Topological Market Stress (TMS) - Quantum FabricTopological Market Stress (TMS) - Quantum Fabric
What Stresses The Market?
Topological Market Stress (TMS) represents a revolutionary fusion of algebraic topology and quantum field theory applied to financial markets. Unlike traditional indicators that analyze price movements linearly, TMS examines the underlying topological structure of market data—detecting when the very fabric of market relationships begins to tear, warp, or collapse.
Drawing inspiration from the ethereal beauty of quantum field visualizations and the mathematical elegance of topological spaces, this indicator transforms complex mathematical concepts into an intuitive, visually stunning interface that reveals hidden market dynamics invisible to conventional analysis.
Theoretical Foundation: Topology Meets Markets
Topological Holes in Market Structure
In algebraic topology, a "hole" represents a fundamental structural break—a place where the normal connectivity of space fails. In markets, these topological holes manifest as:
Correlation Breakdown: When traditional price-volume relationships collapse
Volatility Clustering Failure: When volatility patterns lose their predictive power
Microstructure Stress: When market efficiency mechanisms begin to fail
The Mathematics of Market Topology
TMS constructs a topological space from market data using three key components:
1. Correlation Topology
ρ(P,V) = correlation(price, volume, period)
Hole Formation = 1 - |ρ(P,V)|
When price and volume decorrelate, topological holes begin forming.
2. Volatility Clustering Topology
σ(t) = volatility at time t
Clustering = correlation(σ(t), σ(t-1), period)
Breakdown = 1 - |Clustering|
Volatility clustering breakdown indicates structural instability.
3. Market Efficiency Topology
Efficiency = |price - EMA(price)| / ATR
Measures how far price deviates from its efficient trajectory.
Multi-Scale Topological Analysis
Markets exist across multiple temporal scales simultaneously. TMS analyzes topology at three distinct scales:
Micro Scale (3-15 periods): Immediate structural changes, market microstructure stress
Meso Scale (10-50 periods): Trend-level topology, medium-term structural shifts
Macro Scale (50-200 periods): Long-term structural topology, regime-level changes
The final stress metric combines all scales:
Combined Stress = 0.3×Micro + 0.4×Meso + 0.3×Macro
How TMS Works
1. Topological Space Construction
Each market moment is embedded in a multi-dimensional topological space where:
- Price efficiency forms one dimension
- Correlation breakdown forms another
- Volatility clustering breakdown forms the third
2. Hole Detection Algorithm
The indicator continuously scans this topological space for:
Hole Formation: When stress exceeds the formation threshold
Hole Persistence: How long structural breaks maintain
Hole Collapse: Sudden topology restoration (regime shifts)
3. Quantum Visualization Engine
The visualization system translates topological mathematics into intuitive quantum field representations:
Stress Waves: Main line showing topological stress intensity
Quantum Glow: Surrounding field indicating stress energy
Fabric Integrity: Background showing structural health
Multi-Scale Rings: Orbital representations of different timeframes
4. Signal Generation
Stable Topology (✨): Normal market structure, standard trading conditions
Stressed Topology (⚡): Increased structural tension, heightened volatility expected
Topological Collapse (🕳️): Major structural break, regime shift in progress
Critical Stress (🌋): Extreme conditions, maximum caution required
Inputs & Parameters
🕳️ Topological Parameters
Analysis Window (20-200, default: 50)
Primary period for topological analysis
20-30: High-frequency scalping, rapid structure detection
50: Balanced approach, recommended for most markets
100-200: Long-term position trading, major structural shifts only
Hole Formation Threshold (0.1-0.9, default: 0.3)
Sensitivity for detecting topological holes
0.1-0.2: Very sensitive, detects minor structural stress
0.3: Balanced, optimal for most market conditions
0.5-0.9: Conservative, only major structural breaks
Density Calculation Radius (0.1-2.0, default: 0.5)
Radius for local density estimation in topological space
0.1-0.3: Fine-grained analysis, sensitive to local changes
0.5: Standard approach, balanced sensitivity
1.0-2.0: Broad analysis, focuses on major structural features
Collapse Detection (0.5-0.95, default: 0.7)
Threshold for detecting sudden topology restoration
0.5-0.6: Very sensitive to regime changes
0.7: Balanced, reliable collapse detection
0.8-0.95: Conservative, only major regime shifts
📊 Multi-Scale Analysis
Enable Multi-Scale (default: true)
- Analyzes topology across multiple timeframes simultaneously
- Provides deeper insight into market structure at different scales
- Essential for understanding cross-timeframe topology interactions
Micro Scale Period (3-15, default: 5)
Fast scale for immediate topology changes
3-5: Ultra-fast, tick/minute data analysis
5-8: Fast, 5m-15m chart optimization
10-15: Medium-fast, 30m-1H chart focus
Meso Scale Period (10-50, default: 20)
Medium scale for trend topology analysis
10-15: Short trend structures
20-25: Medium trend structures (recommended)
30-50: Long trend structures
Macro Scale Period (50-200, default: 100)
Slow scale for structural topology
50-75: Medium-term structural analysis
100: Long-term structure (recommended)
150-200: Very long-term structural patterns
⚙️ Signal Processing
Smoothing Method (SMA/EMA/RMA/WMA, default: EMA) Method for smoothing stress signals
SMA: Simple average, stable but slower
EMA: Exponential, responsive and recommended
RMA: Running average, very smooth
WMA: Weighted average, balanced approach
Smoothing Period (1-10, default: 3)
Period for signal smoothing
1-2: Minimal smoothing, noisy but fast
3-5: Balanced, recommended for most applications
6-10: Heavy smoothing, slow but very stable
Normalization (Fixed/Adaptive/Rolling, default: Adaptive)
Method for normalizing stress values
Fixed: Static 0-1 range normalization
Adaptive: Dynamic range adjustment (recommended)
Rolling: Rolling window normalization
🎨 Quantum Visualization
Fabric Style Options:
Quantum Field: Flowing energy visualization with smooth gradients
Topological Mesh: Mathematical topology with stepped lines
Phase Space: Dynamical systems view with circular markers
Minimal: Clean, simple display with reduced visual elements
Color Scheme Options:
Quantum Gradient: Deep space blue → Quantum red progression
Thermal: Black → Hot orange thermal imaging style
Spectral: Purple → Gold full spectrum colors
Monochrome: Dark gray → Light gray elegant simplicity
Multi-Scale Rings (default: true)
- Display orbital rings for different time scales
- Visualizes how topology changes across timeframes
- Provides immediate visual feedback on cross-scale dynamics
Glow Intensity (0.0-1.0, default: 0.6)
Controls the quantum glow effect intensity
0.0: No glow, pure line display
0.6: Balanced, recommended setting
1.0: Maximum glow, full quantum field effect
📋 Dashboard & Alerts
Show Dashboard (default: true)
Real-time topology status display
Current market state and trading recommendations
Stress level visualization and fabric integrity status
Show Theory Guide (default: true)
Educational panel explaining topological concepts
Dashboard interpretation guide
Trading strategy recommendations
Enable Alerts (default: true)
Extreme stress detection alerts
Topological collapse notifications
Hole formation and recovery signals
Visual Logic & Interpretation
Main Visualization Elements
Quantum Stress Line
Primary indicator showing topological stress intensity
Color intensity reflects current market state
Line style varies based on selected fabric style
Glow effect indicates stress energy field
Equilibrium Line
Silver line showing average stress level
Reference point for normal market conditions
Helps identify when stress is elevated or suppressed
Upper/Lower Bounds
Red upper bound: High stress threshold
Green lower bound: Low stress threshold
Quantum fabric fill between bounds shows stress field
Multi-Scale Rings
Aqua circles : Micro-scale topology (immediate changes)
Orange circles: Meso-scale topology (trend-level changes)
Provides cross-timeframe topology visualization
Dashboard Information
Topology State Icons:
✨ STABLE: Normal market structure, standard trading conditions
⚡ STRESSED: Increased structural tension, monitor closely
🕳️ COLLAPSE: Major structural break, regime shift occurring
🌋 CRITICAL: Extreme conditions, reduce risk exposure
Stress Bar Visualization:
Visual representation of current stress level (0-100%)
Color-coded based on current topology state
Real-time percentage display
Fabric Integrity Dots:
●●●●● Intact: Strong market structure (0-30% stress)
●●●○○ Stressed: Weakening structure (30-70% stress)
●○○○○ Fractured: Breaking down structure (70-100% stress)
Action Recommendations:
✅ TRADE: Normal conditions, standard strategies apply
⚠️ WATCH: Monitor closely, increased vigilance required
🔄 ADAPT: Change strategy, regime shift in progress
🛑 REDUCE: Lower risk exposure, extreme conditions
Trading Strategies
In Stable Topology (✨ STABLE)
- Normal trading conditions apply
- Use standard technical analysis
- Regular position sizing appropriate
- Both trend-following and mean-reversion strategies viable
In Stressed Topology (⚡ STRESSED)
- Increased volatility expected
- Widen stop losses to account for higher volatility
- Reduce position sizes slightly
- Focus on high-probability setups
- Monitor for potential regime change
During Topological Collapse (🕳️ COLLAPSE)
- Major regime shift in progress
- Adapt strategy immediately to new market character
- Consider closing positions that rely on previous regime
- Wait for new topology to stabilize before major trades
- Opportunity for contrarian plays if collapse is extreme
In Critical Stress (🌋 CRITICAL)
- Extreme market conditions
- Significantly reduce risk exposure
- Avoid new positions until stress subsides
- Focus on capital preservation
- Consider hedging existing positions
Advanced Techniques
Multi-Timeframe Topology Analysis
- Use higher timeframe TMS for regime context
- Use lower timeframe TMS for precise entry timing
- Alignment across timeframes = highest probability trades
Topology Divergence Trading
- Most powerful at regime boundaries
- Price makes new high/low but topology stress decreases
- Early warning of potential reversals
- Combine with key support/resistance levels
Stress Persistence Analysis
- Long periods of stable topology often precede major moves
- Extended stress periods often resolve in regime changes
- Use persistence tracking for position sizing decisions
Originality & Innovation
TMS represents a genuine breakthrough in applying advanced mathematics to market analysis:
True Topological Analysis: Not a simplified proxy but actual topological space construction and hole detection using correlation breakdown, volatility clustering analysis, and market efficiency measurement.
Quantum Aesthetic: Transforms complex topology mathematics into an intuitive, visually stunning interface inspired by quantum field theory visualizations.
Multi-Scale Architecture: Simultaneous analysis across micro, meso, and macro timeframes provides unprecedented insight into market structure dynamics.
Regime Detection: Identifies fundamental market character changes before they become obvious in price action, providing early warning of structural shifts.
Practical Application: Clear, actionable signals derived from advanced mathematical concepts, making theoretical topology accessible to practical traders.
This is not a combination of existing indicators or a cosmetic enhancement of standard tools. It represents a fundamental reimagining of how we measure, visualize, and interpret market dynamics through the lens of algebraic topology and quantum field theory.
Best Practices
Start with defaults: Parameters are optimized for broad market applicability
Match timeframe: Adjust scales based on your trading timeframe
Confirm with price action: TMS shows market character, not direction
Respect topology changes: Reduce risk during regime transitions
Use appropriate strategies: Adapt approach based on current topology state
Monitor persistence: Track how long topology states maintain
Cross-timeframe analysis: Align multiple timeframes for highest probability trades
Alerts Available
Extreme Topological Stress: Market fabric under severe deformation
Topological Collapse Detected: Regime shift in progress
Topological Hole Forming: Market structure breakdown detected
Topology Stabilizing: Market structure recovering to normal
Chart Requirements
Recommended Markets: All liquid markets (forex, stocks, crypto, futures)
Optimal Timeframes: 5m to Daily (adaptable to any timeframe)
Minimum History: 200 bars for proper topology construction
Best Performance: Markets with clear regime characteristics
Academic Foundation
This indicator draws from cutting-edge research in:
- Algebraic topology and persistent homology
- Quantum field theory visualization techniques
- Market microstructure analysis
- Multi-scale dynamical systems theory
- Correlation topology and network analysis
Disclaimer
This indicator is for educational and research purposes only. It does not constitute financial advice or provide direct buy/sell signals. Topological analysis reveals market structure characteristics, not future price direction. Always use proper risk management and combine with your own analysis. Past performance does not guarantee future results.
See markets through the lens of topology. Trade the structure, not the noise.
Bringing advanced mathematics to practical trading through quantum-inspired visualization.
Trade with insight. Trade with structure.
— Dskyz , for DAFE Trading Systems
Cerca negli script per "market structure"
One Shot One Kill ICT [TradingFinder] Liquidity MMXM + CISD OTE🔵 Introduction
The One Shot One Kill trading setup is one of the most advanced methods in the field of Smart Money Concept (SMC) and ICT. Designed with a focus on concepts such as Liquidity Hunt, Discount Market, and Premium Market, this strategy emphasizes precise Price Action analysis and market structure shifts. It enables traders to identify key entry and exit points using a structured Trading Model.
The core process of this setup begins with a Liquidity Hunt. Initially, the price targets areas like the Previous Day High and Previous Day Low to absorb liquidity. Once the Change in State of Delivery(CISD)is broken, the market structure shifts, signaling readiness for trade entry. At this stage, Fibonacci retracement levels are drawn, and the trader enters a position as the price retraces to the 0.618 Fibonacci level.
Part of the Smart Money approach, this setup combines liquidity analysis with technical tools, creating an opportunity for traders to enter high-accuracy trades. By following this setup, traders can identify critical market moves and capitalize on reversal points effectively.
Bullish :
Bearish :
🔵 How to Use
The One Shot One Kill setup is a structured and advanced trading strategy based on Liquidity Hunt, Fibonacci retracement, and market structure shifts (CISD). With a focus on precise Price Action analysis, this setup helps traders identify key market movements and plan optimal trade entries and exits. It operates in two scenarios: Bullish and Bearish, each with distinct steps.
🟣 Bullish One Shot One Kill
In the Bullish scenario, the process starts with the price moving toward the Previous Day Low, where liquidity is absorbed. At this stage, retail sellers are trapped as they enter short trades at lower levels. Following this, the market reverses upward and breaks the CISD, signaling a shift in market structure toward bullishness.
Once this shift is identified, traders draw Fibonacci levels from the lowest point to the highest point of the move. When the price retraces to the 0.618 Fibonacci level, conditions for a buy position are met. The target for this trade is typically the Previous Day High or other significant liquidity zones where major buyers are positioned, offering a high probability of price reversal.
🟣 Bearish One Shot One Kill
In the Bearish scenario, the price initially moves toward the Previous Day High to absorb liquidity. Retail buyers are trapped as they enter long trades near the highs. After the liquidity hunt, the market reverses downward, breaking the CISD, which signals a bearish shift in market structure. Following this confirmation, Fibonacci levels are drawn from the highest point to the lowest point of the move.
When the price retraces to the 0.618 Fibonacci level, a sell position is initiated. The target for this trade is usually the Previous Day Low or other key liquidity zones where major sellers are active.
This setup provides a precise and logical framework for traders to identify market movements and enter trades at critical reversal points.
🔵 Settings
🟣 CISD Logical settings
Bar Back Check : Determining the return of candles to identify the CISD level.
CISD Level Validity : CISD level validity period based on the number of candles.
🟣 LIQUIDITY Logical settings
Swing period : You can set the swing detection period.
Max Swing Back Method : It is in two modes "All" and "Custom". If it is in "All" mode, it will check all swings, and if it is in "Custom" mode, it will check the swings to the extent you determine.
Max Swing Back : You can set the number of swings that will go back for checking.
🟣 CISD Display settings
Displaying or not displaying swings and setting the color of labels and lines.
🟣 LIQUIDITY Display settings
Displaying or not displaying swings and setting the color of labels and lines.
🔵 Conclusion
The One Shot One Kill setup is one of the most effective and well-structured trading strategies for identifying and capitalizing on key market movements. By incorporating concepts such as Liquidity Hunt, CISD, and Fibonacci retracement, this setup allows traders to enter trades with high precision at optimal points.
The strategy emphasizes detailed Price Action analysis and the identification of Smart Money behavior, helping traders to execute successful trades against the general market trend.
With a focus on identifying liquidity in the Previous Day High and Low and aligning it with Fibonacci retracement levels, this setup provides a robust framework for entering both bullish and bearish trades.
The combination of liquidity analysis and Fibonacci retracement at the 0.618 level enables traders to minimize risk and exploit major market moves effectively.
Ultimately, success with the One Shot One Kill setup requires practice, patience, and strict adherence to its rules. By mastering its concepts and focusing on high-probability setups, traders can enhance their decision-making skills and build a sustainable and professional trading approach.
Triple Differential Moving Average BraidThe Triple Differential Moving Average Braid weaves together three distinct layers of moving averages—short-term, medium-term, and long-term—providing a structured view of market trends across multiple time horizons. It is an integrated construct optimized exclusively for the 1D timeframe. For multi-timeframe analysis and/or trading the lower 1h and 15m charts, it pairs well the Granular Daily Moving Average Ribbon ... adjust the visibility settings accordingly.
Unlike traditional moving average indicators that use a single moving average crossover, this braid-style system incorporates both SMAs and EMAs. The dual-layer approach offers stability and responsiveness, allowing traders to detect trend shifts with greater confidence.
Users can, of course, specify their own color scheme. The indicator consists of three layered moving average pairs. These are named per their default colors:
1. Silver Thread – Tracks immediate price momentum.
2. Royal Guard – Captures market structure and developing trends.
3. Golden Section – Defines major market cycles and overall trend direction.
Each layer is color-coded and dynamically shaded based on whether the faster-moving average is above or below its slower counterpart, providing a visual representation of market strength and trend alignment.
🧵 Silver Thread
The Silver Thread is the fastest-moving layer, comprising the 21D SMA and a 21D EMA. The choice of 21 is intentional, as it corresponds to approximately one full month of trading days in a 5-day-per-week market and is also a Fibonacci number, reinforcing its use in technical analysis.
· The 21D SMA smooths out recent price action, offering a baseline for short-term structure.
· The 21D EMA reacts more quickly to price changes, highlighting shifts in momentum.
· When the SMA is above the EMA, price action remains stable.
· When the SMA falls below the EMA, short-term momentum weakens.
The Silver Thread is a leading indicator within the system, often flipping direction before the medium- and long-term layers follow suit. If the Silver Thread shifts bearish while the Royal Guard remains bullish, this can signal a temporary pullback rather than a full trend reversal.
👑 Royal Guard
The Royal Guard provides a broader perspective on market momentum by using a 50D EMA and a 200D EMA. EMAs prioritize recent price data, making this layer faster-reacting than the Golden Section while still offering a level of stability.
· When the 50D EMA is above the 200D EMA, the market is in a confirmed uptrend.
· When the 50D EMA crosses below the 200D EMA, momentum has shifted bearish.
This layer confirms medium-term trend structure and reacts more quickly to price changes than traditional SMAs, making it especially useful for trend-following traders who need faster confirmation than the Golden Section provides.
If the Silver Thread flips bearish while the Royal Guard remains bullish, traders may be seeing a momentary dip in an otherwise intact uptrend. Conversely, if both the Silver Thread and Royal Guard shift bearish, this suggests a deeper pullback or possible trend reversal.
📜 Golden Section
The Golden Section is the slowest and most stable layer of the system, utilizing a 50D SMA and a 200D SMA—a classic combination used by long-term traders and institutions.
· When the 50D SMA is above the 200D SMA the market is in a strong, sustained uptrend.
· When the 50D SMA falls below the 200D SMA the market is structurally bearish.
Because SMAs give equal weight to past price data, this layer moves slowly and deliberately, ensuring that false breakouts or temporary swings do not distort the bigger picture.
Traders can use the Golden Section to confirm major market trends—when all three layers are bullish, the market is strongly trending upward. If the Golden Section remains bullish while the Royal Guard turns bearish, this may indicate a medium-term correction within a larger uptrend rather than a full reversal.
🎯 Swing Trade Setups
Swing traders can benefit from the multi-layered approach of this indicator by aligning their trades with the overall market structure while capturing short-term momentum shifts.
· Bullish: Look for Silver Thread and Royal Guard alignment before entering. If the Silver Thread flips bullish first, anticipate a momentum shift. If the Royal Guard follows, this confirms a strong medium-term move.
· Bearish: If the Silver Thread turns bearish first, it may signal an upcoming reversal. Waiting for the Royal Guard to follow adds confirmation.
· Confirmation: If the Golden Section remains bullish, a pullback may be an opportunity to enter a trend continuation trade rather than exit prematurely.
🚨 Momentum Shifts
· If the Silver Thread flips bearish but the Royal Guard remains bullish, traders may opt to buy the dip rather than exit their positions.
· If both the Silver Thread and Royal Guard turn bearish, traders should exercise caution, as this suggests a more significant correction.
· When all three layers align in the same direction the market is in a strong trending phase, making swing trades higher probability.
⚠️ Risk Management
· A narrowing of the shaded areas suggests trend exhaustion—consider tightening stop losses.
· When the Golden Section remains bullish, but the other two layers weaken, potential support zones to enter or re-enter positions.
· If all three layers flip bearish, this may indicate a larger trend reversal, prompting an exit from long positions and/or consideration of short setups.
The Triple Differential Moving Average Braid is layered, structured tool for trend analysis, offering insights across multiple timeframes without requiring traders to manually compare different moving averages. It provides a powerful and intuitive way to read the market. Swing traders, trend-followers, and position traders alike can use it to align their trades with dominant market trends, time pullbacks, and anticipate momentum shifts.
By understanding how these three moving average layers interact, traders gain a deeper, more holistic perspective of market structure—one that adapts to both momentum-driven opportunities and longer-term trend positioning.
AMD Setup - Full (Long + Short) ICT ModelICTSNIPERKILLS!
Accumulation, Manipulation, Distribution (AMD) Script!
1. Clarifies Structure: Accumulation, Manipulation, Distribution (AMD)
The script visualizes the AMD framework:
Accumulation → Price ranges inside Initial Balance (IB).
Manipulation → Liquidity sweep above IB High or below IB Low.
Distribution → Market Structure Shift (MSS) confirms a directional move.
This gives you a narrative structure for each session, helping you avoid random trades.
🧠 2. Filters Out Noise with MSS Confirmation
It waits for:
A liquidity sweep (manipulation),
Followed by a market structure shift (MSS),
And then confirms an entry only after a candle closes beyond structure.
This structure:
Reduces false signals,
Improves trade timing,
Helps you align with smart money delivery.
🕘 3. Focuses on the Right Time Window (Initial Balance)
You only engage after the 10:30 AM EST close, once the Initial Balance is formed.This aligns with ICT's focus on:
Killzones (like 9:30–11:00),
Avoiding early overtrading,
Letting the market tip its hand first (through sweeps + MSS).
This timing logic supports discipline and consistency.
🟢🔴 4. Marks Entries with Risk/Reward Guidance
It plots:
AMD SHORT / LONG entries after MSS + candle confirmation,
Basic TP and SL visual markers using a static risk-reward (2:1),
Optional Fair Value Gaps (FVGs) for refinement zones.
While static, these help plan trades visually and frame targets quickly, especially if you're scalping or trading micro futures like MNQ.
📈 5. Alerts You in Real Time
Instead of manually watching:
You'll get alerts when sweeps or MSS setups appear.
You can stay focused during the killzone or walk away and return when signals trigger.
This supports patience and alert-based discipline.
💡
You already:
Use 15M/1M execution,
Wait for ERL or HOD/LOD sweeps,
Look for MSS + CISD,
Trade in killzones only,
Target 50–62–70% Fibs with SMT/FVG confluence.
This script:✅ Automates sweep + MSS detection✅ Plots AMD-based entries visually✅ Simplifies your killzone execution✅ Helps avoid FOMO by filtering setups✅ Keeps your journal entries clean with structure
Supply and Demand [tambangEA]Supply and Demand Indicator Overview
The Supply and Demand indicator on TradingView is a technical tool designed to help traders identify areas of significant buying and selling pressure in the market. By identifying zones where price is likely to react, it helps traders pinpoint key support and resistance levels based on the concepts of supply and demand. This indicator plots zones using four distinct types of market structures:
1. Rally-Base-Rally (RBR) : This structure represents a bullish continuation zone. It occurs when the price rallies (increases), forms a base (consolidates), and then rallies again. The base represents a period where buying interest builds up before the continuation of the upward movement. This zone can act as support, where buyers may step back in if the price revisits the area.
2. Drop-Base-Rally (DBR) : This structure marks a bullish reversal zone. It forms when the price drops, creates a base, and then rallies. The base indicates a potential exhaustion of selling pressure and a build-up of buying interest. When price revisits this zone, it may act as support, signaling a buying opportunity.
3. Rally-Base-Drop (RBD) : This structure signifies a bearish reversal zone. Here, the price rallies, consolidates into a base, and then drops. The base indicates a temporary balance before sellers overpower buyers. If price returns to this zone, it may act as resistance, with selling interest potentially re-emerging.
4. Drop-Base-Drop (DBD) : This structure is a bearish continuation zone. It occurs when the price drops, forms a base, and then continues dropping. This base reflects a pause before further downward movement. The zone may act as resistance, with sellers possibly stepping back in if the price revisits the area.
Features of Supply and Demand Indicator
Automatic Zone Detection : The indicator automatically identifies and plots RBR, DBR, RBD, and DBD zones on the chart, making it easier to see potential supply and demand areas.
Customizable Settings : Users can typically adjust the color and transparency of the zones, time frames for analysis, and zone persistence to suit different trading styles.
Visual Alerts : Many versions include alert functionalities, notifying users when price approaches a plotted supply or demand zone.
How to Use Supply and Demand in Trading
Identify High-Probability Reversal Zones : Look for DBR and RBD zones to identify potential areas where price may reverse direction.
Trade Continuations with RBR and DBD Zones : These zones can indicate strong trends, suggesting that price may continue in the same direction.
Combine with Other Indicators: Use it alongside trend indicators, volume analysis, or price action strategies to confirm potential trade entries and exits.
This indicator is particularly useful for swing and day traders who rely on price reaction zones for entering and exiting trades.
Langlands-Operadic Möbius Vortex (LOMV)Langlands-Operadic Möbius Vortex (LOMV)
Where Pure Mathematics Meets Market Reality
A Revolutionary Synthesis of Number Theory, Category Theory, and Market Dynamics
🎓 THEORETICAL FOUNDATION
The Langlands-Operadic Möbius Vortex represents a groundbreaking fusion of three profound mathematical frameworks that have never before been combined for market analysis:
The Langlands Program: Harmonic Analysis in Markets
Developed by Robert Langlands (Fields Medal recipient), the Langlands Program creates bridges between number theory, algebraic geometry, and harmonic analysis. In our indicator:
L-Function Implementation:
- Utilizes the Möbius function μ(n) for weighted price analysis
- Applies Riemann zeta function convergence principles
- Calculates quantum harmonic resonance between -2 and +2
- Measures deep mathematical patterns invisible to traditional analysis
The L-Function core calculation employs:
L_sum = Σ(return_val × μ(n) × n^(-s))
Where s is the critical strip parameter (0.5-2.5), controlling mathematical precision and signal smoothness.
Operadic Composition Theory: Multi-Strategy Democracy
Category theory and operads provide the mathematical framework for composing multiple trading strategies into a unified signal. This isn't simple averaging - it's mathematical composition using:
Strategy Composition Arity (2-5 strategies):
- Momentum analysis via RSI transformation
- Mean reversion through Bollinger Band mathematics
- Order Flow Polarity Index (revolutionary T3-smoothed volume analysis)
- Trend detection using Directional Movement
- Higher timeframe momentum confirmation
Agreement Threshold System: Democratic voting where strategies must reach consensus before signal generation. This prevents false signals during market uncertainty.
Möbius Function: Number Theory in Action
The Möbius function μ(n) forms the mathematical backbone:
- μ(n) = 1 if n is a square-free positive integer with even number of prime factors
- μ(n) = -1 if n is a square-free positive integer with odd number of prime factors
- μ(n) = 0 if n has a squared prime factor
This creates oscillating weights that reveal hidden market periodicities and harmonic structures.
🔧 COMPREHENSIVE INPUT SYSTEM
Langlands Program Parameters
Modular Level N (5-50, default 30):
Primary lookback for quantum harmonic analysis. Optimized by timeframe:
- Scalping (1-5min): 15-25
- Day Trading (15min-1H): 25-35
- Swing Trading (4H-1D): 35-50
- Asset-specific: Crypto 15-25, Stocks 30-40, Forex 35-45
L-Function Critical Strip (0.5-2.5, default 1.5):
Controls Riemann zeta convergence precision:
- Higher values: More stable, smoother signals
- Lower values: More reactive, catches quick moves
- High frequency: 0.8-1.2, Medium: 1.3-1.7, Low: 1.8-2.3
Frobenius Trace Period (5-50, default 21):
Galois representation lookback for price-volume correlation:
- Measures harmonic relationships in market flows
- Scalping: 8-15, Day Trading: 18-25, Swing: 25-40
HTF Multi-Scale Analysis:
Higher timeframe context prevents trading against major trends:
- Provides market bias and filters signals
- Improves win rates by 15-25% through trend alignment
Operadic Composition Parameters
Strategy Composition Arity (2-5, default 4):
Number of algorithms composed for final signal:
- Conservative: 4-5 strategies (higher confidence)
- Moderate: 3-4 strategies (balanced approach)
- Aggressive: 2-3 strategies (more frequent signals)
Category Agreement Threshold (2-5, default 3):
Democratic voting minimum for signal generation:
- Higher agreement: Fewer but higher quality signals
- Lower agreement: More signals, potential false positives
Swiss-Cheese Mixing (0.1-0.5, default 0.382):
Golden ratio φ⁻¹ based blending of trend factors:
- 0.382 is φ⁻¹, optimal for natural market fractals
- Higher values: Stronger trend following
- Lower values: More contrarian signals
OFPI Configuration:
- OFPI Length (5-30, default 14): Order Flow calculation period
- T3 Smoothing (3-10, default 5): Advanced exponential smoothing
- T3 Volume Factor (0.5-1.0, default 0.7): Smoothing aggressiveness control
Unified Scoring System
Component Weights (sum ≈ 1.0):
- L-Function Weight (0.1-0.5, default 0.3): Mathematical harmony emphasis
- Galois Rank Weight (0.1-0.5, default 0.2): Market structure complexity
- Operadic Weight (0.1-0.5, default 0.3): Multi-strategy consensus
- Correspondence Weight (0.1-0.5, default 0.2): Theory-practice alignment
Signal Threshold (0.5-10.0, default 5.0):
Quality filter producing:
- 8.0+: EXCEPTIONAL signals only
- 6.0-7.9: STRONG signals
- 4.0-5.9: MODERATE signals
- 2.0-3.9: WEAK signals
🎨 ADVANCED VISUAL SYSTEM
Multi-Dimensional Quantum Aura Bands
Five-layer resonance field showing market energy:
- Colors: Theme-matched gradients (Quantum purple, Holographic cyan, etc.)
- Expansion: Dynamic based on score intensity and volatility
- Function: Multi-timeframe support/resistance zones
Morphism Flow Portals
Category theory visualization showing market topology:
- Green/Cyan Portals: Bullish mathematical flow
- Red/Orange Portals: Bearish mathematical flow
- Size/Intensity: Proportional to signal strength
- Recursion Depth (1-8): Nested patterns for flow evolution
Fractal Grid System
Dynamic support/resistance with projected L-Scores:
- Multiple Timeframes: 10, 20, 30, 40, 50-period highs/lows
- Smart Spacing: Prevents level overlap using ATR-based minimum distance
- Projections: Estimated signal scores when price reaches levels
- Usage: Precise entry/exit timing with mathematical confirmation
Wick Pressure Analysis
Rejection level prediction using candle mathematics:
- Upper Wicks: Selling pressure zones (purple/red lines)
- Lower Wicks: Buying pressure zones (purple/green lines)
- Glow Intensity (1-8): Visual emphasis and line reach
- Application: Confluence with fractal grid creates high-probability zones
Regime Intensity Heatmap
Background coloring showing market energy:
- Black/Dark: Low activity, range-bound markets
- Purple Glow: Building momentum and trend development
- Bright Purple: High activity, strong directional moves
- Calculation: Combines trend, momentum, volatility, and score intensity
Six Professional Themes
- Quantum: Purple/violet for general trading and mathematical focus
- Holographic: Cyan/magenta optimized for cryptocurrency markets
- Crystalline: Blue/turquoise for conservative, stability-focused trading
- Plasma: Gold/magenta for high-energy volatility trading
- Cosmic Neon: Bright neon colors for maximum visibility and aggressive trading
📊 INSTITUTIONAL-GRADE DASHBOARD
Unified AI Score Section
- Total Score (-10 to +10): Primary decision metric
- >5: Strong bullish signals
- <-5: Strong bearish signals
- Quality ratings: EXCEPTIONAL > STRONG > MODERATE > WEAK
- Component Analysis: Individual L-Function, Galois, Operadic, and Correspondence contributions
Order Flow Analysis
Revolutionary OFPI integration:
- OFPI Value (-100% to +100%): Real buying vs selling pressure
- Visual Gauge: Horizontal bar chart showing flow intensity
- Momentum Status: SHIFTING, ACCELERATING, STRONG, MODERATE, or WEAK
- Trading Application: Flow shifts often precede major moves
Signal Performance Tracking
- Win Rate Monitoring: Real-time success percentage with emoji indicators
- Signal Count: Total signals generated for frequency analysis
- Current Position: LONG, SHORT, or NONE with P&L tracking
- Volatility Regime: HIGH, MEDIUM, or LOW classification
Market Structure Analysis
- Möbius Field Strength: Mathematical field oscillation intensity
- CHAOTIC: High complexity, use wider stops
- STRONG: Active field, normal position sizing
- MODERATE: Balanced conditions
- WEAK: Low activity, consider smaller positions
- HTF Trend: Higher timeframe bias (BULL/BEAR/NEUTRAL)
- Strategy Agreement: Multi-algorithm consensus level
Position Management
When in trades, displays:
- Entry Price: Original signal price
- Current P&L: Real-time percentage with risk level assessment
- Duration: Bars in trade for timing analysis
- Risk Level: HIGH/MEDIUM/LOW based on current exposure
🚀 SIGNAL GENERATION LOGIC
Balanced Long/Short Architecture
The indicator generates signals through multiple convergent pathways:
Long Entry Conditions:
- Score threshold breach with algorithmic agreement
- Strong bullish order flow (OFPI > 0.15) with positive composite signal
- Bullish pattern recognition with mathematical confirmation
- HTF trend alignment with momentum shifting
- Extreme bullish OFPI (>0.3) with any positive score
Short Entry Conditions:
- Score threshold breach with bearish agreement
- Strong bearish order flow (OFPI < -0.15) with negative composite signal
- Bearish pattern recognition with mathematical confirmation
- HTF trend alignment with momentum shifting
- Extreme bearish OFPI (<-0.3) with any negative score
Exit Logic:
- Score deterioration below continuation threshold
- Signal quality degradation
- Opposing order flow acceleration
- 10-bar minimum between signals prevents overtrading
⚙️ OPTIMIZATION GUIDELINES
Asset-Specific Settings
Cryptocurrency Trading:
- Modular Level: 15-25 (capture volatility)
- L-Function Precision: 0.8-1.3 (reactive to price swings)
- OFPI Length: 10-20 (fast correlation shifts)
- Cascade Levels: 5-7, Theme: Holographic
Stock Index Trading:
- Modular Level: 25-35 (balanced trending)
- L-Function Precision: 1.5-1.8 (stable patterns)
- OFPI Length: 14-20 (standard correlation)
- Cascade Levels: 4-5, Theme: Quantum
Forex Trading:
- Modular Level: 35-45 (smooth trends)
- L-Function Precision: 1.6-2.1 (high smoothing)
- OFPI Length: 18-25 (disable volume amplification)
- Cascade Levels: 3-4, Theme: Crystalline
Timeframe Optimization
Scalping (1-5 minute charts):
- Reduce all lookback parameters by 30-40%
- Increase L-Function precision for noise reduction
- Enable all visual elements for maximum information
- Use Small dashboard to save screen space
Day Trading (15 minute - 1 hour):
- Use default parameters as starting point
- Adjust based on market volatility
- Normal dashboard provides optimal information density
- Focus on OFPI momentum shifts for entries
Swing Trading (4 hour - Daily):
- Increase lookback parameters by 30-50%
- Higher L-Function precision for stability
- Large dashboard for comprehensive analysis
- Emphasize HTF trend alignment
🏆 ADVANCED TRADING STRATEGIES
The Mathematical Confluence Method
1. Wait for Fractal Grid level approach
2. Confirm with projected L-Score > threshold
3. Verify OFPI alignment with direction
4. Enter on portal signal with quality ≥ STRONG
5. Exit on score deterioration or opposing flow
The Regime Trading System
1. Monitor Aether Flow background intensity
2. Trade aggressively during bright purple periods
3. Reduce position size during dark periods
4. Use Möbius Field strength for stop placement
5. Align with HTF trend for maximum probability
The OFPI Momentum Strategy
1. Watch for momentum shifting detection
2. Confirm with accelerating flow in direction
3. Enter on immediate portal signal
4. Scale out at Fibonacci levels
5. Exit on flow deceleration or reversal
⚠️ RISK MANAGEMENT INTEGRATION
Mathematical Position Sizing
- Use Galois Rank for volatility-adjusted sizing
- Möbius Field strength determines stop width
- Fractal Dimension guides maximum exposure
- OFPI momentum affects entry timing
Signal Quality Filtering
- Trade only STRONG or EXCEPTIONAL quality signals
- Increase position size with higher agreement levels
- Reduce risk during CHAOTIC Möbius field periods
- Respect HTF trend alignment for directional bias
🔬 DEVELOPMENT JOURNEY
Creating the LOMV was an extraordinary mathematical undertaking that pushed the boundaries of what's possible in technical analysis. This indicator almost didn't happen. The theoretical complexity nearly proved insurmountable.
The Mathematical Challenge
Implementing the Langlands Program required deep research into:
- Number theory and the Möbius function
- Riemann zeta function convergence properties
- L-function analytical continuation
- Galois representations in finite fields
The mathematical literature spans decades of pure mathematics research, requiring translation from abstract theory to practical market application.
The Computational Complexity
Operadic composition theory demanded:
- Category theory implementation in Pine Script
- Multi-dimensional array management for strategy composition
- Real-time democratic voting algorithms
- Performance optimization for complex calculations
The Integration Breakthrough
Bringing together three disparate mathematical frameworks required:
- Novel approaches to signal weighting and combination
- Revolutionary Order Flow Polarity Index development
- Advanced T3 smoothing implementation
- Balanced signal generation preventing directional bias
Months of intensive research culminated in breakthrough moments when the mathematics finally aligned with market reality. The result is an indicator that reveals market structure invisible to conventional analysis while maintaining practical trading utility.
🎯 PRACTICAL IMPLEMENTATION
Getting Started
1. Apply indicator with default settings
2. Select appropriate theme for your markets
3. Observe dashboard metrics during different market conditions
4. Practice signal identification without trading
5. Gradually adjust parameters based on observations
Signal Confirmation Process
- Never trade on score alone - verify quality rating
- Confirm OFPI alignment with intended direction
- Check fractal grid level proximity for timing
- Ensure Möbius field strength supports position size
- Validate against HTF trend for bias confirmation
Performance Monitoring
- Track win rate in dashboard for strategy assessment
- Monitor component contributions for optimization
- Adjust threshold based on desired signal frequency
- Document performance across different market regimes
🌟 UNIQUE INNOVATIONS
1. First Integration of Langlands Program mathematics with practical trading
2. Revolutionary OFPI with T3 smoothing and momentum detection
3. Operadic Composition using category theory for signal democracy
4. Dynamic Fractal Grid with projected L-Score calculations
5. Multi-Dimensional Visualization through morphism flow portals
6. Regime-Adaptive Background showing market energy intensity
7. Balanced Signal Generation preventing directional bias
8. Professional Dashboard with institutional-grade metrics
📚 EDUCATIONAL VALUE
The LOMV serves as both a practical trading tool and an educational gateway to advanced mathematics. Traders gain exposure to:
- Pure mathematics applications in markets
- Category theory and operadic composition
- Number theory through Möbius function implementation
- Harmonic analysis via L-function calculations
- Advanced signal processing through T3 smoothing
⚖️ RESPONSIBLE USAGE
This indicator represents advanced mathematical research applied to market analysis. While the underlying mathematics are rigorously implemented, markets remain inherently unpredictable.
Key Principles:
- Use as part of comprehensive trading strategy
- Implement proper risk management at all times
- Backtest thoroughly before live implementation
- Understand that past performance does not guarantee future results
- Never risk more than you can afford to lose
The mathematics reveal deep market structure, but successful trading requires discipline, patience, and sound risk management beyond any indicator.
🔮 CONCLUSION
The Langlands-Operadic Möbius Vortex represents a quantum leap forward in technical analysis, bringing PhD-level pure mathematics to practical trading while maintaining visual elegance and usability.
From the harmonic analysis of the Langlands Program to the democratic composition of operadic theory, from the number-theoretic precision of the Möbius function to the revolutionary Order Flow Polarity Index, every component works in mathematical harmony to reveal the hidden order within market chaos.
This is more than an indicator - it's a mathematical lens that transforms how you see and understand market structure.
Trade with mathematical precision. Trade with the LOMV.
*"Mathematics is the language with which God has written the universe." - Galileo Galilei*
*In markets, as in nature, profound mathematical beauty underlies apparent chaos. The LOMV reveals this hidden order.*
— Dskyz, Trade with insight. Trade with anticipation.
TTM Scalper AlertTTM Scalper Alert — Real-Time Pivot Detector
Description:
This is a custom implementation of the classic TTM Scalper Alert, adapted to show early pivot detection and trend structure tracking in real-time. The script identifies potential highs and lows before the full pivot confirmation—giving traders an early edge—and removes outdated signals once pivots are confirmed.
It supports two levels of detection:
Fast Alert Pivots : Identified after Alert Period candles confirm a local reversal.
Confirmed Pivots : Validated only after Pivot Period candles on both sides ensure a true swing high/low.
How It Works:
Fast Detection (Early Pivots):
Detected after Alert Period (AP) candles. These are provisional signals, shown as triangle labels (▲▼) near current price. Only the latest signal is shown; previous fast pivots are deleted to avoid clutter.
Confirmed Pivots:
Detected with a full lookback of Pivot Period (PP) on both sides of the candle. Shown using plotshape with triangle markers (▲▼). Serve as anchors for price structure analysis (HH-HL or LL-LH tracking).
Custom Source Option:
Users can choose to base pivots on High/Low or Close/Open range. Helps adjust sensitivity depending on volatility or bar structure.
How to Interpret:
Trend & Market Structure:
Use Confirmed Pivots (plotshapes) to analyze market structure:
HH → HL: Uptrend
LL → LH: Downtrend
Watch for breaks in structure for possible reversals
Early Alerts:
The floating labels (▲▼) represent early warnings of a potential pivot. Use them to anticipate:
Short-term exhaustion
Quick scalping entries
Divergence setups
Inputs:
Source : Choose from High/Low or Close/Open — affects how pivots are calculated
Alert Period : How fast the script detects an early reversal pattern (used for entry timing)
Pivot Period : How many candles before/after to confirm a full pivot (used for structural analysis)
Best For:
Traders who follow price action and structure
Scalpers and intraday traders who want early signals
Anyone using pivot highs/lows for confluence with other tools (like RSI divergence, Bollinger Bands, VWAP, etc.)
Pro Tips:
Combine this with:
Trend Magic or Supertrend for directional bias
Volume spike filters to confirm reversal intent
RSI/CCI divergence to strengthen reversal pivots
Adjust Alert Period to tune early signal sensitivity (lower = faster but noisier)
Quarterly Theory ICT 04 [TradingFinder] SSMT 4Quarter Divergence🔵 Introduction
Sequential SMT Divergence is an advanced price-action-based analytical technique rooted in the ICT (Inner Circle Trader) methodology. Its primary objective is to identify early-stage divergences between correlated assets within precise time structures. This tool not only breaks down market structure but also enables traders to detect engineered liquidity traps before the market reacts.
In simple terms, SMT (Smart Money Technique) occurs when two correlated assets—such as indices (ES and NQ), currency pairs (EURUSD and GBPUSD), or commodities (Gold and Silver)—exhibit different reactions at key price levels (swing highs or lows). This lack of alignment is often a sign of smart money manipulation and signals a lack of confirmation in the ongoing trend—hinting at an imminent reversal or at least a pause in momentum.
In its Sequential form, SMT divergences are examined through a more granular temporal lens—between intraday quarters (Q1 through Q4). When SMT appears at the transition from one quarter to another (e.g., Q1 to Q2 or Q3 to Q4), the signal becomes significantly more powerful, often aligning with a critical phase in the Quarterly Theory—a framework that segments market behavior into four distinct phases: Accumulation, Manipulation, Distribution, and Reversal/Continuation.
For instance, a Bullish SMT forms when one asset prints a new low while its correlated counterpart fails to break the corresponding low from the previous quarter. This usually indicates absorption of selling pressure and the beginning of accumulation by smart money. Conversely, a Bearish SMT arises when one asset makes a higher high, but the second asset fails to confirm, signaling distribution or a fake-out before a decline.
However, SMT alone is not enough. To confirm a true Market Structure Break (MSB), the appearance of a Precision Swing Point (PSP) is essential—a specific candlestick formation on a lower timeframe (typically 5 to 15 minutes) that reveals the entry of institutional participants. The combination of SMT and PSP provides a more accurate entry point and better understanding of premium and discount zones.
The Sequential SMT Indicator, introduced in this article, dynamically scans charts for such divergence patterns across multiple sessions. It is applicable to various markets including Forex, crypto, commodities, and indices, and shows particularly strong performance during mid-week sessions (Wednesdays and Thursdays)—when most weekly highs and lows tend to form.
Bullish Sequential SMT :
Bearish Sequential SMT :
🔵 How to Use
The Sequential SMT (SSMT) indicator is designed to detect time and structure-based divergences between two correlated assets. This divergence occurs when both assets print a similar swing (high or low) in the previous quarter (e.g., Q3), but in the current quarter (e.g., Q4), only one asset manages to break that swing level—while the other fails to reach it.
This temporal mismatch is precisely identified by the SSMT indicator and often signals smart money activity, a market phase transition, or even the presence of an engineered liquidity trap. The signal becomes especially powerful when paired with a Precision Swing Point (PSP)—a confirming candle on lower timeframes (5m–15m) that typically indicates a market structure break (MSB) and the entry of smart liquidity.
🟣 Bullish Sequential SMT
In the previous quarter, both assets form a similar swing low.
In the current quarter, one asset (e.g., EURUSD) breaks that low and trades below it.
The other asset (e.g., GBPUSD) fails to reach the same low, preserving the structure.
This time-based divergence reflects declining selling pressure, potential absorption, and often marks the end of a manipulation phase and the start of accumulation. If confirmed by a bullish PSP candle, it offers a strong long opportunity, with stop-losses defined just below the swing low.
🟣 Bearish Sequential SMT
In the previous quarter, both assets form a similar swing high.
In the current quarter, one asset (e.g., NQ) breaks above that high.
The other asset (e.g., ES) fails to reach that high, remaining below it.
This type of divergence signals weakening bullish momentum and the likelihood of distribution or a fake-out before a price drop. When followed by a bearish PSP candle, it sets up a strong shorting opportunity with targets in the discount zone and protective stops placed above the swing high.
🔵 Settings
⚙️ Logical Settings
Quarterly Cycles Type : Select the time segmentation method for SMT analysis.
Available modes include: Yearly, Monthly, Weekly, Daily, 90 Minute, and Micro.
These define how the indicator divides market time into Q1–Q4 cycles.
Symbol : Choose the secondary asset to compare with the main chart asset (e.g., XAUUSD, US100, GBPUSD).
Pivot Period : Sets the sensitivity of the pivot detection algorithm. A smaller value increases responsiveness to price swings.
Activate Max Pivot Back : When enabled, limits the maximum number of past pivots to be considered for divergence detection.
Max Pivot Back Length : Defines how many past pivots can be used (if the above toggle is active).
Pivot Sync Threshold : The maximum allowed difference (in bars) between pivots of the two assets for them to be compared.
Validity Pivot Length : Defines the time window (in bars) during which a divergence remains valid before it's considered outdated.
🎨 Display Settings
Show Cycle :Toggles the visual display of the current Quarter (Q1 to Q4) based on the selected time segmentation
Show Cycle Label : Shows the name (e.g., "Q2") of each detected Quarter on the chart.
Show Bullish SMT Line : Draws a line connecting the bullish divergence points.
Show Bullish SMT Label : Displays a label on the chart when a bullish divergence is detected.
Bullish Color : Sets the color for bullish SMT markers (label, shape, and line).
Show Bearish SMT Line : Draws a line for bearish divergence.
Show Bearish SMT Label : Displays a label when a bearish SMT divergence is found.
Bearish Color : Sets the color for bearish SMT visual elements.
🔔 Alert Settings
Alert Name : Custom name for the alert messages (used in TradingView’s alert system).
Message Frequency :
All: Every signal triggers an alert.
Once Per Bar: Alerts once per bar regardless of how many signals occur.
Per Bar Close: Only triggers when the bar closes and the signal still exists.
Time Zone Display : Choose the time zone in which alert timestamps are displayed (e.g., UTC).
Bullish SMT Divergence Alert : Enable/disable alerts specifically for bullish signals.
Bearish SMT Divergence Alert : Enable/disable alerts specifically for bearish signals
🔵 Conclusion
The Sequential SMT (SSMT) indicator is a powerful and precise tool for identifying structural divergences between correlated assets within a time-based framework. Unlike traditional divergence models that rely solely on sequential pivot comparisons, SSMT leverages Quarterly Theory, in combination with concepts like liquidity sweeps, market structure breaks (MSB) and precision swing points (PSP), to provide a deeper and more actionable view of market dynamics.
By using SSMT, traders gain not only the ability to identify where divergence occurs, but also when it matters most within the market cycle. This empowers them to anticipate major moves or traps before they fully materialize, and position themselves accordingly in high-probability trade zones.
Whether you're trading Forex, crypto, indices, or commodities, the true strength of this indicator is revealed when used in sync with the Accumulation, Manipulation, Distribution, and Reversal phases of the market. Integrated with other confluence tools and market models, SSMT can serve as a core component in a professional, rule-based, and highly personalized trading strategy.
Twitter Model ICT [TradingFinder] MMXM ERL D + FVG + M15 MSS/SMT🔵 Introduction
The Twitter Model ICT is a trading approach based on ICT (Inner Circle Trader) models, focusing on price movement between external and internal liquidity in lower timeframes. This model integrates key concepts such as Market Structure Shift (MSS), Smart Money Technique (SMT) divergence, and CISD level break to identify precise entry points in the market.
The primary goal of this model is to determine key liquidity levels, such as the previous day’s high and low (PDH/PDL) and align them with the Fair Value Gap (FVG) in the 1-hour timeframe. The overall strategy involves framing trades around the 1H FVG and using the M15 Market Structure Shift (MSS) for entry confirmation.
The Twitter Model ICT is designed to utilize external liquidity levels, such as PDH/PDL, as key entry zones. The model identifies FVG in the 1-hour timeframe, which acts as a magnet for price movement. Additionally, traders confirm entries using M15 Market Structure Shift (MSS) and SMT divergence.
Bullish Twitter Model :
In a bullish setup, the price sweeps the previous day’s low (PDL), and after confirming reversal signals, buys are executed in internal liquidity zones. Conversely, in a bearish setup, the price sweeps the previous day’s high (PDH), and after confirming weakness signals, sells are executed.
Bearish Twitter Model :
In short setups, entries are only executed above the Midnight Open, while in long setups, entries are taken below the Midnight Open. Adhering to these principles allows traders to define precise entry and exit points and analyze price movement with greater accuracy based on liquidity and market structure.
🔵 How to Use
The Twitter Model ICT is a liquidity-based trading strategy that analyzes price movements relative to the previous day’s high and low (PDH/PDL) and Fair Value Gap (FVG). This model is applicable in both bullish and bearish directions and utilizes the 1-hour (1H) and 15-minute (M15) timeframes for entry confirmation.
The price first sweeps an external liquidity level (PDH or PDL) and then provides an entry opportunity based on Market Structure Shift (MSS) and SMT divergence. Additionally, the entry should be positioned relative to the Midnight Open, meaning long entries should occur below the Midnight Open and short entries above it.
🟣 Bullish Twitter Model
In a bullish setup, the price first sweeps the previous day’s low (PDL) and reaches an external liquidity level. Then, in the 1-hour timeframe (1H), a bullish Fair Value Gap (FVG) forms, which serves as the price target.
To confirm the entry, a Market Structure Shift (MSS) in the 15-minute timeframe (M15) should be observed, signaling a trend reversal to the upside. Additionally, SMT divergence with correlated assets can indicate weakness in selling pressure.
Under these conditions, a long position is taken below the Midnight Open, with a stop-loss placed at the lowest point of the recent bearish move. The price target for this trade is the FVG in the 1-hour timeframe.
🟣 Bearish Twitter Model
In a bearish setup, the price first sweeps the previous day’s high (PDH) and reaches an external liquidity level. Then, in the 1-hour timeframe (1H), a bearish Fair Value Gap (FVG) is identified, serving as the trade target.
To confirm entry, a Market Structure Shift (MSS) in the 15-minute timeframe (M15) should form, signaling a trend shift to the downside. If an SMT divergence is present, it can provide additional confirmation for the trade.
Once these conditions are met, a short position is taken above the Midnight Open, with a stop-loss placed at the highest level of the recent bullish move. The trade's price target is the FVG in the 1-hour timeframe.
🔵 Settings
Bar Back Check : Determining the return of candles to identify the CISD level.
CISD Level Validity : CISD level validity period based on the number of candles.
Daily Position : Determines whether only the first signal of the day is considered or if signals are evaluated throughout the entire day.
Session : Specifies in which trading sessions the indicator will be active.
Second Symbol : This setting allows you to select another asset for comparison with the primary asset. By default, "XAUUSD" (Gold) is set as the second symbol, but you can change it to any currency pair, stock, or cryptocurrency. For example, you can choose currency pairs like EUR/USD or GBP/USD to identify divergences between these two assets.
Divergence Fractal Periods : This parameter defines the number of past candles to consider when identifying divergences. The default value is 2, but you can change it to suit your preferences. This setting allows you to detect divergences more accurately by selecting a greater number of candles.
The indicator allows displaying sessions based on various time zones. The user can select one of the following options :
UTC (Coordinated Universal Time)
Local Time of the Session
User’s Local Time
Show Open Price : Displays the New York market opening price.
Show PDH / PDL : Displays the previous day’s high and low to identify potential entry points.
Show SMT Divergence : Displays lines and labels for bullish ("+SMT") and bearish ("-SMT") divergences.
🔵 Conclusion
The Twitter Model ICT is an effective approach for analyzing and executing trades in financial markets, utilizing a combination of liquidity principles, market structure, and SMT confirmations to identify optimal entry and exit points.
By analyzing the previous day’s high and low (PDH/PDL), Fair Value Gaps (FVG), and Market Structure Shift (MSS) in the 1H and M15 timeframes, traders can pinpoint liquidity-driven trade opportunities. Additionally, considering the Midnight Open level helps traders avoid random entries and ensures better trade placement.
By applying this model, traders can interpret market movements based on liquidity flow and structural changes, allowing them to fine-tune their trading decisions with higher precision. Ultimately, the Twitter Model ICT provides a structured and logical approach for traders who seek to trade based on liquidity behavior and trend shifts in the market.
Enhanced London Session SMC SetupEnhanced London Session SMC Setup Indicator
This Pine Script-based indicator is designed for traders focusing on the London trading session, leveraging smart money concepts (SMC) to identify potential trading opportunities in the GBP/USD currency pair. The script uses multiple techniques such as Order Block Detection, Imbalance (Fair Value Gap) Analysis, Change of Character (CHoCH) detection, and Fibonacci retracement levels to aid in market structure analysis, providing a well-rounded approach to trade setups.
Features:
London Session Highlight:
The indicator visually marks the London trading session (from 08:00 AM to 04:00 PM UTC) on the chart using a blue background, signaling when the high-volume, high-impulse moves tend to occur, helping traders focus their analysis on this key session.
Order Block Detection:
Identifies significant impulse moves that may form order blocks (supply and demand zones). Order blocks are areas where institutions have executed large orders, often leading to price reversals or continuation. The indicator plots the high and low of these order blocks, providing key levels to monitor for potential entries.
Imbalance (Fair Value Gap) Detection:
Detects and highlights price imbalances or fair value gaps (FVG) where the market has moved too quickly, creating a gap in price action. These areas are often revisited by price, offering potential trade opportunities. The upper and lower bounds of the imbalance are visually marked for easy reference.
Change of Character (CHoCH) Detection:
This feature identifies potential trend reversals by detecting significant changes in market character. When the price action shifts from bullish to bearish or vice versa, a CHoCH signal is triggered, and the corresponding level is marked on the chart. This can help traders catch trend reversals at key levels.
Fibonacci Retracement Levels:
The script calculates and plots the key Fibonacci retracement levels (0.618 and 0.786 by default) based on the highest and lowest points over a user-defined swing lookback period. These levels are commonly used by traders to identify potential pullback zones where price may reverse or find support/resistance.
Directional Bias Based on Market Structure:
The indicator provides a market structure analysis by comparing the current highs and lows to the previous periods' highs and lows. This helps in identifying whether the market is in a bullish or bearish state, providing a clear directional bias for trade setups.
Alerts:
The indicator comes with built-in alert conditions to notify the trader when an order block, imbalance, CHoCH, or other significant price action event is detected, ensuring timely action can be taken.
Ideal Usage:
Timeframe: Suitable for intraday trading, particularly focusing on the London session (08:00 AM to 04:00 PM UTC).
Currency Pair: Specifically designed for GBP/USD but can be adapted to other pairs with similar market behavior.
Trading Strategy: Best used in conjunction with a price action strategy, focusing on the key levels identified (order blocks, FVG, CHoCH) and using Fibonacci retracement levels for precision entries.
Target Audience: Ideal for traders who follow smart money concepts (SMC) and are looking for a structured approach to identify high-probability setups during the London session.
The ICT Ultimate Grid | MarketMaverisk GroupThe ICT Ultimate Grid | MarketMaverisk Group
This script is a fully customizable checklist based on ICT (Inner Circle Trader) concepts. It helps traders validate entry conditions across three timeframes:
LTP (Long-Term), ITP (Intermediate-Term), and STP (Short-Term).
⸻
✅ Purpose & Utility:
Instead of generating simple buy/sell signals, this tool assists traders in making structured, confirmation-based decisions. It presents a visual checklist with 11 customizable columns—each can be individually toggled for each timeframe and displays ✅ or ❌ confirmation status.
⸻
🧠 Confirmation Structure:
The checklist covers the following core elements from the ICT methodology:
• ERL⇔IRL and IRL⇔ERL (presented as special confirmations below the table)
• DOL – Drow On liqudity Level
• PD – permium or discuant
• SMT – Smart Money Trap / Inter-market Divergence
• CSD – Change in State of dlivery
• MSS – Market Structure Shift
• MMXM – Market maker (buy or sell) model
• FVG – Fair Value Gap
• OB – Order Block
• BRK.B – breker Block
Each item can be enabled or disabled for LTP, ITP, and STP individually.
⸻
📊 Visual Design:
• Clean, compact table displayed in the top-right corner of the chart.
• Clear color scheme (✅ Green = Confirmed, ❌ Red = Not Confirmed, Grey = Hidden/Disabled).
• Timeframes are stacked row-wise (LTP, ITP, STP).
• Inputs allow fine-grained control over what elements are shown in each timeframe.
• Additional rows are used to confirm:
• HTF Key Level
• Direction: Reversal ↩️ or Continuation 🔂
• Bias: Bullish 🔼 or Bearish 🔽
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📈 Use Case:
This tool is ideal for traders who follow:
• ICT-based trading approaches
• Market structure + Liquidity analysis
• Day trading, scalping, or swing setups
• Confirmation-based entries after higher-timeframe alignment
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⚙️ Recommended Timeframe Settings:
• LTP = D1 or 4H
• ITP = 1H or 15min
• STP = 5min or 3min or 1min
• Session time: Best used between 02:00 and 05:00 on london killzone & 08:00 and 12:00 on New york killzone in New York timezone (UTC -5)
(you can customize this in strategy version)
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🛠 Technical Note:
This version is an indicator and does not generate signals or alerts by itself. For full automation, a strategy version is also available upon request.
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Let me know if you’d like me to also write a “strategy description” or help you prepare the public chart layout 📊 to make your publish clean and attractivE
Apex Edge - MTF Confluence PanelApex Edge – MTF Confluence Panel
Description:
The Apex Edge – MTF Confluence Panel is a powerful multi-timeframe analysis tool built to streamline trade decision-making by aggregating key confluences across three user-defined timeframes. The panel visually presents the state of five core market signals—Trend, Momentum, Sweep, Structure, and Trap—alongside a unified Score column that summarizes directional bias with clarity.
Traders can customize the number of bullish/bearish conditions required to trigger a score signal, allowing the tool to be tailored for both conservative and aggressive trading styles. This script is designed for those who value a clean, structured, and objective approach to identifying market alignment—whether scalping or swing trading.
How it Works:
Across each of the three selected timeframes, the panel evaluates:
Trend: Based on a user-configurable Hull Moving Average (HMA), the script compares price relative to trend to determine bullish, bearish, or neutral bias.
Momentum: Uses OBV (On-Balance Volume) with volume spike detection to identify bursts of strong buying or selling pressure.
Sweep: Detects potential liquidity grabs by identifying price rejections beyond prior swing highs/lows. A break below a previous low with reversal signals bullish intent (and vice versa for bearish).
Structure: Uses dynamic pivot-based logic to identify market structure breaks (BOS) beyond recent confirmed swing levels.
Trap: Flags potential false moves by measuring RSI overbought/oversold signal clusters combined with minimal price movement—highlighting exhaustion or deceptive breaks.
Score: A weighted consensus of the above components. The number of required confluences to trigger a score (default: 3) can be set by the user via input, offering flexibility in signal sensitivity.
Why It’s Useful for Traders:
Quick Decision-Making: The color-coded panel provides instant visual feedback on whether confluences align across timeframes—ideal for fast-paced environments like scalping or high-volatility news sessions.
Multi-Timeframe Confidence: Helps eliminate guesswork by confirming whether higher and lower timeframe conditions support your trade idea.
Customizability: Adjustable confluence threshold means traders can fine-tune how sensitive the system is—more signals for faster entries, stricter confluence for higher conviction trades.
Built-In Alerts: Automated alerts for score alignment, trap detection, and liquidity sweeps allow traders to stay informed even when away from the screen.
Strategic Edge: Supports directional bias confirmation and trade filtering with logic designed to mimic professional decision-making workflows.
Features:
Clean, real-time confluence table across three user-selected timeframes
Configurable score sensitivity via “Minimum Confluences for Score” input
Cell-based colour coding for at-a-glance trade direction
Built-in alerts for score alignment, traps, and sweep triggers
Note - This Indicator works great in sync with Apex Edge - Session Sweep Pro
Useful levels for TP = previous session high/low boxes or fib levels.
⚠️ Disclaimer:
This script is for informational and educational purposes only and should not be considered financial advice. Always perform your own due diligence and practice proper risk management when trading.
Fibonacci Structure & Trend Channel (Expo)█ Overview
The Fibonacci Structure & Trend Channel (Expo) is designed to identify trend direction and potential reversal levels and offer insights into price structure based on Fibonacci ratios. The algorithm plots a Fibonacci channel, making it easier for traders to identify potential retracement points. Additionally, the Fibonacci market structure is plotted to enhance traders' understanding of the underlying order flow.
█ How to Use
Identify Trends
Use the plotted Fibonacci Trend Line to identify the direction of the market trend. A green line typically signifies a bullish trend, while a red line signifies a bearish trend.
Retracement Levels
The plotted Fibonacci levels can act as potential support or resistance levels. Look for price action signs at these levels for entry or exit points.
Channel Trading
If you enable the Fibonacci channel, the upper and lower bounds can act as overbought or oversold levels.
Market Structure
The plotted Fibonacci market structure serves as a valuable tool for dissecting the underlying order flow and gauging the strength or weakness of a trend. By analyzing these structures, traders can identify key levels where supply and demand intersect, which often act as pivotal points for trend reversals or accelerations. This visual representation simplifies complex market dynamics. Whether you're looking to catch a new trend early or seeking confirmation for a potential reversal, understanding the market structure plotted by the Fibonacci ratios can provide actionable insights for various trading strategies.
Use the Table
The information table can provide quick insights into the current trend and when it started.
█ Settings
The Fibonacci settings allow traders to specify the Fibonacci retracement levels that will be used to calculate the trend and its channel.
The Fibonacci Structure Trend Channel structure settings enable traders to fine-tune how the indicator identifies and plots the underlying price structure.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
ICT Donchian Smart Money Structure (Expo)█ Concept Overview
The Inner Circle Trader (ICT) methodology is focused on understanding the actions and implications of the so-called "smart money" - large institutions and professional traders who often influence market movements. Key to this is the concept of market structure and how it can provide insights into potential price moves.
Over time, however, there has been a notable shift in how some traders interpret and apply this methodology. Initially, it was designed with a focus on the fractal nature of markets. Fractals are recurring patterns in price action that are self-similar across different time scales, providing a nuanced and dynamic understanding of market structure.
However, as the ICT methodology has grown in popularity, there has been a drift away from this fractal-based perspective. Instead, many traders have started to focus more on pivot points as their primary tool for understanding market structure.
Pivot points provide static levels of potential support and resistance. While they can be useful in some contexts, relying heavily on them could provide a skewed perspective of market structure. They offer a static, backward-looking view that may not accurately reflect real-time changes in market sentiment or the dynamic nature of markets.
This shift from a fractal-based perspective to a pivot point perspective has significant implications. It can lead traders to misinterpret market structure and potentially make incorrect trading decisions.
To highlight this issue, you've developed a Donchian Structure indicator that mirrors the use of pivot points. The Donchian Channels are formed by the highest high and the lowest low over a certain period, providing another representation of potential market extremes. The fact that the Donchian Structure indicator produces the same results as pivot points underscores the inherent limitations of relying too heavily on these tools.
While the Donchian Structure indicator or pivot points can be useful tools, they should not replace the original, fractal-based perspective of the ICT methodology. These tools can provide a broad overview of market structure but may not capture the intricate dynamics and real-time changes that a fractal-based approach can offer.
It's essential for traders to understand these differences and to apply these tools correctly within the broader context of the ICT methodology and the Smart Money Concept Structure. A well-rounded approach that incorporates fractals, along with other tools and forms of analysis, is likely to provide a more accurate and comprehensive understanding of market structure.
█ Smart Money Concept - Misunderstandings
The Smart Money Concept is a popular concept among traders, and it's based on the idea that the "smart money" - typically large institutional investors, market makers, and professional traders - have superior knowledge or information, and their actions can provide valuable insight for other traders.
One of the biggest misunderstandings with this concept is the belief that tracking smart money activity can guarantee profitable trading.
█ Here are a few common misconceptions:
Following Smart Money Equals Guaranteed Success: Many traders believe that if they can follow the smart money, they will be successful. However, tracking the activity of large institutional investors and other professionals isn't easy, as they use complex strategies, have access to information not available to the public, and often intentionally hide their moves to prevent others from detecting their strategies.
Instantaneous Reaction and Results: Another misconception is that market movements will reflect smart money actions immediately. However, large institutions often slowly accumulate or distribute positions over time to avoid moving the market drastically. As a result, their actions might not produce an immediate noticeable effect on the market.
Smart Money Always Wins: It's not accurate to assume that smart money always makes the right decisions. Even the most experienced institutional investors and professional traders make mistakes, misjudge market conditions, or are affected by unpredictable events.
Smart Money Activity is Transparent: Understanding what constitutes smart money activity can be quite challenging. There are many indicators and metrics that traders use to try and track smart money, such as the COT (Commitments of Traders) reports, Level II market data, block trades, etc. However, these can be difficult to interpret correctly and are often misleading.
Assuming Uniformity Among Smart Money: 'Smart Money' is not a monolithic entity. Different institutional investors and professional traders have different strategies, risk tolerances, and investment horizons. What might be a good trade for a long-term institutional investor might not be a good trade for a short-term professional trader, and vice versa.
█ Market Structure
The Smart Money Concept Structure deals with the interpretation of price action that forms the market structure, focusing on understanding key shifts or changes in the market that may indicate where 'smart money' (large institutional investors and professional traders) might be moving in the market.
█ Three common concepts in this regard are Change of Character (CHoCH), and Shift in Market Structure (SMS), Break of Structure (BMS/BoS).
Change of Character (CHoCH): This refers to a noticeable change in the behavior of price movement, which could suggest that a shift in the market might be about to occur. This might be signaled by a sudden increase in volatility, a break of a trendline, or a change in volume, among other things.
Shift in Market Structure (SMS): This is when the overall structure of the market changes, suggesting a potential new trend. It usually involves a sequence of lower highs and lower lows for a downtrend, or higher highs and higher lows for an uptrend.
Break of Structure (BMS/BoS): This is when a previously defined trend or pattern in the price structure is broken, which may suggest a trend continuation.
A key component of this approach is the use of fractals, which are repeating patterns in price action that can give insights into potential market reversals. They appear at all scales of a price chart, reflecting the self-similar nature of markets.
█ Market Structure - Misunderstandings
One of the biggest misunderstandings about the ICT approach is the over-reliance or incorrect application of pivot points. Pivot points are a popular tool among traders due to their simplicity and easy-to-understand nature. However, when it comes to the Smart Money Concept and trying to follow the steps of professional traders or large institutions, relying heavily on pivot points can create misconceptions and lead to confusion. Here's why:
Delayed and Static Information: Pivot points are inherently backward-looking because they're calculated based on the previous period's data. As such, they may not reflect real-time market dynamics or sudden changes in market sentiment. Furthermore, they present a static view of market structure, delineating pre-defined levels of support and resistance. This static nature can be misleading because markets are fundamentally dynamic and constantly changing due to countless variables.
Inadequate Representation of Market Complexity: Markets are influenced by a myriad of factors, including economic indicators, geopolitical events, institutional actions, and market sentiment, among others. Relying on pivot points alone for reading market structure oversimplifies this complexity and can lead to a myopic understanding of market dynamics.
False Signals and Misinterpretations: Pivot points can often give false signals, especially in volatile markets. Prices might react to these levels temporarily but then continue in the original direction, leading to potential misinterpretation of market structure and sentiment. Also, a trader might wrongly perceive a break of a pivot point as a significant market event, when in fact, it could be due to random price fluctuations or temporary volatility.
Over-simplification: Viewing market structure only through the lens of pivot points simplifies the market to static levels of support and resistance, which can lead to misinterpretation of market dynamics. For instance, a trader might view a break of a pivot point as a definite sign of a trend, when it could just be a temporary price spike.
Ignoring the Fractal Nature of Markets: In the context of the Smart Money Concept Structure, understanding the fractal nature of markets is crucial. Fractals are self-similar patterns that repeat at all scales and provide a more dynamic and nuanced understanding of market structure. They can help traders identify shifts in market sentiment or direction in real-time, providing more relevant and timely information compared to pivot points.
The key takeaway here is not that pivot points should be entirely avoided or that they're useless. They can provide valuable insights and serve as a useful tool in a trader's toolbox when used correctly. However, they should not be the sole or primary method for understanding the market structure, especially in the context of the Smart Money Concept Structure.
█ Fractals
Instead, traders should aim for a comprehensive understanding of markets that incorporates a range of tools and concepts, including but not limited to fractals, order flow, volume analysis, fundamental analysis, and, yes, even pivot points. Fractals offer a more dynamic and nuanced view of the market. They reflect the recursive nature of markets and can provide valuable insights into potential market reversals. Because they appear at all scales of a price chart, they can provide a more holistic and real-time understanding of market structure.
In contrast, the Smart Money Concept Structure, focusing on fractals and comprehensive market analysis, aims to capture a more holistic and real-time view of the market. Fractals, being self-similar patterns that repeat at different scales, offer a dynamic understanding of market structure. As a result, they can help to identify shifts in market sentiment or direction as they happen, providing a more detailed and timely perspective.
Furthermore, a comprehensive market analysis would consider a broader set of factors, including order flow, volume analysis, and fundamental analysis, which could provide additional insights into 'smart money' actions.
█ Donchian Structure
Donchian Channels are a type of indicator used in technical analysis to identify potential price breakouts and trends, and they may also serve as a tool for understanding market structure. The channels are formed by taking the highest high and the lowest low over a certain number of periods, creating an envelope of price action.
Donchian Channels (or pivot points) can be useful tools for providing a general view of market structure, and they may not capture the intricate dynamics associated with the Smart Money Concept Structure. A more nuanced approach, centered on real-time fractals and a comprehensive analysis of various market factors, offers a more accurate understanding of 'smart money' actions and market structure.
█ Here is why Donchian Structure may be misleading:
Lack of Nuance: Donchian Channels, like pivot points, provide a simplified view of market structure. They don't take into account the nuanced behaviors of price action or the complex dynamics between buyers and sellers that can be critical in the Smart Money Concept Structure.
Limited Insights into 'Smart Money' Actions: While Donchian Channels can highlight potential breakout points and trends, they don't necessarily provide insights into the actions of 'smart money'. These large institutional traders often use sophisticated strategies that can't be easily inferred from price action alone.
█ Indicator Overview
We have built this Donchian Structure indicator to show that it returns the same results as using pivot points. The Donchian Structure indicator can be a useful tool for market analysis. However, it should not be seen as a direct replacement or equivalent to the original Smart Money concept, nor should any indicator based on pivot points. The indicator highlights the importance of understanding what kind of trading tools we use and how they can affect our decisions.
The Donchian Structure Indicator displays CHoCH, SMS, BoS/BMS, as well as premium and discount areas. This indicator plots everything in real-time and allows for easy backtesting on any market and timeframe. A unique candle coloring has been added to make it more engaging and visually appealing when identifying new trading setups and strategies. This candle coloring is "leading," meaning it can signal a structural change before it actually happens, giving traders ample time to plan their next trade accordingly.
█ How to use
The indicator is great for traders who want to simplify their view on the market structure and easily backtest Smart Money Concept Strategies. The added candle coloring function serves as a heads-up for structure change or can be used as trend confirmation. This new candle coloring feature can generate many new Smart Money Concepts strategies.
█ Features
Market Structure
The market structure is based on the Donchian channel, to which we have added what we call 'Structure Response'. This addition makes the indicator more useful, especially in trending markets. The core concept involves traders buying at a discount and selling or shorting at a premium, depending on the order flow. Structure response enables traders to determine the order flow more clearly. Consequently, more trading opportunities will appear in trending markets.
Structure Candles
Structure Candles highlight the current order flow and are significantly more responsive to structural changes. They can provide traders with a heads-up before a break in structure occurs
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Institutional Support/Resistance Locator🏛️ Institutional Support/Resistance Locator
Overview
The Institutional Support/Resistance Locator identifies high-probability demand and supply zones based on strong price rejection, large candle bodies, and elevated volume . These zones are commonly targeted or defended by institutional participants, helping traders anticipate potential reversal or continuation areas.
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How It Works
The indicator uses a confluence of conditions to detect zones:
• Large Body Candles: Body size must exceed the moving average body size multiplied by a user-defined factor.
• High Volume: Volume must exceed the moving average volume by a configurable multiplier.
• Wick Rejection: Candles must show strong upper or lower wicks indicating aggressive rejection.
• If all criteria are met:
• Bullish candles form a Demand Zone.
• Bearish candles form a Supply Zone.
Each zone is plotted for a customizable number of future bars, representing areas where institutions may re-engage with the market.
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Key Features
• ✅ Highlights institutional demand and supply areas dynamically
• ✅ Customizable sensitivity: body, volume, wick, padding, and zone extension
• ✅ Zones plotted as translucent regions with auto-expiry
• ✅ Works across all timeframes and markets
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How to Use
• Trend Traders: Use demand zones for potential bounce entries in uptrends, and supply zones for pullback short entries in downtrends.
• Range Traders: Use zones as potential reversal points inside sideways market structures.
• Scalpers & Intraday Traders: Combine with volume or price action near zones for refined entries.
Always validate zone reactions with supporting indicators or price behavior.
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Why This Combination?
The combination of wick rejection, volume confirmation, and large candle structure is designed to reflect footprints of smart money. Rather than relying on fixed pivots or subjective zones, this logic adapts to the current market context with statistically grounded conditions.
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Why It’s Worth Using
This tool offers traders a structured way to interpret institutional activity on charts without relying on guesswork. By plotting potential high-impact areas, it helps improve reaction time.
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Note :
• This script is open-source and non-commercial.
• No performance guarantees or unrealistic claims are made.
• It is intended for educational and analytical purposes only.
FVG, Swing, Target, D/W/M High Low Detector Basic by Trader Riaz"FVG, Swing, Target, D/W/M High Low Detector Basic by Trader Riaz " is a powerful TradingView indicator designed to enhance your trading strategy by identifying key market structures and levels. This all-in-one tool detects Fair Value Gaps (FVGs), Swing Highs/Lows, and previous Day, Previous Week, and Previous Month Highs/Lows, helping traders make informed decisions with ease.
Key Features:
Bullish & Bearish FVG Detection: Highlights Fair Value Gaps with customizable colors, labels, and extension options.
Swing Highs & Lows: Automatically detects and marks Swing Highs and Lows with adjustable display settings and extensions.
Next Target Levels: Identifies potential price targets based on market direction (rising or falling).
Daily, Weekly, and Monthly High/Low Levels: Displays previous day, week, and month highs/lows with customizable colors.
Customizable Settings: Fully adjustable inputs for colors, number of levels to display, and extension periods.
Clean Visuals: Intuitive and non-intrusive design with dashed lines, labels, and tooltips for better chart readability.
This indicator is ideal for traders looking to identify key price levels, improve market structure analysis, and enhance their trading strategies.
Happy Trading,
Trader Riaz
ICT FVG & Swing Detector Basic by Trader RiazICT FVG & Swing Detector Basic by Trader Riaz
Unlock Precision Trading with the Ultimate Fair Value Gap (FVG) and Swing Detection Tool!
Developed by Trader Riaz , the ICT FVG and Swing Detector Basic is a powerful Pine Script indicator designed to help traders identify key market structures with ease. Whether you're a day trader, swing trader, or scalper, this indicator provides actionable insights by detecting Bullish and Bearish Fair Value Gaps (FVGs) and Swing Highs/Lows on any timeframe. Perfect for trading forex, stocks, crypto, and more on TradingView!
Key Features:
1: Bullish and Bearish FVG Detection
- Automatically identifies Bullish FVGs (highlighted in green) and Bearish FVGs (highlighted in red) to spot potential reversal or continuation zones.
- Displays FVGs as shaded boxes with a dashed midline at 70% opacity, making it easy to see the midpoint of the gap for precise entries and exits.
- Labels are placed inside the FVG boxes at the extreme right for clear visibility.
2: Customizable FVG Display
- Control the number of Bullish and Bearish FVGs displayed on the chart with user-defined inputs (fvg_bull_count and fvg_bear_count).
- Toggle the visibility of Bullish and Bearish FVGs with simple checkboxes (show_bull_fvg and show_bear_fvg) to declutter your chart.
3: Swing High and Swing Low Detection
- Detects Swing Highs (blue lines) and Swing Lows (red lines) to identify key market turning points.
- Labels are positioned at the extreme right edge of the lines for better readability and alignment.
- Customize the number of Swing Highs and Lows displayed (swing_high_count and swing_low_count) to focus on the most recent market structures.
4: Fully Customizable Display
- Toggle visibility for Swing Highs and Lows (show_swing_high and show_swing_low) to suit your trading style.
- Adjust the colors of Swing High and Low lines (swing_high_color and swing_low_color) to match your chart preferences.
5: Clean and Efficient Design
- Built with Pine Script v6 for optimal performance on TradingView.
- Automatically removes older FVGs and Swing points when the user-defined count is exceeded, keeping your chart clean and focused.
- Labels are strategically placed to avoid clutter while providing clear information.
Why Use This Indicator?
Precision Trading: Identify high-probability setups with FVGs and Swing points, commonly used in Smart Money Concepts (SMC) and Institutional Trading strategies.
User-Friendly: Easy-to-use inputs allow traders of all levels to customize the indicator to their needs.
Versatile: Works on any market (Forex, Stocks, Crypto, Commodities) and timeframe (1M, 5M, 1H, 4H, Daily, etc.).
Developed by Trader Riaz: Backed by the expertise of Trader Riaz, a seasoned trader dedicated to creating tools that empower the TradingView community.
How to Use:
- Add the Custom FVG and Swing Detector to your chart on TradingView.
- Adjust the input settings to control the number of FVGs and Swing points displayed.
- Toggle visibility for Bullish/Bearish FVGs and Swing Highs/Lows as needed.
- Use the identified FVGs and Swing points to plan your trades, set stop-losses, and target key levels.
Ideal For:
- Traders using Smart Money Concepts (SMC), Price Action, or Market Structure strategies.
- Those looking to identify liquidity grabs, imbalances, and trend reversals.
- Beginners and advanced traders seeking a reliable tool to enhance their technical analysis.
Happy trading!
paranimonipobre
Chart Description: Buy Low, Sell High with Market Structure
This chart utilizes a dynamic trading strategy based on Bollinger Bands, RSI, and market structure analysis to identify high-probability buy and sell signals while aligning with prevailing trends.
Key Elements:
Bollinger Bands:
The upper (red) and lower (green) bands define volatility boundaries based on standard deviations.
The middle line (blue) represents the 20-period simple moving average.
Market Structure:
Swing highs (red triangles labeled "SH") and swing lows (green triangles labeled "SL") are identified to analyze the trend.
Background colors indicate trend direction:
Green Background: Uptrend (Higher Lows).
Red Background: Downtrend (Lower Highs).
RSI Indicator:
Shown in a separate pane, with overbought (red) at 70 and oversold (green) at 30.
Helps confirm signal validity by identifying momentum extremes.
Buy and Sell Signals:
Buy Signals (Green):
Triggered when the price crosses above the lower Bollinger Band, RSI is oversold (<30), and the market is in an uptrend.
Displayed as green "BUY" labels below bars.
Sell Signals (Red):
Triggered when the price crosses below the upper Bollinger Band, RSI is overbought (>70), and the market is in a downtrend.
Displayed as red "SELL" labels above bars.
How to Use:
Trend Identification:
Follow market structure analysis to determine the current trend direction.
Trade only in the direction of the trend (e.g., buy in an uptrend, sell in a downtrend).
Signal Confirmation:
Look for signals aligning with Bollinger Bands, RSI levels, and market structure.
Ignore signals that conflict with the trend to avoid false entries.
Market Conditions:
Best suited for trending markets with clear higher lows or lower highs.
Signals in choppy or sideways markets may require additional confirmation.
Trading IQ - ICT LibraryLibrary "ICTlibrary"
Used to calculate various ICT related price levels and strategies. An ongoing project.
Hello Coders!
This library is meant for sourcing ICT related concepts. While some functions might generate more output than you require, you can specify "Lite Mode" as "true" in applicable functions to slim down necessary inputs.
isLastBar(userTF)
Identifies the last bar on the chart before a timeframe change
Parameters:
userTF (simple int) : the timeframe you wish to calculate the last bar for, must be converted to integer using 'timeframe.in_seconds()'
Returns: bool true if bar on chart is last bar of higher TF, dalse if bar on chart is not last bar of higher TF
necessaryData(atrTF)
returns necessaryData UDT for historical data access
Parameters:
atrTF (float) : user-selected timeframe ATR value.
Returns: logZ. log return Z score, used for calculating order blocks.
method gradBoxes(gradientBoxes, idColor, timeStart, bottom, top, rightCoordinate)
creates neon like effect for box drawings
Namespace types: array
Parameters:
gradientBoxes (array) : an array.new() to store the gradient boxes
idColor (color)
timeStart (int) : left point of box
bottom (float) : bottom of box price point
top (float) : top of box price point
rightCoordinate (int) : right point of box
Returns: void
checkIfTraded(tradeName)
checks if recent trade is of specific name
Parameters:
tradeName (string)
Returns: bool true if recent trade id matches target name, false otherwise
checkIfClosed(tradeName)
checks if recent closed trade is of specific name
Parameters:
tradeName (string)
Returns: bool true if recent closed trade id matches target name, false otherwise
IQZZ(atrMult, finalTF)
custom ZZ to quickly determine market direction.
Parameters:
atrMult (float) : an atr multiplier used to determine the required price move for a ZZ direction change
finalTF (string) : the timeframe used for the atr calcuation
Returns: dir market direction. Up => 1, down => -1
method drawBos(id, startPoint, getKeyPointTime, getKeyPointPrice, col, showBOS, isUp)
calculates and draws Break Of Structure
Namespace types: array
Parameters:
id (array)
startPoint (chart.point)
getKeyPointTime (int) : the actual time of startPoint, simplystartPoint.time
getKeyPointPrice (float) : the actual time of startPoint, simplystartPoint.price
col (color) : color of the BoS line / label
showBOS (bool) : whether to show label/line. This function still calculates internally for other ICT related concepts even if not drawn.
isUp (bool) : whether BoS happened during price increase or price decrease.
Returns: void
method drawMSS(id, startPoint, getKeyPointTime, getKeyPointPrice, col, showMSS, isUp, upRejections, dnRejections, highArr, lowArr, timeArr, closeArr, openArr, atrTFarr, upRejectionsPrices, dnRejectionsPrices)
calculates and draws Market Structure Shift. This data is also used to calculate Rejection Blocks.
Namespace types: array
Parameters:
id (array)
startPoint (chart.point)
getKeyPointTime (int) : the actual time of startPoint, simplystartPoint.time
getKeyPointPrice (float) : the actual time of startPoint, simplystartPoint.price
col (color) : color of the MSS line / label
showMSS (bool) : whether to show label/line. This function still calculates internally for other ICT related concepts even if not drawn.
isUp (bool) : whether MSS happened during price increase or price decrease.
upRejections (array)
dnRejections (array)
highArr (array) : array containing historical highs, should be taken from the UDT "necessaryData" defined above
lowArr (array) : array containing historical lows, should be taken from the UDT "necessaryData" defined above
timeArr (array) : array containing historical times, should be taken from the UDT "necessaryData" defined above
closeArr (array) : array containing historical closes, should be taken from the UDT "necessaryData" defined above
openArr (array) : array containing historical opens, should be taken from the UDT "necessaryData" defined above
atrTFarr (array) : array containing historical atr values (of user-selected TF), should be taken from the UDT "necessaryData" defined above
upRejectionsPrices (array) : array containing up rejections prices. Is sorted and used to determine selective looping for invalidations.
dnRejectionsPrices (array) : array containing down rejections prices. Is sorted and used to determine selective looping for invalidations.
Returns: void
method getTime(id, compare, timeArr)
gets time of inputted price (compare) in an array of data
this is useful when the user-selected timeframe for ICT concepts is greater than the chart's timeframe
Namespace types: array
Parameters:
id (array) : the array of data to search through, to find which index has the same value as "compare"
compare (float) : the target data point to find in the array
timeArr (array) : array of historical times
Returns: the time that the data point in the array was recorded
method OB(id, highArr, signArr, lowArr, timeArr, sign)
store bullish orderblock data
Namespace types: array
Parameters:
id (array)
highArr (array) : array of historical highs
signArr (array) : array of historical price direction "math.sign(close - open)"
lowArr (array) : array of historical lows
timeArr (array) : array of historical times
sign (int) : orderblock direction, -1 => bullish, 1 => bearish
Returns: void
OTEstrat(OTEstart, future, closeArr, highArr, lowArr, timeArr, longOTEPT, longOTESL, longOTElevel, shortOTEPT, shortOTESL, shortOTElevel, structureDirection, oteLongs, atrTF, oteShorts)
executes the OTE strategy
Parameters:
OTEstart (chart.point)
future (int) : future time point for drawings
closeArr (array) : array of historical closes
highArr (array) : array of historical highs
lowArr (array) : array of historical lows
timeArr (array) : array of historical times
longOTEPT (string) : user-selected long OTE profit target, please create an input.string() for this using the example below
longOTESL (int) : user-selected long OTE stop loss, please create an input.string() for this using the example below
longOTElevel (float) : long entry price of selected retracement ratio for OTE
shortOTEPT (string) : user-selected short OTE profit target, please create an input.string() for this using the example below
shortOTESL (int) : user-selected short OTE stop loss, please create an input.string() for this using the example below
shortOTElevel (float) : short entry price of selected retracement ratio for OTE
structureDirection (string) : current market structure direction, this should be "Up" or "Down". This is used to cancel pending orders if market structure changes
oteLongs (bool) : input.bool() for whether OTE longs can be executed
atrTF (float) : atr of the user-seleceted TF
oteShorts (bool) : input.bool() for whether OTE shorts can be executed
@exampleInputs
oteLongs = input.bool(defval = false, title = "OTE Longs", group = "Optimal Trade Entry")
longOTElevel = input.float(defval = 0.79, title = "Long Entry Retracement Level", options = , group = "Optimal Trade Entry")
longOTEPT = input.string(defval = "-0.5", title = "Long TP", options = , group = "Optimal Trade Entry")
longOTESL = input.int(defval = 0, title = "How Many Ticks Below Swing Low For Stop Loss", group = "Optimal Trade Entry")
oteShorts = input.bool(defval = false, title = "OTE Shorts", group = "Optimal Trade Entry")
shortOTElevel = input.float(defval = 0.79, title = "Short Entry Retracement Level", options = , group = "Optimal Trade Entry")
shortOTEPT = input.string(defval = "-0.5", title = "Short TP", options = , group = "Optimal Trade Entry")
shortOTESL = input.int(defval = 0, title = "How Many Ticks Above Swing Low For Stop Loss", group = "Optimal Trade Entry")
Returns: void (0)
displacement(logZ, atrTFreg, highArr, timeArr, lowArr, upDispShow, dnDispShow, masterCoords, labelLevels, dispUpcol, rightCoordinate, dispDncol, noBorders)
calculates and draws dispacements
Parameters:
logZ (float) : log return of current price, used to determine a "significant price move" for a displacement
atrTFreg (float) : atr of user-seleceted timeframe
highArr (array) : array of historical highs
timeArr (array) : array of historical times
lowArr (array) : array of historical lows
upDispShow (int) : amount of historical upside displacements to show
dnDispShow (int) : amount of historical downside displacements to show
masterCoords (map) : a map to push the most recent displacement prices into, useful for having key levels in one data structure
labelLevels (string) : used to determine label placement for the displacement, can be inside box, outside box, or none, example below
dispUpcol (color) : upside displacement color
rightCoordinate (int) : future time for displacement drawing, best is "last_bar_time"
dispDncol (color) : downside displacement color
noBorders (bool) : input.bool() to remove box borders, example below
@exampleInputs
labelLevels = input.string(defval = "Inside" , title = "Box Label Placement", options = )
noBorders = input.bool(defval = false, title = "No Borders On Levels")
Returns: void
method getStrongLow(id, startIndex, timeArr, lowArr, strongLowPoints)
unshift strong low data to array id
Namespace types: array
Parameters:
id (array)
startIndex (int) : the starting index for the timeArr array of the UDT "necessaryData".
this point should start from at least 1 pivot prior to find the low before an upside BoS
timeArr (array) : array of historical times
lowArr (array) : array of historical lows
strongLowPoints (array) : array of strong low prices. Used to retrieve highest strong low price and see if need for
removal of invalidated strong lows
Returns: void
method getStrongHigh(id, startIndex, timeArr, highArr, strongHighPoints)
unshift strong high data to array id
Namespace types: array
Parameters:
id (array)
startIndex (int) : the starting index for the timeArr array of the UDT "necessaryData".
this point should start from at least 1 pivot prior to find the high before a downside BoS
timeArr (array) : array of historical times
highArr (array) : array of historical highs
strongHighPoints (array)
Returns: void
equalLevels(highArr, lowArr, timeArr, rightCoordinate, equalHighsCol, equalLowsCol, liteMode)
used to calculate recent equal highs or equal lows
Parameters:
highArr (array) : array of historical highs
lowArr (array) : array of historical lows
timeArr (array) : array of historical times
rightCoordinate (int) : a future time (right for boxes, x2 for lines)
equalHighsCol (color) : user-selected color for equal highs drawings
equalLowsCol (color) : user-selected color for equal lows drawings
liteMode (bool) : optional for a lite mode version of an ICT strategy. For more control over drawings leave as "True", "False" will apply neon effects
Returns: void
quickTime(timeString)
used to quickly determine if a user-inputted time range is currently active in NYT time
Parameters:
timeString (string) : a time range
Returns: true if session is active, false if session is inactive
macros(showMacros, noBorders)
used to calculate and draw session macros
Parameters:
showMacros (bool) : an input.bool() or simple bool to determine whether to activate the function
noBorders (bool) : an input.bool() to determine whether the box anchored to the session should have borders
Returns: void
po3(tf, left, right, show)
use to calculate HTF po3 candle
@tip only call this function on "barstate.islast"
Parameters:
tf (simple string)
left (int) : the left point of the candle, calculated as bar_index + left,
right (int) : :the right point of the candle, calculated as bar_index + right,
show (bool) : input.bool() whether to show the po3 candle or not
Returns: void
silverBullet(silverBulletStratLong, silverBulletStratShort, future, userTF, H, L, H2, L2, noBorders, silverBulletLongTP, historicalPoints, historicalData, silverBulletLongSL, silverBulletShortTP, silverBulletShortSL)
used to execute the Silver Bullet Strategy
Parameters:
silverBulletStratLong (simple bool)
silverBulletStratShort (simple bool)
future (int) : a future time, used for drawings, example "last_bar_time"
userTF (simple int)
H (float) : the high price of the user-selected TF
L (float) : the low price of the user-selected TF
H2 (float) : the high price of the user-selected TF
L2 (float) : the low price of the user-selected TF
noBorders (bool) : an input.bool() used to remove the borders from box drawings
silverBulletLongTP (series silverBulletLevels)
historicalPoints (array)
historicalData (necessaryData)
silverBulletLongSL (series silverBulletLevels)
silverBulletShortTP (series silverBulletLevels)
silverBulletShortSL (series silverBulletLevels)
Returns: void
method invalidFVGcheck(FVGarr, upFVGpricesSorted, dnFVGpricesSorted)
check if existing FVGs are still valid
Namespace types: array
Parameters:
FVGarr (array)
upFVGpricesSorted (array) : an array of bullish FVG prices, used to selective search through FVG array to remove invalidated levels
dnFVGpricesSorted (array) : an array of bearish FVG prices, used to selective search through FVG array to remove invalidated levels
Returns: void (0)
method drawFVG(counter, FVGshow, FVGname, FVGcol, data, masterCoords, labelLevels, borderTransp, liteMode, rightCoordinate)
draws FVGs on last bar
Namespace types: map
Parameters:
counter (map) : a counter, as map, keeping count of the number of FVGs drawn, makes sure that there aren't more FVGs drawn
than int FVGshow
FVGshow (int) : the number of FVGs to show. There should be a bullish FVG show and bearish FVG show. This function "drawFVG" is used separately
for bearish FVG and bullish FVG.
FVGname (string) : the name of the FVG, "FVG Up" or "FVG Down"
FVGcol (color) : desired FVG color
data (FVG)
masterCoords (map) : a map containing the names and price points of key levels. Used to define price ranges.
labelLevels (string) : an input.string with options "Inside", "Outside", "Remove". Determines whether FVG labels should be inside box, outside,
or na.
borderTransp (int)
liteMode (bool)
rightCoordinate (int) : the right coordinate of any drawings. Must be a time point.
Returns: void
invalidBlockCheck(bullishOBbox, bearishOBbox, userTF)
check if existing order blocks are still valid
Parameters:
bullishOBbox (array) : an array declared using the UDT orderBlock that contains bullish order block related data
bearishOBbox (array) : an array declared using the UDT orderBlock that contains bearish order block related data
userTF (simple int)
Returns: void (0)
method lastBarRejections(id, rejectionColor, idShow, rejectionString, labelLevels, borderTransp, liteMode, rightCoordinate, masterCoords)
draws rejectionBlocks on last bar
Namespace types: array
Parameters:
id (array) : the array, an array of rejection block data declared using the UDT rejection block
rejectionColor (color) : the desired color of the rejection box
idShow (int)
rejectionString (string) : the desired name of the rejection blocks
labelLevels (string) : an input.string() to determine if labels for the block should be inside the box, outside, or none.
borderTransp (int)
liteMode (bool) : an input.bool(). True = neon effect, false = no neon.
rightCoordinate (int) : atime for the right coordinate of the box
masterCoords (map) : a map that stores the price of key levels and assigns them a name, used to determine price ranges
Returns: void
method OBdraw(id, OBshow, BBshow, OBcol, BBcol, bullishString, bearishString, isBullish, labelLevels, borderTransp, liteMode, rightCoordinate, masterCoords)
draws orderblocks and breaker blocks for data stored in UDT array()
Namespace types: array
Parameters:
id (array) : the array, an array of order block data declared using the UDT orderblock
OBshow (int) : the number of order blocks to show
BBshow (int) : the number of breaker blocks to show
OBcol (color) : color of order blocks
BBcol (color) : color of breaker blocks
bullishString (string) : the title of bullish blocks, which is a regular bullish orderblock or a bearish orderblock that's converted to breakerblock
bearishString (string) : the title of bearish blocks, which is a regular bearish orderblock or a bullish orderblock that's converted to breakerblock
isBullish (bool) : whether the array contains bullish orderblocks or bearish orderblocks. If bullish orderblocks,
the array will naturally contain bearish BB, and if bearish OB, the array will naturally contain bullish BB
labelLevels (string) : an input.string() to determine if labels for the block should be inside the box, outside, or none.
borderTransp (int)
liteMode (bool) : an input.bool(). True = neon effect, false = no neon.
rightCoordinate (int) : atime for the right coordinate of the box
masterCoords (map) : a map that stores the price of key levels and assigns them a name, used to determine price ranges
Returns: void
FVG
UDT for FVG calcualtions
Fields:
H (series float) : high price of user-selected timeframe
L (series float) : low price of user-selected timeframe
direction (series string) : FVG direction => "Up" or "Down"
T (series int) : => time of bar on user-selected timeframe where FVG was created
fvgLabel (series label) : optional label for FVG
fvgLineTop (series line) : optional line for top of FVG
fvgLineBot (series line) : optional line for bottom of FVG
fvgBox (series box) : optional box for FVG
labelLine
quickly pair a line and label together as UDT
Fields:
lin (series line) : Line you wish to pair with label
lab (series label) : Label you wish to pair with line
orderBlock
UDT for order block calculations
Fields:
orderBlockData (array) : array containing order block x and y points
orderBlockBox (series box) : optional order block box
vioCount (series int) : = 0 violation count of the order block. 0 = Order Block, 1 = Breaker Block
traded (series bool)
status (series string) : = "OB" status == "OB" => Level is order block. status == "BB" => Level is breaker block.
orderBlockLab (series label) : options label for the order block / breaker block.
strongPoints
UDT for strong highs and strong lows
Fields:
price (series float) : price of the strong high or strong low
timeAtprice (series int) : time of the strong high or strong low
strongPointLabel (series label) : optional label for strong point
strongPointLine (series line) : optional line for strong point
overlayLine (series line) : optional lines for strong point to enhance visibility
overlayLine2 (series line) : optional lines for strong point to enhance visibility
displacement
UDT for dispacements
Fields:
highPrice (series float) : high price of displacement
lowPrice (series float) : low price of displacement
timeAtPrice (series int) : time of bar where displacement occurred
displacementBox (series box) : optional box to draw displacement
displacementLab (series label) : optional label for displacement
po3data
UDT for po3 calculations
Fields:
dHigh (series float) : higher timeframe high price
dLow (series float) : higher timeframe low price
dOpen (series float) : higher timeframe open price
dClose (series float) : higher timeframe close price
po3box (series box) : box to draw po3 candle body
po3line (array) : line array to draw po3 wicks
po3Labels (array) : label array to label price points of po3 candle
macros
UDT for session macros
Fields:
sessions (array) : Array of sessions, you can populate this array using the "quickTime" function located above "export macros".
prices (matrix) : Matrix of session data -> open, high, low, close, time
sessionTimes (array) : Array of session names. Pairs with array sessions.
sessionLines (matrix) : Optional array for sesion drawings.
OTEtimes
UDT for data storage and drawings associated with OTE strategy
Fields:
upTimes (array) : time of highest point before trade is taken
dnTimes (array) : time of lowest point before trade is taken
tpLineLong (series line) : line to mark tp level long
tpLabelLong (series label) : label to mark tp level long
slLineLong (series line) : line to mark sl level long
slLabelLong (series label) : label to mark sl level long
tpLineShort (series line) : line to mark tp level short
tpLabelShort (series label) : label to mark tp level short
slLineShort (series line) : line to mark sl level short
slLabelShort (series label) : label to mark sl level short
sweeps
UDT for data storage and drawings associated with liquidity sweeps
Fields:
upSweeps (matrix) : matrix containing liquidity sweep price points and time points for up sweeps
dnSweeps (matrix) : matrix containing liquidity sweep price points and time points for down sweeps
upSweepDrawings (array) : optional up sweep box array. Pair the size of this array with the rows or columns,
dnSweepDrawings (array) : optional up sweep box array. Pair the size of this array with the rows or columns,
raidExitDrawings
UDT for drawings associated with the Liquidity Raid Strategy
Fields:
tpLine (series line) : tp line for the liquidity raid entry
tpLabel (series label) : tp label for the liquidity raid entry
slLine (series line) : sl line for the liquidity raid entry
slLabel (series label) : sl label for the liquidity raid entry
m2022
UDT for data storage and drawings associated with the Model 2022 Strategy
Fields:
mTime (series int) : time of the FVG where entry limit order is placed
mIndex (series int) : array index of FVG where entry limit order is placed. This requires an array of FVG data, which is defined above.
mEntryDistance (series float) : the distance of the FVG to the 50% range. M2022 looks for the fvg closest to 50% mark of range.
mEntry (series float) : the entry price for the most eligible fvg
fvgHigh (series float) : the high point of the eligible fvg
fvgLow (series float) : the low point of the eligible fvg
longFVGentryBox (series box) : long FVG box, used to draw the eligible FVG
shortFVGentryBox (series box) : short FVG box, used to draw the eligible FVG
line50P (series line) : line used to mark 50% of the range
line100P (series line) : line used to mark 100% (top) of the range
line0P (series line) : line used to mark 0% (bottom) of the range
label50P (series label) : label used to mark 50% of the range
label100P (series label) : label used to mark 100% (top) of the range
label0P (series label) : label used to mark 0% (bottom) of the range
sweepData (array)
silverBullet
UDT for data storage and drawings associated with the Silver Bullet Strategy
Fields:
session (series bool)
sessionStr (series string) : name of the session for silver bullet
sessionBias (series string)
sessionHigh (series float) : = high high of session // use math.max(silverBullet.sessionHigh, high)
sessionLow (series float) : = low low of session // use math.min(silverBullet.sessionLow, low)
sessionFVG (series float) : if applicable, the FVG created during the session
sessionFVGdraw (series box) : if applicable, draw the FVG created during the session
traded (series bool)
tp (series float) : tp of trade entered at the session FVG
sl (series float) : sl of trade entered at the session FVG
sessionDraw (series box) : optional draw session with box
sessionDrawLabel (series label) : optional label session with label
silverBulletDrawings
UDT for trade exit drawings associated with the Silver Bullet Strategy
Fields:
tpLine (series line) : tp line drawing for strategy
tpLabel (series label) : tp label drawing for strategy
slLine (series line) : sl line drawing for strategy
slLabel (series label) : sl label drawing for strategy
unicornModel
UDT for data storage and drawings associated with the Unicorn Model Strategy
Fields:
hPoint (chart.point)
hPoint2 (chart.point)
hPoint3 (chart.point)
breakerBlock (series box) : used to draw the breaker block required for the Unicorn Model
FVG (series box) : used to draw the FVG required for the Unicorn model
topBlock (series float) : price of top of breaker block, can be used to detail trade entry
botBlock (series float) : price of bottom of breaker block, can be used to detail trade entry
startBlock (series int) : start time of the breaker block, used to set the "left = " param for the box
includes (array) : used to store the time of the breaker block, or FVG, or the chart point sequence that setup the Unicorn Model.
entry (series float) : // eligible entry price, for longs"math.max(topBlock, FVG.get_top())",
tpLine (series line) : optional line to mark PT
tpLabel (series label) : optional label to mark PT
slLine (series line) : optional line to mark SL
slLabel (series label) : optional label to mark SL
rejectionBlocks
UDT for data storage and drawings associated with rejection blocks
Fields:
rejectionPoint (chart.point)
bodyPrice (series float) : candle body price closest to the rejection point, for "Up" rejections => math.max(open, close),
rejectionBox (series box) : optional box drawing of the rejection block
rejectionLabel (series label) : optional label for the rejection block
equalLevelsDraw
UDT for data storage and drawings associated with equal highs / equal lows
Fields:
connector (series line) : single line placed at the first high or low, y = avgerage of distinguished equal highs/lows
connectorLab (series label) : optional label to be placed at the highs or lows
levels (array) : array containing the equal highs or lows prices
times (array) : array containing the equal highs or lows individual times
startTime (series int) : the time of the first high or low that forms a sequence of equal highs or lows
radiate (array) : options label to "radiate" the label in connector lab. Can be used for anything
necessaryData
UDT for data storage of historical price points.
Fields:
highArr (array) : array containing historical high points
lowArr (array) : array containing historical low points
timeArr (array) : array containing historical time points
logArr (array) : array containing historical log returns
signArr (array) : array containing historical price directions
closeArr (array) : array containing historical close points
binaryTimeArr (array) : array containing historical time points, uses "push" instead of "unshift" to allow for binary search
binaryCloseArr (array) : array containing historical close points, uses "push" instead of "unshift" to allow the correct
binaryOpenArr (array) : array containing historical optn points, uses "push" instead of "unshift" to allow the correct
atrTFarr (array) : array containing historical user-selected TF atr points
openArr (array) : array containing historical open points
Pure Price Action Order & Breaker Blocks [LuxAlgo]The Pure Price Action Order & Breaker Blocks indicator is a pure price action adaptation of our previously published and highly popular Order-Blocks-Breaker-Blocks script.
Similar to its earlier version, this indicator detects order blocks that can automatically turn into breaker blocks on the chart once mitigated. However, the key difference/uniqueness is that the pure price action version relies solely on price patterns, eliminating the need for length definitions. In other words, it removes the limitation of user-defined inputs, ensuring a robust and objective analysis of market dynamics.
🔶 USAGE
An order block is a significant area on a price chart where there was a notable accumulation or distribution of orders, often identified by a strong price move followed by consolidation. Traders use order blocks to identify potential support or resistance levels.
A mitigated order block refers to an order block that has been invalidated due to subsequent market movements. It may no longer hold the same significance in the current market context. However, when the price mitigates an order block, a breaker block is confirmed. It is possible that the price might trade back to this breaker block, potentially offering a new trading opportunity.
Users can optionally enable the "Historical Polarity Changes" labels within the settings menu to see where breaker blocks might have previously provided effective trade setups.
This feature is most effective when using replay mode. Please note that these labels are subject to backpainting.
🔶 DETAILS
The swing points detection feature relies exclusively on price action, eliminating the need for numerical user-defined settings.
The first step involves detecting short-term swing points, where a short-term swing high (STH) is identified as a price peak surrounded by lower highs on both sides. Similarly, a short-term swing low is recognized as a price trough surrounded by higher lows on both sides.
Intermediate-term swing and long-term swing points are detected using the same approach but with a slight modification. Instead of directly analyzing price candles, we now utilize the previously detected short-term swing points. For intermediate-term swing points, we rely on short-term swing points, while for long-term swing points, we use the intermediate-term ones.
🔶 SETTINGS
Detection: Market structure used to detect swing points for creating order blocks.
Show Last Bullish OB: Number of the most recent bullish order/breaker blocks to display on the chart.
Show Last Bearish OB: Number of the most recent bearish order/breaker blocks to display on the chart.
Use Candle Body: Allows users to use candle bodies as order block areas instead of the full candle range.
🔹 Style
Show Historical Polarity Changes: Allows users to see labels indicating where a swing high/low previously occurred within a breaker block.
🔶 RELATED SCRIPTS
Pure-Price-Action-Structures.
Order-Blocks-Breaker-Blocks.
Predictive Trend and Structure (Expo)█ Overview
The Predictive Trend and Structure indicator is designed for traders seeking to identify future trend directions and interruptions in trend continuation. This indicator is unique because it employs standard deviation to predict upcoming trend directions and potential trend continuation levels. This enables traders to stay ahead of the market.
█ How It Works
This indicator primarily functions based on the calculated standard deviation of the trend over a specified period. It evaluates the trend direction by comparing the current trend value to its previous one and scales the standard deviation, allowing for adjustments in sensitivity to price fluctuations.
█ How to Use
Trend
You can easily identify when a future trend begins by observing where the trend level is displayed. If the price breaks above and remains above the trend, it indicates a bullish trend. Conversely, if the price breaks below and stays below, it signifies a bearish trend.
Support and Resistance
With the Predictive Structure enabled, the indicator aids in identifying potential support and resistance levels.
Trend Continuation Break
Trend continuation breaks occur when prices breaks support or resistance, indicating the existing trend may persist. The indicator plots these levels in advance, allowing traders to quickly identify where trend continuation might occur.
█ Settings
Period for Std Dev: Determines the number of periods used for the standard deviation calculation, impacting the indicator's sensitivity to price changes.
Standard Deviation Scaler: Scales the computed standard deviation, affecting the deviations needed to confirm trends and the indicator's focus on significant trend changes.
Predictive Structure: Enables or disables the prediction of market structures like potential levels of structure breaks/trend continuation breaks.
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
X HL QA market structure tool designed to frame price action within a defined context of prior session dynamics. It accomplishes this by anchoring a set of reference levels to the high, low, and open prices of a user-specified higher timeframe (e.g., 4H, 1D, etc.) and projecting those levels onto the current chart for ongoing analysis.
At its core, the indicator establishes a reference range—derived from the previous completed instance of the selected timeframe—and overlays this on the current timeframe. This range serves as a foundational structure for price interpretation in the current session.
Building upon this framework, the script constructs a set of symmetrical quadrants (or deviation zones) both inside and outside of the prior range. These include:
The midpoint (EQ) of the prior range
Levels at ±0.25x, ±0.75x, ±1.0x, ±1.5x, and ±2.0x the range height
These levels act as contextual zones that traders can use to interpret price behavior—whether it's consolidating within the prior range, approaching fair value (EQ), or expanding into directional continuation or reversal zones beyond the range.
The script operates in both real-time and historical contexts. On live bars, it dynamically updates the key levels to provide an evolving view of current price positioning. Simultaneously, it supports the display of historical levels for past sessions, enabling robust backtesting and comparative analysis of price behavior relative to previous quadrant structures.
Ultimately, this tool serves as a positional map, helping traders assess where price is trading relative to significant levels from the prior session, offering insights into potential support/resistance, overextension, or mean reversion scenarios.
Key Technical Features
Multi-Timeframe Support:
request.security() is used to pull data from a user-defined higher timeframe regardless of the current chart interval.
Visual Flexibility:
Toggle between "line" and "channel" mode.
Line color, width, and visibility are all user-controlled.
Anchoring Options:
Deviation levels can be calculated from either the previous period's open or its EQ (midpoint), giving flexibility depending on analytical preference.
Efficient Labeling:
Labels are only rendered on the last bar and are automatically cleared and redrawn to prevent duplication.
Label style, size, text color, and background color are all user-configurable.
Trading Application
This indicator is especially suited for:
1. Mean Reversion Strategies
When price moves beyond +1.0 or +1.5 deviations from the EQ or open, it may signal overextension and a potential snap back to the midpoint or range.
2. Breakout Confirmation
Sustained price action beyond ±1.0 levels may indicate trend strength or continuation beyond historical balance zones.
3. Contextual Range Awareness
EQ and Open provide structure from which traders can judge whether price is in a state of balance or imbalance.
Labels offer at-a-glance interpretation of key levels across any chosen timeframe.
4. Fractal and Multi-Session Analysis
Analysts can layer daily, weekly, and monthly versions of this indicator to observe confluence or divergence of higher timeframe structure.
Change in State of Delivery (CISD) [SB Instant]🧠 Modified by SB | Core Logic by LuxAlgo
🔗 Licensed under CC BY-NC-SA 4.0
Change in State of Delivery (CISD) is a concept rooted in observing shifts in order flow behavior, designed to detect the first signs of trend exhaustion and potential reversal. This model tracks when the current delivery (trend) structure — bullish or bearish — is violated by an opposing force, signaling a potential change in market intent.
In simple terms:
A Bullish CISD is triggered when sellers fail to maintain control, and buyers break above a delivery line.
A Bearish CISD is triggered when buyers fail, and sellers break below a delivery line.
This version uses real-time logic, triggering alerts immediately on break, rather than waiting for candle-close confirmation — giving faster, actionable signals to precision-driven traders.
⚙️ Core Features
Detection Modes
Classic: Traditional swing-based structural break detection
Liquidity Sweep: Logic incorporating wick sweeps (liquidity grabs)
Custom Parameters
Swing Length: Number of candles used to identify swing points
Minimum CISD Duration: Minimum length required for valid delivery phase
Maximum Swing Validity: How long the structure remains valid for potential breaks
Visual Options
Label and line styling options
Solid line = Initial break of delivery structure
Dashed line = Continuation break in the same trend direction
This allows you to visually differentiate a new reversal vs. a continuation of the existing trend.
🚨 Built-in Alerts
Bullish CISD Detected (Instant)
Bearish CISD Detected (Instant)
These alerts fire immediately when structure is broken, offering early confirmation for aggressive or reactive trade setups.
🔔 IMPORTANT:
If an alert triggers but the delivery line is not present, wait for the price to form the CISD label again and manually mark the price level using a horizontal ray. This ensures you are trading from a clearly defined structure.
🕒 Recommended Timeframes
✅ Use 30-Minute or 4-Hour charts to identify high-confidence CISD zones
🎯 Then drop to the 1-Minute or 5-Minute chart for precise entry execution
This top-down approach aligns higher timeframe narrative with lower timeframe entry triggers, increasing your edge in both timing and context.
🧠 How to Use CISD Effectively
Bullish Scenario:
Watch for breaks above bearish delivery structures, especially if confirmed with:
Fair Value Gaps (FVG)
The Strat 2-2 reversal
MSS (Market Structure Shift)
Bearish Scenario:
Look for breaks below bullish delivery setups in alignment with:
BOS (Break of Structure)
The Strat 3-1-2
Bearish liquidity sweeps
Key Tip:
Solid line = Initial CISD (new shift)
Dashed line = Continuation of current trend
This visual distinction helps you determine when a market is shifting vs. extending.
📎 Disclaimer
This tool is provided for educational purposes only and is not intended as financial advice. Always backtest, paper trade, and manage risk responsibly.
📚 Credits
Original CISD framework developed by LuxAlgo
Real-time execution logic, alert enhancements, and intraday utility designed by SB (SamB)
