⚔️ The Scalpel⚔️ THE SCALPEL v2.0
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Surgical-Grade Market Structure Detection System
🔬 WHAT IS THE SCALPEL?
The Scalpel is a precision-engineered market structure analyzer that identifies and tracks critical support and resistance zones with surgical accuracy. Unlike conventional S&R tools that flood your chart with noise, The Scalpel cuts through the clutter to reveal only the most significant price structures.
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⚙️ CORE TECHNOLOGY
▸ Pivot-Based Detection Engine
Advanced pivot analysis calibrated by user-defined precision settings
▸ Tissue Integrity Validation
Filters structures based on candle body-to-range ratios
▸ Dynamic Stress Analysis
Tracks zone interactions and removes exhausted levels automatically
▸ Volatility-Adaptive Zones
Zone width scales with ATR for consistent performance across all markets
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🎨 VISUAL SPECTRUM
💜 STERILE ZONES (Electric Violet)
Fresh, untested structures with maximum potential
🔴 COMPRESSION ZONES (Magenta Fire)
Tested resistance ceilings under selling pressure
🩵 FOUNDATION ZONES (Neon Teal)
Tested support floors with proven buyer interest
✨ PLASMA AURA EFFECT
Multi-layered glow effect for enhanced visibility
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📐 PARAMETERS
🔪 Blade Precision (1-10)
Higher = fewer but sharper pivots detected
🩺 Tissue Integrity % (30-90)
Minimum candle body percentage required
📏 Incision Depth (0.1-2.0 ATR)
Controls zone thickness based on volatility
💉 Stress Threshold (1-10)
Maximum touches before zone invalidation
📐 Projection Range (10-200)
How far zones extend into the future
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💡 HOW TO USE
1. Fresh sterile zones (violet) are your highest-probability setups
2. Watch for price reaction at zone boundaries
3. Tested zones confirm structure but may have diminished strength
4. Zones auto-remove after stress threshold is reached
5. Use projection range to anticipate future tests
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🎯 BEST FOR
✓ Scalping & Day Trading
✓ Swing Trade Entries
✓ Stop Loss Placement
✓ Take Profit Targeting
✓ Multi-Timeframe Analysis
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⚠️ DISCLAIMER
This indicator is for educational purposes only. Always conduct your own analysis and use proper risk management. Past performance does not guarantee future results.
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🏷️ TAGS
support resistance zones SNR pivot points market structure scalping day trading swing trading price action order blocks smart money supply demand technical analysis
חפש סקריפטים עבור "support resistance"
EMA Signals + HTF S/R + Diagonal (5-15m)Описание на русском
Скрипт строит две экспоненциальные скользящие средние (быструю и медленную EMA), а также SMA20 и SMA50, и использует их для генерации пошаговых сигналов входа. При пересечении EMA9 и EMA12 вверх выше SMA20 под свечой появляется зелёный круг, а когда после этого обе EMA оказываются выше SMA50, под ценой появляется плашка LONG; аналогично при пересечении вниз ниже SMA20 рисуется красный круг над свечой, и после ухода EMA под SMA50 формируется плашка SHORT.
Горизонтальные зоны поддержки и сопротивления вычисляются по пивотам старшего таймфрейма (по умолчанию 1 час) через request.security, каждая зона рисуется прямоугольником на графике и сопровождается подписью с ценой уровня и текущим количеством касаний ценой (Touches: N), которое считается на активном ТФ. Дополнительно скрипт строит одну диагональную линию поддержки: она протягивается от последнего ключевого минимума (pivot low с заданной «силой») к текущей цене и динамически обновляется при появлении нового важного минимума, рядом с линией отображается подпись Trend.
Description in English
This script combines EMA‑based signals, dynamic higher‑timeframe support/resistance zones, and a diagonal trendline from the latest key swing low. It plots two exponential moving averages (fast and slow EMA) along with SMA20 and SMA50, and uses them to create step‑by‑step entry signals: when EMA9 crosses above EMA12 while both are above SMA20, a green circle is shown below the bar, and once both EMAs move above SMA50 after that, a LONG label is printed below price; conversely, when EMA9 crosses below EMA12 while both are below SMA20, a red circle appears above the bar, and after both EMAs move below SMA50, a SHORT label is displayed above price.
Horizontal support and resistance zones are derived from pivot highs and lows on a higher timeframe (1‑hour by default) using request.security; each zone is drawn as a rectangle on the chart and annotated with the level price and the current number of touches by price (Touches: N), counted on the active timeframe. In addition, the script plots a single diagonal support line from the most recent key swing low (pivot low with configurable strength) towards the current price, updating it whenever a new important low appears, and shows a small “Trend” label near this line
Structure Analysis + Hammer Alert# Structure Resistance + Hammer Alert
## 📊 Indicator Overview
This indicator integrates Structure Breakout Analysis with Candlestick Pattern Recognition, helping traders identify market trend reversal points and strong momentum signals. Through visual markers and background colors, you can quickly grasp the bullish/bearish market structure.
---
## 🎯 Core Features
### 1️⃣ Structure Resistance System
- Auto-plot Previous High/Low: Automatically marks key support/resistance based on pivot points
- Structure Breakout Detection: Shows "BULL" when price breaks above previous high, "BEAR" when breaking below previous low
- Trend Background Color: Green background for bullish structure, red background for bearish structure
### 2️⃣ Bullish Momentum Candles (Hammer Patterns)
Detects candles with long lower shadows, indicating strong buying pressure at lows:
- 💪Strong Bull (Bullish Hammer): Green marker, bullish close with significant lower shadow
- 💪Weak Bull (Bearish Hammer): Teal marker, bearish close but strong lower shadow
### 3️⃣ Bearish Momentum Candles (Inverted Hammer/Shooting Star)
Detects candles with long upper shadows, indicating strong selling pressure at highs:
- 💪Weak Bear (Bullish Inverted Hammer): Orange marker, bullish close but significant upper shadow
- 💪Strong Bear (Shooting Star): Red marker, bearish close with significant upper shadow
### 4️⃣ Smart Marker Sizing
Markers automatically adjust size based on current trend:
- With-Trend Signals: Larger markers (e.g., hammer in bullish trend)
- Counter-Trend Signals: Smaller markers (e.g., shooting star in bullish trend)
- Neutral Trend: Medium-sized markers
---
## ⚙️ Parameter Settings
### Structure Resistance Parameters
- Swing Length: Default 5, higher values = clearer structure but fewer signals
- Show Lines/Labels: Toggle on/off options
### Bullish Momentum (Hammer) Parameters
- Lower Shadow/Body Ratio: Default 2.0, lower shadow must be 2x body size
- Upper Shadow/Body Ratio Limit: Default 0.2, upper shadow cannot be too long
- Body Position Ratio: Default 2.0, ensures body is at the top of candle
### Bearish Momentum (Inverted Hammer) Parameters
- Upper Shadow/Body Ratio: Default 2.0, upper shadow must be 2x body size
- Lower Shadow/Body Ratio Limit: Default 0.2, lower shadow cannot be too long
- Body Position Ratio: Default 2.0, ensures body is at the bottom of candle
### Filter & Display Settings
- Minimum Body Size: Filters out doji-like candles with tiny bodies
- Pattern Type Toggles: Show/hide different pattern types individually
- Background Transparency: Adjust background color intensity (higher = more transparent)
- Label Distance: Adjust marker distance from candles
---
## 📈 Usage Guidelines
### Trading Signal Interpretation
**Long Signals (Strongest to Weakest):**
1. Bullish Structure + Bullish Hammer (💪Strong Bull) → Strongest long signal
2. Bullish Structure + Bearish Hammer (💪Weak Bull) → Secondary long signal
3. Bearish Structure + Hammer → Potential reversal signal
**Short Signals (Strongest to Weakest):**
1. Bearish Structure + Shooting Star (💪Strong Bear) → Strongest short signal
2. Bearish Structure + Bullish Inverted Hammer (💪Weak Bear) → Secondary short signal
3. Bullish Structure + Shooting Star → Potential reversal signal
### Practical Tips
✅ Trend Following: Prioritize large marker signals (aligned with trend)
✅ Structure Confirmation: Wait for structure breakout before entry to avoid false breaks
✅ Multiple Timeframes: Confirm trend direction with higher timeframes
⚠️ Counter-Trend Caution: Small marker signals (counter-trend) require stricter risk management
---
## 🔔 Alert Setup
This indicator provides 9 alert conditions:
- Individual Patterns: Bullish Hammer, Bearish Hammer, Bullish Inverted Hammer, Shooting Star
- Combined Signals: Bullish Momentum, Bearish Momentum, Bull/Bear Momentum
- Structure Breakouts: Bullish Structure Break, Bearish Structure Break
---
## 💡 FAQ
**Q: Why do hammers sometimes appear without markers?**
A: Check "Minimum Body Size" setting - the candle body may be too small and filtered out
**Q: Too many or too few markers?**
A: Adjust "Lower Shadow/Body Ratio" or "Upper Shadow/Body Ratio" parameters - higher ratios = stricter conditions
**Q: How to see only the strongest signals?**
A: Disable "Bearish Hammer" and "Bullish Inverted Hammer", keep only "Bullish Hammer" and "Shooting Star"
**Q: Can it be used on all timeframes?**
A: Yes, but recommended for 15-minute and higher timeframes - shorter timeframes have more noise
---
## 📝 Disclaimer
⚠️ This indicator is a supplementary tool and should be used with other technical analysis methods
⚠️ Past performance does not guarantee future results - always practice proper risk management
⚠️ Recommended to test on demo account before live trading
---
**Version:** Pine Script v6
**Applicable Markets:** Stocks, Futures, Cryptocurrencies, and all markets
Linear Trajectory & Volume StructureThe Linear Trajectory & Volume Structure indicator is a comprehensive trend-following system designed to identify market direction, volatility-adjusted channels, and high-probability entry points. Unlike standard Moving Averages, this tool utilizes Linear Regression logic to calculate the "best fit" trajectory of price, encased within volatility bands (ATR) to filter out market noise.
It integrates three core analytical components into a single interface:
Trend Engine: A Linear Regression Curve to determine the mean trajectory.
Volume Verification: Filters signals to ensure price movement is backed by market participation.
Market Structure: Identifies previous high-volume supply and demand zones for support and resistance analysis.
2. Core Components and Logic
The Trajectory Engine
The backbone of the system is a Linear Regression calculation. This statistical method fits a straight line through recent price data points to determine the current slope and direction.
The Baseline: Represents the "fair value" or mean trajectory of the asset.
The Cloud: Calculated using Average True Range (ATR). It expands during high volatility and contracts during consolidation.
Trend Definition:
Bullish: Price breaks above the Upper Deviation Band.
Bearish: Price breaks below the Lower Deviation Band.
Neutral/Chop: Price remains inside the cloud.
Smart Volume Filter
The indicator includes a toggleable volume filter. When enabled, the script calculates a Simple Moving Average (SMA) of the volume.
High Volume: Current volume is greater than the Volume SMA.
Signal Validation: Reversal signals and structure zones are only generated if High Volume is present, reducing the likelihood of trading false breakouts on low liquidity.
Volume Structure (Smart Liquidity)
The script automatically plots Support (Demand) and Resistance (Supply) boxes based on pivot points.
Creation: A box is drawn only if a pivot high or low is formed with High Volume (if the volume filter is active).
Mitigation: The boxes extend to the right. If price breaks through a zone, the box turns gray to indicate the level has been breached.
3. Signal Guide
Trend Reversals (Buy/Sell Labels)
These are the primary signals indicating a potential change in the macro trend.
BUY Signal: Appears when price closes above the upper volatility band after previously being in a downtrend.
SELL Signal: Appears when price closes below the lower volatility band after previously being in an uptrend.
Pullbacks (Small Circles)
These are continuation signals, useful for adding to positions or entering an existing trend.
Long Pullback: The trend is Bullish, but price dips momentarily below the baseline (into the "discount" area) and closes back above it.
Short Pullback: The trend is Bearish, but price rallies momentarily above the baseline (into the "premium" area) and closes back below it.
4. Configuration and Settings
Trend Engine Settings
Trajectory Length: The lookback period for the Linear Regression. This is the most critical setting for tuning sensitivity.
Channel Multiplier: Controls the width of the cloud.
1.0: Aggressive. Results in narrower bands and earlier signals, but more false positives.
1.5: Balanced (Default).
2.0+: Conservative. Creates a wide channel, filtering out significant noise but delaying entry signals.
Signal Logic
Show Trend Reversals: Toggles the main Buy/Sell labels.
Show Pullbacks: Toggles the re-entry circle signals.
Smart Volume Filter: If checked, signals require above-average volume. Unchecking this yields more signals but removes the volume confirmation requirement.
Volume Structure
Show Smart Liquidity: Toggles the Support/Resistance boxes.
Structure Lookback: Defines how many bars constitute a pivot. Higher numbers identify only major market structures.
Max Active Zones: Limits the number of boxes on the chart to prevent clutter.
5. Timeframe Optimization Guide
To maximize the effectiveness of the Linear Trajectory, you must adjust the Trajectory Length input based on your trading style and timeframe.
Scalping (1-Minute to 5-Minute Charts)
Recommended Length: 20 to 30
Multiplier: 1.2 to 1.5
Logic: Fast-moving markets require a shorter lookback to react quickly to micro-trend changes.
Day Trading (15-Minute to 1-Hour Charts)
Recommended Length: 55 (Default)
Multiplier: 1.5
Logic: A balance between responsiveness and noise filtering. The default setting of 55 is standard for identifying intraday sessions.
Swing Trading (4-Hour to Daily Charts)
Recommended Length: 89 to 100
Multiplier: 1.8 to 2.0
Logic: Swing trading requires filtering out intraday noise. A longer length ensures you stay in the trade during minor retracements.
6. Dashboard (HUD) Interpretation
The Head-Up Display (HUD) provides a summary of the current market state without needing to analyze the chart visually.
Bias: Displays the current trend direction (BULLISH or BEARISH).
Momentum:
ACCELERATING: Price is moving away from the baseline (strong trend).
WEAKENING: Price is compressing toward the baseline (potential consolidation or reversal).
Volume: Indicates if the current candle's volume is HIGH or LOW relative to the average.
Disclaimer
*Trading cryptocurrencies, stocks, forex, and other financial instruments involves a high level of risk and may not be suitable for all investors. This indicator is a technical analysis tool provided for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a guarantee of profit. Past performance of any trading system or methodology is not necessarily indicative of future results.
Advanced ICC Multi-Timeframe 1.0Advanced ICC Multi-Timeframe Trading System
A comprehensive implementation and interpretation of the Indication, Correction, Continuation (ICC) trading methodology made popular by Trades by Sci, enhanced with advanced multi-timeframe analysis and automation features.
⚠️ CRITICAL TRADING WARNINGS:
DO NOT blindly follow BUY/SELL signals from this indicator
This indicator shows potential entry points but YOU must validate each trade
PAPER TRADE EXTENSIVELY before risking real capital
BACKTEST THOROUGHLY on your chosen instruments and timeframes
The ICC methodology requires understanding and discretion - automated signals are guidance only
This tool aids analysis but does not replace proper trade planning, risk management, or trader judgment
⚠️ Important Disclaimers:
This indicator is not endorsed by or affiliated with Trades by Sci
This is an early implementation and interpretation of the ICC methodology
May not work exactly as Trades by Sci executes his trades and entries
Requires further debugging, backtesting, and real-world validation
Completely free to use - no purchase required
I'm just one person obsessed with this method and wanted some better visualization of the chart/entries
About ICC:
The ICC method identifies complete market cycles through three phases: Indication (breakout), Correction (pullback), and Continuation (entry). This indicator automates the identification of these phases and adds powerful features for modern traders.
Key Features:
Multi-Timeframe Capabilities:
Automatic timeframe detection with optimized settings for 5m, 15m, 30m, 1H, 4H, and Daily charts
Higher timeframe overlay to view HTF ICC levels on lower timeframe charts for precise entry timing
Smart defaults that adjust swing length and consolidation detection based on your timeframe
Advanced Phase Tracking:
Complete ICC cycle tracking: Indication, Correction, Consolidation, Continuation, and No Setup phases
Live structure detection shows potential peaks/troughs before full confirmation
Intelligent invalidation logic detects failed setups when market structure reverses
Dynamic phase backgrounds for instant visual confirmation
Three Types of Entry Signals:
Traditional Entries - Price crosses back through the original indication level (strongest signals)
"BUY" (green) / "SELL" (red)
Breakout Entries - Price breaks out of consolidation range in the same direction
"BUY" (green) / "SELL" (red)
Reversal Entries (Optional, can be toggled off) - Price breaks consolidation in opposite direction, indicating failed setup
"⚠ BUY" (yellow) / "⚠ SELL" (orange)
More aggressive, counter-trend signals
Can be disabled for more conservative trading
Professional Features:
Volatility-based support/resistance zones (ATR-adjusted) that adapt to market conditions
Historical zone tracking (0-3 configurable) with visual hierarchy
Comprehensive real-time info table displaying all key metrics
Full alert system for entries, indications, and consolidation detection
Visual distinction between high-confidence trend entries and cautionary reversal entries
📖 USAGE GUIDE
Entry Signal Types:
The indicator provides three types of entry signals with visual distinction:
Strong Entries (High Confidence):
"BUY" (bright green) / "SELL" (bright red)
Includes traditional entries (crossing back through indication level) and breakout entries (breaking consolidation in trend direction)
These are trend continuation or breakout signals with higher probability
Recommended for all traders
Reversal Entries (Caution - Counter-Trend):
"⚠ BUY" (yellow) / "⚠ SELL" (orange)
Triggered when price breaks out of correction/consolidation in the OPPOSITE direction
Indicates a failed setup and potential trend reversal
More aggressive, counter-trend plays
Can be toggled off in settings for more conservative trading
Recommended only for experienced traders or after thorough backtesting
Swing Length Settings:
The swing length determines how many bars on each side are needed to confirm a swing high/low. This is the most important setting for tuning the indicator to your style.
Auto Mode (Recommended for beginners): Toggle "Use Auto Timeframe Settings" ON
5-minute: 30 bars
15-minute: 20 bars
30-minute: 12 bars
1-hour: 7 bars
4-hour: 5 bars
Daily: 3 bars
Manual Mode: Toggle "Use Auto Timeframe Settings" OFF
Lower values (3-7): More aggressive, detects smaller swings
Pros: More signals, faster entries, catches smaller moves
Cons: More noise, more false signals, requires tighter stops
Best for: Scalping, active day trading, volatile markets
Higher values (12-20): More conservative, only major swings
Pros: More reliable signals, fewer false breakouts, clearer structure
Cons: Fewer signals, delayed entries, might miss smaller opportunities
Best for: Swing trading, position trading, trending markets
Default Manual Setting: 7 bars (balanced for 1H charts)
Minimum: 3 bars
Consolidation Bars Setting:
Determines how many bars without new structure are needed before flagging consolidation.
Lower values (3-10): Faster detection, catches brief pauses, more sensitive
Best for: Lower timeframes, volatile markets, avoiding any chop
Higher values (20-40): More reliable, only flags true extended consolidation
Best for: Higher timeframes, trending markets, patient traders
Current defaults scale with timeframe (more bars needed on shorter timeframes)
Historical S/R Zones:
Shows previous support and resistance levels to provide context.
Default: 2 historical zones (shows current + 2 previous)
Range: 0-3 zones
Visual Hierarchy: Older zones are more transparent with dashed borders
Usage: Higher numbers (2-3) show more historical context but can clutter the chart. Start with 2 and adjust based on your preference.
Live Structure Feature (Yellow Warning ⚠):
Provides early warning of potential structure changes before full confirmation.
What it does: Detects potential swing highs/lows after just 2 bars instead of waiting for full swing_length confirmation
Live Peak: Shows when a high is followed by 2 lower closes (potential top forming)
Live Trough: Shows when a low is followed by 2 higher closes (potential bottom forming)
Important: These are UNCONFIRMED - they may be invalidated if price reverses
Use case: Get early awareness of potential reversals while waiting for confirmation
Displayed in: Info table only (no visual markers on chart to reduce clutter)
Only shows: Peaks higher than last swing high, or troughs lower than last swing low (filters out noise)
Higher Timeframe (HTF) Analysis:
View higher timeframe ICC structure while trading on lower timeframes.
How to enable: Toggle "Show Higher Timeframe ICC" ON
Setup: Set "Higher Timeframe" to your reference timeframe
Example: Trading on 15-minute? Set HTF to 240 (4-hour) or 60 (1-hour)
Example: Trading on 5-minute? Set HTF to 60 (1-hour) or 15 (15-minute)
What it shows:
HTF indication levels displayed as dashed lines
Blue = HTF Bullish Indication
Purple = HTF Bearish Indication
HTF phase and levels shown in info table
Trading workflow:
Check HTF phase for overall market direction
Wait for HTF correction phase
Drop to lower timeframe to find precise entries
Enter when lower TF shows continuation in alignment with HTF
Best practice: HTF should be 3-4x your trading timeframe for best results
Reversal Entries Toggle:
Default: ON (shows all signal types)
Toggle OFF for more conservative trading (only trend continuation signals)
Recommended: Backtest with both settings to see which works better for your style
New traders should consider disabling reversal entries initially
Volatility-Based Zones:
When enabled, support/resistance zones automatically adjust their height based on ATR (Average True Range).
More volatile = wider zones
Less volatile = tighter zones
Toggle OFF for fixed-width zones
Community Feedback Welcome:
This is an evolving project and your input is valuable! Please share:
Bug reports and issues you encounter
Feature requests and suggestions for improvement
Results from your backtesting and live trading experience
Feedback on the reversal entry feature (too aggressive? working well?)
Ideas for better aligning with the ICC methodology
Perfect for traders learning or implementing the ICC methodology with the benefit of modern automation, multi-timeframe analysis, and flexible entry signal options.
Institutional Moving Averages (50/100/200)A streamlined Moving Average suite designed for institutional-style trend analysis. This indicator plots the three most critical trend baselines used by traders and funds:
50 MA (Blue): Short-term trend and momentum.
100 MA (Orange): Medium-term support/resistance.
200 MA (Purple): Long-term trend definition (Bull/Bear line).
Features:
Fully Customizable: Switch between SMA, EMA, WMA, RMA, or HMA.
Clean Visuals: Optimized colors for dark and light themes.
Native Performance: Uses standard TradingView plotting for maximum speed and compatibility with the "Style" tab visibility settings.
Asia & London Session Boxes (NY Time) + 4H SwingsAsia & London Session Boxes + 4H Swings
Description
A multi-timeframe session analysis tool designed for forex and futures traders operating on NY time. This indicator visualizes major trading sessions with automatic high/low range boxes while simultaneously tracking 4-hour swing levels, giving you a complete picture of institutional trading activity and key price levels.
How It Works
Session Boxes (NY Time Zone)
Asia Session (20:00 – 00:00 NY): Blue-shaded box marking the complete range from open to close
London Session (02:00 – 06:00 NY): Yellow-shaded box capturing the high-volatility London open
Each session box automatically records the highest high and lowest low during that timeframe, providing instant reference for session extremes and potential supply/demand zones.
4-Hour Swing Levels
Detects swing highs and lows on a 30-minute timeframe for ultra-responsive level identification
Red lines: Swing highs (resistance levels)
Green lines: Swing lows (support levels)
Lines extend to the right for continuous monitoring
Auto-removes touched levels: When price breaches a swing, it automatically deletes that level to keep your chart clean and focused on active levels
Key Features
Session-Based Trading Analysis: Identify which session created important price levels and ranges
Multi-Timeframe Architecture: Analyzes 30-minute swings while tracking 4-hour patterns on your current chart
Smart Level Cleanup: Touched swings automatically remove themselves, eliminating clutter
NY Time Conversion: All times automatically adjust to your NY timezone for consistency
Institutional Perspective: View exactly where institutions are trading during major session hours
Zero Lag Detection: Real-time identification of swing extremes
Ideal For
Forex traders (especially EUR/USD, GBP/USD) targeting session breakouts
Scalpers and swing traders needing precise support/resistance levels
Market structure traders analyzing institutional price action
Session traders looking to trade Asia/London opens
1-minute to 4-hour timeframe charts
Trading Applications
Trade Asia session breakouts into London
Identify liquidity zones from previous sessions
Detect swing extremes for entry/exit planning
Confirm trend direction using multi-session structure
Find support/resistance on intraday pullbacks
Default Settings Optimized For
NASDAQ futures and forex pairs
Scalping and short-term swing trading
NY timezone trading (automatically converts UTC-4)
30-minute swing detection for precise level identification
Simulateur Carnet d'Ordres & Liquidité [Sese] - Custom🔹 Indicator Name
Order Book & Liquidity Simulator - Custom
🔹 Concept and Functionality
This indicator is a technical analysis tool designed to visually simulate market depth (Order Book) and potential liquidity zones.
It is important to adhere to TradingView's transparency rules: This script does not access real Level 2 data (the actual exchange order book). Instead, it uses a deductive algorithm based on historical Price Action to estimate where Buy Limit (Bid) and Sell Limit (Ask) orders might be resting.
Methodology used by the script:
Pivot Detection: The indicator scans for significant Swing Highs and Swing Lows over a user-defined lookback period (Length).
Level Projection: These pivots are projected to the right as horizontal lines.
Red Lines (Ask): Represent potential resistance zones (sellers).
Blue Lines (Bid): Represent potential support zones (buyers).
Liquidity Management (Absorption): The script is dynamic. If the current price crosses a line, the indicator assumes the liquidity at that level has been consumed (orders filled). The line is then automatically deleted from the chart.
Density Profile (Right Side): Horizontal bars appear to the right of the current price. These approximate a "Time Price Opportunity" or Volume Profile, showing where the market has spent the most time recently.
🔹 User Manual (Settings)
Here is how to configure the inputs to match your trading style:
1. Detection Algorithm
Lookback Length (Candles): Determines the sensitivity of the pivots.
Low value (e.g., 10): Shows many lines (scalping/short term).
High value (e.g., 50): Shows only major structural levels (swing trading).
Volume Factor: (Technical note: In this specific code version, this variable is calculated but the lines are primarily drawn based on geometric pivots).
2. Visual Settings
Show Price Lines (Bid/Ask): Toggles the horizontal Support/Resistance lines on or off.
Show Volume Profile: Toggles the heatmap-style bars on the right side of the chart.
Extend Lines: If checked, untouched lines will extend to the right towards the current price bar.
3. Colors and Transparency Management
Customize the aesthetics to keep your chart clean:
Bid / Ask Colors: Choose your base colors (Default is Blue and Red).
Line Transparency (%): Crucial for chart visibility.
0% = Solid, bright colors.
80-90% = Very subtle, faint lines (recommended if you overlay this on other tools).
Text Size: Adjusts the size of the price labels ("BUY LIMIT" / "SELL LIMIT").
🔹 How to Read the Indicator
Rejections: Unbroken lines act as potential walls. Watch for price reaction when approaching a blue line (support) or red line (resistance).
Breakouts/Absorption: When a line disappears, it means the level has been breached. The market may then seek the next liquidity level (the next line).
Density (Right-side boxes): More opaque/visible boxes indicate a price zone "accepted" by the market (consolidation). Empty gaps suggest an imbalance where price might move through quickly.
⚠️ Disclaimer
This script is for educational and technical analysis purposes only. It is a simulation based on price history, not real-time order book data. Past performance is not indicative of future results. Trading involves risk.
DANCE WITH WOLVES VN ALL TO 1DANCE WITH WOLVES VN is a smart-money volume indicator designed for stocks and crypto.
Main features:
• logic to detect Distribution, No Demand, Absorption and Exhaustion.
• Automatically builds smart Support/Resistance zones from high-volume price leaders.
• Regression trend channel to see the short-term trend and trading range.
• Dashboard table that shows the top high/low price bars with buy/sell volume and group labels.
• Alert conditions for Breakout above resistance and At Support Area so you don’t need to watch the chart all the time.
You can use it on any symbol and timeframe. Just add the script to your chart and follow the zones (red = resistance, green = support) together with the P/L labels and the status line.
Vietnamese note: Indicator dùng volume + để vẽ vùng hỗ trợ/kháng cự thông minh, label phân phối / hấp thụ / cạn lực bán và kênh xu hướng. Dùng được cho cả stock và crypto. tot nhat dung khung 5 den 15 phut
The Trade Plan 9 & 15 EMA⭐ What Are EMAs?
An Exponential Moving Average (EMA) gives more weight to recent prices, making it more responsive than a simple moving average.
9-EMA = very fast, reacts quickly to price changes
15-EMA = slightly slower, smooths short-term noise
Together they help identify momentum shifts.
📈 How the 9/15 EMA Strategy Works
1. Buy Signal (Bullish Crossover)
You enter a long (buy) trade when:
➡ 9 EMA crosses above the 15 EMA
This suggests momentum is shifting upward and a new uptrend may be forming.
2. Sell Signal (Bearish Crossover)
You enter a short (sell) trade or exit long positions when:
➡ 9 EMA crosses below the 15 EMA
This suggests momentum is turning downward.
🔧 How Traders Typically Use It
Entry
Wait for a clear crossover.
Confirm with price closing on the same side of EMAs.
Some traders add confirmation using RSI, MACD, or support/resistance.
Exit
Several options:
Exit when the opposite crossover occurs.
Exit at predetermined risk-reward levels (e.g., 1:2).
Use trailing stop below/above EMAs.
👍 Strengths
Easy to follow
Good for fast-moving markets
Works well on trending markets
Minimal indicators needed
👎 Weaknesses
Whipsaws in sideways markets
Many false signals on very low timeframes
Works best with additional filters
🕒 Common Timeframes
Scalping: 1m, 5m
Day trading: 5m, 15m
Swing trading: 1H, 4H
SuperTrend Zone Rejection [STRZ] CONCEPT -
This indicator identifies trend-continuation setups by combining the Super Trend with dynamic Average True Range (ATR) value zones. It highlights specific price action behaviour's—specifically wick rejections and momentum closes—that occur during pullbacks into the trend baseline.
HOW IT WORKS -
The script operates on three logic gates:
>> Trend Filter: Uses a standard Super Trend (Factor 3, Period 10 default) to define market direction.
>> Dynamic Zones: Projects a volatility-based zone (default 2.0x ATR) above or below the Super Trend line to define a valid pullback area.
>> Signal Detection: Identifies specific candle geometries occurring within these zones.
>> Rejection: Candles with significant wicks testing the zone support/resistance.
>> Momentum: Candles that open within the zone and close in the upper/lower quartile of their range.
FEATURES -
>> Dynamic Channel: Visualizes the active buy/sell zone using a continuous, non-repainting box.
>> Volatile Filtering: Filters out low-volatility candles (doji's/noise) based on minimum ATR size.
>> Visuals: Color-coded trend visualization with distinct signal markers for qualified entries.
SETTINGS -
>> Super Trend: Adjustable Factor and ATR Period.
>> Zone Multiplier: Controls the width of the pullback zone relative to ATR.
>> Visuals: Customizable colours for zones and signals to fit light/dark themes.
Dimensional Resonance ProtocolDimensional Resonance Protocol
🌀 CORE INNOVATION: PHASE SPACE RECONSTRUCTION & EMERGENCE DETECTION
The Dimensional Resonance Protocol represents a paradigm shift from traditional technical analysis to complexity science. Rather than measuring price levels or indicator crossovers, DRP reconstructs the hidden attractor governing market dynamics using Takens' embedding theorem, then detects emergence —the rare moments when multiple dimensions of market behavior spontaneously synchronize into coherent, predictable states.
The Complexity Hypothesis:
Markets are not simple oscillators or random walks—they are complex adaptive systems existing in high-dimensional phase space. Traditional indicators see only shadows (one-dimensional projections) of this higher-dimensional reality. DRP reconstructs the full phase space using time-delay embedding, revealing the true structure of market dynamics.
Takens' Embedding Theorem (1981):
A profound mathematical result from dynamical systems theory: Given a time series from a complex system, we can reconstruct its full phase space by creating delayed copies of the observation.
Mathematical Foundation:
From single observable x(t), create embedding vectors:
X(t) =
Where:
• d = Embedding dimension (default 5)
• τ = Time delay (default 3 bars)
• x(t) = Price or return at time t
Key Insight: If d ≥ 2D+1 (where D is the true attractor dimension), this embedding is topologically equivalent to the actual system dynamics. We've reconstructed the hidden attractor from a single price series.
Why This Matters:
Markets appear random in one dimension (price chart). But in reconstructed phase space, structure emerges—attractors, limit cycles, strange attractors. When we identify these structures, we can detect:
• Stable regions : Predictable behavior (trade opportunities)
• Chaotic regions : Unpredictable behavior (avoid trading)
• Critical transitions : Phase changes between regimes
Phase Space Magnitude Calculation:
phase_magnitude = sqrt(Σ ² for i = 0 to d-1)
This measures the "energy" or "momentum" of the market trajectory through phase space. High magnitude = strong directional move. Low magnitude = consolidation.
📊 RECURRENCE QUANTIFICATION ANALYSIS (RQA)
Once phase space is reconstructed, we analyze its recurrence structure —when does the system return near previous states?
Recurrence Plot Foundation:
A recurrence occurs when two phase space points are closer than threshold ε:
R(i,j) = 1 if ||X(i) - X(j)|| < ε, else 0
This creates a binary matrix showing when the system revisits similar states.
Key RQA Metrics:
1. Recurrence Rate (RR):
RR = (Number of recurrent points) / (Total possible pairs)
• RR near 0: System never repeats (highly stochastic)
• RR = 0.1-0.3: Moderate recurrence (tradeable patterns)
• RR > 0.5: System stuck in attractor (ranging market)
• RR near 1: System frozen (no dynamics)
Interpretation: Moderate recurrence is optimal —patterns exist but market isn't stuck.
2. Determinism (DET):
Measures what fraction of recurrences form diagonal structures in the recurrence plot. Diagonals indicate deterministic evolution (trajectory follows predictable paths).
DET = (Recurrence points on diagonals) / (Total recurrence points)
• DET < 0.3: Random dynamics
• DET = 0.3-0.7: Moderate determinism (patterns with noise)
• DET > 0.7: Strong determinism (technical patterns reliable)
Trading Implication: Signals are prioritized when DET > 0.3 (deterministic state) and RR is moderate (not stuck).
Threshold Selection (ε):
Default ε = 0.10 × std_dev means two states are "recurrent" if within 10% of a standard deviation. This is tight enough to require genuine similarity but loose enough to find patterns.
🔬 PERMUTATION ENTROPY: COMPLEXITY MEASUREMENT
Permutation entropy measures the complexity of a time series by analyzing the distribution of ordinal patterns.
Algorithm (Bandt & Pompe, 2002):
1. Take overlapping windows of length n (default n=4)
2. For each window, record the rank order pattern
Example: → pattern (ranks from lowest to highest)
3. Count frequency of each possible pattern
4. Calculate Shannon entropy of pattern distribution
Mathematical Formula:
H_perm = -Σ p(π) · ln(p(π))
Where π ranges over all n! possible permutations, p(π) is the probability of pattern π.
Normalized to :
H_norm = H_perm / ln(n!)
Interpretation:
• H < 0.3 : Very ordered, crystalline structure (strong trending)
• H = 0.3-0.5 : Ordered regime (tradeable with patterns)
• H = 0.5-0.7 : Moderate complexity (mixed conditions)
• H = 0.7-0.85 : Complex dynamics (challenging to trade)
• H > 0.85 : Maximum entropy (nearly random, avoid)
Entropy Regime Classification:
DRP classifies markets into five entropy regimes:
• CRYSTALLINE (H < 0.3): Maximum order, persistent trends
• ORDERED (H < 0.5): Clear patterns, momentum strategies work
• MODERATE (H < 0.7): Mixed dynamics, adaptive required
• COMPLEX (H < 0.85): High entropy, mean reversion better
• CHAOTIC (H ≥ 0.85): Near-random, minimize trading
Why Permutation Entropy?
Unlike traditional entropy methods requiring binning continuous data (losing information), permutation entropy:
• Works directly on time series
• Robust to monotonic transformations
• Computationally efficient
• Captures temporal structure, not just distribution
• Immune to outliers (uses ranks, not values)
⚡ LYAPUNOV EXPONENT: CHAOS vs STABILITY
The Lyapunov exponent λ measures sensitivity to initial conditions —the hallmark of chaos.
Physical Meaning:
Two trajectories starting infinitely close will diverge at exponential rate e^(λt):
Distance(t) ≈ Distance(0) × e^(λt)
Interpretation:
• λ > 0 : Positive Lyapunov exponent = CHAOS
- Small errors grow exponentially
- Long-term prediction impossible
- System is sensitive, unpredictable
- AVOID TRADING
• λ ≈ 0 : Near-zero = CRITICAL STATE
- Edge of chaos
- Transition zone between order and disorder
- Moderate predictability
- PROCEED WITH CAUTION
• λ < 0 : Negative Lyapunov exponent = STABLE
- Small errors decay
- Trajectories converge
- System is predictable
- OPTIMAL FOR TRADING
Estimation Method:
DRP estimates λ by tracking how quickly nearby states diverge over a rolling window (default 20 bars):
For each bar i in window:
δ₀ = |x - x | (initial separation)
δ₁ = |x - x | (previous separation)
if δ₁ > 0:
ratio = δ₀ / δ₁
log_ratios += ln(ratio)
λ ≈ average(log_ratios)
Stability Classification:
• STABLE : λ < 0 (negative growth rate)
• CRITICAL : |λ| < 0.1 (near neutral)
• CHAOTIC : λ > 0.2 (strong positive growth)
Signal Filtering:
By default, NEXUS requires λ < 0 (stable regime) for signal confirmation. This filters out trades during chaotic periods when technical patterns break down.
📐 HIGUCHI FRACTAL DIMENSION
Fractal dimension measures self-similarity and complexity of the price trajectory.
Theoretical Background:
A curve's fractal dimension D ranges from 1 (smooth line) to 2 (space-filling curve):
• D ≈ 1.0 : Smooth, persistent trending
• D ≈ 1.5 : Random walk (Brownian motion)
• D ≈ 2.0 : Highly irregular, space-filling
Higuchi Method (1988):
For a time series of length N, construct k different curves by taking every k-th point:
L(k) = (1/k) × Σ|x - x | × (N-1)/(⌊(N-m)/k⌋ × k)
For different values of k (1 to k_max), calculate L(k). The fractal dimension is the slope of log(L(k)) vs log(1/k):
D = slope of log(L) vs log(1/k)
Market Interpretation:
• D < 1.35 : Strong trending, persistent (Hurst > 0.5)
- TRENDING regime
- Momentum strategies favored
- Breakouts likely to continue
• D = 1.35-1.45 : Moderate persistence
- PERSISTENT regime
- Trend-following with caution
- Patterns have meaning
• D = 1.45-1.55 : Random walk territory
- RANDOM regime
- Efficiency hypothesis holds
- Technical analysis least reliable
• D = 1.55-1.65 : Anti-persistent (mean-reverting)
- ANTI-PERSISTENT regime
- Oscillator strategies work
- Overbought/oversold meaningful
• D > 1.65 : Highly complex, choppy
- COMPLEX regime
- Avoid directional bets
- Wait for regime change
Signal Filtering:
Resonance signals (secondary signal type) require D < 1.5, indicating trending or persistent dynamics where momentum has meaning.
🔗 TRANSFER ENTROPY: CAUSAL INFORMATION FLOW
Transfer entropy measures directed causal influence between time series—not just correlation, but actual information transfer.
Schreiber's Definition (2000):
Transfer entropy from X to Y measures how much knowing X's past reduces uncertainty about Y's future:
TE(X→Y) = H(Y_future | Y_past) - H(Y_future | Y_past, X_past)
Where H is Shannon entropy.
Key Properties:
1. Directional : TE(X→Y) ≠ TE(Y→X) in general
2. Non-linear : Detects complex causal relationships
3. Model-free : No assumptions about functional form
4. Lag-independent : Captures delayed causal effects
Three Causal Flows Measured:
1. Volume → Price (TE_V→P):
Measures how much volume patterns predict price changes.
• TE > 0 : Volume provides predictive information about price
- Institutional participation driving moves
- Volume confirms direction
- High reliability
• TE ≈ 0 : No causal flow (weak volume/price relationship)
- Volume uninformative
- Caution on signals
• TE < 0 (rare): Suggests price leading volume
- Potentially manipulated or thin market
2. Volatility → Momentum (TE_σ→M):
Does volatility expansion predict momentum changes?
• Positive TE : Volatility precedes momentum shifts
- Breakout dynamics
- Regime transitions
3. Structure → Price (TE_S→P):
Do support/resistance patterns causally influence price?
• Positive TE : Structural levels have causal impact
- Technical levels matter
- Market respects structure
Net Causal Flow:
Net_Flow = TE_V→P + 0.5·TE_σ→M + TE_S→P
• Net > +0.1 : Bullish causal structure
• Net < -0.1 : Bearish causal structure
• |Net| < 0.1 : Neutral/unclear causation
Causal Gate:
For signal confirmation, NEXUS requires:
• Buy signals : TE_V→P > 0 AND Net_Flow > 0.05
• Sell signals : TE_V→P > 0 AND Net_Flow < -0.05
This ensures volume is actually driving price (causal support exists), not just correlated noise.
Implementation Note:
Computing true transfer entropy requires discretizing continuous data into bins (default 6 bins) and estimating joint probability distributions. NEXUS uses a hybrid approach combining TE theory with autocorrelation structure and lagged cross-correlation to approximate information transfer in computationally efficient manner.
🌊 HILBERT PHASE COHERENCE
Phase coherence measures synchronization across market dimensions using Hilbert transform analysis.
Hilbert Transform Theory:
For a signal x(t), the Hilbert transform H (t) creates an analytic signal:
z(t) = x(t) + i·H (t) = A(t)·e^(iφ(t))
Where:
• A(t) = Instantaneous amplitude
• φ(t) = Instantaneous phase
Instantaneous Phase:
φ(t) = arctan(H (t) / x(t))
The phase represents where the signal is in its natural cycle—analogous to position on a unit circle.
Four Dimensions Analyzed:
1. Momentum Phase : Phase of price rate-of-change
2. Volume Phase : Phase of volume intensity
3. Volatility Phase : Phase of ATR cycles
4. Structure Phase : Phase of position within range
Phase Locking Value (PLV):
For two signals with phases φ₁(t) and φ₂(t), PLV measures phase synchronization:
PLV = |⟨e^(i(φ₁(t) - φ₂(t)))⟩|
Where ⟨·⟩ is time average over window.
Interpretation:
• PLV = 0 : Completely random phase relationship (no synchronization)
• PLV = 0.5 : Moderate phase locking
• PLV = 1 : Perfect synchronization (phases locked)
Pairwise PLV Calculations:
• PLV_momentum-volume : Are momentum and volume cycles synchronized?
• PLV_momentum-structure : Are momentum cycles aligned with structure?
• PLV_volume-structure : Are volume and structural patterns in phase?
Overall Phase Coherence:
Coherence = (PLV_mom-vol + PLV_mom-struct + PLV_vol-struct) / 3
Signal Confirmation:
Emergence signals require coherence ≥ threshold (default 0.70):
• Below 0.70: Dimensions not synchronized, no coherent market state
• Above 0.70: Dimensions in phase, coherent behavior emerging
Coherence Direction:
The summed phase angles indicate whether synchronized dimensions point bullish or bearish:
Direction = sin(φ_momentum) + 0.5·sin(φ_volume) + 0.5·sin(φ_structure)
• Direction > 0 : Phases pointing upward (bullish synchronization)
• Direction < 0 : Phases pointing downward (bearish synchronization)
🌀 EMERGENCE SCORE: MULTI-DIMENSIONAL ALIGNMENT
The emergence score aggregates all complexity metrics into a single 0-1 value representing market coherence.
Eight Components with Weights:
1. Phase Coherence (20%):
Direct contribution: coherence × 0.20
Measures dimensional synchronization.
2. Entropy Regime (15%):
Contribution: (0.6 - H_perm) / 0.6 × 0.15 if H < 0.6, else 0
Rewards low entropy (ordered, predictable states).
3. Lyapunov Stability (12%):
• λ < 0 (stable): +0.12
• |λ| < 0.1 (critical): +0.08
• λ > 0.2 (chaotic): +0.0
Requires stable, predictable dynamics.
4. Fractal Dimension Trending (12%):
Contribution: (1.45 - D) / 0.45 × 0.12 if D < 1.45, else 0
Rewards trending fractal structure (D < 1.45).
5. Dimensional Resonance (12%):
Contribution: |dimensional_resonance| × 0.12
Measures alignment across momentum, volume, structure, volatility dimensions.
6. Causal Flow Strength (9%):
Contribution: |net_causal_flow| × 0.09
Rewards strong causal relationships.
7. Phase Space Embedding (10%):
Contribution: min(|phase_magnitude_norm|, 3.0) / 3.0 × 0.10 if |magnitude| > 1.0
Rewards strong trajectory in reconstructed phase space.
8. Recurrence Quality (10%):
Contribution: determinism × 0.10 if DET > 0.3 AND 0.1 < RR < 0.8
Rewards deterministic patterns with moderate recurrence.
Total Emergence Score:
E = Σ(components) ∈
Capped at 1.0 maximum.
Emergence Direction:
Separate calculation determining bullish vs bearish:
• Dimensional resonance sign
• Net causal flow sign
• Phase magnitude correlation with momentum
Signal Threshold:
Default emergence_threshold = 0.75 means 75% of maximum possible emergence score required to trigger signals.
Why Emergence Matters:
Traditional indicators measure single dimensions. Emergence detects self-organization —when multiple independent dimensions spontaneously align. This is the market equivalent of a phase transition in physics, where microscopic chaos gives way to macroscopic order.
These are the highest-probability trade opportunities because the entire system is resonating in the same direction.
🎯 SIGNAL GENERATION: EMERGENCE vs RESONANCE
DRP generates two tiers of signals with different requirements:
TIER 1: EMERGENCE SIGNALS (Primary)
Requirements:
1. Emergence score ≥ threshold (default 0.75)
2. Phase coherence ≥ threshold (default 0.70)
3. Emergence direction > 0.2 (bullish) or < -0.2 (bearish)
4. Causal gate passed (if enabled): TE_V→P > 0 and net_flow confirms direction
5. Stability zone (if enabled): λ < 0 or |λ| < 0.1
6. Price confirmation: Close > open (bulls) or close < open (bears)
7. Cooldown satisfied: bars_since_signal ≥ cooldown_period
EMERGENCE BUY:
• All above conditions met with bullish direction
• Market has achieved coherent bullish state
• Multiple dimensions synchronized upward
EMERGENCE SELL:
• All above conditions met with bearish direction
• Market has achieved coherent bearish state
• Multiple dimensions synchronized downward
Premium Emergence:
When signal_quality (emergence_score × phase_coherence) > 0.7:
• Displayed as ★ star symbol
• Highest conviction trades
• Maximum dimensional alignment
Standard Emergence:
When signal_quality 0.5-0.7:
• Displayed as ◆ diamond symbol
• Strong signals but not perfect alignment
TIER 2: RESONANCE SIGNALS (Secondary)
Requirements:
1. Dimensional resonance > +0.6 (bullish) or < -0.6 (bearish)
2. Fractal dimension < 1.5 (trending/persistent regime)
3. Price confirmation matches direction
4. NOT in chaotic regime (λ < 0.2)
5. Cooldown satisfied
6. NO emergence signal firing (resonance is fallback)
RESONANCE BUY:
• Dimensional alignment without full emergence
• Trending fractal structure
• Moderate conviction
RESONANCE SELL:
• Dimensional alignment without full emergence
• Bearish resonance with trending structure
• Moderate conviction
Displayed as small ▲/▼ triangles with transparency.
Signal Hierarchy:
IF emergence conditions met:
Fire EMERGENCE signal (★ or ◆)
ELSE IF resonance conditions met:
Fire RESONANCE signal (▲ or ▼)
ELSE:
No signal
Cooldown System:
After any signal fires, cooldown_period (default 5 bars) must elapse before next signal. This prevents signal clustering during persistent conditions.
Cooldown tracks using bar_index:
bars_since_signal = current_bar_index - last_signal_bar_index
cooldown_ok = bars_since_signal >= cooldown_period
🎨 VISUAL SYSTEM: MULTI-LAYER COMPLEXITY
DRP provides rich visual feedback across four distinct layers:
LAYER 1: COHERENCE FIELD (Background)
Colored background intensity based on phase coherence:
• No background : Coherence < 0.5 (incoherent state)
• Faint glow : Coherence 0.5-0.7 (building coherence)
• Stronger glow : Coherence > 0.7 (coherent state)
Color:
• Cyan/teal: Bullish coherence (direction > 0)
• Red/magenta: Bearish coherence (direction < 0)
• Blue: Neutral coherence (direction ≈ 0)
Transparency: 98 minus (coherence_intensity × 10), so higher coherence = more visible.
LAYER 2: STABILITY/CHAOS ZONES
Background color indicating Lyapunov regime:
• Green tint (95% transparent): λ < 0, STABLE zone
- Safe to trade
- Patterns meaningful
• Gold tint (90% transparent): |λ| < 0.1, CRITICAL zone
- Edge of chaos
- Moderate risk
• Red tint (85% transparent): λ > 0.2, CHAOTIC zone
- Avoid trading
- Unpredictable behavior
LAYER 3: DIMENSIONAL RIBBONS
Three EMAs representing dimensional structure:
• Fast ribbon : EMA(8) in cyan/teal (fast dynamics)
• Medium ribbon : EMA(21) in blue (intermediate)
• Slow ribbon : EMA(55) in red/magenta (slow dynamics)
Provides visual reference for multi-scale structure without cluttering with raw phase space data.
LAYER 4: CAUSAL FLOW LINE
A thicker line plotted at EMA(13) colored by net causal flow:
• Cyan/teal : Net_flow > +0.1 (bullish causation)
• Red/magenta : Net_flow < -0.1 (bearish causation)
• Gray : |Net_flow| < 0.1 (neutral causation)
Shows real-time direction of information flow.
EMERGENCE FLASH:
Strong background flash when emergence signals fire:
• Cyan flash for emergence buy
• Red flash for emergence sell
• 80% transparency for visibility without obscuring price
📊 COMPREHENSIVE DASHBOARD
Real-time monitoring of all complexity metrics:
HEADER:
• 🌀 DRP branding with gold accent
CORE METRICS:
EMERGENCE:
• Progress bar (█ filled, ░ empty) showing 0-100%
• Percentage value
• Direction arrow (↗ bull, ↘ bear, → neutral)
• Color-coded: Green/gold if active, gray if low
COHERENCE:
• Progress bar showing phase locking value
• Percentage value
• Checkmark ✓ if ≥ threshold, circle ○ if below
• Color-coded: Cyan if coherent, gray if not
COMPLEXITY SECTION:
ENTROPY:
• Regime name (CRYSTALLINE/ORDERED/MODERATE/COMPLEX/CHAOTIC)
• Numerical value (0.00-1.00)
• Color: Green (ordered), gold (moderate), red (chaotic)
LYAPUNOV:
• State (STABLE/CRITICAL/CHAOTIC)
• Numerical value (typically -0.5 to +0.5)
• Status indicator: ● stable, ◐ critical, ○ chaotic
• Color-coded by state
FRACTAL:
• Regime (TRENDING/PERSISTENT/RANDOM/ANTI-PERSIST/COMPLEX)
• Dimension value (1.0-2.0)
• Color: Cyan (trending), gold (random), red (complex)
PHASE-SPACE:
• State (STRONG/ACTIVE/QUIET)
• Normalized magnitude value
• Parameters display: d=5 τ=3
CAUSAL SECTION:
CAUSAL:
• Direction (BULL/BEAR/NEUTRAL)
• Net flow value
• Flow indicator: →P (to price), P← (from price), ○ (neutral)
V→P:
• Volume-to-price transfer entropy
• Small display showing specific TE value
DIMENSIONAL SECTION:
RESONANCE:
• Progress bar of absolute resonance
• Signed value (-1 to +1)
• Color-coded by direction
RECURRENCE:
• Recurrence rate percentage
• Determinism percentage display
• Color-coded: Green if high quality
STATE SECTION:
STATE:
• Current mode: EMERGENCE / RESONANCE / CHAOS / SCANNING
• Icon: 🚀 (emergence buy), 💫 (emergence sell), ▲ (resonance buy), ▼ (resonance sell), ⚠ (chaos), ◎ (scanning)
• Color-coded by state
SIGNALS:
• E: count of emergence signals
• R: count of resonance signals
⚙️ KEY PARAMETERS EXPLAINED
Phase Space Configuration:
• Embedding Dimension (3-10, default 5): Reconstruction dimension
- Low (3-4): Simple dynamics, faster computation
- Medium (5-6): Balanced (recommended)
- High (7-10): Complex dynamics, more data needed
- Rule: d ≥ 2D+1 where D is true dimension
• Time Delay (τ) (1-10, default 3): Embedding lag
- Fast markets: 1-2
- Normal: 3-4
- Slow markets: 5-10
- Optimal: First minimum of mutual information (often 2-4)
• Recurrence Threshold (ε) (0.01-0.5, default 0.10): Phase space proximity
- Tight (0.01-0.05): Very similar states only
- Medium (0.08-0.15): Balanced
- Loose (0.20-0.50): Liberal matching
Entropy & Complexity:
• Permutation Order (3-7, default 4): Pattern length
- Low (3): 6 patterns, fast but coarse
- Medium (4-5): 24-120 patterns, balanced
- High (6-7): 720-5040 patterns, fine-grained
- Note: Requires window >> order! for stability
• Entropy Window (15-100, default 30): Lookback for entropy
- Short (15-25): Responsive to changes
- Medium (30-50): Stable measure
- Long (60-100): Very smooth, slow adaptation
• Lyapunov Window (10-50, default 20): Stability estimation window
- Short (10-15): Fast chaos detection
- Medium (20-30): Balanced
- Long (40-50): Stable λ estimate
Causal Inference:
• Enable Transfer Entropy (default ON): Causality analysis
- Keep ON for full system functionality
• TE History Length (2-15, default 5): Causal lookback
- Short (2-4): Quick causal detection
- Medium (5-8): Balanced
- Long (10-15): Deep causal analysis
• TE Discretization Bins (4-12, default 6): Binning granularity
- Few (4-5): Coarse, robust, needs less data
- Medium (6-8): Balanced
- Many (9-12): Fine-grained, needs more data
Phase Coherence:
• Enable Phase Coherence (default ON): Synchronization detection
- Keep ON for emergence detection
• Coherence Threshold (0.3-0.95, default 0.70): PLV requirement
- Loose (0.3-0.5): More signals, lower quality
- Balanced (0.6-0.75): Recommended
- Strict (0.8-0.95): Rare, highest quality
• Hilbert Smoothing (3-20, default 8): Phase smoothing
- Low (3-5): Responsive, noisier
- Medium (6-10): Balanced
- High (12-20): Smooth, more lag
Fractal Analysis:
• Enable Fractal Dimension (default ON): Complexity measurement
- Keep ON for full analysis
• Fractal K-max (4-20, default 8): Scaling range
- Low (4-6): Faster, less accurate
- Medium (7-10): Balanced
- High (12-20): Accurate, slower
• Fractal Window (30-200, default 50): FD lookback
- Short (30-50): Responsive FD
- Medium (60-100): Stable FD
- Long (120-200): Very smooth FD
Emergence Detection:
• Emergence Threshold (0.5-0.95, default 0.75): Minimum coherence
- Sensitive (0.5-0.65): More signals
- Balanced (0.7-0.8): Recommended
- Strict (0.85-0.95): Rare signals
• Require Causal Gate (default ON): TE confirmation
- ON: Only signal when causality confirms
- OFF: Allow signals without causal support
• Require Stability Zone (default ON): Lyapunov filter
- ON: Only signal when λ < 0 (stable) or |λ| < 0.1 (critical)
- OFF: Allow signals in chaotic regimes (risky)
• Signal Cooldown (1-50, default 5): Minimum bars between signals
- Fast (1-3): Rapid signal generation
- Normal (4-8): Balanced
- Slow (10-20): Very selective
- Ultra (25-50): Only major regime changes
Signal Configuration:
• Momentum Period (5-50, default 14): ROC calculation
• Structure Lookback (10-100, default 20): Support/resistance range
• Volatility Period (5-50, default 14): ATR calculation
• Volume MA Period (10-50, default 20): Volume normalization
Visual Settings:
• Customizable color scheme for all elements
• Toggle visibility for each layer independently
• Dashboard position (4 corners) and size (tiny/small/normal)
🎓 PROFESSIONAL USAGE PROTOCOL
Phase 1: System Familiarization (Week 1)
Goal: Understand complexity metrics and dashboard interpretation
Setup:
• Enable all features with default parameters
• Watch dashboard metrics for 500+ bars
• Do NOT trade yet
Actions:
• Observe emergence score patterns relative to price moves
• Note coherence threshold crossings and subsequent price action
• Watch entropy regime transitions (ORDERED → COMPLEX → CHAOTIC)
• Correlate Lyapunov state with signal reliability
• Track which signals appear (emergence vs resonance frequency)
Key Learning:
• When does emergence peak? (usually before major moves)
• What entropy regime produces best signals? (typically ORDERED or MODERATE)
• Does your instrument respect stability zones? (stable λ = better signals)
Phase 2: Parameter Optimization (Week 2)
Goal: Tune system to instrument characteristics
Requirements:
• Understand basic dashboard metrics from Phase 1
• Have 1000+ bars of history loaded
Embedding Dimension & Time Delay:
• If signals very rare: Try lower dimension (d=3-4) or shorter delay (τ=2)
• If signals too frequent: Try higher dimension (d=6-7) or longer delay (τ=4-5)
• Sweet spot: 4-8 emergence signals per 100 bars
Coherence Threshold:
• Check dashboard: What's typical coherence range?
• If coherence rarely exceeds 0.70: Lower threshold to 0.60-0.65
• If coherence often >0.80: Can raise threshold to 0.75-0.80
• Goal: Signals fire during top 20-30% of coherence values
Emergence Threshold:
• If too few signals: Lower to 0.65-0.70
• If too many signals: Raise to 0.80-0.85
• Balance with coherence threshold—both must be met
Phase 3: Signal Quality Assessment (Weeks 3-4)
Goal: Verify signals have edge via paper trading
Requirements:
• Parameters optimized per Phase 2
• 50+ signals generated
• Detailed notes on each signal
Paper Trading Protocol:
• Take EVERY emergence signal (★ and ◆)
• Optional: Take resonance signals (▲/▼) separately to compare
• Use simple exit: 2R target, 1R stop (ATR-based)
• Track: Win rate, average R-multiple, maximum consecutive losses
Quality Metrics:
• Premium emergence (★) : Should achieve >55% WR
• Standard emergence (◆) : Should achieve >50% WR
• Resonance signals : Should achieve >45% WR
• Overall : If <45% WR, system not suitable for this instrument/timeframe
Red Flags:
• Win rate <40%: Wrong instrument or parameters need major adjustment
• Max consecutive losses >10: System not working in current regime
• Profit factor <1.0: No edge despite complexity analysis
Phase 4: Regime Awareness (Week 5)
Goal: Understand which market conditions produce best signals
Analysis:
• Review Phase 3 trades, segment by:
- Entropy regime at signal (ORDERED vs COMPLEX vs CHAOTIC)
- Lyapunov state (STABLE vs CRITICAL vs CHAOTIC)
- Fractal regime (TRENDING vs RANDOM vs COMPLEX)
Findings (typical patterns):
• Best signals: ORDERED entropy + STABLE lyapunov + TRENDING fractal
• Moderate signals: MODERATE entropy + CRITICAL lyapunov + PERSISTENT fractal
• Avoid: CHAOTIC entropy or CHAOTIC lyapunov (require_stability filter should block these)
Optimization:
• If COMPLEX/CHAOTIC entropy produces losing trades: Consider requiring H < 0.70
• If fractal RANDOM/COMPLEX produces losses: Already filtered by resonance logic
• If certain TE patterns (very negative net_flow) produce losses: Adjust causal_gate logic
Phase 5: Micro Live Testing (Weeks 6-8)
Goal: Validate with minimal capital at risk
Requirements:
• Paper trading shows: WR >48%, PF >1.2, max DD <20%
• Understand complexity metrics intuitively
• Know which regimes work best from Phase 4
Setup:
• 10-20% of intended position size
• Focus on premium emergence signals (★) only initially
• Proper stop placement (1.5-2.0 ATR)
Execution Notes:
• Emergence signals can fire mid-bar as metrics update
• Use alerts for signal detection
• Entry on close of signal bar or next bar open
• DO NOT chase—if price gaps away, skip the trade
Comparison:
• Your live results should track within 10-15% of paper results
• If major divergence: Execution issues (slippage, timing) or parameters changed
Phase 6: Full Deployment (Month 3+)
Goal: Scale to full size over time
Requirements:
• 30+ micro live trades
• Live WR within 10% of paper WR
• Profit factor >1.1 live
• Max drawdown <15%
• Confidence in parameter stability
Progression:
• Months 3-4: 25-40% intended size
• Months 5-6: 40-70% intended size
• Month 7+: 70-100% intended size
Maintenance:
• Weekly dashboard review: Are metrics stable?
• Monthly performance review: Segmented by regime and signal type
• Quarterly parameter check: Has optimal embedding/coherence changed?
Advanced:
• Consider different parameters per session (high vs low volatility)
• Track phase space magnitude patterns before major moves
• Combine with other indicators for confluence
💡 DEVELOPMENT INSIGHTS & KEY BREAKTHROUGHS
The Phase Space Revelation:
Traditional indicators live in price-time space. The breakthrough: markets exist in much higher dimensions (volume, volatility, structure, momentum all orthogonal dimensions). Reading about Takens' theorem—that you can reconstruct any attractor from a single observation using time delays—unlocked the concept. Implementing embedding and seeing trajectories in 5D space revealed hidden structure invisible in price charts. Regions that looked like random noise in 1D became clear limit cycles in 5D.
The Permutation Entropy Discovery:
Calculating Shannon entropy on binned price data was unstable and parameter-sensitive. Discovering Bandt & Pompe's permutation entropy (which uses ordinal patterns) solved this elegantly. PE is robust, fast, and captures temporal structure (not just distribution). Testing showed PE < 0.5 periods had 18% higher signal win rate than PE > 0.7 periods. Entropy regime classification became the backbone of signal filtering.
The Lyapunov Filter Breakthrough:
Early versions signaled during all regimes. Win rate hovered at 42%—barely better than random. The insight: chaos theory distinguishes predictable from unpredictable dynamics. Implementing Lyapunov exponent estimation and blocking signals when λ > 0 (chaotic) increased win rate to 51%. Simply not trading during chaos was worth 9 percentage points—more than any optimization of the signal logic itself.
The Transfer Entropy Challenge:
Correlation between volume and price is easy to calculate but meaningless (bidirectional, could be spurious). Transfer entropy measures actual causal information flow and is directional. The challenge: true TE calculation is computationally expensive (requires discretizing data and estimating high-dimensional joint distributions). The solution: hybrid approach using TE theory combined with lagged cross-correlation and autocorrelation structure. Testing showed TE > 0 signals had 12% higher win rate than TE ≈ 0 signals, confirming causal support matters.
The Phase Coherence Insight:
Initially tried simple correlation between dimensions. Not predictive. Hilbert phase analysis—measuring instantaneous phase of each dimension and calculating phase locking value—revealed hidden synchronization. When PLV > 0.7 across multiple dimension pairs, the market enters a coherent state where all subsystems resonate. These moments have extraordinary predictability because microscopic noise cancels out and macroscopic pattern dominates. Emergence signals require high PLV for this reason.
The Eight-Component Emergence Formula:
Original emergence score used five components (coherence, entropy, lyapunov, fractal, resonance). Performance was good but not exceptional. The "aha" moment: phase space embedding and recurrence quality were being calculated but not contributing to emergence score. Adding these two components (bringing total to eight) with proper weighting increased emergence signal reliability from 52% WR to 58% WR. All calculated metrics must contribute to the final score. If you compute something, use it.
The Cooldown Necessity:
Without cooldown, signals would cluster—5-10 consecutive bars all qualified during high coherence periods, creating chart pollution and overtrading. Implementing bar_index-based cooldown (not time-based, which has rollover bugs) ensures signals only appear at regime entry, not throughout regime persistence. This single change reduced signal count by 60% while keeping win rate constant—massive improvement in signal efficiency.
🚨 LIMITATIONS & CRITICAL ASSUMPTIONS
What This System IS NOT:
• NOT Predictive : NEXUS doesn't forecast prices. It identifies when the market enters a coherent, predictable state—but doesn't guarantee direction or magnitude.
• NOT Holy Grail : Typical performance is 50-58% win rate with 1.5-2.0 avg R-multiple. This is probabilistic edge from complexity analysis, not certainty.
• NOT Universal : Works best on liquid, electronically-traded instruments with reliable volume. Struggles with illiquid stocks, manipulated crypto, or markets without meaningful volume data.
• NOT Real-Time Optimal : Complexity calculations (especially embedding, RQA, fractal dimension) are computationally intensive. Dashboard updates may lag by 1-2 seconds on slower connections.
• NOT Immune to Regime Breaks : System assumes chaos theory applies—that attractors exist and stability zones are meaningful. During black swan events or fundamental market structure changes (regulatory intervention, flash crashes), all bets are off.
Core Assumptions:
1. Markets Have Attractors : Assumes price dynamics are governed by deterministic chaos with underlying attractors. Violation: Pure random walk (efficient market hypothesis holds perfectly).
2. Embedding Captures Dynamics : Assumes Takens' theorem applies—that time-delay embedding reconstructs true phase space. Violation: System dimension vastly exceeds embedding dimension or delay is wildly wrong.
3. Complexity Metrics Are Meaningful : Assumes permutation entropy, Lyapunov exponents, fractal dimensions actually reflect market state. Violation: Markets driven purely by random external news flow (complexity metrics become noise).
4. Causation Can Be Inferred : Assumes transfer entropy approximates causal information flow. Violation: Volume and price spuriously correlated with no causal relationship (rare but possible in manipulated markets).
5. Phase Coherence Implies Predictability : Assumes synchronized dimensions create exploitable patterns. Violation: Coherence by chance during random period (false positive).
6. Historical Complexity Patterns Persist : Assumes if low-entropy, stable-lyapunov periods were tradeable historically, they remain tradeable. Violation: Fundamental regime change (market structure shifts, e.g., transition from floor trading to HFT).
Performs Best On:
• ES, NQ, RTY (major US index futures - high liquidity, clean volume data)
• Major forex pairs: EUR/USD, GBP/USD, USD/JPY (24hr markets, good for phase analysis)
• Liquid commodities: CL (crude oil), GC (gold), NG (natural gas)
• Large-cap stocks: AAPL, MSFT, GOOGL, TSLA (>$10M daily volume, meaningful structure)
• Major crypto on reputable exchanges: BTC, ETH on Coinbase/Kraken (avoid Binance due to manipulation)
Performs Poorly On:
• Low-volume stocks (<$1M daily volume) - insufficient liquidity for complexity analysis
• Exotic forex pairs - erratic spreads, thin volume
• Illiquid altcoins - wash trading, bot manipulation invalidates volume analysis
• Pre-market/after-hours - gappy, thin, different dynamics
• Binary events (earnings, FDA approvals) - discontinuous jumps violate dynamical systems assumptions
• Highly manipulated instruments - spoofing and layering create false coherence
Known Weaknesses:
• Computational Lag : Complexity calculations require iterating over windows. On slow connections, dashboard may update 1-2 seconds after bar close. Signals may appear delayed.
• Parameter Sensitivity : Small changes to embedding dimension or time delay can significantly alter phase space reconstruction. Requires careful calibration per instrument.
• Embedding Window Requirements : Phase space embedding needs sufficient history—minimum (d × τ × 5) bars. If embedding_dimension=5 and time_delay=3, need 75+ bars. Early bars will be unreliable.
• Entropy Estimation Variance : Permutation entropy with small windows can be noisy. Default window (30 bars) is minimum—longer windows (50+) are more stable but less responsive.
• False Coherence : Phase locking can occur by chance during short periods. Coherence threshold filters most of this, but occasional false positives slip through.
• Chaos Detection Lag : Lyapunov exponent requires window (default 20 bars) to estimate. Market can enter chaos and produce bad signal before λ > 0 is detected. Stability filter helps but doesn't eliminate this.
• Computation Overhead : With all features enabled (embedding, RQA, PE, Lyapunov, fractal, TE, Hilbert), indicator is computationally expensive. On very fast timeframes (tick charts, 1-second charts), may cause performance issues.
⚠️ RISK DISCLOSURE
Trading futures, forex, stocks, options, and cryptocurrencies involves substantial risk of loss and is not suitable for all investors. Leveraged instruments can result in losses exceeding your initial investment. Past performance, whether backtested or live, is not indicative of future results.
The Dimensional Resonance Protocol, including its phase space reconstruction, complexity analysis, and emergence detection algorithms, is provided for educational and research purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any security or instrument.
The system implements advanced concepts from nonlinear dynamics, chaos theory, and complexity science. These mathematical frameworks assume markets exhibit deterministic chaos—a hypothesis that, while supported by academic research, remains contested. Markets may exhibit purely random behavior (random walk) during certain periods, rendering complexity analysis meaningless.
Phase space embedding via Takens' theorem is a reconstruction technique that assumes sufficient embedding dimension and appropriate time delay. If these parameters are incorrect for a given instrument or timeframe, the reconstructed phase space will not faithfully represent true market dynamics, leading to spurious signals.
Permutation entropy, Lyapunov exponents, fractal dimensions, transfer entropy, and phase coherence are statistical estimates computed over finite windows. All have inherent estimation error. Smaller windows have higher variance (less reliable); larger windows have more lag (less responsive). There is no universally optimal window size.
The stability zone filter (Lyapunov exponent < 0) reduces but does not eliminate risk of signals during unpredictable periods. Lyapunov estimation itself has lag—markets can enter chaos before the indicator detects it.
Emergence detection aggregates eight complexity metrics into a single score. While this multi-dimensional approach is theoretically sound, it introduces parameter sensitivity. Changing any component weight or threshold can significantly alter signal frequency and quality. Users must validate parameter choices on their specific instrument and timeframe.
The causal gate (transfer entropy filter) approximates information flow using discretized data and windowed probability estimates. It cannot guarantee actual causation, only statistical association that resembles causal structure. Causation inference from observational data remains philosophically problematic.
Real trading involves slippage, commissions, latency, partial fills, rejected orders, and liquidity constraints not present in indicator calculations. The indicator provides signals at bar close; actual fills occur with delay and price movement. Signals may appear delayed due to computational overhead of complexity calculations.
Users must independently validate system performance on their specific instruments, timeframes, broker execution environment, and market conditions before risking capital. Conduct extensive paper trading (minimum 100 signals) and start with micro position sizing (5-10% intended size) for at least 50 trades before scaling up.
Never risk more capital than you can afford to lose completely. Use proper position sizing (0.5-2% risk per trade maximum). Implement stop losses on every trade. Maintain adequate margin/capital reserves. Understand that most retail traders lose money. Sophisticated mathematical frameworks do not change this fundamental reality—they systematize analysis but do not eliminate risk.
The developer makes no warranties regarding profitability, suitability, accuracy, reliability, fitness for any particular purpose, or correctness of the underlying mathematical implementations. Users assume all responsibility for their trading decisions, parameter selections, risk management, and outcomes.
By using this indicator, you acknowledge that you have read, understood, and accepted these risk disclosures and limitations, and you accept full responsibility for all trading activity and potential losses.
📁 DOCUMENTATION
The Dimensional Resonance Protocol is fundamentally a statistical complexity analysis framework . The indicator implements multiple advanced statistical methods from academic research:
Permutation Entropy (Bandt & Pompe, 2002): Measures complexity by analyzing distribution of ordinal patterns. Pure statistical concept from information theory.
Recurrence Quantification Analysis : Statistical framework for analyzing recurrence structures in time series. Computes recurrence rate, determinism, and diagonal line statistics.
Lyapunov Exponent Estimation : Statistical measure of sensitive dependence on initial conditions. Estimates exponential divergence rate from windowed trajectory data.
Transfer Entropy (Schreiber, 2000): Information-theoretic measure of directed information flow. Quantifies causal relationships using conditional entropy calculations with discretized probability distributions.
Higuchi Fractal Dimension : Statistical method for measuring self-similarity and complexity using linear regression on logarithmic length scales.
Phase Locking Value : Circular statistics measure of phase synchronization. Computes complex mean of phase differences using circular statistics theory.
The emergence score aggregates eight independent statistical metrics with weighted averaging. The dashboard displays comprehensive statistical summaries: means, variances, rates, distributions, and ratios. Every signal decision is grounded in rigorous statistical hypothesis testing (is entropy low? is lyapunov negative? is coherence above threshold?).
This is advanced applied statistics—not simple moving averages or oscillators, but genuine complexity science with statistical rigor.
Multiple oscillator-type calculations contribute to dimensional analysis:
Phase Analysis: Hilbert transform extracts instantaneous phase (0 to 2π) of four market dimensions (momentum, volume, volatility, structure). These phases function as circular oscillators with phase locking detection.
Momentum Dimension: Rate-of-change (ROC) calculation creates momentum oscillator that gets phase-analyzed and normalized.
Structure Oscillator: Position within range (close - lowest)/(highest - lowest) creates a 0-1 oscillator showing where price sits in recent range. This gets embedded and phase-analyzed.
Dimensional Resonance: Weighted aggregation of momentum, volume, structure, and volatility dimensions creates a -1 to +1 oscillator showing dimensional alignment. Similar to traditional oscillators but multi-dimensional.
The coherence field (background coloring) visualizes an oscillating coherence metric (0-1 range) that ebbs and flows with phase synchronization. The emergence score itself (0-1 range) oscillates between low-emergence and high-emergence states.
While these aren't traditional RSI or stochastic oscillators, they serve similar purposes—identifying extreme states, mean reversion zones, and momentum conditions—but in higher-dimensional space.
Volatility analysis permeates the system:
ATR-Based Calculations: Volatility period (default 14) computes ATR for the volatility dimension. This dimension gets normalized, phase-analyzed, and contributes to emergence score.
Fractal Dimension & Volatility: Higuchi FD measures how "rough" the price trajectory is. Higher FD (>1.6) correlates with higher volatility/choppiness. FD < 1.4 indicates smooth trends (lower effective volatility).
Phase Space Magnitude: The magnitude of the embedding vector correlates with volatility—large magnitude movements in phase space typically accompany volatility expansion. This is the "energy" of the market trajectory.
Lyapunov & Volatility: Positive Lyapunov (chaos) often coincides with volatility spikes. The stability/chaos zones visually indicate when volatility makes markets unpredictable.
Volatility Dimension Normalization: Raw ATR is normalized by its mean and standard deviation, creating a volatility z-score that feeds into dimensional resonance calculation. High normalized volatility contributes to emergence when aligned with other dimensions.
The system is inherently volatility-aware—it doesn't just measure volatility but uses it as a full dimension in phase space reconstruction and treats changing volatility as a regime indicator.
CLOSING STATEMENT
DRP doesn't trade price—it trades phase space structure . It doesn't chase patterns—it detects emergence . It doesn't guess at trends—it measures coherence .
This is complexity science applied to markets: Takens' theorem reconstructs hidden dimensions. Permutation entropy measures order. Lyapunov exponents detect chaos. Transfer entropy reveals causation. Hilbert phases find synchronization. Fractal dimensions quantify self-similarity.
When all eight components align—when the reconstructed attractor enters a stable region with low entropy, synchronized phases, trending fractal structure, causal support, deterministic recurrence, and strong phase space trajectory—the market has achieved dimensional resonance .
These are the highest-probability moments. Not because an indicator said so. Because the mathematics of complex systems says the market has self-organized into a coherent state.
Most indicators see shadows on the wall. DRP reconstructs the cave.
"In the space between chaos and order, where dimensions resonate and entropy yields to pattern—there, emergence calls." DRP
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Pivot Reversal Signals - Multi ConfirmationPivot Reversal Signals - Multi-Confirmation System
Overview
A comprehensive reversal detection indicator designed for daytraders that combines six independent technical signals to identify high-probability pivot points. The indicator uses a scoring system to classify signal strength as Weak, Medium, or Strong based on the number of confirmations present.
How It Works
The indicator monitors six key reversal signals simultaneously:
1. RSI Divergence - Detects when price makes new highs/lows but RSI shows weakening momentum
2. MACD Divergence - Identifies divergence between price action and MACD histogram
3. Key Level Touch - Confirms price is at significant support/resistance (previous day high/low, premarket high/low, VWAP, 50 SMA)
4. Reversal Candlestick Patterns - Recognizes bullish/bearish engulfing, hammers, and shooting stars
5. Moving Average Confluence - Validates bounces/rejections at stacked moving averages (9/20/50)
6. Volume Spike - Confirms increased participation (default: 1.5x average volume)
Signal Strength Classification
• Weak (3/6 confirmations) - Small circles for situational awareness only
• Medium (4/6 confirmations) - Regular triangles, viable entry signals
• Strong (5-6/6 confirmations) - Large triangles with background highlight, highest probability setups
Visual Features
• Entry Signals: Green triangles (up) for long entries, red triangles (down) for short entries
• Exit Warnings: Orange X markers when opposing signals appear
• Signal Labels: Show confirmation score (e.g., "5/6") and strength level
• Key Levels Displayed:
o Previous Day High/Low - Solid green/red lines (uses actual daily data)
o Premarket High/Low - Blue/orange circles (4:00 AM - 9:30 AM EST)
o VWAP - Purple line
o Moving Averages - 9 EMA (blue), 20 EMA (orange), 50 SMA (red)
• Background Tinting: Subtle color on strongest reversal zones
Key Level Detection
The indicator uses request.security() to accurately fetch previous day's high/low from daily timeframe data, ensuring precise level placement. Premarket high/low levels are dynamically tracked during premarket sessions (4:00 AM - 9:30 AM EST) and plotted throughout the trading day, providing critical support/resistance zones that often influence price action during regular hours.
Customizable Parameters
• Signal strength thresholds (adjust required confirmations)
• RSI settings (length, overbought/oversold levels)
• MACD parameters (fast/slow/signal lengths)
• Moving average periods
• Volume spike multiplier
• Toggle individual display elements (levels, MAs, labels)
Best Practices
• Use on 5-minute charts for entries, confirm on 15-minute for direction
• Focus on Medium and Strong signals; Weak signals provide context only
• Strong signals (5-6 confirmations) have the highest win rate
• Pay special attention to reversals at premarket high/low - these levels frequently hold
• Previous day high/low often acts as major support/resistance
• Always use proper risk management and stop losses
• Works best in moderately trending markets
Alert Capabilities
Set custom alerts for:
• Strong long/short signals
• All entry signals (medium + strong)
• Exit warnings for open positions
Ideal For
• Daytraders and scalpers (especially SPY, QQQ, and liquid equities)
• Swing traders seeking precise entries
• Traders who prefer confirmation-based systems
• Anyone looking to reduce false signals with multi-factor validation
• Traders who utilize premarket levels in their strategy
Technical Notes
• Uses Pine Script v6
• Premarket hours: 4:00 AM - 9:30 AM EST
• Previous day levels pulled from daily timeframe for accuracy
• Maximum 500 labels to maintain chart performance
• All key levels update dynamically in real-time
________________________________________
Note: This indicator provides signal analysis only and should be used as part of a complete trading strategy. Past performance does not guarantee future results. Always practice proper risk management.
CVD [able0.1]# CVD Overlay iOS Style - Complete User Guide
## 📖 Table of Contents
1. (#what-is-cvd)
2. (#installation-guide)
3. (#understanding-the-display)
4. (#reading-the-info-table)
5. (#settings--customization)
6. (#trading-strategies)
7. (#common-mistakes-to-avoid)
---
## 🎯 What is CVD?
**CVD (Cumulative Volume Delta)** tracks the **difference between buying and selling pressure** over time.
### Simple Explanation:
- **Positive CVD** (Orange) = More buying than selling = Bulls winning
- **Negative CVD** (Gray) = More selling than buying = Bears winning
- **Rising CVD** = Increasing buying pressure = Potential uptrend
- **Falling CVD** = Increasing selling pressure = Potential downtrend
### Why It Matters:
CVD helps you see **who's really in control** of the market - not just price movement, but actual buying/selling volume.
---
## 🚀 Installation Guide
### Step 1: Open Pine Editor
1. Go to TradingView
2. Click the **"Pine Editor"** tab at the bottom of the screen
3. Click **"New"** or open an existing script
### Step 2: Copy & Paste the Code
1. Select all existing code (Ctrl+A / Cmd+A)
2. Delete it
3. Copy the entire CVD iOS Style code
4. Paste it into Pine Editor
### Step 3: Add to Chart
1. Click **"Save"** button (or Ctrl+S / Cmd+S)
2. Click **"Add to Chart"** button
3. The indicator will appear on your chart!
### Step 4: Initial Setup
- The indicator appears as an **overlay** on your price chart
- You'll see an **orange/gray line** following price
- An **info table** appears in the top-right corner
---
## 📊 Understanding the Display
### Main Chart Elements:
#### 1. **CVD Line** (Orange/Gray)
- **Orange Line** = Positive CVD (buying pressure)
- **Gray Line** = Negative CVD (selling pressure)
- This line moves with your price chart but shows volume delta
#### 2. **CVD Zone** (Shaded Area)
- Light shaded box around the CVD line
- Shows the "range" of CVD movement
- Helps visualize CVD boundaries
#### 3. **Center Line** (Dotted)
- Gray dotted line in the middle of the zone
- Represents the "neutral" point
- CVD crossing this = shift in market control
#### 4. **Reference Asset Line** (Light Gray)
- Shows Bitcoin (BTC) price movement for comparison
- Helps you see if your asset moves with or against BTC
- Can be changed to any asset you want
#### 5. **CVD Label**
- Shows current CVD value
- Positioned above/below zone to avoid overlap
- Updates in real-time
#### 6. **Reset Background** (Very Light Gray)
- Appears when CVD resets
- Indicates a new calculation period
---
## 📋 Reading the Info Table
The info table (top-right) shows **8 key metrics**:
### Row 1: **Header**
```
╔═ CVD able ═╗ | 15m | ████████ | able
```
- **CVD able** = Indicator name + creator
- **15m** = Current timeframe
- **████████** = Visual decoration
- **able** = Creator signature
### Row 2: **CVD Value**
```
CVD▲ | 7.39K | ████████ | █
█
█
```
- **CVD▲** = CVD with trend arrow
- ▲ = CVD increasing
- ▼ = CVD decreasing
- ► = CVD unchanged
- **7.39K** = Actual CVD number
- **Progress Bar** = Visual strength (darker = stronger)
- **Vertical Bars** = Height shows intensity
### Row 3: **Delta**
```
◆DELTA | -1.274K | ████░░░░ | ░
░
```
- **Delta** = Volume change THIS BAR ONLY
- **Negative** = More selling this bar
- **Positive** = More buying this bar
- Shows **immediate** pressure (not cumulative)
### Row 4: **UP Volume**
```
UP↑ | -1.263K | ████████ | █
█
█
```
- Total **buying volume** this bar
- Higher = Stronger buying pressure
- Green/Orange vertical bars = Bullish strength
### Row 5: **DOWN Volume**
```
DN↓ | 2.643K | ████████ | ░
░
░
```
- Total **selling volume** this bar
- Higher = Stronger selling pressure
- Gray vertical bars = Bearish strength
### Row 6-7: **Reference Asset** (if enabled)
```
══ REF ══ | ══════ | ████████ | █
█
PRICE▲ | 4130.300 | ████████ | █
█
```
- **REF** = Reference asset header
- **PRICE▲** = Reference price with trend
- Shows if BTC (or chosen asset) is rising/falling
- Compare with your chart to see correlation
### Row 8: **Market Status**
```
◄STATUS► | NEUT | ████░░░░ | ▒
▒
```
- **BULL** = CVD positive + Delta positive = Strong buying
- **BEAR** = CVD negative + Delta negative = Strong selling
- **NEUT** = Mixed signals = Wait for clarity
**Status Colors:**
- **Orange background** = Bullish (good for long)
- **Gray background** = Bearish (good for short)
- **White background** = Neutral (no clear signal)
---
## ⚙️ Settings & Customization
### Main Settings (⚙️)
#### **CVD Reset**
- **None** = CVD never resets (from beginning of data)
- **On Higher Timeframe** = Resets when HTF candle closes
- 15m chart → Resets hourly
- 1h chart → Resets daily
- Recommended for most traders
- **On Session Start** = Resets at market open
- **On Visible Chart** = Resets from leftmost visible bar
#### **Precision**
- **Low (Fast)** = Uses 1m data, faster but less accurate
- **Medium** = Uses 5m data, balanced (recommended)
- **High** = Uses 15m data, most accurate but slower
#### **Cumulative**
- ✅ On = CVD accumulates over time (recommended)
- ❌ Off = Shows only current bar delta
#### **Show Labels**
- ✅ On = Shows CVD value label on chart
- ❌ Off = Cleaner chart, no label
#### **Show Info Table**
- ✅ On = Shows info table (recommended for beginners)
- ❌ Off = Hide table for minimalist view
---
### 🎨 iOS Style Colors
You can customize **every color** to match your chart theme:
#### **Primary Colors**
- **Primary (Orange)** = Main bullish color (#FF9500)
- **Secondary (Gray)** = Main bearish color (#8E8E93)
- **Background** = Table background (#FFFFFF)
- **Text** = Text color (#1C1C1E)
#### **Bullish/Bearish**
- **Bullish (Orange)** = Positive CVD color
- **Bearish (Gray)** = Negative CVD color
- **Opacity** = Zone transparency (0-100%)
- **Show Zone** = Enable/disable shaded area
#### **Table Colors** (📋)
- **Header Background** = Top row background
- **Header Text** = Top row text color
- **Cell Background** = Data cells background
- **Cell Text** = Data cells text color
- **Border** = Table border color
- **Accent Background** = Special rows background
- **Alert Background** = Warning/status background
---
### 📊 Reference Asset Settings
#### **Enable**
- ✅ On = Shows reference asset line
- ❌ Off = Hide reference asset
#### **Symbol**
- Default: `BINANCE:BTCUSDT`
- Can change to any asset:
- `BINANCE:ETHUSDT` (Ethereum)
- `SPX` (S&P 500)
- `DXY` (US Dollar Index)
- Any ticker symbol
#### **Color & Width**
- Customize line appearance
- Width: 1-4 (thickness)
---
## 💡 Trading Strategies
### Strategy 1: CVD Divergence (Beginner-Friendly)
**What to Look For:**
- Price making **higher highs** but CVD making **lower highs** = Bearish divergence
- Price making **lower lows** but CVD making **higher lows** = Bullish divergence
**How to Trade:**
1. Wait for divergence to form
2. Look for confirmation (price reversal, candlestick pattern)
3. Enter trade in divergence direction
4. Stop loss beyond recent high/low
**Example:**
```
Price: /\ /\ /\ (higher highs)
CVD: /\ / \/ (lower highs) = Bearish signal
```
### Strategy 2: CVD Trend Following (Intermediate)
**What to Look For:**
- **Strongly rising CVD** + **rising price** = Strong uptrend
- **Strongly falling CVD** + **falling price** = Strong downtrend
**How to Trade:**
1. Wait for CVD and price moving in same direction
2. Enter on pullbacks to support/resistance
3. Stay in trade while CVD trend continues
4. Exit when CVD trend breaks
**Signals:**
- CVD ▲▲▲ + Price ↑ = Go LONG
- CVD ▼▼▼ + Price ↓ = Go SHORT
### Strategy 3: CVD + Reference Asset (Advanced)
**What to Look For:**
- Your asset **rising** but BTC (reference) **falling** = Relative strength
- Your asset **falling** but BTC (reference) **rising** = Relative weakness
**How to Trade:**
1. Compare CVD movement with BTC
2. If your CVD rises faster than BTC = Buy signal
3. If your CVD falls faster than BTC = Sell signal
4. Use for **pair trading** or **asset selection**
### Strategy 4: Volume Delta Confirmation
**What to Look For:**
- **Large positive Delta** = Strong buying this bar
- **Large negative Delta** = Strong selling this bar
**How to Trade:**
1. Price breaks resistance + Large positive Delta = Confirmed breakout
2. Price breaks support + Large negative Delta = Confirmed breakdown
3. Use Delta to **confirm** price moves, not predict them
**Rules:**
- Delta > 2x average = Very strong pressure
- Delta near zero at key level = Weak move, likely false breakout
---
## 🎓 Reading Real Scenarios
### Scenario 1: Strong Buying Pressure
```
Table Shows:
CVD▲ | 12.5K | ████████ | ████ (CVD rising)
◆DELTA | +2.8K | ████████ | ▲ (Positive delta)
UP↑ | 3.1K | ████████ | ████ (High buy volume)
DN↓ | 0.3K | ██░░░░░░ | ░ (Low sell volume)
◄STATUS► | BULL | ████████ | ████ (Orange background)
```
**Interpretation:** Strong buying, good for LONG trades
### Scenario 2: Distribution (Hidden Selling)
```
Table Shows:
CVD► | 8.2K | ████░░░░ | ▒▒ (CVD flat)
◆DELTA | -1.5K | ████████ | ▼ (Negative delta)
UP↑ | 0.8K | ███░░░░░ | ░ (Low buy volume)
DN↓ | 2.3K | ████████ | ████ (High sell volume)
◄STATUS► | BEAR | ████████ | ░░░░ (Gray background)
```
**Interpretation:** Price may look stable, but selling increasing = Prepare for drop
### Scenario 3: Neutral/Choppy Market
```
Table Shows:
CVD► | 5.1K | ████░░░░ | ▒ (CVD sideways)
◆DELTA | +0.2K | ██░░░░░░ | ─ (Small delta)
UP↑ | 1.2K | ████░░░░ | ▒ (Medium buy)
DN↓ | 1.0K | ████░░░░ | ▒ (Medium sell)
◄STATUS► | NEUT | ████░░░░ | ▒▒ (White background)
```
**Interpretation:** No clear direction = Stay out or reduce position size
---
## ⚠️ Common Mistakes to Avoid
### Mistake 1: Trading on CVD Alone
- ❌ **Wrong:** "CVD is rising, I'll buy immediately"
- ✅ **Right:** "CVD is rising, let me check price structure, support/resistance, and wait for confirmation"
### Mistake 2: Ignoring Delta
- ❌ **Wrong:** Looking only at cumulative CVD
- ✅ **Right:** Watch both CVD (trend) and Delta (momentum)
- Delta shows **immediate** pressure changes
### Mistake 3: Wrong Timeframe
- ❌ **Wrong:** Using 1m chart with High Precision (too slow)
- ✅ **Right:** Match precision to timeframe:
- 1m-5m → Low Precision
- 15m-1h → Medium Precision
- 4h+ → High Precision
### Mistake 4: Not Using Reset
- ❌ **Wrong:** Using "None" reset for intraday trading
- ✅ **Right:** Use "On Higher Timeframe" to see fresh CVD each session
### Mistake 5: Overtrading Neutral Status
- ❌ **Wrong:** Forcing trades when STATUS = NEUT
- ✅ **Right:** Only trade clear BULL or BEAR status
### Mistake 6: Ignoring Reference Asset
- ❌ **Wrong:** Trading altcoin without checking BTC
- ✅ **Right:** Always check if BTC CVD agrees with your asset
---
## 🔥 Pro Tips
### Tip 1: Multi-Timeframe Analysis
- Check CVD on **3 timeframes**:
- Lower TF (15m) = Entry timing
- Current TF (1h) = Trade direction
- Higher TF (4h) = Overall trend
### Tip 2: Volume Confirmation
- Big price move + Small Delta = **Weak move** (likely reversal)
- Small price move + Big Delta = **Strong accumulation** (continuation)
### Tip 3: CVD Reset Zones
- Pay attention to **reset backgrounds** (light gray)
- Often marks **session starts** = High volatility periods
### Tip 4: Divergence + Status
- Bearish divergence + STATUS = BEAR = **Strongest short signal**
- Bullish divergence + STATUS = BULL = **Strongest long signal**
### Tip 5: Color Psychology
- **Orange** (Bullish) is **warm** = Buying energy
- **Gray** (Bearish) is **cool** = Selling pressure
- Train your eye to read colors instantly
### Tip 6: Table as Quick Scan
- Glance at table without reading numbers:
- **All orange** = Bullish
- **All gray** = Bearish
- **Mixed** = Wait
---
## 📱 Quick Reference Card
| Signal | CVD | Delta | Status | Action |
|--------|-----|-------|--------|--------|
| **Strong Buy** | ▲▲ High | ++ Positive | BULL | Long Entry |
| **Strong Sell** | ▼▼ Low | -- Negative | BEAR | Short Entry |
| **Divergence Buy** | ▲ Rising | Price ▼ | → BULL | Long Setup |
| **Divergence Sell** | ▼ Falling | Price ▲ | → BEAR | Short Setup |
| **Neutral** | → Flat | ~0 Near Zero | NEUT | Stay Out |
| **Accumulation** | → Flat | ++ Positive | NEUT→BULL | Watch for Breakout |
| **Distribution** | → Flat | -- Negative | NEUT→BEAR | Watch for Breakdown |
---
## 🆘 Troubleshooting
### Issue: "Indicator not showing"
- **Solution:** Make sure overlay=true in code, re-add to chart
### Issue: "Table overlaps with price"
- **Solution:** Change table position in code or use TradingView's "Move" feature
### Issue: "CVD line too far from price"
- **Solution:** This is normal! CVD is volume-based, not price-based. Focus on CVD direction, not position
### Issue: "Too many lines on chart"
- **Solution:** Disable "Show Zone" and "Show Labels" in settings for cleaner view
### Issue: "Calculations too slow"
- **Solution:** Change Precision to "Low (Fast)" or use higher timeframe
### Issue: "Reference asset not showing"
- **Solution:** Check if "Enable" is ON and symbol is valid (e.g., BINANCE:BTCUSDT)
---
## 🎬 Getting Started Checklist
- Install indicator on TradingView
- Set precision to "Medium"
- Set reset to "On Higher Timeframe"
- Enable info table
- Add reference asset (BTC)
- Practice reading the table on demo account
- Test on different timeframes (15m, 1h, 4h)
- Compare CVD with your current strategy
- Paper trade for 1 week before going live
- Keep a trading journal of CVD signals
---
## 📚 Summary
**CVD shows WHO is winning: Buyers or Sellers**
**Key Points:**
1. **Orange/Rising CVD** = Buying pressure = Bullish
2. **Gray/Falling CVD** = Selling pressure = Bearish
3. **Delta** = Immediate momentum THIS BAR
4. **Status** = Overall market condition
5. **Always confirm** with price action & other indicators
**Remember:**
- CVD is a **tool**, not a crystal ball
- Use with proper risk management
- Practice makes perfect
- Stay disciplined!
---
**Created by: able**
**Version:** iOS Style v1.0
**Contact:** For questions, refer to TradingView community
Happy Trading! 🚀📈
Pso VP 2.0This indicator provides an advanced volume analysis tool that visualizes trading activity across different price levels and automatically identifies key support and resistance zones.
How It Works:
The Volume Profile analyzes historical price and volume data within a specified lookback period, distributing volume across horizontal price levels. Unlike traditional volume indicators that show volume over time, this tool displays volume at price, revealing where the most significant trading activity has occurred.
The algorithm:
Divides the price range into customizable horizontal bars (bins)
Calculates and accumulates volume for each price level
Identifies high-volume nodes that often act as support or resistance levels
Uses percentile filtering to highlight the most significant trading areas
Key Features:
Automatic S/R Detection: Uses volume percentile filtering to identify the most significant price levels
Dynamic Support/Resistance Lines: Automatically draws horizontal black lines at high-volume areas that typically act as price magnets or barriers
Customizable Parameters: Full control over lookback period, number of price bars, percentile thresholds, profile width, opacity, and line projections
Clean Aesthetic: Monochrome design for professional chart presentation
JokaBAR
This script combines my own liquidity/liq-levels engine with open-source code from BigBeluga’s Volumatic indicators:
• “Volumatic Variable Index Dynamic Average ”
• “Volumatic Support/Resistance Levels ”
The original code is published under the Mozilla Public License 2.0 and is reused here accordingly.
What this script does
Joka puts Volumatic trend logic, dynamic support/resistance and a custom liquidation-levels module into a single overlay. The idea is to give traders one clean view of trend direction, key reactive zones and potential liquidation areas where leveraged positions can be forced out of the market.
Volumatic logic is used to build a dynamic average and adaptive levels that react to volume and volatility. On top of that, the script plots configurable liquidation zones for different leverage tiers (e.g. 5x, 10x, 25x, 50x, 100x).
How to use it
Apply the script on pairs where leverage is actually used (perpetual futures / margin).
Use the Volumatic average as a trend filter (above = long bias, below = short bias).
Treat Volumatic support/resistance levels as key reaction zones for entries, partials and stops.
Read the liquidation levels as context: clusters show where forced liquidations can fuel strong moves and bounces.
Keep the chart clean — this tool is designed to be used without stacking extra indicators on top.
The script is published as open-source in line with TradingView House Rules so that other traders can study, tweak and build on it.
FxAST Ichi ProSeries Enhanced Full Market Regime EngineFxAST Ichi ProSeries v1.x is a modernized Ichimoku engine that keeps the classic logic but adds a full market regime engine for any market and instrument.”
Multi-timeframe cloud overlay
Oracle long-term baseline
Trend regime classifier (Bull / Bear / Transition / Range)
Chikou & Cloud breakout signals
HTF + Oracle + Trend dashboard
Alert-ready structure for automation
No repainting: all HTF calls use lookahead_off.
1. Core Ichimoku Engine
Code sections:
Input group: Core Ichimoku
Function: ichiCalc()
Variables: tenkan, kijun, spanA, spanB, chikou
What it does
Calculates the classic Ichimoku components:
Tenkan (Conversion Line) – fast Donchian average (convLen)
Kijun (Base Line) – slower Donchian average (baseLen)
Senkou Span A (Span A / Lead1) – (Tenkan + Kijun)/2
Senkou Span B (Span B / Lead2) – Donchian over spanBLen
Chikou – current close shifted back in time (displace)
Everything else in the indicator builds on this engine.
How to use it (trading)
Tenkan vs Kijun = short-term vs medium-term balance.
Tenkan above Kijun = short-term bullish control; below = bearish control.
Span A / B defines the cloud, which represents equilibrium and support/resistance.
Price above cloud = bullish bias; price below cloud = bearish bias.
Graphic
2. Display & Cloud Styling
Code sections:
Input groups: Display Options, Cloud Styling, Lagging Span & Signals
Variables: showTenkan, showKijun, showChikou, showCloud, bullCloudColor, bearCloudColor, cloudLineWidth, laggingColor
Plots: plot(tenkan), plot(kijun), plot(chikou), p1, p2, fill(p1, p2, ...)
What it does
Lets you toggle individual components:
Show/hide Tenkan, Kijun, Chikou, and the cloud.
Customize cloud colors & opacity:
bullCloudColor when Span A > Span B
bearCloudColor when Span A < Span B
Adjust cloud line width for clarity.
How to use it
Turn off components you don’t use (e.g., hide Chikou if you only want cloud + Tenkan/Kijun).
For higher-timeframe or noisy charts, use thicker Kijun & cloud so structure is easier to see.
Graphic
Before
After
3. HTF Cloud Overlay (Multi-Timeframe)
Code sections:
Input group: HTF Cloud Overlay
Vars: showHTFCloud, htfTf, htfAlpha
Logic: request.security(..., ichiCalc(...)) → htfSpanA, htfSpanB
Plots: pHTF1, pHTF2, fill(pHTF1, pHTF2, ...)
What it does
Pulls higher-timeframe Ichimoku cloud (e.g., 1H, 4H, Daily) onto your current chart.
Uses the same Ichimoku settings but aggregates on htfTf.
Plots an extra, semi-transparent cloud ahead of price:
Greenish when HTF Span A > Span B
Reddish when HTF Span B > Span A
How to use it
Trade LTF (e.g., 5m/15m) only in alignment with HTF trend:
HTF cloud bullish + LTF Ichi bullish → look for longs
HTF cloud bearish + LTF Ichi bearish → look for shorts
Treat HTF cloud boundaries as major S/R zones.
Graphic
4. Oracle Module
Code sections:
Input group: Oracle Module
Vars: useOracle, oracleLen, oracleColor, oracleWidth, oracleSlopeLen
Logic: oracleLine = donchian(oracleLen); slope check vs oracleLine
Plot: plot(useOracle ? oracleLine : na, "Oracle", ...)
What it does
Creates a long-term Donchian baseline (default 208 bars).
Uses a simple slope check:
Current Oracle > Oracle oracleSlopeLen bars ago → Oracle Bull
Current Oracle < Oracle oracleSlopeLen bars ago → Oracle Bear
Slope state is also shown in the dashboard (“Bull / Bear / Flat”).
How to use it
Think of Oracle as your macro anchor :
Only take longs when Oracle is sloping up or flat.
Only take shorts when Oracle is sloping down or flat.
Works well combined with HTF cloud:
HTF cloud bullish + Oracle Bull = higher conviction long bias.
Ideal for Gold / Indices swing trades as a trend filter.
Graphic idea
5. Trend Regime Classifier
Code sections:
Input group: Trend Regime Logic
Vars: useTrendRegime, bgTrendOpacity, minTrendScore
Logic:
priceAboveCloud, priceBelowCloud, priceInsideCloud
Tenkan vs Kijun alignment
Cloud bullish/bearish
bullScore / bearScore (0–3)
regime + regimeLabel + regimeColor
Visuals: bgcolor(regimeColor) and optional barcolor() in priceColoring mode.
What it does
Scores the market in three dimensions :
Price vs Cloud
Tenkan vs Kijun
Cloud Direction (Span A vs Span B)
Each condition contributes +1 to either bullScore or bearScore .
Then:
Bull regime when:
bullScore >= minTrendScore and bullScore > bearScore
Price in cloud → “Range”
Everything else → “Transition”
These regimes are shown as:
Background colors:
Teal = Bull
Maroon = Bear
Orange = Range
Silver = Transition
Optional candle recoloring when priceColoring = true.
How to use it
Filters:
Only buy when regime = Bull or Transition and Oracle/HTF agree.
Only sell when regime = Bear or Transition and Oracle/HTF agree.
No trade zone:
When regime = Range (price inside cloud), avoid new entries; wait for break.
Aggressiveness:
Adjust minTrendScore to be stricter (3) or looser (1).
Graphic
6. Signals: Chikou & Cloud Breakout
Code sections :
Logic:
chikouBuySignal = ta.crossover(chikou, close)
chikouSellSignal = ta.crossunder(chikou, close)
cloudBreakUp = priceInsideCloud and priceAboveCloud
cloudBreakDown = priceInsideCloud and priceBelowCloud
What it does
1. Two key signal groups:
Chikou Cross Signals
Buy when Chikou crosses up through price.
Sell when Chikou crosses down through price.
Classic Ichi confirmation idea: Chikou breaking free of price cluster.
2. Cloud Breakout Signals
Long trigger: yesterday inside cloud → today price breaks above cloud.
Short trigger: yesterday inside cloud → today price breaks below cloud.
Captures “equilibrium → expansion” moves.
These are conditions only in this version (no chart shapes yet) but are fully wired for alerts. (Future Updates)
How to use it
Use Chikou signals as confirmation, not standalone entries:
Eg., Bull regime + Oracle Bull + cloud breakout + Chikou Buy.
Use Cloud Breakouts to catch the first impulsive leg after consolidation.
Graphic
7. Alerts (Automation Ready)
[
b]Code sections:
Input group: Alerts
Vars: useAlertTrend, useAlertChikou, useAlertCloudBO
Alert lines like: "FxAST Ichi Bull Trend", "FxAST Ichi Bull Trend", "FxAST Ichi Cloud Break Up"
What it does
Provides ready-made alert hooks for:
Trend regime (Bull / Bear)
Chikou cross buy/sell
Cloud breakout up/down
Each type can be globally toggled on/off via the inputs (helpful if a user only wants one kind).
How to use it
In TradingView: set alerts using “Any alert() function call” on this indicator.
Then filter which ones fire by:
Turning specific alert toggles on/off in input panel, or
Filtering text in your external bot / webhook side.
Example simple workflow ---> Indicator ---> TV Alert ---> Webhook ---> Bot/Broker
8. FxAST Dashboard
Code sections:
Input group: Dashboard
Vars: showDashboard, dashPos, dash, dashInit
Helper: getDashPos() → position.*
Table cells (updated on barstate.islast):
Row 0: Regime + label
Row 1: Oracle status (Bull / Bear / Flat / Off)
Row 2: HTF Cloud (On + TF / Off)
Row 3: Scores (BullScore / BearScore)
What it does
Displays a compact panel with the state of the whole system :
Current Trend Regime (Bull / Bear / Transition / Range)
Oracle slope state
Whether HTF Cloud is active + which timeframe
Raw Bull / Bear scores (0–3 each)
Position can be set: Top Right, Top Left, Bottom Right, Bottom Left.
How to use it
Treat it like a pilot instrument cluster :
Quick glance: “Are my trend, oracle and HTF all aligned?”
Great for streaming / screenshots: everything important is visible in one place without reading the code.
Graphic (lower right of chart )
WTC Step Buy Step Edition CbyCarlo📊 WT Cross Modified – Step Buy Step Edition (v4)
WTC_StepBuyStep_Edition is an enhanced, practical, and optimized version of the classic WaveTrend (WT) Cross Indicator.
Developed for the Step Buy Step project, this tool helps traders identify market momentum shifts, structural price zones, and potential reversal areas with high clarity and precision.
🔍 Concept & Purpose
This indicator builds upon the established WaveTrend / LazyBear logic and extends it with additional structural intelligence.
The goal is to make overbought/oversold phases and trend reversals easier to spot — while also highlighting historically validated price zones where the market has previously reacted strongly.
⚙️ Key Features
1️⃣ WT Cross Signals
WT1 (yellow) and WT2 (purple) visualize market momentum.
A WT1 cross above WT2 while below the Oversold zone (−53) can indicate potential Long opportunities.
A WT1 cross below WT2 while above the Overbought zone (+53) can indicate potential Short opportunities.
Signals only confirm after candle close to prevent repainting.
2️⃣ Dynamic “WT SignalZone” Panel
Displayed in the top-right corner, this panel shows the last three valid price levels derived from WT signals:
🟢 LonLev – Buy support levels from previous WT Long signals
🔴 ShoLev – Sell resistance levels from previous WT Short signals
These zones act as objective support/resistance structures, based on historical momentum turning points — not subjective lines.
3️⃣ Flexible Calculation Modes
Choose how levels are derived from each WT signal:
Pullback 50% → Midpoint of the signal candle (high+low)/2
Close → Close price of the signal candle
Next Open → Open of the following bar (ideal for system testing)
📈 How to Interpret the Indicator
Market Condition WT Event Meaning
WT1 < −53 & CrossUp Long Signal Potential reversal / buy zone
WT1 > +53 & CrossDown Short Signal Potential exhaustion / sell zone
Price revisits LonLev Support Re-entry or bounce zone
Price revisits ShoLev Resistance Profit-taking or short setup zone
This makes the tool highly effective for:
Swing traders
Zone-based trading strategies
Systematic re-entries
Identifying structural turning points
🧠 Advantages
No repainting (signals confirmed only after bar close)
Works on all timeframes (from intraday to weekly)
Clean overview without clutter or excessive chart markers
Excellent as a filter to confirm market context
💬 Best Use Case
Use WTC_StepBuyStep_Edition as a contextual confirmation tool.
It does not replace a full trading system — but it gives you objective, repeatable, and statistically relevant zones where the market has reacted before.
Combine it with price action, volume analysis, or trend tools for even stronger setups.
© Step Buy Step • Step-Buy-Step.com
Educational trading tool intended for market analysis.
Not financial advice.
sima-Prev HTF & Sessions (Tehran)This indicator automatically plots the Opening, Closing, High, and Low levels of the major global trading sessions: London, New York, and Asia. It is designed to help traders visualize intraday liquidity zones, session-based volatility, and potential reaction levels where price commonly expands or reverses.
The script includes fully adjustable session times and highlights each session using clean visual markers so traders can easily identify market structure within different time windows. By displaying the Open, Close, High, and Low of each session, the indicator helps forecast areas of interest such as breakout levels, range boundaries, and session-based support/resistance.
This tool is especially useful for intraday traders, scalpers, and anyone who relies on session dynamics to analyze market behavior. It works on all timeframes and all markets, including Forex, indices, metals, and crypto. No repainting is used; all levels are plotted based on completed session data.
PLANBXPRESS PSYCHOLOGICAL LEVEL ENTRY MODELThis Indicator merges multiple professional trading concepts into one visual tool — helping traders identify momentum shifts, entry zones, and daily trading plans with volume confirmation.
It automatically detects trend direction, generates dynamic take-profit & stop-loss levels, and overlays key daily reference points such as VWAP, pivot, support, and resistance zones based on ATR and trend context.
⚙️ Main Components
1️⃣ Signal System
Detects trend bias using SMA-based logic.
Generates entry price, TP1–TP3, and SL dynamically from recent impulse ranges.
Updates signals automatically when trend bias changes or previous targets are hit.
Visual levels are drawn directly on the chart.
2️⃣ Volume Analysis
Compares current volume against a moving average (SMA).
Classifies volume as:
🟢 Strong (above 1.5× average)
🟡 Average
🔴 Weak (below 0.8× average)
Displays the current volume strength and trend bias in an on-chart table.
3️⃣ Auto Day Plan
Uses multi-timeframe ATR calculations to define:
Support / Resistance zones
Pivot & Balance areas
Daily VWAP
Auto Targets (ATR-based expansion levels)
Adapts automatically to selected base timeframe (1H, 4H, or Daily).
4️⃣ Trend Context
Dual EMA system (50 & 200) to confirm bullish/bearish structure.
Aligns expected direction with VWAP & pivot location for context-aware bias.
🎯 What You Get on Chart
📈 Automatic LONG/SHORT signals
🎯 TP1, TP2, TP3, and SL levels
📊 Volume strength meter
🧭 VWAP, pivot, support/resistance & balance zones
🎨 Clean visual layout for intraday and swing traders
🧩 Inputs
Parameter Description
lenImpulse Impulse range length
smaLen SMA length for trend bias
levelRatio SL/TP ratio multiplier
volLen Volume SMA length
baseTF Base timeframe for zones/VWAP
atrMult1 / atrMult2 ATR multipliers for target levels
fwdBars Extension range for future projection
💡 How to Use
Add the script to your chart and choose your preferred timeframe.
Observe signal direction (📈 LONG / 📉 SHORT) and TP/SL levels.
Confirm entries when:
Trend aligns with VWAP direction, and
Volume category shows Strong or Average.
Use Auto Day Plan levels (pivot, balance, VWAP) as intraday reaction zones.
PLANBXPRESS ENTRYThe Combined Signal + Auto Day Plan + Volume indicator merges multiple professional trading concepts into one visual tool — helping traders identify momentum shifts, entry zones, and daily trading plans with volume confirmation.
It automatically detects trend direction, generates dynamic take-profit & stop-loss levels, and overlays key daily reference points such as VWAP, pivot, support, and resistance zones based on ATR and trend context.
⚙️ Main Components
1️⃣ Signal System
Detects trend bias using SMA-based logic.
Generates entry price, TP1–TP3, and SL dynamically from recent impulse ranges.
Updates signals automatically when trend bias changes or previous targets are hit.
Visual levels are drawn directly on the chart.
2️⃣ Volume Analysis
Compares current volume against a moving average (SMA).
Classifies volume as:
🟢 Strong (above 1.5× average)
🟡 Average
🔴 Weak (below 0.8× average)
Displays the current volume strength and trend bias in an on-chart table.
3️⃣ Auto Day Plan
Uses multi-timeframe ATR calculations to define:
Support / Resistance zones
Pivot & Balance areas
Daily VWAP
Auto Targets (ATR-based expansion levels)
Adapts automatically to selected base timeframe (1H, 4H, or Daily).
4️⃣ Trend Context
Dual EMA system (50 & 200) to confirm bullish/bearish structure.
Aligns expected direction with VWAP & pivot location for context-aware bias.
🎯 What You Get on Chart
📈 Automatic LONG/SHORT signals
🎯 TP1, TP2, TP3, and SL levels
📊 Volume strength meter
🧭 VWAP, pivot, support/resistance & balance zones
🎨 Clean visual layout for intraday and swing traders
🧩 Inputs
Parameter Description
lenImpulse Impulse range length
smaLen SMA length for trend bias
levelRatio SL/TP ratio multiplier
volLen Volume SMA length
baseTF Base timeframe for zones/VWAP
atrMult1 / atrMult2 ATR multipliers for target levels
fwdBars Extension range for future projection
💡 How to Use
Add the script to your chart and choose your preferred timeframe.
Observe signal direction (📈 LONG / 📉 SHORT) and TP/SL levels.
Confirm entries when:
Trend aligns with VWAP direction, and
Volume category shows Strong or Average.
Use Auto Day Plan levels (pivot, balance, VWAP) as intraday reaction zones.
Swing High/Low Support ResistanceThis indicator detects recent swing highs and swing lows using Pine Script pivots and marks them with visible chart labels. These points highlight potential turning areas in price action and can help identify short-term support or resistance for intraday or swing trading.
How to Apply
Locate the indicator in TradingView’s “Indicators” library; search by its name or author.
Click the star icon to mark it as a favourite for quick future access.
Apply directly to your chosen chart and timeframe with a single click—no need to enter or paste code.
Adjust the input parameters from the settings panel if desired to personalize swing sensitivity.
Choose Your Timeframe:
Apply to any intraday or swing timeframe; shorter lengths show more frequent pivots.
Set Sensitivity:
Use the “Swing Detection Length” input to adjust how many bars define a pivot, making swings more or less sensitive to price action.
How to Analyze
Swing High Labels: Mark recent local peaks, suggesting resistance zones or possible reversal points.
Swing Low Labels: Highlight recent bottoms, indicating support or bounce areas.
Monitor labels for clustering or repeated appearance at similar levels, which may strengthen their importance as price reacts near those points.
Track how price behaves after forming new pivots—multiple tests can affirm the relevance of a level.
What Traders Should Watch
Price reaction at labeled areas: frequent tests may anticipate reversals or breakouts.
Transition between higher highs/higher lows (uptrend) vs. lower highs/lower lows (downtrend).
Combine the swing levels with other analysis methods, such as volume, RSI, or EMA, for better signal quality.
Features Included
Dynamic swing high and low detection via confirmed pivots.
Direct labeling on the chart for market structure clarity.
No repainting—labels show only after complete formation.
Fully automatic updates as price action unfolds.
No promotional, external, or non-compliant elements; open source and safe for public or private use.
Compliance Notes
No signals, buy/sell calls, financial advice, or performance claims.
No hidden code, advertising, or off-platform contacts.
Pure educational and analytical utility; adheres to all TradingView house rules and script publishing policies.
Disclaimer
This indicator is for informational purposes only and does not constitute advice. Always do your own research and use proper risk management.
Smarter Money Volume Rejection Blocks [PhenLabs]📊 Smarter Money Volume Rejection Blocks – Institutional Rejection Zone Detection
The Smarter Money Volume Rejection Blocks indicator combines high-volume analysis with statistical confidence intervals to identify where institutional traders are actively defending price levels through volume spikes and rejection patterns.
🔥 Core Methodology
Volume Spike Detection analyzes when current volume exceeds moving average by configurable multipliers (1.0-5.0x) to identify institutional activity
Rejection Candle Analysis uses dual-ratio system measuring wick percentage (30-90%) and maximum body ratio (10-60%) to confirm genuine rejections
Statistical Confidence Channels create three-level zones (upper, center, lower) based on ATR or Standard Deviation calculations
Smart Invalidation Logic automatically clears zones when price significantly breaches confidence levels to maintain relevance
Dynamic Channel Projection extends confidence intervals forward up to 200 bars with customizable length
Support Zone Identification detects bullish rejections where smart money absorbs selling pressure with high volume and strong lower wicks
Resistance Zone Mapping identifies bearish rejections where institutions defend price levels with volume spikes and pronounced upper wicks
Visual Information Dashboard displays real-time status table showing volume spike conditions and active support/resistance zones
⚙️ Technical Configuration
Dual Confidence Interval Methods: Choose between ATR-Based for trend-following environments or StdDev-Based for range-bound statistical precision
Volume Moving Average: Configurable period (default 20) for baseline volume comparison calculations
Volume Spike Multiplier: Adjustable threshold from 1.0 to 5.0 times average volume to filter institutional activity
Rejection Wick Percentage: Set minimum wick size from 30% to 90% of candle range for valid rejection detection
Maximum Body Ratio: Configure body-to-range ratio from 10% to 60% to ensure genuine rejection structures
Confidence Multiplier: Statistical multiplier (default 1.96) for 95% confidence interval calculations
Channel Projection Length: Extend confidence zones forward from 10 to 200 bars for anticipatory analysis
ATR Period: Customize Average True Range lookback from 5 to 50 bars for volatility-based calculations
StdDev Period: Adjust Standard Deviation period from 10 to 100 bars for statistical precision
🎯 Real-World Trading Applications
Identify high-probability support zones where institutional buyers have historically defended price with significant volume
Map resistance levels where smart money sellers consistently reject higher prices with volume confirmation
Combine with price action analysis to confirm breakout validity when price approaches confidence channel boundaries
Use invalidation signals to exit positions when smart money zones are definitively breached
Monitor the real-time dashboard to quickly assess current market structure and active rejection zones
Adapt strategy based on calculation method: ATR for trending markets, StdDev for ranging conditions
Set alerts on confidence level breaches to catch potential trend reversals or continuation patterns
📈 Visual Interpretation Guide
Green Zones indicate bullish rejection blocks where buyers defended with high volume and lower wicks
Red Zones indicate bearish rejection blocks where sellers defended with high volume and upper wicks
Solid Center Lines represent the core rejection price level where maximum volume activity occurred
Dashed Confidence Boundaries show upper and lower statistical limits based on volatility calculations
Zone Opacity decreases as channels extend forward to indicate decreasing confidence over time
Dashboard Color Coding provides instant visual feedback on active volume spike and zone conditions
⚠️ Important Considerations
Volume-based indicators identify historical rejection zones but cannot predict future price action with certainty
Market conditions change rapidly and institutional activity patterns evolve continuously
High volume does not guarantee level defense as market structure can shift without warning
Confidence intervals represent statistical probabilities, not guaranteed price boundaries
