
When a supported instrument is detected, the indicator automatically switches to the corresponding futures contract for volume analysis. For stocks, cryptocurrencies, and other assets, the indicator uses the native volume data from the current chart.
**Visual feedback:**
An information table appears in the top-right corner of the MACD pane showing:
- Current chart symbol
- Exchange name
- Currency pair or asset name
- Volume source being used (highlighted in orange for futures, yellow for native volume)
- Current high volume status
This provides complete transparency about which data source the indicator is using for its volume analysis.
## How to Use
### Basic Setup
1. Add the indicator to your chart
2. The indicator displays in a separate pane (MACD) and overlay (signals/volume bars)
3. Default settings work well for most assets, but can be customized
### Signal Interpretation
### Visual Signals
**Visual Signals:**
- **Green "BUY" label** - Bullish MACD crossover confirmed by high volume
- **Red "SELL" label** - Bearish MACD crossunder confirmed by high volume
- **Green/Red candles** - Highlight bars with volume exceeding the threshold
- **Light green/red background** - Emphasizes signal bars on the chart
**Information Table:**
A detailed information table appears in the top-right corner of the MACD pane, providing real-time transparency about the indicator's operation:
- **Chart:** Current symbol being analyzed
- **Exchange:** The exchange or data feed being used
- **Pair:** The currency pair or asset name extracted from the ticker
- **Volume From:** The actual symbol used for volume analysis
- Orange color indicates CME or COMEX futures are being used (automatic institutional volume)
- Yellow color indicates native volume from the chart symbol is being used
- Hover tooltip shows whether automatic futures mapping is active
- **High Volume:** Current status showing YES (green) when volume exceeds threshold, NO (gray) otherwise
This table ensures complete transparency and allows you to verify that the correct volume source is being used for your analysis.
**Volume Analysis:**
- Gray histogram bars = Normal volume
- Red histogram bars = High volume (exceeds threshold)
- Green line = Volume moving average baseline
**MACD Analysis:**
- Blue line = MACD line (momentum indicator)
- Orange line = Signal line (trend confirmation)
- Gray dotted line = Zero line (bullish above, bearish below)
### Parameter Customization
**MACD Parameters:**
- Adjust Fast/Slow EMA lengths for different sensitivities
- Shorter periods = More signals, faster response
- Longer periods = Fewer signals, less noise
**Volume Parameters:**
- **Volume MA Period:** Higher values smooth volume analysis
- **High Volume Ratio:** Lower values (1.5x) = More signals; Higher values (3.0x) = Fewer, stronger signals
- **Volume Lookback Bars:** Controls how recent the volume spike must be
**Direction Filters:**
- **Only Buy Signals:** Enables long-only strategy mode
- **Only Sell Signals:** Enables short-only strategy mode
### Alert Configuration
The indicator includes three alert types:
1. **Buy Signal Alert** - Triggers when bullish signal appears
2. **Sell Signal Alert** - Triggers when bearish signal appears
3. **High Volume Alert** - Triggers when volume exceeds threshold
To set up alerts:
1. Click the indicator name → "Add alert on Smart MACD Volume Trader"
2. Select desired alert condition
3. Configure notification method (popup, email, webhook, etc.)
## Trading Strategy Guidelines
### Best Practices
**Recommended markets:**
- Liquid stocks (large-cap, high daily volume)
- Major forex pairs (EURUSD, GBPUSD, USDJPY, AUDUSD, USDCAD, USDCHF, NZDUSD)
- Exotic forex pairs (USDMXN, USDRUB, USDBRL, USDZAR)
- Cross pairs (EURJPY, GBPJPY, EURGBP, AUDJPY, EURAUD, GBPAUD)
- Precious metals (Gold, Silver with automatic COMEX futures mapping)
- Energy commodities (Crude Oil, Natural Gas with automatic NYMEX futures mapping)
- Industrial metals (Copper with automatic COMEX futures mapping)
- Major cryptocurrency pairs
- Index futures and ETFs
**Timeframe recommendations:**
- **Day trading:** 5-minute to 15-minute charts
- **Swing trading:** 1-hour to 4-hour charts
- **Position trading:** Daily charts
**Risk management:**
- Use signals as entry confirmation, not standalone strategy
- Combine with support/resistance levels
- Consider overall market trend direction
- Always use stop-loss orders
### Strategy Examples
**Trend Following Strategy:**
1. Identify overall trend using higher timeframe (e.g., daily chart)
2. Trade only in trend direction
3. Use "Only Buy" filter in uptrends, "Only Sell" in downtrends
4. Enter on signal, exit on opposite signal or at resistance/support
**Volume Breakout Strategy:**
1. Wait for consolidation period (low volume, tight MACD range)
2. Enter when signal appears with high volume (confirms breakout)
3. Target previous swing highs/lows
4. Stop loss below/above recent consolidation
**Forex Scalping Strategy (with automatic CME futures):**
1. The indicator automatically detects forex pairs and uses CME futures volume
2. Trade during active sessions only (use session filter)
3. Focus on quick profits (10-20 pips)
4. Exit at opposite signal or profit target
**Commodities Trading Strategy (Gold, Silver, Oil):**
1. The indicator automatically maps to COMEX and NYMEX futures contracts
2. Trade during high-liquidity sessions (overlap of major markets)
3. Use the high volume confirmation to identify institutional entry points
4. Combine with key support and resistance levels for entries
5. Monitor the information table to confirm futures volume is being used (orange color)
6. Exit on opposite MACD signal or at predefined profit targets
## Why This Combination Works
### The Volume Advantage
Studies consistently show that price movements accompanied by high volume are more likely to continue, while low-volume movements often reverse. This indicator leverages this principle by requiring volume confirmation.
**Key benefits:**
1. **Reduced False Signals:** Eliminates MACD whipsaws during low-volume consolidation
2. **Confirmation Bias:** Two independent indicators (price momentum + volume) agreeing
3. **Institutional Alignment:** High volume often indicates institutional participation
4. **Trend Validation:** Volume confirms that price momentum has "conviction"
### Statistical Edge
By combining two uncorrelated signals (MACD crossovers and volume spikes), the indicator creates a higher-probability setup than either signal alone. The lookback mechanism ensures signals aren't missed if volume spike slightly precedes the MACD cross.
## Supported Exchanges and Automatic Detection
The indicator includes intelligent asset detection that works across multiple exchanges and ticker formats:
**Forex Exchanges (Automatic CME Mapping):**
- FX (TradingView forex feed)
- OANDA
- FXCM
- SAXO
- FOREXCOM
- PEPPERSTONE
- EASYMARKETS
- FX_IDC
**Commodity Exchanges (Automatic COMEX/NYMEX Mapping):**
- TVC (TradingView commodity feed)
- COMEX (directly)
- NYMEX (directly)
- ICEUS
**Other Asset Classes (Native Volume):**
- Stock exchanges (NASDAQ, NYSE, AMEX, etc.)
- Cryptocurrency exchanges (BINANCE, COINBASE, KRAKEN, etc.)
- Index providers (SP, DJ, etc.)
The detection algorithm analyzes three factors:
1. Exchange prefix in the ticker symbol
2. Pattern matching for currency pairs (6-letter codes)
3. Commodity identifiers in the symbol name
This ensures accurate automatic detection regardless of which data feed or exchange you use for charting. The information table in the top-right corner always displays which volume source is being used, providing complete transparency.
## Technical Details
**Calculations:**
- MACD Fast MA: EMA(close, fastLength)
- MACD Slow MA: EMA(close, slowLength)
- MACD Line: Fast MA - Slow MA
- Signal Line: SMA(MACD Line, signalLength)
- Volume MA: Exponential MA of volume
- High Volume: Current volume >= Volume MA × Ratio
**Signal logic:**
```
Buy Signal = (MACD crosses above Signal) AND (High volume in last N bars)
Sell Signal = (MACD crosses below Signal) AND (High volume in last N bars)
```
## Parameters Reference
| Parameter | Default | Description |
|-----------|---------|-------------|
| Volume Symbol | Blank | Manual override for volume source (leave blank for automatic detection) |
| Use CME Futures | False | Legacy option (automatic detection is now built-in) |
| Alert Session | 1530-2200 | Active session time range for alerts |
| Timezone | UTC+1 | Timezone for alert sessions |
| Volume MA Period | 20 | Number of periods for volume moving average |
| High Volume Ratio | 2.0 | Volume threshold multiplier (2.0 = 200% of average) |
| Volume Lookback | 5 | Number of bars to check for high volume confirmation |
| MACD Fast Length | 12 | Fast EMA period for MACD calculation |
| MACD Slow Length | 26 | Slow EMA period for MACD calculation |
| MACD Signal Length | 9 | Signal line SMA period |
| Only Buy | False | Filter to show only bullish signals |
| Only Sell | False | Filter to show only bearish signals |
| Show Signals | True | Display buy and sell labels on chart |
## Optimization Tips
**For volatile markets (crypto, small caps):**
- Increase High Volume Ratio to 2.5-3.0
- Reduce Volume Lookback to 3-4 bars
- Consider faster MACD settings (8, 17, 9)
**For stable markets (large-cap stocks, bonds):**
- Decrease High Volume Ratio to 1.5-1.8
- Increase Volume MA Period to 30-50
- Use standard MACD settings
**For forex (with automatic CME futures):**
- The indicator automatically uses CME futures when forex pairs are detected
- Set appropriate trading session based on your timezone
- Use Volume Lookback of 5-7 bars
- Consider session-based alerts only
- Monitor the information table to verify correct futures mapping
**For commodities (Gold, Silver, Oil, Copper):**
- The indicator automatically maps to COMEX and NYMEX futures
- Increase High Volume Ratio to 2.0-2.5 for metals
- Use slightly higher Volume MA Period (25-30) for smoother analysis
- Trade during active market hours for best volume data
- The information table will show the futures contract being used (orange highlight)
## Limitations and Considerations
**What this indicator does NOT do:**
- Does not predict future price direction
- Does not guarantee profitable trades
- Does not replace proper risk management
- Does not work well in extremely low-volume conditions
**Market conditions to avoid:**
- Pre-market and after-hours sessions (low volume)
- Major news events (volatile, unpredictable volume)
- Holidays and low-liquidity periods
- Extremely low float stocks
## Conclusion
Smart MACD Volume Trader represents a significant evolution of the traditional MACD indicator by combining volume confirmation with automatic institutional volume integration. This dual-confirmation approach significantly improves signal quality by filtering out low-conviction price movements and ensuring traders work with accurate volume data.
The indicator's automatic detection and mapping system supports over 24 instruments across forex, commodities, and metals markets. By intelligently switching to CME and COMEX futures contracts when appropriate, the indicator provides forex and commodity traders with the same quality of volume data that stock traders naturally have access to.
This indicator is particularly valuable for traders who want to:
- Align their entries with institutional money flow
- Avoid getting trapped in false breakouts
- Trade forex pairs with reliable volume data
- Access accurate volume information for gold, silver, and energy commodities
- Combine momentum and volume analysis in a single, streamlined tool
Whether you are day trading stocks, swing trading forex pairs, or positioning in commodities markets, this indicator provides a robust framework for identifying high-probability momentum trades backed by genuine institutional participation. The automatic futures mapping works seamlessly across all supported instruments, requiring no manual configuration or expertise in futures markets.
---
## Support and Updates
This indicator is actively maintained and updated based on user feedback and market conditions. For questions about implementation or custom modifications, please use the comments section below.
**Disclaimer:** This indicator is for educational and informational purposes only. Past performance does not guarantee future results. Always conduct your own analysis and risk management before trading.
Multi-Timeframe EMA Trend Dashboard with Volume and RSI Filters═══════════════════════════════════════════════════════════
MULTI-TIMEFRAME EMA TREND DASHBOARD
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OVERVIEW
This indicator provides a comprehensive view of trend direction across multiple timeframes using the classic EMA 20/50 crossover methodology, enhanced with volume confirmation and RSI filtering. It aggregates trend information from six timeframes into a single dashboard for efficient market analysis.
The indicator is designed for educational purposes and to assist traders in identifying potential trend alignments across different time horizons.
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FEATURES
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MULTI-TIMEFRAME ANALYSIS
• Monitors 6 timeframes simultaneously: 1m, 5m, 15m, 1H, 4H, 1D
• Each timeframe analyzed independently using request.security()
• Non-repainting implementation with proper lookahead settings
• Calculates overall trend strength as percentage of bullish timeframes
EMA CROSSOVER SYSTEM
• Fast EMA (default: 20) and Slow EMA (default: 50)
• Bullish: Fast EMA > Slow EMA
• Bearish: Fast EMA < Slow EMA
• Neutral: Fast EMA = Slow EMA (rare condition)
• Visual EMA plots with optional fill area
VOLUME CONFIRMATION
• Optional volume filter for crossover signals
• Compares current volume against moving average (default: 20-period SMA)
• Categorizes volume as: High (>1.5x average), Normal (>average), Low (70), oversold (<30), and neutral zones
• Used in quality score calculation
• Optional display toggle
SUPPORT & RESISTANCE DETECTION
• Automatic detection using highest/lowest over lookback period (default: 50 bars)
• Plots resistance (red), support (green), and mid-level (gray)
• Step-line style for clear visualization
• Optional display toggle
QUALITY SCORING SYSTEM
• Rates trade setups from 1-5 stars
• Considers: MTF alignment, volume confirmation, RSI positioning
• 5 stars: 4+ timeframes aligned + volume confirmed + RSI 50-70
• 4 stars: 4+ timeframes aligned + volume confirmed
• 3 stars: 3+ timeframes aligned
• 2 stars: Exactly 3 timeframes aligned
• 1 star: Other conditions
VISUAL DASHBOARD
• Clean table display (position customizable)
• Color-coded trend indicators (green/red/yellow)
• Extended statistics panel (toggleable)
• Shows: Trends, Strength, Quality, RSI, Volume, Price Distance
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TECHNICAL SPECIFICATIONS
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CALCULATIONS
Trend Determination per Timeframe:
• request.security() fetches EMA values with gaps=off, lookahead=off
• Compares Fast EMA vs Slow EMA
• Returns: 1 (bullish), -1 (bearish), 0 (neutral)
Trend Strength:
• Counts number of bullish timeframes
• Formula: (bullish_count / 6) × 100
• Range: 0% (all bearish) to 100% (all bullish)
Price Distance from EMA:
• Formula: ((close - EMA) / EMA) × 100
• Positive: Price above EMA
• Negative: Price below EMA
• Warning when absolute distance > 5%
ANTI-REPAINTING MEASURES
• All request.security() calls use lookahead=barmerge.lookahead_off
• Dashboard updates only on barstate.islast
• Historical bars remain unchanged
• Crossover signals finalize on bar close
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USAGE GUIDE
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INTERPRETING THE DASHBOARD
Timeframe Rows:
• Each row shows individual timeframe trend status
• Look for alignment (multiple timeframes same direction)
• Higher timeframes generally more significant
Strength Indicator:
• >66.67%: Strong bullish (4+ timeframes bullish)
• 33.33-66.67%: Mixed/choppy conditions
• <33.33%: Strong bearish (4+ timeframes bearish)
Quality Score:
• Higher stars = better confluence of factors
• 5-star setups have strongest multi-factor confirmation
• Lower scores may indicate weaker or conflicting signals
SUGGESTED APPLICATIONS
Trend Confirmation:
• Check if multiple timeframes confirm current chart trend
• Higher agreement = stronger trend confidence
• Use for position sizing decisions
Entry Timing:
• Wait for EMA crossover on chart timeframe
• Confirm with higher timeframe alignment
• Volume above average preferred
• RSI not in extreme zones
Divergence Detection:
• When lower timeframes diverge from higher
• May indicate trend exhaustion or reversal
• Requires additional confirmation
CUSTOMIZATION
EMA Settings:
• Adjust Fast/Slow lengths for different sensitivities
• Shorter periods = more responsive, more signals
• Longer periods = smoother, fewer signals
• Common alternatives: 10/30, 12/26, 50/200
Volume Filter:
• Enable for higher-quality signals (fewer false positives)
• Disable in always-liquid markets or for more signals
• Adjust MA length based on typical volume patterns
Display Options:
• Toggle EMAs, S/R levels, extended stats as needed
• Choose dashboard position to avoid chart overlap
• Adjust colors for visibility preferences
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ALERTS
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AVAILABLE ALERT CONDITIONS
1. Bullish EMA Cross (Volume Confirmed)
2. Bearish EMA Cross (Volume Confirmed)
3. Strong Bullish Alignment (4+ timeframes)
4. Strong Bearish Alignment (4+ timeframes)
5. Trend Strength Increasing (>16.67% jump)
6. Trend Strength Decreasing (>16.67% drop)
7. Excellent Trade Setup (5-star rating)
Alert messages use standard placeholders:
• {{ticker}} - Symbol name
• {{close}} - Current close price
• {{time}} - Bar timestamp
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LIMITATIONS & CONSIDERATIONS
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KNOWN LIMITATIONS
• Lower timeframe data may not be available on all symbols
• 1-minute data typically limited to recent history
• request.security() subject to TradingView data limits
• Dashboard requires screen space (may overlap on small screens)
• More complex calculations may affect load time on slower devices
NOT SUITABLE FOR
• Highly volatile/illiquid instruments (many false signals)
• News-driven markets during announcements
• Automated trading without additional filters
• Markets where EMA strategies don't perform well
DOES NOT PROVIDE
• Exact entry/exit prices
• Stop-loss or take-profit levels
• Position sizing recommendations
• Guaranteed profit signals
• Market predictions
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BEST PRACTICES
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RECOMMENDED USAGE
✓ Combine with price action analysis
✓ Use appropriate risk management
✓ Backtest on historical data before live use
✓ Adjust settings for specific market characteristics
✓ Wait for higher-quality setups in important trades
✓ Consider overall market context and fundamentals
NOT RECOMMENDED
✗ Using as standalone trading system without confirmation
✗ Trading every signal without discretion
✗ Ignoring risk management principles
✗ Trading without understanding the methodology
✗ Applying to unsuitable markets/timeframes
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EDUCATIONAL BACKGROUND
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EMA CROSSOVER STRATEGY
The Exponential Moving Average crossover is a classical trend-following technique:
• Golden Cross: Fast EMA crosses above Slow EMA (bullish signal)
• Death Cross: Fast EMA crosses below Slow EMA (bearish signal)
• Widely used since the 1970s in various markets
• More responsive than SMA due to exponential weighting
MULTI-TIMEFRAME ANALYSIS
Analyzing multiple timeframes helps traders:
• Identify alignment between short and long-term trends
• Reduce false signals from single-timeframe noise
• Understand market context across different horizons
• Make informed decisions about trade duration
VOLUME ANALYSIS
Volume confirmation adds reliability:
• High volume suggests institutional participation
• Low volume signals may indicate false breakouts
• Volume precedes price in many market theories
• Helps distinguish genuine moves from noise
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TECHNICAL IMPLEMENTATION
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CODE STRUCTURE
• Organized in clear sections with proper commenting
• Uses explicit type declarations (int, float, bool, color, string)
• Constants defined at top (BULLISH=1, BEARISH=-1, etc.)
• Functions documented with @function, @param, @returns
• Follows PineCoders naming conventions (camelCase variables)
PERFORMANCE OPTIMIZATION
• var keyword for table (created once, not every bar)
• Calculations cached where possible
• Dashboard updates only on last bar
• Minimal redundant security() calls
SECURITY IMPLEMENTATION
• Proper gaps and lookahead parameters
• No future data leakage
• Signals finalize on bar close
• Historical bars remain static
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VERSION INFORMATION
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Current Version: 2.0
Pine Script Version: 5
Last Updated: 2024
Developed by: Zakaria Safri
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SETTINGS REFERENCE
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EMA SETTINGS
• Fast EMA Length: 1-500 (default: 20)
• Slow EMA Length: 1-500 (default: 50)
VOLUME & MOMENTUM
• Use Volume Confirmation: true/false (default: true)
• Volume MA Length: 1-500 (default: 20)
• Show RSI Levels: true/false (default: true)
• RSI Length: 1-500 (default: 14)
PRICE ACTION FEATURES
• Show Price Distance: true/false (default: true)
• Show Key Levels: true/false (default: true)
• S/R Lookback Period: 10-500 (default: 50)
DISPLAY SETTINGS
• Show EMAs on Chart: true/false (default: true)
• Fast EMA Color: customizable (default: cyan)
• Slow EMA Color: customizable (default: orange)
• EMA Line Width: 1-5 (default: 2)
• Show Fill Between EMAs: true/false (default: true)
• Show Crossover Signals: true/false (default: true)
DASHBOARD SETTINGS
• Position: Top Left/Right, Bottom Left/Right
• Show Extended Statistics: true/false (default: true)
ALERT SETTINGS
• Alert on Multi-TF Alignment: true/false (default: true)
• Alert on Trend Strength Change: true/false (default: true)
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RISK DISCLAIMER
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This indicator is provided for educational and informational purposes only. It should not be considered financial advice or a recommendation to buy or sell any security.
IMPORTANT NOTICES:
• Past performance does not indicate future results
• All trading involves risk of capital loss
• No indicator guarantees profitable trades
• Always conduct independent research and analysis
• Use proper risk management and position sizing
• Consult a qualified financial advisor before trading
• The developer assumes no liability for trading losses
By using this indicator, you acknowledge that you understand these risks and accept full responsibility for your trading decisions.
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SUPPORT & CONTRIBUTIONS
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FEEDBACK WELCOME
• Constructive comments appreciated
• Bug reports help improve the indicator
• Feature suggestions considered for future versions
• Share your experience to help other users
OPEN SOURCE
This code is published as open source for the TradingView community to:
• Learn from the implementation
• Modify for personal use
• Understand multi-timeframe analysis techniques
If you find this indicator useful, please consider:
• Leaving a thoughtful review
• Sharing with other traders who might benefit
• Following for future updates and releases
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ADDITIONAL RESOURCES
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RECOMMENDED READING
• TradingView Pine Script documentation
• PineCoders community resources
• Technical analysis textbooks on moving averages
• Multi-timeframe trading strategy guides
• Risk management principles
RELATED CONCEPTS
• Trend following strategies
• Moving average convergence/divergence
• Multiple timeframe analysis
• Volume-price relationships
• Momentum indicators
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Thank you for using this indicator. Trade responsibly and continue learning!
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Historical Matrix Analyzer [PhenLabs]📊Historical Matrix Analyzer
Version: PineScriptv6
📌Description
The Historical Matrix Analyzer is an advanced probabilistic trading tool that transforms technical analysis into a data-driven decision support system. By creating a comprehensive 56-cell matrix that tracks every combination of RSI states and multi-indicator conditions, this indicator reveals which market patterns have historically led to profitable outcomes and which have not.
At its core, the indicator continuously monitors seven distinct RSI states (ranging from Extreme Oversold to Extreme Overbought) and eight unique indicator combinations (MACD direction, volume levels, and price momentum). For each of these 56 possible market states, the system calculates average forward returns, win rates, and occurrence counts based on your configurable lookback period. The result is a color-coded probability matrix that shows you exactly where you stand in the historical performance landscape.
The standout feature is the Current State Panel, which provides instant clarity on your active market conditions. This panel displays signal strength classifications (from Strong Bullish to Strong Bearish), the average return percentage for similar past occurrences, an estimated win rate using Bayesian smoothing to prevent small-sample distortions, and a confidence level indicator that warns you when insufficient data exists for reliable conclusions.
🚀Points of Innovation
Multi-dimensional state classification combining 7 RSI levels with 8 indicator combinations for 56 unique trackable market conditions
Bayesian win rate estimation with adjustable smoothing strength to provide stable probability estimates even with limited historical samples
Real-time active cell highlighting with “NOW” marker that visually connects current market conditions to their historical performance data
Configurable color intensity sensitivity allowing traders to adjust heat-map responsiveness from conservative to aggressive visual feedback
Dual-panel display system separating the comprehensive statistics matrix from an easy-to-read current state summary panel
Intelligent confidence scoring that automatically warns traders when occurrence counts fall below reliable thresholds
🔧Core Components
RSI State Classification: Segments RSI readings into 7 distinct zones (Extreme Oversold <20, Oversold 20-30, Weak 30-40, Neutral 40-60, Strong 60-70, Overbought 70-80, Extreme Overbought >80) to capture momentum extremes and transitions
Multi-Indicator Condition Tracking: Simultaneously monitors MACD crossover status (bullish/bearish), volume relative to moving average (high/low), and price direction (rising/falling) creating 8 binary-encoded combinations
Historical Data Storage Arrays: Maintains rolling lookback windows storing RSI states, indicator states, prices, and bar indices for precise forward-return calculations
Forward Performance Calculator: Measures price changes over configurable forward bar periods (1-20 bars) from each historical state, accumulating total returns and win counts per matrix cell
Bayesian Smoothing Engine: Applies statistical prior assumptions (default 50% win rate) weighted by user-defined strength parameter to stabilize estimated win rates when sample sizes are small
Dynamic Color Mapping System: Converts average returns into color-coded heat map with intensity adjusted by sensitivity parameter and transparency modified by confidence levels
🔥Key Features
56-Cell Probability Matrix: Comprehensive grid displaying every possible combination of RSI state and indicator condition, with each cell showing average return percentage, estimated win rate, and occurrence count for complete statistical visibility
Current State Info Panel: Dedicated display showing your exact position in the matrix with signal strength emoji indicators, numerical statistics, and color-coded confidence warnings for immediate situational awareness
Customizable Lookback Period: Adjustable historical window from 50 to 500 bars allowing traders to focus on recent market behavior or capture longer-term pattern stability across different market cycles
Configurable Forward Performance Window: Select target holding periods from 1 to 20 bars ahead to align probability calculations with your trading timeframe, whether day trading or swing trading
Visual Heat Mapping: Color-coded cells transition from red (bearish historical performance) through gray (neutral) to green (bullish performance) with intensity reflecting statistical significance and occurrence frequency
Intelligent Data Filtering: Minimum occurrence threshold (1-10) removes unreliable patterns with insufficient historical samples, displaying gray warning colors for low-confidence cells
Flexible Layout Options: Independent positioning of statistics matrix and info panel to any screen corner, accommodating different chart layouts and personal preferences
Tooltip Details: Hover over any matrix cell to see full RSI label, complete indicator status description, precise average return, estimated win rate, and total occurrence count
🎨Visualization
Statistics Matrix Table: A 9-column by 8-row grid with RSI states labeling vertical axis and indicator combinations on horizontal axis, using compact abbreviations (XOverS, OverB, MACD↑, Vol↓, P↑) for space efficiency
Active Cell Indicator: The current market state cell displays “⦿ NOW ⦿” in yellow text with enhanced color saturation to immediately draw attention to relevant historical performance
Signal Strength Visualization: Info panel uses emoji indicators (🔥 Strong Bullish, ✅ Bullish, ↗️ Weak Bullish, ➖ Neutral, ↘️ Weak Bearish, ⛔ Bearish, ❄️ Strong Bearish, ⚠️ Insufficient Data) for rapid interpretation
Histogram Plot: Below the price chart, a green/red histogram displays the current cell’s average return percentage, providing a time-series view of how historical performance changes as market conditions evolve
Color Intensity Scaling: Cell background transparency and saturation dynamically adjust based on both the magnitude of average returns and the occurrence count, ensuring visual emphasis on reliable patterns
Confidence Level Display: Info panel bottom row shows “High Confidence” (green), “Medium Confidence” (orange), or “Low Confidence” (red) based on occurrence counts relative to minimum threshold multipliers
📖Usage Guidelines
RSI Period
Default: 14
Range: 1 to unlimited
Description: Controls the lookback period for RSI momentum calculation. Standard 14-period provides widely-recognized overbought/oversold levels. Decrease for faster, more sensitive RSI reactions suitable for scalping. Increase (21, 28) for smoother, longer-term momentum assessment in swing trading. Changes affect how quickly the indicator moves between the 7 RSI state classifications.
MACD Fast Length
Default: 12
Range: 1 to unlimited
Description: Sets the faster exponential moving average for MACD calculation. Standard 12-period setting works well for daily charts and captures short-term momentum shifts. Decreasing creates more responsive MACD crossovers but increases false signals. Increasing smooths out noise but delays signal generation, affecting the bullish/bearish indicator state classification.
MACD Slow Length
Default: 26
Range: 1 to unlimited
Description: Defines the slower exponential moving average for MACD calculation. Traditional 26-period setting balances trend identification with responsiveness. Must be greater than Fast Length. Wider spread between fast and slow increases MACD sensitivity to trend changes, impacting the frequency of indicator state transitions in the matrix.
MACD Signal Length
Default: 9
Range: 1 to unlimited
Description: Smoothing period for the MACD signal line that triggers bullish/bearish state changes. Standard 9-period provides reliable crossover signals. Shorter values create more frequent state changes and earlier signals but with more whipsaws. Longer values produce more confirmed, stable signals but with increased lag in detecting momentum shifts.
Volume MA Period
Default: 20
Range: 1 to unlimited
Description: Lookback period for volume moving average used to classify volume as “high” or “low” in indicator state combinations. 20-period default captures typical monthly trading patterns. Shorter periods (10-15) make volume classification more reactive to recent spikes. Longer periods (30-50) require more sustained volume changes to trigger state classification shifts.
Statistics Lookback Period
Default: 200
Range: 50 to 500
Description: Number of historical bars used to calculate matrix statistics. 200 bars provides substantial data for reliable patterns while remaining responsive to regime changes. Lower values (50-100) emphasize recent market behavior and adapt quickly but may produce volatile statistics. Higher values (300-500) capture long-term patterns with stable statistics but slower adaptation to changing market dynamics.
Forward Performance Bars
Default: 5
Range: 1 to 20
Description: Number of bars ahead used to calculate forward returns from each historical state occurrence. 5-bar default suits intraday to short-term swing trading (5 hours on hourly charts, 1 week on daily charts). Lower values (1-3) target short-term momentum trades. Higher values (10-20) align with position trading and longer-term pattern exploitation.
Color Intensity Sensitivity
Default: 2.0
Range: 0.5 to 5.0, step 0.5
Description: Amplifies or dampens the color intensity response to average return magnitudes in the matrix heat map. 2.0 default provides balanced visual emphasis. Lower values (0.5-1.0) create subtle coloring requiring larger returns for full saturation, useful for volatile instruments. Higher values (3.0-5.0) produce vivid colors from smaller returns, highlighting subtle edges in range-bound markets.
Minimum Occurrences for Coloring
Default: 3
Range: 1 to 10
Description: Required minimum sample size before applying color-coded performance to matrix cells. Cells with fewer occurrences display gray “insufficient data” warning. 3-occurrence default filters out rare patterns. Lower threshold (1-2) shows more data but includes unreliable single-event statistics. Higher thresholds (5-10) ensure only well-established patterns receive visual emphasis.
Table Position
Default: top_right
Options: top_left, top_right, bottom_left, bottom_right
Description: Screen location for the 56-cell statistics matrix table. Position to avoid overlapping critical price action or other indicators on your chart. Consider chart orientation and candlestick density when selecting optimal placement.
Show Current State Panel
Default: true
Options: true, false
Description: Toggle visibility of the dedicated current state information panel. When enabled, displays signal strength, RSI value, indicator status, average return, estimated win rate, and confidence level for active market conditions. Disable to declutter charts when only the matrix table is needed.
Info Panel Position
Default: bottom_left
Options: top_left, top_right, bottom_left, bottom_right
Description: Screen location for the current state information panel (when enabled). Position independently from statistics matrix to optimize chart real estate. Typically placed opposite the matrix table for balanced visual layout.
Win Rate Smoothing Strength
Default: 5
Range: 1 to 20
Description: Controls Bayesian prior weighting for estimated win rate calculations. Acts as virtual sample size assuming 50% win rate baseline. Default 5 provides moderate smoothing preventing extreme win rate estimates from small samples. Lower values (1-3) reduce smoothing effect, allowing win rates to reflect raw data more directly. Higher values (10-20) increase conservatism, pulling win rate estimates toward 50% until substantial evidence accumulates.
✅Best Use Cases
Pattern-based discretionary trading where you want historical confirmation before entering setups that “look good” based on current technical alignment
Swing trading with holding periods matching your forward performance bar setting, using high-confidence bullish cells as entry filters
Risk assessment and position sizing, allocating larger size to trades originating from cells with strong positive average returns and high estimated win rates
Market regime identification by observing which RSI states and indicator combinations are currently producing the most reliable historical patterns
Backtesting validation by comparing your manual strategy signals against the historical performance of the corresponding matrix cells
Educational tool for developing intuition about which technical condition combinations have actually worked versus those that feel right but lack historical evidence
⚠️Limitations
Historical patterns do not guarantee future performance, especially during unprecedented market events or regime changes not represented in the lookback period
Small sample sizes (low occurrence counts) produce unreliable statistics despite Bayesian smoothing, requiring caution when acting on low-confidence cells
Matrix statistics lag behind rapidly changing market conditions, as the lookback period must accumulate new state occurrences before updating performance data
Forward return calculations use fixed bar periods that may not align with actual trade exit timing, support/resistance levels, or volatility-adjusted profit targets
💡What Makes This Unique
Multi-Dimensional State Space: Unlike single-indicator tools, simultaneously tracks 56 distinct market condition combinations providing granular pattern resolution unavailable in traditional technical analysis
Bayesian Statistical Rigor: Implements proper probabilistic smoothing to prevent overconfidence from limited data, a critical feature missing from most pattern recognition tools
Real-Time Contextual Feedback: The “NOW” marker and dedicated info panel instantly connect current market conditions to their historical performance profile, eliminating guesswork
Transparent Occurrence Counts: Displays sample sizes directly in each cell, allowing traders to judge statistical reliability themselves rather than hiding data quality issues
Fully Customizable Analysis Window: Complete control over lookback depth and forward return horizons lets traders align the tool precisely with their trading timeframe and strategy requirements
🔬How It Works
1. State Classification and Encoding
Each bar’s RSI value is evaluated and assigned to one of 7 discrete states based on threshold levels (0: <20, 1: 20-30, 2: 30-40, 3: 40-60, 4: 60-70, 5: 70-80, 6: >80)
Simultaneously, three binary conditions are evaluated: MACD line position relative to signal line, current volume relative to its moving average, and current close relative to previous close
These three binary conditions are combined into a single indicator state integer (0-7) using binary encoding, creating 8 possible indicator combinations
The RSI state and indicator state are stored together, defining one of 56 possible market condition cells in the matrix
2. Historical Data Accumulation
As each bar completes, the current state classification, closing price, and bar index are stored in rolling arrays maintained at the size specified by the lookback period
When the arrays reach capacity, the oldest data point is removed and the newest added, creating a sliding historical window
This continuous process builds a comprehensive database of past market conditions and their subsequent price movements
3. Forward Return Calculation and Statistics Update
On each bar, the indicator looks back through the stored historical data to find bars where sufficient forward bars exist to measure outcomes
For each historical occurrence, the price change from that bar to the bar N periods ahead (where N is the forward performance bars setting) is calculated as a percentage return
This percentage return is added to the cumulative return total for the specific matrix cell corresponding to that historical bar’s state classification
Occurrence counts are incremented, and wins are tallied for positive returns, building comprehensive statistics for each of the 56 cells
The Bayesian smoothing formula combines these raw statistics with prior assumptions (neutral 50% win rate) weighted by the smoothing strength parameter to produce estimated win rates that remain stable even with small samples
💡Note:
The Historical Matrix Analyzer is designed as a decision support tool, not a standalone trading system. Best results come from using it to validate discretionary trade ideas or filter systematic strategy signals. Always combine matrix insights with proper risk management, position sizing rules, and awareness of broader market context. The estimated win rate feature uses Bayesian statistics specifically to prevent false confidence from limited data, but no amount of smoothing can create reliable predictions from fundamentally insufficient sample sizes. Focus on high-confidence cells (green-colored confidence indicators) with occurrence counts well above your minimum threshold for the most actionable insights.
Chronos Reversal Labs🧬 Chronos Reversal Lab - Machine Learning Market Structure Analysis
OVERVIEW
Chronos Reversal Lab (CRL) is an advanced market structure analyzer that combines computational intelligence kernels with classical technical analysis to identify high-probability reversal opportunities. The system integrates Shannon Entropy analysis, Detrended Fluctuation Analysis (DFA), Kalman adaptive filtering, and harmonic pattern recognition into a unified confluence-based signal engine.
WHAT MAKES IT ORIGINAL
Unlike traditional reversal indicators that rely solely on oscillators or pattern recognition, CRL employs a multi-kernel machine learning approach that analyzes market behavior through information theory, statistical physics, and adaptive state-space estimation. The system combines these computational methods with geometric pattern analysis and market microstructure to create a comprehensive reversal detection framework.
HOW IT WORKS (Technical Methodology)
1. COMPUTATIONAL KERNELS
Shannon Entropy Analysis
Measures market uncertainty using information theory:
• Discretizes price returns into bins (user-configurable 5-20 bins)
• Calculates probability distribution entropy over lookback window
• Normalizes entropy to 0-1 scale (0 = perfectly predictable, 1 = random)
• Low entropy states (< 0.3 default) indicate algorithmic clarity phases
• When entropy drops, directional moves become statistically more probable
Detrended Fluctuation Analysis (DFA)
Statistical technique measuring long-range correlations:
• Analyzes price series across multiple box sizes (4 to user-set maximum)
• Calculates fluctuation scaling exponent (Alpha)
• Alpha > 0.5: Trend persistence (momentum regime)
• Alpha < 0.5: Mean reversion tendency (reversal regime)
• Alpha range 0.3-1.5 mapped to trading strategies
Kalman Adaptive Filter
State-space estimation for lag-free trend tracking:
• Maintains separate fast and slow Kalman filters
• Process noise and measurement noise are user-configurable
• Tracks price state with adaptive gain adjustments
• Calculates acceleration (second derivative) for momentum detection
• Provides cleaner trend signals than traditional moving averages
2. HARMONIC PATTERN DETECTION
Identifies geometric reversal patterns:
• Gartley: 0.618 AB/XA, 0.786 AD/XA retracement
• Bat: 0.382-0.5 AB/XA, 0.886 AD/XA retracement
• Butterfly: 0.786 AB/XA, 1.272-1.618 AD/XA extension
• Cypher: 0.382-0.618 AB/XA, 0.786 AD/XA retracement
Pattern Validation Process:
• Requires alternating swing structure (XABCD points)
• Fibonacci ratio tolerance: 0.02-0.20 (user-adjustable precision)
• Minimum 50% ratio accuracy score required
• PRZ (Potential Reversal Zone) calculated around D point
• Zone size: ATR-based with pattern-specific multipliers
• Active pattern tracking with 100-bar invalidation window
3. MARKET STRUCTURE ANALYSIS
Swing Point Detection:
• Pivot-based swing identification (3-21 bars configurable)
• Minimum swing size: ATR multiples (0.5-5.0x)
• Adaptive filtering: volatility regime adjustment (0.7-1.3x)
• Swing confirmation tracking with RSI and volume context
• Maintains structural history (up to 500 swings)
Break of Structure (BOS):
• Detects price crossing previous swing highs/lows
• Used for trend continuation vs reversal classification
• Optional requirement for signal validation
Support/Resistance Detection:
• Identifies horizontal levels from swing clusters
• Touch counting algorithm (price within ATR×0.3 tolerance)
• Weighted by recency and number of tests
• Dynamic updating as structure evolves
4. CONFLUENCE SCORING SYSTEM
Multi-factor analysis with regime-aware weighting:
Hierarchical Kernel Logic:
• Entropy gates advanced kernel activation
• Only when entropy < threshold do DFA and Kalman accelerate scoring
• Prevents false signals during chaotic (high entropy) conditions
Scoring Components:
ML Kernels (when entropy low):
• Low entropy + trend alignment: +3.0 points × trend weight
• DFA super-trend (α>1.5): +4.0 points × trend weight
• DFA persistence (α>0.65): +2.5 points × trend weight
• DFA mean-reversion (α<0.35): +2.0 points × mean-reversion weight
• Kalman acceleration: up to +3.0 points (scaled by magnitude)
Classical Technical Analysis:
• RSI oversold (<30) / overbought (>70): +1.5 points
• RSI divergence (bullish/bearish): +2.5 points
• High relative volume (>1.5x): +0-2.0 points (scaled)
• Volume impulse (>2.0x): +1.5 points
• VWAP extremes: +1.0 point
• Trend alignment (Kalman fast vs slow): +1.5 points
• MACD crossover/momentum: +1.0 point
Structural Factors:
• Near support (within 0.5 ATR): +0-2.0 points (inverse distance)
• Near resistance (within 0.5 ATR): +0-2.0 points (inverse distance)
• Harmonic PRZ zone: +3.0 to +6.0 points (pattern score dependent)
• Break of structure: +1.5 points
Regime Adjustments:
• Trend weight: 1.5× in trend regime, 0.5× in mean-reversion
• Mean-reversion weight: 1.5× in MR regime, 0.5× in trend
• Volatility multiplier: 0.7-1.3× based on ATR regime
• Theory mode multiplier: 0.8× (Conservative) to 1.2× (APEX)
Final Threshold:
Base threshold (default 3.5) adjusted by:
• Theory mode: -0.3 (APEX) to +0.8 (Conservative)
• Regime: +0.5 (high vol) to -0.3 (low vol or strong trend)
• Filter: +0.2 if regime filter enabled
5. SIGNAL GENERATION ARCHITECTURE
Five-stage validation process:
Stage 1 - ML Kernel Analysis:
• Entropy threshold check
• DFA regime classification
• Kalman acceleration confirmation
Stage 2 - Structural Confirmation:
• Market structure supports directional bias
• BOS alignment (if required)
• Swing point validation
Stage 3 - Trigger Validation:
• Engulfing candle (if required)
• HTF bias confirmation (if strict HTF enabled)
• Harmonic PRZ alignment (if confirmation enabled)
Stage 4 - Consistency Check:
• Anticipation depth: checks N bars back (1-13 configurable)
• Ensures Kalman acceleration direction persists
• Filters whipsaw conditions
Stage 5 - Structural Soundness (Critical Filter):
• Verifies adequate room before next major swing level
• Long signals: must have >0.25 ATR clearance to last swing high
• Short signals: must have >0.25 ATR clearance to last swing low
• Prevents trades directly into obvious structural barriers
Dynamic Risk Management:
• Stop-loss: Placed beyond last structural swing ± 2 ticks
• Take-profit 1: Risk × configurable R1 multiplier (default 1.5R)
• Take-profit 2: Risk × configurable R2 multiplier (default 3.0R)
• Confidence score: Calibrated 0-99% based on confluence + kernel boost
6. ADAPTIVE REGIME SYSTEM
Continuous market state monitoring:
Trend Regime:
• Kalman fast vs slow positioning
• Multi-timeframe alignment (optional HTF)
• Strength: ATR-normalized fast/slow spread
Volatility Regime:
• Current ATR vs 100-bar average
• Regime ratio: 0.7-1.3 typical range
• Affects swing size filtering and cooldown periods
Signal Cooldown:
• Base: User-set bars (1-300)
• High volatility (>1.5): cooldown × 1.5
• Low volatility (<0.5): cooldown × 0.7
• Post-BOS: minimum 20-bar cooldown enforced
FOUR OPERATIONAL MODES
CONSERVATIVE MODE:
• Threshold adjustment: +0.8
• Mode multiplier: 0.8×
• Strictest filtering for highest quality
• Recommended for: Beginners, large accounts, swing trading
• Expected signals: 3-5 per week (typical volatile instrument)
BALANCED MODE:
• Threshold adjustment: +0.3
• Mode multiplier: 1.0×
• Standard operational parameters
• Recommended for: General trading, learning phase
• Expected signals: 5-10 per week
APEX MODE:
• Threshold adjustment: -0.3
• Mode multiplier: 1.2×
• Maximum sensitivity, reduced cooldowns
• Recommended for: Scalping, high volatility, experienced traders
• Expected signals: 10-20 per week
INSTITUTIONAL MODE:
• Threshold adjustment: +0.5
• Mode multiplier: 1.1×
• Enhanced structural weighting, HTF emphasis
• Recommended for: Professional traders, swing positions
• Expected signals: 4-8 per week
VISUAL COMPONENTS
1. Fibonacci Retracement Levels
• Auto-calculated from most recent swing structure
• Standard levels: 0%, 23.6%, 38.2%, 50%, 61.8%, 78.6%, 100%, 127.2%, 161.8%, 200%, 261.8%
• Key levels emphasized (50%, 61.8%, 100%, 161.8%)
• Color gradient from bullish to bearish based on level
• Automatic cleanup when levels are crossed
• Label intensity control (None/Fib only/All)
2. Support and Resistance Lines
• Dynamic horizontal levels from swing clusters
• Width: 2px solid lines
• Colors: Green (support), Red (resistance)
• Labels show price and level type
• Touch-based validation (minimum 2 touches)
• Real-time updates and invalidation
3. Harmonic PRZ Boxes
• Displayed around pattern completion (D point)
• Pattern-specific colors (Gartley: purple, Bat: orange, etc.)
• Box height: ATR-based zone sizing
• Score-dependent transparency
• 100-bar active window before removal
4. Confluence Boxes
• Appear when confluence ≥ threshold
• Yellow/orange gradient based on score strength
• Height: High to low of bar
• Width: 1 bar on each side
• Real-time score-based transparency
5. Kalman Filter Lines
• Fast filter: Bullish color (green default)
• Slow filter: Bearish color (red default)
• Width: 2px
• Transparency adjustable (0-90%)
• Optional display toggle
6. Signal Markers
• Long: Green triangle below bar (tiny size)
• Short: Red triangle above bar (tiny size)
• Appear only on confirmed signals
• Includes alert generation
7. Premium Dashboard
Features real-time metrics with visual gauges:
Layout Options:
• Position: 4 corners selectable
• Size: Small (9 rows) / Normal (12 rows) / Large (14 rows)
• Themes: Supreme, Cosmic, Vortex, Heritage
Metrics Displayed:
• Gamma (DFA - 0.5): Shows trend persistence vs mean-reversion
• TCI (Trend Strength): ATR-normalized Kalman spread with gauge
• v/c (Relative Volume): Current vs average with color coding
• Entropy: Market predictability state with gauge
• HFL (High-Frequency Line): Kalman fast/slow difference / ATR
• HFL_acc (Acceleration): Second derivative momentum
• Mem Bias: Net bullish-bearish confluence (-1 to +1)
• Assurance: Confidence × (1-entropy) metric
• Squeeze: Bollinger Band / Keltner Channel squeeze detection
• Breakout P: Probability estimate from DFA + trend + acceleration
• Score: Final confluence vs threshold (normalized)
• Neighbors: Active harmonic patterns count
• Signal Strength: Strong/Moderate/Weak classification
• Signal Banner: Current directional bias with emoji indicators
Gauge Visualization:
• 10-bar horizontal gauges (█ filled, ░ empty)
• Color-coded: Green (strong) / Gold (moderate) / Red (weak)
• Real-time updates every bar
HOW TO USE
Step 1: Configure Mode and Resolution
• Select Theory Mode based on trading style (Conservative/Balanced/APEX/Institutional)
• Set Structural Resolution (Standard for fast markets, High for balanced, Ultra/Institutional for swing)
• Enable Adaptive Filtering (recommended for all volatile assets)
Step 2: Enable Desired Kernels
• Shannon Entropy: Essential for predictability detection (recommended ON)
• DFA Analysis: Critical for regime classification (recommended ON)
• Kalman Filter: Provides lag-free trend tracking (recommended ON)
• All three work synergistically; disabling reduces effectiveness
Step 3: Configure Confluence Factors
• Enable desired technical factors (RSI, MACD, Volume, Divergence)
• Enable Liquidity Mapping for support/resistance proximity scoring
• Enable Harmonic Detection if trading pattern-based setups
• Adjust base confluence threshold (3.5 default; higher = fewer, cleaner signals)
Step 4: Set Trigger Requirements
• Require Engulfing: Adds precision, reduces frequency (recommended for Conservative)
• Require BOS: Ensures structural alignment (recommended for trend-following)
• Require Structural Soundness: Critical filter preventing traps (highly recommended)
• Strict HTF Bias: For multi-timeframe traders only
Step 5: Adjust Visual Preferences
• Enable/disable Fibonacci levels, S/R lines, PRZ boxes, confluence boxes
• Set label intensity (None/Fib/All)
• Adjust transparency (0-90%) for overlay clarity
• Configure dashboard position, size, and theme
Step 6: Configure Alerts
• Enable master alerts toggle
• Select alert types: Anticipation, Confirmation, High Confluence, Low Entropy
• Enable JSON details for automated trading integration
Step 7: Interpret Signals
• Wait for triangle markers (green up = long, red down = short)
• Check dashboard for confluence score, entropy, DFA regime
• Verify signal aligns with higher timeframe bias (if using HTF setting)
• Confirm adequate space to take-profit levels (no nearby structural barriers)
Step 8: Execute and Manage
• Enter at close of signal candle (or next bar open)
• Set stop-loss at calculated level (visible in alert if JSON enabled)
• Scale out at TP1 (1.5R default), trail remaining to TP2 (3.0R default)
• Exit early if entropy spikes >0.7 or DFA regime flips against position
CUSTOMIZATION GUIDE
Timeframe Optimization:
Scalping (1-5 minutes):
• Theory Mode: APEX
• Anticipation Depth: 3-5
• Structural Resolution: STANDARD
• Signal Cooldown: 8-12 bars
• Enable fast kernels, disable HTF bias
Day Trading (15m-1H):
• Theory Mode: BALANCED
• Anticipation Depth: 5-8
• Structural Resolution: HIGH
• Signal Cooldown: 12-20 bars
• Standard configuration
Swing Trading (4H-Daily):
• Theory Mode: INSTITUTIONAL
• Anticipation Depth: 8-13
• Structural Resolution: ULTRA or INSTITUTIONAL
• Signal Cooldown: 20-50 bars
• Enable HTF bias, strict confirmations
Market Type Optimization:
Forex Majors:
• All kernels enabled
• Harmonic patterns effective
• Balanced or Institutional mode
• Standard settings work well
Stock Indices:
• Emphasis on volume analysis
• DFA critical for regime detection
• Conservative or Balanced mode
• Enable liquidity mapping
Cryptocurrencies:
• Adaptive filtering essential
• Higher volatility regime expected
• APEX mode for active trading
• Wider ATR multiples for swing sizing
IMPORTANT DISCLAIMERS
• This indicator does not predict future price movements
• Computational kernels calculate probabilities, not certainties
• Past confluence scores do not guarantee future signal performance
• Always backtest on YOUR specific instruments and timeframes before live trading
• Machine learning kernels require calibration period (minimum 100 bars of data)
• Performance varies significantly across market conditions and regimes
• Signals are suggestions for analysis, not automated trading instructions
• Proper risk management (stops, position sizing) is mandatory
• Complex calculations may impact performance on lower-end devices
• Designed for liquid markets; avoid illiquid or gap-prone instruments
PERFORMANCE CONSIDERATIONS
Computational Intensity:
• DFA analysis: Moderate (scales with length and box size parameters)
• Entropy calculation: Moderate (scales with lookback and bins)
• Kalman filtering: Low (efficient state-space updates)
• Harmonic detection: Moderate to High (pattern matching across swing history)
• Overall: Medium computational load
Optimization Tips:
• Reduce Structural Analysis Depth (144 default → 50-100 for faster performance)
• Increase Calc Step (2 default → 3-4 for lighter load)
• Reduce Pattern Analysis Depth (8 default → 3-5 if harmonics not primary focus)
• Limit Draw Window (150 bars default prevents visual clutter on long charts)
• Disable unused confluence factors to reduce calculations
Best Suited For:
• Liquid instruments: Major forex, stock indices, large-cap crypto
• Active timeframes: 5-minute through daily (avoid tick/second charts)
• Trending or ranging markets: Adapts to both via regime detection
• Pattern traders: Harmonic integration adds geometric confluence
• Multi-timeframe analysts: HTF bias and regime detection support this approach
Not Recommended For:
• Illiquid penny stocks or micro-cap altcoins
• Markets with frequent gaps (stocks outside regular hours without gap adjustment)
• Extremely fast timeframes (tick, second charts) due to calculation overhead
• Pure mean-reversion systems (unless using CONSERVATIVE mode with DFA filters)
METHODOLOGY NOTE
The computational kernels (Shannon Entropy, DFA, Kalman Filter) are established statistical and signal processing techniques adapted for financial time series analysis. These are deterministic mathematical algorithms, not predictive AI models. The term "machine learning" refers to the adaptive, data-driven nature of the calculations, not neural networks or training processes.
Confluence scoring is rule-based with regime-dependent weighting. The system does not "learn" from historical trades but adapts its sensitivity to current volatility and trend conditions through mathematical regime classification.
SUPPORT & UPDATES
• Questions about configuration or usage? Send me a message on TradingView
• Feature requests are welcome for consideration in future updates
• Bug reports appreciated and addressed promptly
• I respond to messages within 24 hours
• Regular updates included (improvements, optimizations, new features)
FINAL REMINDERS
• This is an analytical tool for confluence analysis, not a standalone trading system
• Combine with your existing strategy, risk management, and market analysis
• Start with paper trading to learn the system's behavior on your markets
• Allow 50-100 signals minimum for performance evaluation
• Adjust parameters based on YOUR timeframe, instrument, and trading style
• No indicator guarantees profitable trades - proper risk management is essential
— Dskyz, Trade with insight. Trade with anticipation.
