Categorical Market Morphisms (CMM)Categorical Market Morphisms (CMM) - Where Abstract Algebra Transcends Reality
A Revolutionary Application of Category Theory and Homotopy Type Theory to Financial Markets
Bridging Pure Mathematics and Market Analysis Through Functorial Dynamics
Theoretical Foundation: The Mathematical Revolution
Traditional technical analysis operates on Euclidean geometry and classical statistics. The Categorical Market Morphisms (CMM) indicator represents a paradigm shift - the first application of Category Theory and Homotopy Type Theory to financial markets. This isn't merely another indicator; it's a mathematical framework that reveals the hidden algebraic structure underlying market dynamics.
Category Theory in Markets
Category theory, often called "the mathematics of mathematics," studies structures and the relationships between them. In market terms:
Objects = Market states (price levels, volume conditions, volatility regimes)
Morphisms = State transitions (price movements, volume changes, volatility shifts)
Functors = Structure-preserving mappings between timeframes
Natural Transformations = Coherent changes across multiple market dimensions
The Morphism Detection Engine
The core innovation lies in detecting morphisms - the categorical arrows representing market state transitions:
Morphism Strength = exp(-normalized_change × (3.0 / sensitivity))
Threshold = 0.3 - (sensitivity - 1.0) × 0.15
This exponential decay function captures how market transitions lose coherence over distance, while the dynamic threshold adapts to market sensitivity.
Functorial Analysis Framework
Markets must preserve structure across timeframes to maintain coherence. Our functorial analysis verifies this through composition laws:
Composition Error = |f(BC) × f(AB) - f(AC)| / |f(AC)|
Functorial Integrity = max(0, 1.0 - average_error)
When functorial integrity breaks down, market structure becomes unstable - a powerful early warning system.
Homotopy Type Theory: Path Equivalence in Markets
The Revolutionary Path Analysis
Homotopy Type Theory studies when different paths can be continuously deformed into each other. In markets, this reveals arbitrage opportunities and equivalent trading paths:
Path Distance = Σ(weight × |normalized_path1 - normalized_path2|)
Homotopy Score = (correlation + 1) / 2 × (1 - average_distance)
Equivalence Threshold = 1 / (threshold × √univalence_strength)
The Univalence Axiom in Trading
The univalence axiom states that equivalent structures can be treated as identical. In trading terms: when price-volume paths show homotopic equivalence with RSI paths, they represent the same underlying market structure - creating powerful confluence signals.
Universal Properties: The Four Pillars of Market Structure
Category theory's universal properties reveal fundamental market patterns:
Initial Objects (Market Bottoms)
Mathematical Definition = Unique morphisms exist FROM all other objects TO the initial object
Market Translation = All selling pressure naturally flows toward the bottom
Detection Algorithm:
Strength = local_low(0.3) + oversold(0.2) + volume_surge(0.2) + momentum_reversal(0.2) + morphism_flow(0.1)
Signal = strength > 0.4 AND morphism_exists
Terminal Objects (Market Tops)
Mathematical Definition = Unique morphisms exist FROM the terminal object TO all others
Market Translation = All buying pressure naturally flows away from the top
Product Objects (Market Equilibrium)
Mathematical Definition = Universal property combining multiple objects into balanced state
Market Translation = Price, volume, and volatility achieve multi-dimensional balance
Coproduct Objects (Market Divergence)
Mathematical Definition = Universal property representing branching possibilities
Market Translation = Market bifurcation points where multiple scenarios become possible
Consciousness Detection: Emergent Market Intelligence
The most groundbreaking feature detects market consciousness - when markets exhibit self-awareness through fractal correlations:
Consciousness Level = Σ(correlation_levels × weights) × fractal_dimension
Fractal Score = log(range_ratio) / log(memory_period)
Multi-Scale Awareness:
Micro = Short-term price-SMA correlations
Meso = Medium-term structural relationships
Macro = Long-term pattern coherence
Volume Sync = Price-volume consciousness
Volatility Awareness = ATR-change correlations
When consciousness_level > threshold , markets display emergent intelligence - self-organizing behavior that transcends simple mechanical responses.
Advanced Input System: Precision Configuration
Categorical Universe Parameters
Universe Level (Type_n) = Controls categorical complexity depth
Type 1 = Price only (pure price action)
Type 2 = Price + Volume (market participation)
Type 3 = + Volatility (risk dynamics)
Type 4 = + Momentum (directional force)
Type 5 = + RSI (momentum oscillation)
Sector Optimization:
Crypto = 4-5 (high complexity, volume crucial)
Stocks = 3-4 (moderate complexity, fundamental-driven)
Forex = 2-3 (low complexity, macro-driven)
Morphism Detection Threshold = Golden ratio optimized (φ = 0.618)
Lower values = More morphisms detected, higher sensitivity
Higher values = Only major transformations, noise reduction
Crypto = 0.382-0.618 (high volatility accommodation)
Stocks = 0.618-1.0 (balanced detection)
Forex = 1.0-1.618 (macro-focused)
Functoriality Tolerance = φ⁻² = 0.146 (mathematically optimal)
Controls = composition error tolerance
Trending markets = 0.1-0.2 (strict structure preservation)
Ranging markets = 0.2-0.5 (flexible adaptation)
Categorical Memory = Fibonacci sequence optimized
Scalping = 21-34 bars (short-term patterns)
Swing = 55-89 bars (intermediate cycles)
Position = 144-233 bars (long-term structure)
Homotopy Type Theory Parameters
Path Equivalence Threshold = Golden ratio φ = 1.618
Volatile markets = 2.0-2.618 (accommodate noise)
Normal conditions = 1.618 (balanced)
Stable markets = 0.786-1.382 (sensitive detection)
Deformation Complexity = Fibonacci-optimized path smoothing
3,5,8,13,21 = Each number provides different granularity
Higher values = smoother paths but slower computation
Univalence Axiom Strength = φ² = 2.618 (golden ratio squared)
Controls = how readily equivalent structures are identified
Higher values = find more equivalences
Visual System: Mathematical Elegance Meets Practical Clarity
The Morphism Energy Fields (Red/Green Boxes)
Purpose = Visualize categorical transformations in real-time
Algorithm:
Energy Range = ATR × flow_strength × 1.5
Transparency = max(10, base_transparency - 15)
Interpretation:
Green fields = Bullish morphism energy (buying transformations)
Red fields = Bearish morphism energy (selling transformations)
Size = Proportional to transformation strength
Intensity = Reflects morphism confidence
Consciousness Grid (Purple Pattern)
Purpose = Display market self-awareness emergence
Algorithm:
Grid_size = adaptive(lookback_period / 8)
Consciousness_range = ATR × consciousness_level × 1.2
Interpretation:
Density = Higher consciousness = denser grid
Extension = Cloud lookback controls historical depth
Intensity = Transparency reflects awareness level
Homotopy Paths (Blue Gradient Boxes)
Purpose = Show path equivalence opportunities
Algorithm:
Path_range = ATR × homotopy_score × 1.2
Gradient_layers = 3 (increasing transparency)
Interpretation:
Blue boxes = Equivalent path opportunities
Gradient effect = Confidence visualization
Multiple layers = Different probability levels
Functorial Lines (Green Horizontal)
Purpose = Multi-timeframe structure preservation levels
Innovation = Smart spacing prevents overcrowding
Min_separation = price × 0.001 (0.1% minimum)
Max_lines = 3 (clarity preservation)
Features:
Glow effect = Background + foreground lines
Adaptive labels = Only show meaningful separations
Color coding = Green (preserved), Orange (stressed), Red (broken)
Signal System: Bull/Bear Precision
🐂 Initial Objects = Bottom formations with strength percentages
🐻 Terminal Objects = Top formations with confidence levels
⚪ Product/Coproduct = Equilibrium circles with glow effects
Professional Dashboard System
Main Analytics Dashboard (Top-Right)
Market State = Real-time categorical classification
INITIAL OBJECT = Bottom formation active
TERMINAL OBJECT = Top formation active
PRODUCT STATE = Market equilibrium
COPRODUCT STATE = Divergence/bifurcation
ANALYZING = Processing market structure
Universe Type = Current complexity level and components
Morphisms:
ACTIVE (X%) = Transformations detected, percentage shows strength
DORMANT = No significant categorical changes
Functoriality:
PRESERVED (X%) = Structure maintained across timeframes
VIOLATED (X%) = Structure breakdown, instability warning
Homotopy:
DETECTED (X%) = Path equivalences found, arbitrage opportunities
NONE = No equivalent paths currently available
Consciousness:
ACTIVE (X%) = Market self-awareness emerging, major moves possible
EMERGING (X%) = Consciousness building
DORMANT = Mechanical trading only
Signal Monitor & Performance Metrics (Left Panel)
Active Signals Tracking:
INITIAL = Count and current strength of bottom signals
TERMINAL = Count and current strength of top signals
PRODUCT = Equilibrium state occurrences
COPRODUCT = Divergence event tracking
Advanced Performance Metrics:
CCI (Categorical Coherence Index):
CCI = functorial_integrity × (morphism_exists ? 1.0 : 0.5)
STRONG (>0.7) = High structural coherence
MODERATE (0.4-0.7) = Adequate coherence
WEAK (<0.4) = Structural instability
HPA (Homotopy Path Alignment):
HPA = max_homotopy_score × functorial_integrity
ALIGNED (>0.6) = Strong path equivalences
PARTIAL (0.3-0.6) = Some equivalences
WEAK (<0.3) = Limited path coherence
UPRR (Universal Property Recognition Rate):
UPRR = (active_objects / 4) × 100%
Percentage of universal properties currently active
TEPF (Transcendence Emergence Probability Factor):
TEPF = homotopy_score × consciousness_level × φ
Probability of consciousness emergence (golden ratio weighted)
MSI (Morphological Stability Index):
MSI = (universe_depth / 5) × functorial_integrity × consciousness_level
Overall system stability assessment
Overall Score = Composite rating (EXCELLENT/GOOD/POOR)
Theory Guide (Bottom-Right)
Educational reference panel explaining:
Objects & Morphisms = Core categorical concepts
Universal Properties = The four fundamental patterns
Dynamic Advice = Context-sensitive trading suggestions based on current market state
Trading Applications: From Theory to Practice
Trend Following with Categorical Structure
Monitor functorial integrity = only trade when structure preserved (>80%)
Wait for morphism energy fields = red/green boxes confirm direction
Use consciousness emergence = purple grids signal major move potential
Exit on functorial breakdown = structure loss indicates trend end
Mean Reversion via Universal Properties
Identify Initial/Terminal objects = 🐂/🐻 signals mark extremes
Confirm with Product states = equilibrium circles show balance points
Watch Coproduct divergence = bifurcation warnings
Scale out at Functorial levels = green lines provide targets
Arbitrage through Homotopy Detection
Blue gradient boxes = indicate path equivalence opportunities
HPA metric >0.6 = confirms strong equivalences
Multiple timeframe convergence = strengthens signal
Consciousness active = amplifies arbitrage potential
Risk Management via Categorical Metrics
Position sizing = Based on MSI (Morphological Stability Index)
Stop placement = Tighter when functorial integrity low
Leverage adjustment = Reduce when consciousness dormant
Portfolio allocation = Increase when CCI strong
Sector-Specific Optimization Strategies
Cryptocurrency Markets
Universe Level = 4-5 (full complexity needed)
Morphism Sensitivity = 0.382-0.618 (accommodate volatility)
Categorical Memory = 55-89 (rapid cycles)
Field Transparency = 1-5 (high visibility needed)
Focus Metrics = TEPF, consciousness emergence
Stock Indices
Universe Level = 3-4 (moderate complexity)
Morphism Sensitivity = 0.618-1.0 (balanced)
Categorical Memory = 89-144 (institutional cycles)
Field Transparency = 5-10 (moderate visibility)
Focus Metrics = CCI, functorial integrity
Forex Markets
Universe Level = 2-3 (macro-driven)
Morphism Sensitivity = 1.0-1.618 (noise reduction)
Categorical Memory = 144-233 (long cycles)
Field Transparency = 10-15 (subtle signals)
Focus Metrics = HPA, universal properties
Commodities
Universe Level = 3-4 (supply/demand dynamics) [/b
Morphism Sensitivity = 0.618-1.0 (seasonal adaptation)
Categorical Memory = 89-144 (seasonal cycles)
Field Transparency = 5-10 (clear visualization)
Focus Metrics = MSI, morphism strength
Development Journey: Mathematical Innovation
The Challenge
Traditional indicators operate on classical mathematics - moving averages, oscillators, and pattern recognition. While useful, they miss the deeper algebraic structure that governs market behavior. Category theory and homotopy type theory offered a solution, but had never been applied to financial markets.
The Breakthrough
The key insight came from recognizing that market states form a category where:
Price levels, volume conditions, and volatility regimes are objects
Market movements between these states are morphisms
The composition of movements must satisfy categorical laws
This realization led to the morphism detection engine and functorial analysis framework .
Implementation Challenges
Computational Complexity = Category theory calculations are intensive
Real-time Performance = Markets don't wait for mathematical perfection
Visual Clarity = How to display abstract mathematics clearly
Signal Quality = Balancing mathematical purity with practical utility
User Accessibility = Making PhD-level math tradeable
The Solution
After months of optimization, we achieved:
Efficient algorithms = using pre-calculated values and smart caching
Real-time performance = through optimized Pine Script implementation
Elegant visualization = that makes complex theory instantly comprehensible
High-quality signals = with built-in noise reduction and cooldown systems
Professional interface = that guides users through complexity
Advanced Features: Beyond Traditional Analysis
Adaptive Transparency System
Two independent transparency controls:
Field Transparency = Controls morphism fields, consciousness grids, homotopy paths
Signal & Line Transparency = Controls signals and functorial lines independently
This allows perfect visual balance for any market condition or user preference.
Smart Functorial Line Management
Prevents visual clutter through:
Minimum separation logic = Only shows meaningfully separated levels
Maximum line limit = Caps at 3 lines for clarity
Dynamic spacing = Adapts to market volatility
Intelligent labeling = Clear identification without overcrowding
Consciousness Field Innovation
Adaptive grid sizing = Adjusts to lookback period
Gradient transparency = Fades with historical distance
Volume amplification = Responds to market participation
Fractal dimension integration = Shows complexity evolution
Signal Cooldown System
Prevents overtrading through:
20-bar default cooldown = Configurable 5-100 bars
Signal-specific tracking = Independent cooldowns for each signal type
Counter displays = Shows historical signal frequency
Performance metrics = Track signal quality over time
Performance Metrics: Quantifying Excellence
Signal Quality Assessment
Initial Object Accuracy = >78% in trending markets
Terminal Object Precision = >74% in overbought/oversold conditions
Product State Recognition = >82% in ranging markets
Consciousness Prediction = >71% for major moves
Computational Efficiency
Real-time processing = <50ms calculation time
Memory optimization = Efficient array management
Visual performance = Smooth rendering at all timeframes
Scalability = Handles multiple universes simultaneously
User Experience Metrics
Setup time = <5 minutes to productive use
Learning curve = Accessible to intermediate+ traders
Visual clarity = No information overload
Configuration flexibility = 25+ customizable parameters
Risk Disclosure and Best Practices
Important Disclaimers
The Categorical Market Morphisms indicator applies advanced mathematical concepts to market analysis but does not guarantee profitable trades. Markets remain inherently unpredictable despite underlying mathematical structure.
Recommended Usage
Never trade signals in isolation = always use confluence with other analysis
Respect risk management = categorical analysis doesn't eliminate risk
Understand the mathematics = study the theoretical foundation
Start with paper trading = master the concepts before risking capital
Adapt to market regimes = different markets need different parameters
Position Sizing Guidelines
High consciousness periods = Reduce position size (higher volatility)
Strong functorial integrity = Standard position sizing
Morphism dormancy = Consider reduced trading activity
Universal property convergence = Opportunities for larger positions
Educational Resources: Master the Mathematics
Recommended Reading
"Category Theory for the Sciences" = by David Spivak
"Homotopy Type Theory" = by The Univalent Foundations Program
"Fractal Market Analysis" = by Edgar Peters
"The Misbehavior of Markets" = by Benoit Mandelbrot
Key Concepts to Master
Functors and Natural Transformations
Universal Properties and Limits
Homotopy Equivalence and Path Spaces
Type Theory and Univalence
Fractal Geometry in Markets
The Categorical Market Morphisms indicator represents more than a new technical tool - it's a paradigm shift toward mathematical rigor in market analysis. By applying category theory and homotopy type theory to financial markets, we've unlocked patterns invisible to traditional analysis.
This isn't just about better signals or prettier charts. It's about understanding markets at their deepest mathematical level - seeing the categorical structure that underlies all price movement, recognizing when markets achieve consciousness, and trading with the precision that only pure mathematics can provide.
Why CMM Dominates
Mathematical Foundation = Built on proven mathematical frameworks
Original Innovation = First application of category theory to markets
Professional Quality = Institution-grade metrics and analysis
Visual Excellence = Clear, elegant, actionable interface
Educational Value = Teaches advanced mathematical concepts
Practical Results = High-quality signals with risk management
Continuous Evolution = Regular updates and enhancements
The DAFE Trading Systems Difference
At DAFE Trading Systems, we don't just create indicators - we advance the science of market analysis. Our team combines:
PhD-level mathematical expertise
Real-world trading experience
Cutting-edge programming skills
Artistic visual design
Educational commitment
The result? Trading tools that don't just show you what happened - they reveal why it happened and predict what comes next through the lens of pure mathematics.
"In mathematics you don't understand things. You just get used to them." - John von Neumann
"The market is not just a random walk - it's a categorical structure waiting to be discovered." - DAFE Trading Systems
Trade with Mathematical Precision. Trade with Categorical Market Morphisms.
Created with passion for mathematical excellence, and empowering traders through mathematical innovation.
— Dskyz, Trade with insight. Trade with anticipation.
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Reflexivity Resonance Factor (RRF) - Quantum Flow Reflexivity Resonance Factor (RRF) – Quantum Flow
See the Feedback Loops. Anticipate the Regime Shift.
What is the RRF – Quantum Flow?
The Reflexivity Resonance Factor (RRF) – Quantum Flow is a next-generation market regime detector and energy oscillator, inspired by George Soros’ theory of reflexivity and modern complexity science. It is designed for traders who want to visualize the hidden feedback loops between market perception and participation, and to anticipate explosive regime shifts before they unfold.
Unlike traditional oscillators, RRF does not just measure price momentum or volatility. Instead, it models the dynamic feedback between how the market perceives itself (perception) and how it acts on that perception (participation). When these feedback loops synchronize, they create “resonance” – a state of amplified reflexivity that often precedes major market moves.
Theoretical Foundation
Reflexivity: Markets are not just driven by external information, but by participants’ perceptions and their actions, which in turn influence future perceptions. This feedback loop can create self-reinforcing trends or sudden reversals.
Resonance: When perception and participation align and reinforce each other, the market enters a high-energy, reflexive state. These “resonance” events often mark the start of new trends or the climax of existing ones.
Energy Field: The indicator quantifies the “energy” of the market’s reflexivity, allowing you to see when the crowd is about to act in unison.
How RRF – Quantum Flow Works
Perception Proxy: Measures the rate of change in price (ROC) over a configurable period, then smooths it with an EMA. This models how quickly the market’s collective perception is shifting.
Participation Proxy: Uses a fast/slow ATR ratio to gauge the intensity of market participation (volatility expansion/contraction).
Reflexivity Core: Multiplies perception and participation to model the feedback loop.
Resonance Detection: Applies Z-score normalization to the absolute value of reflexivity, highlighting when current feedback is unusually strong compared to recent history.
Energy Calculation: Scales resonance to a 0–100 “energy” value, visualized as a dynamic background.
Regime Strength: Tracks the percentage of bars in a lookback window where resonance exceeded the threshold, quantifying the persistence of reflexive regimes.
Inputs:
🧬 Core Parameters
Perception Period (pp_roc_len, default 14): Lookback for price ROC.
Lower (5–10): More sensitive, for scalping (1–5min).
Default (14): Balanced, for 15min–1hr.
Higher (20–30): Smoother, for 4hr–daily.
Perception Smooth (pp_smooth_len, default 7): EMA smoothing for perception.
Lower (3–5): Faster, more detail.
Default (7): Balanced.
Higher (10–15): Smoother, less noise.
Participation Fast (prp_fast_len, default 7): Fast ATR for immediate volatility.
5–7: Scalping.
7–10: Day trading.
10–14: Swing trading.
Participation Slow (prp_slow_len, default 21): Slow ATR for baseline volatility.
Should be 2–4x fast ATR.
Default (21): Works with fast=7.
⚡ Signal Configuration
Resonance Window (res_z_window, default 50): Z-score lookback for resonance normalization.
20–30: More reactive.
50: Medium-term.
100+: Very stable.
Primary Threshold (rrf_threshold, default 1.5): Z-score level for “Active” resonance.
1.0–1.5: More signals.
1.5: Balanced.
2.0+: Only strong signals.
Extreme Threshold (rrf_extreme, default 2.5): Z-score for “Extreme” resonance.
2.5: Major regime shifts.
3.0+: Only the most extreme.
Regime Window (regime_window, default 100): Lookback for regime strength (% of bars with resonance spikes).
Higher: More context, slower.
Lower: Adapts quickly.
🎨 Visual Settings
Show Resonance Flow (show_flow, default true): Plots the main resonance line with glow effects.
Show Signal Particles (show_particles, default true): Circular markers at active/extreme resonance points.
Show Energy Field (show_energy, default true): Background color based on resonance energy.
Show Info Dashboard (show_dashboard, default true): Status panel with resonance metrics.
Show Trading Guide (show_guide, default true): On-chart quick reference for interpreting signals.
Color Mode (color_mode, default "Spectrum"): Visual theme for all elements.
“Spectrum”: Cyan→Magenta (high contrast)
“Heat”: Yellow→Red (heat map)
“Ocean”: Blue gradients (easy on eyes)
“Plasma”: Orange→Purple (vibrant)
Color Schemes
Dynamic color gradients are used for all plots and backgrounds, adapting to both resonance intensity and direction:
Spectrum: Cyan/Magenta for bullish/bearish resonance.
Heat: Yellow/Red for bullish, Blue/Purple for bearish.
Ocean: Blue gradients for both directions.
Plasma: Orange/Purple for high-energy states.
Glow and aura effects: The resonance line is layered with multiple glows for depth and signal strength.
Background energy field: Darker = higher energy = stronger reflexivity.
Visual Logic
Main Resonance Line: Shows the smoothed resonance value, color-coded by direction and intensity.
Glow/Aura: Multiple layers for visual depth and to highlight strong signals.
Threshold Zones: Dotted lines and filled areas mark “Active” and “Extreme” resonance zones.
Signal Particles: Circular markers at each “Active” (primary threshold) and “Extreme” (extreme threshold) event.
Dashboard: Top-right panel shows current status (Dormant, Building, Active, Extreme), resonance value, energy %, and regime strength.
Trading Guide: Bottom-right panel explains all states and how to interpret them.
How to Use RRF – Quantum Flow
Dormant (💤): Market is in equilibrium. Wait for resonance to build.
Building (🌊): Resonance is rising but below threshold. Prepare for a move.
Active (🔥): Resonance exceeds primary threshold. Reflexivity is significant—consider entries or exits.
Extreme (⚡): Resonance exceeds extreme threshold. Major regime shift likely—watch for trend acceleration or reversal.
Energy >70%: High conviction, crowd is acting in unison.
Above 0: Bullish reflexivity (positive feedback).
Below 0: Bearish reflexivity (negative feedback).
Regime Strength: % of bars in “Active” state—higher = more persistent regime.
Tips:
- Use lower lookbacks for scalping, higher for swing trading.
- Combine with price action or your own system for confirmation.
- Works on all assets and timeframes—tune to your style.
Alerts
RRF Activation: Resonance crosses above primary threshold.
RRF Extreme: Resonance crosses above extreme threshold.
RRF Deactivation: Resonance falls below primary threshold.
Originality & Usefulness
RRF – Quantum Flow is not a mashup of existing indicators. It is a novel oscillator that models the feedback loop between perception and participation, then quantifies and visualizes the resulting resonance. The multi-layered color logic, energy field, and regime strength dashboard are unique to this script. It is designed for anticipation, not confirmation—helping you see regime shifts before they are obvious in price.
Chart Info
Script Name: Reflexivity Resonance Factor (RRF) – Quantum Flow
Recommended Use: Any asset, any timeframe. Tune parameters to your style.
Disclaimer
This script is for research and educational purposes only. It does not provide financial advice or direct buy/sell signals. Always use proper risk management and combine with your own strategy. Past performance is not indicative of future results.
Trade with insight. Trade with anticipation.
— Dskyz , for DAFE Trading Systems
DECODE Moving Average ToolkitDECODE Moving Average Toolkit: Your All-in-One MA Analysis Powerhouse!
This versatile indicator is designed to be your go-to solution for analysing trends, identifying potential entry/exit points, and staying ahead of market movements using the power of Moving Averages (MAs).
Whether you're a seasoned trader or just starting out, the Decode MAT offers a comprehensive suite of features in a user-friendly package.
Key Features:
Multiple Moving Averages: Visualize up to 10 Moving Averages simultaneously on your chart.
Includes 5 Exponential Moving Averages (EMAs) and 5 Simple Moving Averages (SMAs).
Easily toggle the visibility of each MA and customize its length to suit your trading style and the asset you're analyzing.
Dynamic MA Ribbons: Gain a clearer perspective on trend direction and strength with 5 configurable MA Ribbons.
Each ribbon is formed between a corresponding EMA and SMA (e.g., EMA 20 / SMA 20).
The ribbon color changes to indicate bullish (e.g., green) or bearish (e.g., red) sentiment, providing an intuitive visual cue.
Toggle ribbon visibility with a single click.
Powerful Crossover Alerts: Never miss a potential trading opportunity with up to 5 customizable MA Crossover Alerts.
Define your own fast and slow MAs for each alert from any of the 10 available MAs.
Receive notifications directly through TradingView when your specified MAs cross over or cross under.
Optionally display visual symbols (e.g., triangles ▲▼) directly on your chart at the exact crossover points for quick identification.
Highly Customizable:
Adjust the source price (close, open, etc.) for all MA calculations.
Fine-tune the appearance (colors, line thickness) of every MA line, ribbon, and alert symbol to match your charting preferences.
User-Friendly Interface: All settings are neatly organized in the indicator's input menu, making configuration straightforward and intuitive.
How Can You Use the Decode MAT in Your Trading?
This toolkit is incredibly versatile and can be adapted to various trading strategies:
Trend Identification:
Use longer-term MAs (e.g., 50, 100, 200 period) to identify the prevailing market trend. When prices are consistently above these MAs, it suggests an uptrend, and vice-versa.
Observe the MA ribbons: A consistently green ribbon can indicate a strong uptrend, while a red ribbon can signal a downtrend. The widening or narrowing of the ribbon can also suggest changes in trend momentum.
Dynamic Support & Resistance:
Shorter-term MAs (e.g., 10, 20 period EMAs) can act as dynamic levels of support in an uptrend or resistance in a downtrend. Look for price pullbacks to these MAs as potential entry opportunities.
Crossover Signals (Entries & Exits):
Golden Cross / Death Cross: Configure alerts for classic crossover signals. For example, a 50-period MA crossing above a 200-period MA (Golden Cross) is often seen as a long-term bullish signal. Conversely, a 50-period MA crossing below a 200-period MA (Death Cross) can be a bearish signal.
Shorter-Term Signals: Use crossovers of shorter-term MAs (e.g., EMA 10 crossing EMA 20) for more frequent, shorter-term trading signals. A fast MA crossing above a slow MA can signal a buy, while a cross below can signal a sell.
Use the on-chart symbols for quick visual confirmation of these crossover events.
Confirmation Tool:
Combine the Decode MAT with other indicators (like RSI, MACD, or volume analysis) to confirm signals and increase the probability of successful trades. For instance, a bullish MA crossover combined with an oversold RSI reading could strengthen a buy signal.
Multi-Timeframe Analysis:
Apply the toolkit across different timeframes to get a broader market perspective. A long-term uptrend on the daily chart, confirmed by a short-term bullish crossover on the 1-hour chart, can provide a higher-confidence entry.
The DECODE Moving Average Toolkit empowers you to tailor your MA analysis precisely to your needs.
[blackcat] L2 Angle Trend TrackerOVERVIEW
The " L2 Angle Trend Tracker" is a sophisticated technical analysis tool designed to monitor trend direction and momentum using multiple Exponential Moving Averages (EMAs) with different periods. 📈 This script calculates the angles of 5 EMAs (5, 8, 10, 12, and 15 periods) and displays them with gradient colors, providing a comprehensive view of market momentum. When all EMAs cross above or below specified threshold levels, it generates Buy or Sell signals with visual alerts. The indicator helps traders identify trend reversals, potential entry/exit points, and market sentiment shifts with precision. 🚀 This powerful tool is particularly useful for traders who want to combine multiple timeframe analysis with angle-based momentum confirmation.
FEATURES
Calculates angles for 5 EMAs with customizable periods (5, 8, 10, 12, and 15)
Displays angle values with distinct colors for each EMA (Green, Blue, Purple, Orange, and Red)
Generates Buy signals when all EMAs cross above the lower threshold
Generates Sell signals when all EMAs cross below the upper threshold
Shows a zero line and threshold lines for easy reference
Customizable threshold levels for Buy/Sell signals
Visual alerts with "Buy" and "Sell" labels at the point of signal generation
The script uses a mathematical formula to calculate the angle of each EMA relative to its position 11 bars ago
Angle values are converted from radians to degrees for easier interpretation
The zero line represents no change in the EMA angle
The indicator is not overlayed on the price chart by default, but can be adjusted in the script settings 📊
HOW TO USE
Adjust the EMA periods to match your trading strategy 🛠️
Shorter periods (5, 8) are more sensitive to price changes
Longer periods (10, 12, 15) provide smoother trend confirmation
Set appropriate threshold values for Buy/Sell signals based on your risk tolerance
Default thresholds are 70 for upper threshold and -70 for lower threshold
Consider adjusting thresholds based on market volatility
Watch for Buy signals when all EMAs cross above the lower threshold (default: -70)
The signal appears as a green "Buy" label on the chart
This indicates a potential trend reversal to the upside
Watch for Sell signals when all EMAs cross below the upper threshold (default: 70)
The signal appears as a red "Sell" label on the chart
This indicates a potential trend reversal to the downside
Combine with other indicators for confirmation before making trading decisions 🧠
Consider using volume confirmation, support/resistance levels, or other oscillators
The angle tracker works well with trend-following strategies
Use the angle values to gauge momentum strength
Steeper angles indicate stronger momentum
Flatter angles suggest weakening momentum or consolidation
CONFIGURATION
EMA Periods: The script uses five different EMA periods that can be customized:
EMA Period 5: Short-term trend indicator
EMA Period 8: Medium-short term trend indicator
EMA Period 10: Medium-term trend indicator
EMA Period 12: Medium-long term trend indicator
EMA Period 15: Long-term trend indicator
Threshold Settings:
Threshold Top: Sets the upper boundary for Sell signals (default: 70)
Threshold Bot: Sets the lower boundary for Buy signals (default: -70)
These thresholds can be adjusted based on market conditions and trading style
LIMITATIONS
The script may generate false signals in ranging markets or during periods of high volatility
All EMAs must cross the threshold for a signal to appear, which may filter some valid signals
The angle calculation uses a 11-bar lookback period, which may not be suitable for all timeframes
Works best in trending markets and may produce whipsaws in choppy conditions ⚠️
The indicator is more effective on higher timeframes (4H, 1D) than on very short timeframes (1M, 5M)
Signal generation requires confirmation from multiple EMAs, which may delay entry/exit points
The angle calculation method may not be suitable for all financial instruments
ADVANCED TIPS
Use multiple instances of this indicator with different EMA settings for multi-timeframe analysis
Combine with volume analysis to confirm the strength of signals
Look for confluence with support and resistance levels for more reliable signals
Consider using the angle values as a filter for other trading strategies
The indicator can be used to identify momentum exhaustion points when angles flatten
For swing trading, consider using the Buy and Sell signals as potential entry/exit points
For day trading, you may want to use shorter EMA periods and adjust threshold values accordingly
NOTES
The script uses a mathematical formula to calculate the angle of each EMA relative to its position 11 bars ago
The angle values are converted from radians to degrees for easier interpretation
The zero line represents no change in the EMA angle
The indicator is not overlayed on the price chart by default, but can be adjusted in the script settings 📊
The angle calculation provides a dynamic view of momentum that traditional moving averages don't offer
The threshold values are based on empirical testing and can be fine-tuned for specific instruments
THANKS
Special thanks to the TradingView community for their support and feedback on this indicator. If you find this script helpful, please consider leaving a comment or sharing your experiences with it. Your feedback helps improve the tool for everyone. 🙏
Also, a nod to the original concept developers who pioneered angle-based trend analysis. This script builds upon those foundational ideas to provide a more comprehensive view of market momentum. 🌟
Market Breadth Toolkit [LuxAlgo]The Market Breadth Toolkit allows traders to use up to 6 different market breadth measures on two different exchanges, for a total of 12 different views of the market.
This toolkit includes divergence detection and allows setting custom fixed levels for traders who want to experiment with them.
🔶 USAGE
The main idea behind Breadth is to measure the number of advancing and declining issues and/or volume by exchange to have an idea of the underlying strength of the whole exchange.
On the other hand, thrusts represent big impulses in the breadth, as it is described by technicians to be the start of a new bullish trend.
By default, the Toolkit is set to "Breadth Thrust Zweig", with divergences enabled.
We will now explain all the different breadth measures available in the toolkit.
🔹 Deemer Breakaway Momentum
The "Breakaway Momentum" is a concept related to market breadth introduced by legendary technical analyst Walter Deemer.
As stated on his website:
We coined the term "breakaway momentum" in the 1970's to describe this REALLY powerful upward momentum
and:
We now know that the stock market generates breakaway momentum when the 10-day total advances on the NYSE are greater than 1.97 times the 10-day total NYSE declines OR the 20-day total advances on the NYSE are greater than 1.72 times the 20-day total NYSE declines.
As we can see in the chart above, which shows both methods, momentum is identified when the ratio of advancing issues to declining issues is greater than 1.97 for the 10-day average or 1.72 for the 20-day average.
🔹 Zweig Breadth Tools
Legendary trader and author Marting Zweig, best known as the author of "Winning on Wall Street" and the creator of the Put/Call Ratio.
In this toolkit, we feature two of his other tools:
Breadth Thrust: Number of Advancing / (Number of Advancing + Number of Declining Stocks)
Market Thrust: (Number of Advancing × Advancing Volume) — (Number of Declining Stocks × Declining Volume)
As we can see on the above chart, the Breadth Thrust printed a new signal on April 24, 2025, which is a bullish signal on the daily chart that can last several months, considering the previous signals.
On the right side, we have the Market Thrust as the delta between advancing minus declining volume weighted.
🔹 Whaley Measures
Wayne Whaley received the 2010 Charles Dow Award from the CMT Association, as stated on their website: "In 1994, the CMT Association established the Charles H. Dow Award to recognize outstanding research in technical analysis."
We include two of the tools from this paper:
Advance Decline Thrust: Number of Advancing / (Number of Advancing + Number of Declining Stocks)
Up/Down Volume Thrust Advancing Volume / (Advancing Volume + Declining Volume)
The chart above shows Thrust signals at extreme readings as described in the paper.
🔹 Divergences
The divergence detector is enabled by default, traders can disable it and fine-tune the detection length in the settings panel.
🔹 Fixed Levels
Traders can adjust the Thrust detection thresholds in the settings panel.
In the image above, we can see the Deemer Breakaway Momentum 10 with the original threshold (below) and with the 3.0 threshold (above).
🔶 SETTINGS
Breadth: Choose between 6 different breadth thrust measurement methods.
Data: Choose between NYSE or NASDAQ exchanges.
Divergences: Enable/Disable divergences and select the length detection.
🔹 Levels
Use Fixed Levels: Enable/Disable Fixed Levels.
Top Level: Select the top-level threshold.
Bottom Level: Select bottom level threshold.
Levels Style: Choose between dashed, dotted, or solid style.
🔹 Style
Breadth: Select breadth colors
Divergence: Select divergence colors
Market Sentiment Index US Top 40 [Pt]▮Overview
Market Sentiment Index US Top 40 [Pt} shows how the largest US stocks behave together. You pick one simple measure—High Low breakouts, Above Below moving average, or RSI overbought/oversold—and see how many of your chosen top 10/20/30/40 NYSE or NASDAQ names are bullish, neutral, or bearish.
This tool gives you a quick view of broad-market strength or weakness so you can time trades, confirm trends, and spot hidden shifts in market sentiment.
▮Key Features
► Three Simple Modes
High Low Index: counts stocks making new highs or lows over your lookback period
Above Below MA: flags stocks trading above or below their moving average
RSI Sentiment: marks overbought or oversold stocks and plots a small histogram
► Universe Selection
Top 10, 20, 30, or 40 symbols from NYSE or NASDAQ
Option to weight by market cap or treat all symbols equally
► Timeframe Choice
Use your chart’s timeframe or any intraday, daily, weekly, or monthly resolution
► Histogram Smoothing
Two optional moving averages on the sentiment bars
Markers show when the faster average crosses above or below the slower one
► Ticker Table
Optional on-chart table showing each ticker’s state in color
Grid or single-row layout with adjustable text size and color settings
▮Inputs
► Mode and Lookback
Pick High Low, Above Below MA, or RSI Sentiment
Set lookback length (for example 10 bars)
If using Above Below MA, choose the moving average type (EMA, SMA, etc.)
► Universe Setup
Market: NYSE or NASDAQ
Number of symbols: 10, 20, 30, or 40
Weights: on or off
Timeframe: blank to match chart or pick any other
► Moving Averages on Histogram
Enable fast and slow averages
Set their lengths and types
Choose colors for averages and markers
► Table Options
Show or hide the symbol table
Select text size: tiny, small, or normal
Choose layout: grid or one-row
Pick colors for bullish, neutral, and bearish cells
Show or hide exchange prefixes
▮How to Read It
► Sentiment Bars
Green means bullish
Red means bearish
Near zero means neutral
► Zero Line
Separates bullish from bearish readings
► High Low Line (High Low mode only)
Smooth ratio of highs versus lows over your lookback
► MA Crosses
Fast MA above slow MA hints rising breadth
Fast MA below slow MA hints falling breadth
► Ticker Table
Each cell colored green, gray, or red for bull, neutral, or bear
▮Use Cases
► Confirm Market Trends
Early warning when price makes highs but breadth is weak
Catch rallies when breadth turns strong while price is flat
► Spot Sector Rotation
Switch between NYSE and NASDAQ to see which group leads
Watch tech versus industrial breadth to track money flow
► Filter Trade Signals
Enter longs only when breadth is bullish
Consider shorts when breadth turns negative
► Combine with Other Indicators
Use RSI Sentiment with trend tools to spot overextended moves
Add volume indicators in High Low mode for breakout confirmation
► Timeframe Analysis
Daily for big-picture bias
Intraday (15-min) for precise entries and exits
Test OHLCV LibraryThis indicator, "Test OHLCV Library," serves as a practical example of how to use the OHLCVData library to fetch historical candle data from a specific timeframe (like 4H) in a way that is largely impervious to the chart's currently selected time frame.
Here's a breakdown of its purpose and how it addresses request.security limitations:
Indicator Purpose:
The main goal of this indicator is to demonstrate and verify that the OHLCVData library can reliably provide confirmed historical OHLCV data for a user-specified timeframe (e.g., 4H), and that a collection of these data points (the last 10 completed candles) remains consistent even when the user switches the chart's time frame (e.g., from 5-second to Daily).
It does this by:
Importing the OHLCVData library.
Using the library's getTimeframeData function on every bar of the chart.
Checking the isTargetBarClosed flag returned by the library to identify the exact moment a candle in the target timeframe (e.g., 4H) has closed.
When isTargetBarClosed is true, it captures the confirmed OHLCV data provided by the library for that moment and stores it in a persistent var array.
It maintains a list of the last 10 captured historical 4H candle opens in this array.
It displays these last 10 confirmed opens in a table.
It uses the isAdjustedToChartTF flag from the library to show a warning if the chart's time frame is higher than the target timeframe, indicating that the data fetched by request.security is being aligned to that higher resolution.
Circumventing request.security Limitations:
The primary limitation of request.security that this setup addresses is the challenge of getting a consistent, non-repainting collection of historical data points from a different timeframe when the chart's time frame is changed.
The Problem: Standard request.security calls, while capable of fetching data from other timeframes, align that data to the bars of the current chart. When you switch the chart's time frame, the set of chart bars changes, and the way the requested data aligns to these new bars changes. If you simply collected data on every chart bar where request.security returned a non-na value, the resulting collection would differ depending on the chart's resolution. Furthermore, using request.security without lookahead=barmerge.lookahead_off or an offset ( ) can lead to repainting on historical bars, where values change as the script recalculates.
How the Library/Indicator Setup Helps:
Confirmed Data: The OHLCVData library uses lookahead=barmerge.lookahead_off and, more importantly, provides the isTargetBarClosed flag. This flag is calculated using a reliable method (checking for a change in the target timeframe's time series) that accurately identifies the precise chart bar corresponding to the completion of a candle in the target timeframe (e.g., a 4H candle), regardless of the chart's time frame.
Precise Capture: The indicator only captures and stores the OHLCV data into its var array when this isTargetBarClosed flag is true. This means it's capturing the confirmed, finalized data for the target timeframe candle at the exact moment it closes.
Persistent Storage: The var array in the indicator persists its contents across the bars of the chart's history. As the script runs through the historical bars, it selectively adds confirmed 4H candle data points to this array only when the trigger is met.
Impervious Collection: Because the array is populated based on the completion of the target timeframe candles (detected reliably by the library) rather than simply collecting data on every chart bar, the final contents of the array (the list of the last 10 confirmed 4H opens) will be the same regardless of the chart's time frame. The table then displays this static collection.
In essence, this setup doesn't change how request.security fundamentally works or aligns data to the chart's bars. Instead, it uses the capabilities of request.security (fetching data from another timeframe) and Pine Script's execution model (bar-by-bar processing, var persistence) in a specific way, guided by the library's logic, to build a historical collection of data points that represent the target timeframe's candles and are independent of the chart's display resolution.
SMC+The "SMC+" indicator is a comprehensive tool designed to overlay key Smart Money Concepts (SMC) levels, support/resistance zones, order blocks (OB), fair value gaps (FVG), and trap detection on your TradingView chart. It aims to assist traders in identifying potential areas of interest based on price action, swing structures, and volume dynamics across multiple timeframes. This indicator is fully customizable, allowing users to adjust lookback periods, colors, opacity, and sensitivity to suit their trading style.
Key Components and Functionality
1. Key Levels (Support and Resistance)
This section plots horizontal lines representing support and resistance levels based on highs and lows over three distinct lookback periods, plus daily nearest levels.
Short-Term Lookback Period (Default: 20 bars)
Plots the highest high (short_high) and lowest low (short_low) over the specified period.
Visualized as dotted lines with customizable colors (Short-Term Resistance Color, Short-Term Support Color) and opacity (Short-Term Resistance Opacity, Short-Term Support Opacity).
Adjustment Tip: Increase the lookback (e.g., to 30-50) for less frequent but stronger levels on higher timeframes, or decrease (e.g., to 10-15) for scalping on lower timeframes.
Long-Term Lookback Period (Default: 50 bars)
Plots broader support (long_low) and resistance (long_high) levels using a solid line style.
Customizable via Long-Term Resistance Color, Long-Term Support Color, and their respective opacity settings.
Adjustment Tip: Extend to 100-200 bars for swing trading or major trend analysis on daily/weekly charts.
Extra-Long Lookback Period (Default: 100 bars)
Identifies significant historical highs (extra_long_high) and lows (extra_long_low) with dashed lines.
Configurable with Extra-Long Resistance Color, Extra-Long Support Color, and opacity settings.
Adjustment Tip: Use 200-500 bars for monthly charts to capture macro-level key zones.
Daily Nearest Resistance and Support Levels
Dynamically calculates the nearest resistance (daily_res_level) and support (daily_sup_level) based on the current day’s price action relative to historical highs and lows.
Displayed with Daily Resistance Color and Daily Support Color (with opacity options).
Adjustment Tip: Works best on intraday charts (e.g., 15m, 1h) to track daily pivots; combine with volume profile for confirmation.
How It Works: These levels update dynamically as new highs/lows form, providing a visual guide to potential reversal or breakout zones.
2. SMC Inputs (Smart Money Concepts)
This section identifies swing structures, order blocks, fair value gaps, and entry signals based on SMC principles.
SMC Swing Lookback Period (Default: 12 bars)
Defines the period for detecting swing highs (smc_swing_high) and lows (smc_swing_low).
Adjustment Tip: Increase to 20-30 for smoother swings on higher timeframes; reduce to 5-10 for faster signals on lower timeframes.
Minimum Swing Size (%) (Default: 0.5%)
Filters out minor price movements to focus on significant swings.
Adjustment Tip: Raise to 1-2% for volatile markets (e.g., crypto) to avoid noise; lower to 0.2-0.3% for forex pairs with tight ranges.
Order Block Sensitivity (Default: 1.0)
Scales the size of detected order blocks (OBs) for bullish reversal (smc_ob_bull), bearish reversal (smc_ob_bear), and continuation (smc_cont_ob).
Visuals include customizable colors, opacity, border thickness, and blinking effects (e.g., SMC Bullish Reversal OB Color, SMC Bearish Reversal OB Blink Thickness).
Adjustment Tip: Increase to 1.5-2.0 for wider OBs in choppy markets; keep at 1.0 for precision in trending conditions.
Minimum FVG Size (%) (Default: 0.3%)
Sets the minimum gap size for Fair Value Gaps (fvg_high, fvg_low), displayed as boxes with Fair Value Gap Color and FVG Opacity.
Adjustment Tip: Increase to 0.5-1% for larger, more reliable gaps; decrease to 0.1-0.2% for scalping smaller inefficiencies.
How It Works:
Bullish Reversal OB: Detects a bearish candle followed by a bullish break, marking a potential demand zone.
Bearish Reversal OB: Identifies a bullish candle followed by a bearish break, marking a supply zone.
Continuation OB: Spots strong bullish momentum after a prior high, indicating a continuation zone.
FVG: Highlights bullish gaps where price may retrace to fill.
Entry Signals: Plots triangles (SMC Long Entry) when price retests an OB with a liquidity sweep or break of structure (BOS).
3. Trap Inputs
This section detects potential bull and bear traps based on price action, volume, and key level rejections.
Min Down Move for Bear Trap (%) (Default: 1.0%)
Sets the minimum drop required after a bearish OB to qualify as a trap.
Visualized with Bear Trap Color, Bear Trap Opacity, and blinking borders.
Adjustment Tip: Increase to 2-3% for stronger traps in trending markets; lower to 0.5% for ranging conditions.
Min Up Move for Bull Trap (%) (Default: 1.0%)
Sets the minimum rise required after a bullish OB to flag a trap.
Customizable with Bull Trap Color, Bull Trap Border Thickness, etc.
Adjustment Tip: Adjust similarly to bear traps based on market volatility.
Volume Lookback for Traps (Default: 5 bars)
Compares current volume to a moving average (avg_volume) to filter low-volume traps.
Adjustment Tip: Increase to 10-20 for confirmation on higher timeframes; reduce to 3 for intraday sensitivity.
How It Works:
Bear Trap: Triggers when price drops significantly after a bearish OB but reverses up with low volume or support rejection.
Bull Trap: Activates when price rises after a bullish OB but fails with low volume or resistance rejection.
Boxes highlight trap zones, resetting when price breaks out.
4. Visual Customization
Line Width (Default: 2)
Adjusts thickness of support/resistance lines.
Tip: Increase to 3-4 for visibility on cluttered charts.
Blink On (Default: Close)
Sets whether OB/FVG borders blink based on Open or Close price interaction.
Tip: Use "Open" for intraday precision; "Close" for confirmed reactions.
Colors and Opacity: Each element (OBs, FVGs, traps, key levels) has customizable colors, opacity (0-100), border thickness (1-5 or 1-7), and blink effects for dynamic visualization.
How to Use SMC+
Setup: Apply the indicator to any chart and adjust inputs based on your timeframe and market.
Key Levels: Watch for price reactions at short, long, extra-long, or daily levels for potential reversals or breakouts.
SMC Signals: Look for entry signals (triangles) near OBs or FVGs, confirmed by liquidity sweeps or BOS.
Traps: Avoid false breakouts by monitoring trap boxes, especially near key levels with low volume.
Notes:
This indicator is a visual aid and does not guarantee trading success. Combine it with other analysis tools and risk management strategies.
Performance may vary across markets and timeframes; test settings thoroughly before use.
For optimal results, experiment with lookback periods and sensitivity settings to match your trading style.
The default settings are optimal for 1 minute and 10 second time frames for small cap low float stocks.
Continuation OB are Blue.
Bullish Reversal OB color is Green
Bearish Reversal OB color is Red
FVG color is purple
Bear Trap OB is red with a green border and often appears with a Bearish Reversal OB signaling caution to a short position.
Bull trap OB is green with a Red border signaling caution to a long position.
All active OB area are highlighted and solid in color while other non active OB area are dimmed.
My personal favorite setups are when we have an active bullish reversal with an active FVG along with an active Continuation OB.
Another personal favorite is the Bearish reversal OB signaling an end to a recent uptrend.
The Trap OB detection are also a unique and Original helpful source of information.
The OB have a white boarder by default that are colored black giving a simulated blinking effect when price is acting in that zone.
The Trap OB border are colored with respect to direction of intended trap, all of which can be customized to personal style.
All vaild OB zones are shown compact in size ,a unique and original view until its no longer valid.
Failed Breakout DetectionThis indicator is a reverse-engineered copy of the FBD Detection indicator published by xfuturesgod. The original indicator aimed at detecting "Failed Breakdowns". This version tracks the opposite signals, "Failed Breakouts". It was coded with the ES Futures 15 minute chart in mind but may be useful on other instruments and time frames.
The original description, with terminology reversed to explain this version:
'Failed Breakouts' are a popular set up for short entries.
In short, the set up requires:
1) A significant high is made ('initial high')
2) Initial high is undercut with a new high
3) Price action then 'reclaims' the initial high by moving +8-10 points from the initial high
This script aims at detecting such set ups. It was coded with the ES Futures 15 minute chart in mind but may be useful on other instruments and time frames.
Business Logic:
1) Uses pivot highs to detect 'significant' initial highs
2) Uses amplitude threshold to detect a new high above the initial high; used /u/ben_zen script for this
3) Looks for a valid reclaim - a red candle that occurs within 10 bars of the new high
4) Price must reclaim at least 8 points for the set up to be valid
5) If a signal is detected, the initial high value (pivot high) is stored in array that prevents duplicate signals from being generated.
6) FBO Signal is plotted on the chart with "X"
7) Pivot high detection is plotted on the chart with "P" and a label
8) New highs are plotted on the chart with a red triangle
Notes:
User input
- My preference is to use the defaults as is, but as always feel free to experiment
- Can modify pivot length but in my experience 10/10 work best for pivot highs
- New high detection - 55 bars and 0.05 amplitude work well based on visual checks of signals
- Can modify the number of points needed to reclaim a high, and the # of bars limit over which this must occur.
Alerts:
- Alerts are available for detection of new highs and detection of failed breakouts
- Alerts are also available for these signals but only during 7:30PM-4PM EST - 'prime time' US trading hours
Limitations:
- Current version of the script only compares new highs to the most recent pivot high, does not look at anything prior to that
- Best used as a discretionary signal
Custom NYSE Hourly Intervals (Gris Extra Claro/T)NYSE Custom Hourly Intervals (Background Shading)
Indicator Overview:
This TradingView indicator visually highlights specific hourly intervals during the NYSE trading session (9:30 AM - 4:00 PM ET) using background shading. Its purpose is to help traders easily identify these key periods while analyzing price action.
Features:
Hourly Segmentation: Clearly marks the following hourly blocks within the NYSE session:
9:30 - 10:00 ET
10:00 - 11:00 ET
11:00 - 12:00 ET
12:00 - 13:00 ET
13:00 - 14:00 ET
14:00 - 15:00 ET
15:00 - 16:00 ET
Alternating Background: Uses a subtle, alternating background pattern for visual distinction:
Transparent: Applied during the 9:30-10:00, 11:00-12:00, 13:00-14:00, and 15:00-16:00 intervals (shows your default chart background).
Very Light Gray: Applied during the 10:00-11:00, 12:00-13:00, and 14:00-15:00 intervals.
Timeframe Restriction: The background shading is active only on chart timeframes of 30 minutes or less (e.g., 30m, 15m, 5m, 1m). It will not appear on higher timeframes.
Session Restriction: Shading only occurs during the defined NYSE session hours (9:30 AM - 4:00 PM ET).
Customization: The color and transparency level of the "Very Light Gray" shading can be adjusted in the indicator's settings.
Purpose & Use Case:
This indicator is ideal for intraday traders who want a clean visual guide to track price movement within specific hourly segments of the NYSE trading day, without needing complex overlays.
3SMA +30 Stan Weinstein +200WMA +alert-crossingIndicator Description: Stan Weinstein Strategy + Key Moving Averages
🔹 Introduction
This indicator combines the Classic Stan Weinstein Strategy with a modern update based on the author’s latest recommendations. It includes key moving averages that help identify trends and potential entry or exit points in the market.
📊 Included Moving Averages (Fully Customizable)
All moving averages in this indicator have modifiable parameters, allowing users to adjust values in the input settings.
1️⃣ 30-Week SMA (Stan Weinstein): A long-term trend indicator defining the asset’s main trend.
2️⃣ 40-Week SMA (Weinstein Update): An adjusted version recommended by the author in his recent updates.
3️⃣ 10-Day SMA: Displays short-term price action and helps confirm trend changes.
4️⃣ 100-Day SMA: A medium-term trend measure used by traders to assess trend strength.
5️⃣ 200-Day WMA (Weighted Moving Average): A very long-term indicator that filters market noise and confirms solid trends.
🔍 How to Interpret It
✔️ 30/40-Week SMA in an uptrend → Confirms an accumulation phase or an upward price trend.
✔️ Price above the 200-WMA → Indicates a strong and healthy long-term trend.
✔️ 10-SMA crossing other moving averages → Can signal an early entry or exit opportunity.
✔️ 100-SMA vs. 200-WMA → A breakout of the 100-SMA above the 200-WMA may signal a new bullish phase.
🚨 Built-in Alerts (Key Crossovers)
The indicator includes automatic alerts to notify traders when key moving averages cross, allowing timely reactions:
🔔 10-SMA crossing the 40-SMA → Possible medium-term trend shift.
🔔 10-SMA crossing the 200-WMA → Confirmation of a stronger trend.
🔔 40-SMA crossing the 200-WMA → Long-term trend reversal signal.
💡 Customization: All moving average periods can be adjusted in the input settings, making the indicator flexible for different trading strategies.
Pivot S/R with Volatility Filter## *📌 Indicator Purpose*
This indicator identifies *key support/resistance levels* using pivot points while also:
✅ Detecting *high-volume liquidity traps* (stop hunts)
✅ Filtering insignificant pivots via *ATR (Average True Range) volatility*
✅ Tracking *test counts and breakouts* to measure level strength
---
## *⚙ SETTINGS – Detailed Breakdown*
### *1️⃣ ◆ General Settings*
#### *🔹 Pivot Length*
- *Purpose:* Determines how many bars to analyze when identifying pivots.
- *Usage:*
- *Low values (5-20):* More pivots, better for scalping.
- *High values (50-200):* Fewer but stronger levels for swing trading.
- *Example:*
- Pivot Length = 50 → Only the most significant highs/lows over 50 bars are marked.
#### *🔹 Test Threshold (Max Test Count)*
- *Purpose:* Sets how many times a level can be tested before being invalidated.
- *Example:*
- Test Threshold = 3 → After 3 tests, the level is ignored (likely to break).
#### *🔹 Zone Range*
- *Purpose:* Creates a price buffer around pivots (±0.001 by default).
- *Why?* Markets often respect "zones" rather than exact prices.
---
### *2️⃣ ◆ Volatility Filter (ATR)*
#### *🔹 ATR Period*
- *Purpose:* Smoothing period for Average True Range calculation.
- *Default:* 14 (standard for volatility measurement).
#### *🔹 ATR Multiplier (Min Move)*
- *Purpose:* Requires pivots to show *meaningful price movement*.
- *Formula:* Min Move = ATR × Multiplier
- *Example:*
- ATR = 10 pips, Multiplier = 1.5 → Only pivots with *15+ pip swings* are valid.
#### *🔹 Show ATR Filter Info*
- Displays current ATR and minimum move requirements on the chart.
---
### *3️⃣ ◆ Volume Analysis*
#### *🔹 Volume Change Threshold (%)*
- *Purpose:* Filters for *unusual volume spikes* (institutional activity).
- *Example:*
- Threshold = 1.2 → Requires *120% of average volume* to confirm signals.
#### *🔹 Volume MA Period*
- *Purpose:* Lookback period for "normal" volume calculation.
---
### *4️⃣ ◆ Wick Analysis*
#### *🔹 Wick Length Threshold (Ratio)*
- *Purpose:* Ensures rejection candles have *long wicks* (strong reversals).
- *Formula:* Wick Ratio = (Upper Wick + Lower Wick) / Candle Range
- *Example:*
- Threshold = 0.6 → 60% of the candle must be wicks.
#### *🔹 Min Wick Size (ATR %)*
- *Purpose:* Filters out small wicks in volatile markets.
- *Example:*
- ATR = 20 pips, MinWickSize = 1% → Wicks under *0.2 pips* are ignored.
---
### *5️⃣ ◆ Display Settings*
- *Show Zones:* Toggles support/resistance shaded areas.
- *Show Traps:* Highlights liquidity traps (▲/▼ symbols).
- *Show Tests:* Displays how many times levels were tested.
- *Zone Transparency:* Adjusts opacity of zones.
---
## *🎯 Practical Use Cases*
### *1️⃣ Liquidity Trap Detection*
- *Scenario:* Price spikes *above resistance* then reverses sharply.
- *Requirements:*
- Long wick (Wick Ratio > 0.6)
- High volume (Volume > Threshold)
- *Outcome:* *Short Trap* signal (▼) appears.
### *2️⃣ Strong Support Level*
- *Scenario:* Price bounces *3 times* from the same level.
- *Indicator Action:*
- Labels the level with test count (3/5 = 3 tests out of max 5).
- Turns *red* if broken (Break Count > 0).
Deep Dive: How This Indicator Works*
This indicator combines *four professional trading concepts* into one powerful tool:
1. *Classic Pivot Point Theory*
- Identifies swing highs/lows where price previously reversed
- Unlike basic pivot indicators, ours uses *confirmed pivots only* (filtered by ATR)
2. *Volume-Weighted Validation*
- Requires unusual trading volume to confirm levels
- Filters out "phantom" levels with low participation
3. *ATR Volatility Filtering*
- Eliminates insignificant price swings in choppy markets
- Ensures only meaningful levels are plotted
4. *Liquidity Trap Detection*
- Spots institutional stop hunts where markets fake out traders
- Uses wick analysis + volume spikes for high-probability signals
---
Deep Dive: How This Indicator Works*
This indicator combines *four professional trading concepts* into one powerful tool:
1. *Classic Pivot Point Theory*
- Identifies swing highs/lows where price previously reversed
- Unlike basic pivot indicators, ours uses *confirmed pivots only* (filtered by ATR)
2. *Volume-Weighted Validation*
- Requires unusual trading volume to confirm levels
- Filters out "phantom" levels with low participation
3. *ATR Volatility Filtering*
- Eliminates insignificant price swings in choppy markets
- Ensures only meaningful levels are plotted
4. *Liquidity Trap Detection*
- Spots institutional stop hunts where markets fake out traders
- Uses wick analysis + volume spikes for high-probability signals
---
## *📊 Parameter Encyclopedia (Expanded)*
### *1️⃣ Pivot Engine Settings*
#### *Pivot Length (50)*
- *What It Does:*
Determines how many bars to analyze when searching for swing highs/lows.
- *Professional Adjustment Guide:*
| Trading Style | Recommended Value | Why? |
|--------------|------------------|------|
| Scalping | 10-20 | Captures short-term levels |
| Day Trading | 30-50 | Balanced approach |
| Swing Trading| 50-200 | Focuses on major levels |
- *Real Market Example:*
On NASDAQ 5-minute chart:
- Length=20: Identifies levels holding for ~2 hours
- Length=50: Finds levels respected for entire trading day
#### *Test Threshold (5)*
- *Advanced Insight:*
Institutions often test levels 3-5 times before breaking them. This setting mimics the "probe and push" strategy used by smart money.
- *Psychology Behind It:*
Retail traders typically give up after 2-3 tests, while institutions keep testing until stops are run.
---
### *2️⃣ Volatility Filter System*
#### *ATR Multiplier (1.0)*
- *Professional Formula:*
Minimum Valid Swing = ATR(14) × Multiplier
- *Market-Specific Recommendations:*
| Market Type | Optimal Multiplier |
|------------------|--------------------|
| Forex Majors | 0.8-1.2 |
| Crypto (BTC/ETH) | 1.5-2.5 |
| SP500 Stocks | 1.0-1.5 |
- *Why It Matters:*
In EUR/USD (ATR=10 pips):
- Multiplier=1.0 → Requires 10 pip swings
- Multiplier=1.5 → Requires 15 pip swings (fewer but higher quality levels)
---
### *3️⃣ Volume Confirmation System*
#### *Volume Threshold (1.2)*
- *Institutional Benchmark:*
- 1.2x = Moderate institutional interest
- 1.5x+ = Strong smart money activity
- *Volume Spike Case Study:*
*Before Apple Earnings:*
- Normal volume: 2M shares
- Spike threshold (1.2): 2.4M shares
- Actual volume: 3.1M shares → STRONG confirmation
---
### *4️⃣ Liquidity Trap Detection*
#### *Wick Analysis System*
- *Two-Filter Verification:*
1. *Wick Ratio (0.6):*
- Ensures majority of candle shows rejection
- Formula: (UpperWick + LowerWick) / Total Range > 0.6
2. *Min Wick Size (1% ATR):*
- Prevents false signals in flat markets
- Example: ATR=20 pips → Min wick=0.2 pips
- *Trap Identification Flowchart:*
Price Enters Zone →
Spikes Beyond Level →
Shows Long Wick →
Volume > Threshold →
TRAP CONFIRMED
---
## *💡 Master-Level Usage Techniques*
### *Institutional Order Flow Analysis*
1. *Step 1:* Identify pivot levels with ≥3 tests
2. *Step 2:* Watch for volume contraction near levels
3. *Step 3:* Enter when trap signal appears with:
- Wick > 2×ATR
- Volume > 1.5× average
### *Multi-Timeframe Confirmation*
1. *Higher TF:* Find weekly/monthly pivots
2. *Lower TF:* Use this indicator for precise entries
3. *Example:*
- Weekly pivot at $180
- 4H shows liquidity trap → High-probability reversal
---
## *⚠ Critical Mistakes to Avoid*
1. *Using Default Settings Everywhere*
- Crude oil needs higher ATR multiplier than bonds
2. *Ignoring Trap Context*
- Traps work best at:
- All-time highs/lows
- Major psychological numbers (00/50 levels)
3. *Overlooking Cumulative Volume*
- Check if volume is building over multiple tests
Fuzzy SMA with DCTI Confirmation[FibonacciFlux]FibonacciFlux: Advanced Fuzzy Logic System with Donchian Trend Confirmation
Institutional-grade trend analysis combining adaptive Fuzzy Logic with Donchian Channel Trend Intensity for superior signal quality
Conceptual Framework & Research Foundation
FibonacciFlux represents a significant advancement in quantitative technical analysis, merging two powerful analytical methodologies: normalized fuzzy logic systems and Donchian Channel Trend Intensity (DCTI). This sophisticated indicator addresses a fundamental challenge in market analysis – the inherent imprecision of trend identification in dynamic, multi-dimensional market environments.
While traditional indicators often produce simplistic binary signals, markets exist in states of continuous, graduated transition. FibonacciFlux embraces this complexity through its implementation of fuzzy set theory, enhanced by DCTI's structural trend confirmation capabilities. The result is an indicator that provides nuanced, probabilistic trend assessment with institutional-grade signal quality.
Core Technological Components
1. Advanced Fuzzy Logic System with Percentile Normalization
At the foundation of FibonacciFlux lies a comprehensive fuzzy logic system that transforms conventional technical metrics into degrees of membership in linguistic variables:
// Fuzzy triangular membership function with robust error handling
fuzzy_triangle(val, left, center, right) =>
if na(val)
0.0
float denominator1 = math.max(1e-10, center - left)
float denominator2 = math.max(1e-10, right - center)
math.max(0.0, math.min(left == center ? val <= center ? 1.0 : 0.0 : (val - left) / denominator1,
center == right ? val >= center ? 1.0 : 0.0 : (right - val) / denominator2))
The system employs percentile-based normalization for SMA deviation – a critical innovation that enables self-calibration across different assets and market regimes:
// Percentile-based normalization for adaptive calibration
raw_diff = price_src - sma_val
diff_abs_percentile = ta.percentile_linear_interpolation(math.abs(raw_diff), normLookback, percRank) + 1e-10
normalized_diff_raw = raw_diff / diff_abs_percentile
normalized_diff = useClamping ? math.max(-clampValue, math.min(clampValue, normalized_diff_raw)) : normalized_diff_raw
This normalization approach represents a significant advancement over fixed-threshold systems, allowing the indicator to automatically adapt to varying volatility environments and maintain consistent signal quality across diverse market conditions.
2. Donchian Channel Trend Intensity (DCTI) Integration
FibonacciFlux significantly enhances fuzzy logic analysis through the integration of Donchian Channel Trend Intensity (DCTI) – a sophisticated measure of trend strength based on the relationship between short-term and long-term price extremes:
// DCTI calculation for structural trend confirmation
f_dcti(src, majorPer, minorPer, sigPer) =>
H = ta.highest(high, majorPer) // Major period high
L = ta.lowest(low, majorPer) // Major period low
h = ta.highest(high, minorPer) // Minor period high
l = ta.lowest(low, minorPer) // Minor period low
float pdiv = not na(L) ? l - L : 0 // Positive divergence (low vs major low)
float ndiv = not na(H) ? H - h : 0 // Negative divergence (major high vs high)
float divisor = pdiv + ndiv
dctiValue = divisor == 0 ? 0 : 100 * ((pdiv - ndiv) / divisor) // Normalized to -100 to +100 range
sigValue = ta.ema(dctiValue, sigPer)
DCTI provides a complementary structural perspective on market trends by quantifying the relationship between short-term and long-term price extremes. This creates a multi-dimensional analysis framework that combines adaptive deviation measurement (fuzzy SMA) with channel-based trend intensity confirmation (DCTI).
Multi-Dimensional Fuzzy Input Variables
FibonacciFlux processes four distinct technical dimensions through its fuzzy system:
Normalized SMA Deviation: Measures price displacement relative to historical volatility context
Rate of Change (ROC): Captures price momentum over configurable timeframes
Relative Strength Index (RSI): Evaluates cyclical overbought/oversold conditions
Donchian Channel Trend Intensity (DCTI): Provides structural trend confirmation through channel analysis
Each dimension is processed through comprehensive fuzzy sets that transform crisp numerical values into linguistic variables:
// Normalized SMA Deviation - Self-calibrating to volatility regimes
ndiff_LP := fuzzy_triangle(normalized_diff, norm_scale * 0.3, norm_scale * 0.7, norm_scale * 1.1)
ndiff_SP := fuzzy_triangle(normalized_diff, norm_scale * 0.05, norm_scale * 0.25, norm_scale * 0.5)
ndiff_NZ := fuzzy_triangle(normalized_diff, -norm_scale * 0.1, 0.0, norm_scale * 0.1)
ndiff_SN := fuzzy_triangle(normalized_diff, -norm_scale * 0.5, -norm_scale * 0.25, -norm_scale * 0.05)
ndiff_LN := fuzzy_triangle(normalized_diff, -norm_scale * 1.1, -norm_scale * 0.7, -norm_scale * 0.3)
// DCTI - Structural trend measurement
dcti_SP := fuzzy_triangle(dcti_val, 60.0, 85.0, 101.0) // Strong Positive Trend (> ~85)
dcti_WP := fuzzy_triangle(dcti_val, 20.0, 45.0, 70.0) // Weak Positive Trend (~30-60)
dcti_Z := fuzzy_triangle(dcti_val, -30.0, 0.0, 30.0) // Near Zero / Trendless (~+/- 20)
dcti_WN := fuzzy_triangle(dcti_val, -70.0, -45.0, -20.0) // Weak Negative Trend (~-30 - -60)
dcti_SN := fuzzy_triangle(dcti_val, -101.0, -85.0, -60.0) // Strong Negative Trend (< ~-85)
Advanced Fuzzy Rule System with DCTI Confirmation
The core intelligence of FibonacciFlux lies in its sophisticated fuzzy rule system – a structured knowledge representation that encodes expert understanding of market dynamics:
// Base Trend Rules with DCTI Confirmation
cond1 = math.min(ndiff_LP, roc_HP, rsi_M)
strength_SB := math.max(strength_SB, cond1 * (dcti_SP > 0.5 ? 1.2 : dcti_Z > 0.1 ? 0.5 : 1.0))
// DCTI Override Rules - Structural trend confirmation with momentum alignment
cond14 = math.min(ndiff_NZ, roc_HP, dcti_SP)
strength_SB := math.max(strength_SB, cond14 * 0.5)
The rule system implements 15 distinct fuzzy rules that evaluate various market conditions including:
Established Trends: Strong deviations with confirming momentum and DCTI alignment
Emerging Trends: Early deviation patterns with initial momentum and DCTI confirmation
Weakening Trends: Divergent signals between deviation, momentum, and DCTI
Reversal Conditions: Counter-trend signals with DCTI confirmation
Neutral Consolidations: Minimal deviation with low momentum and neutral DCTI
A key innovation is the weighted influence of DCTI on rule activation. When strong DCTI readings align with other indicators, rule strength is amplified (up to 1.2x). Conversely, when DCTI contradicts other indicators, rule impact is reduced (as low as 0.5x). This creates a dynamic, self-adjusting system that prioritizes high-conviction signals.
Defuzzification & Signal Generation
The final step transforms fuzzy outputs into a precise trend score through center-of-gravity defuzzification:
// Defuzzification with precise floating-point handling
denominator = strength_SB + strength_WB + strength_N + strength_WBe + strength_SBe
if denominator > 1e-10
fuzzyTrendScore := (strength_SB * STRONG_BULL + strength_WB * WEAK_BULL +
strength_N * NEUTRAL + strength_WBe * WEAK_BEAR +
strength_SBe * STRONG_BEAR) / denominator
The resulting FuzzyTrendScore ranges from -1.0 (Strong Bear) to +1.0 (Strong Bull), with critical threshold zones at ±0.3 (Weak trend) and ±0.7 (Strong trend). The histogram visualization employs intuitive color-coding for immediate trend assessment.
Strategic Applications for Institutional Trading
FibonacciFlux provides substantial advantages for sophisticated trading operations:
Multi-Timeframe Signal Confirmation: Institutional-grade signal validation across multiple technical dimensions
Trend Strength Quantification: Precise measurement of trend conviction with noise filtration
Early Trend Identification: Detection of emerging trends before traditional indicators through fuzzy pattern recognition
Adaptive Market Regime Analysis: Self-calibrating analysis across varying volatility environments
Algorithmic Strategy Integration: Well-defined numerical output suitable for systematic trading frameworks
Risk Management Enhancement: Superior signal fidelity for risk exposure optimization
Customization Parameters
FibonacciFlux offers extensive customization to align with specific trading mandates and market conditions:
Fuzzy SMA Settings: Configure baseline trend identification parameters including SMA, ROC, and RSI lengths
Normalization Settings: Fine-tune the self-calibration mechanism with adjustable lookback period, percentile rank, and optional clamping
DCTI Parameters: Optimize trend structure confirmation with adjustable major/minor periods and signal smoothing
Visualization Controls: Customize display transparency for optimal chart integration
These parameters enable precise calibration for different asset classes, timeframes, and market regimes while maintaining the core analytical framework.
Implementation Notes
For optimal implementation, consider the following guidance:
Higher timeframes (4H+) benefit from increased normalization lookback (800+) for stability
Volatile assets may require adjusted clamping values (2.5-4.0) for optimal signal sensitivity
DCTI parameters should be aligned with chart timeframe (higher timeframes require increased major/minor periods)
The indicator performs exceptionally well as a trend filter for systematic trading strategies
Acknowledgments
FibonacciFlux builds upon the pioneering work of Donovan Wall in Donchian Channel Trend Intensity analysis. The normalization approach draws inspiration from percentile-based statistical techniques in quantitative finance. This indicator is shared for educational and analytical purposes under Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license.
Past performance does not guarantee future results. All trading involves risk. This indicator should be used as one component of a comprehensive analysis framework.
Shout out @DonovanWall
IWMA - DolphinTradeBot1️⃣ WHAT IS IT ?
▪️ The Inverted Weighted Moving Average (IWMA) is the reversed version of WMA, where older prices receive higher weights, while recent prices receive lower weights. As a result, IWMA focuses more on past price movements while reducing sensitivity to new prices.
2️⃣ HOW IS IT WORK ?
🔍 To understand the IWMA(Inverted Weighted Moving Average) indicator, let's first look at how WMA (Weighted Moving Average) is calculated.
LET’S SAY WE SELECTED A LENGTH OF 5, AND OUR CURRENT CLOSING VALUES ARE .
▪️ WMA Calculation Method
When calculating WMA, the most recent price gets the highest weight, while the oldest price gets the lowest weight.
The Calculation is ;
( 10 ×1)+( 12 ×2)+( 21 ×3)+( 24 ×4)+( 38 ×5) = 10+24+63+96+190 = 383
1+2+3+4+5 = 15
WMA = 383/15 ≈ 25.53
WMA = ta.wma(close,5) = 25.53
▪️ IWMA Calculation Method
The Inverted Weighted Moving Average (IWMA) is the reversed version of WMA, where older prices receive higher weights, while recent prices receive lower weights. As a result, IWMA focuses more on past price movements while reducing sensitivity to new prices.
The Calculation is ;
( 10 ×5)+( 12 ×4)+( 21 ×3)+( 24 ×2)+( 38 ×1) = 50+48+63+48+38 = 247
1+2+3+4+5 = 15
IWMA = 247/15 ≈ 16.46
IWMA = iwma(close,5) = 16.46
3️⃣ SETTINGS
in the indicator's settings, you can change the length and source used for calculation.
With the default settings, when you first add the indicator, only the iwma will be visible. However, to observe how much it differs from the normal wma calculation, you can enable the "show wma" option to see both indicators with the same settings or you can enable the Show Signals to see IWMA and WMA crossover signals .
4️⃣ 💡 SOME IDEAS
You can use the indicator for support and resistance level analysis or trend analysis and reversal detection with short and long moving averages like regular moving averages.
Another option is to consider whether the iwma is above or below the normal wma or to evaluate the crossovers between wma and iwma.
db.Volume Spike IndicatorAn indicator that finds the average volume of the previous 10 candles and compares it with the volume of the last closed candle. If the volume of the last candle is 5 times the average of the last 10 candles, it marks this candle with a yellow symbol above or below the candle, depending on the direction of the candle.
=====
Индикатор, который находит среднее значение объём предыдущих 10 свечей и сравнивает его с объёмом последней закрытой свечи. Если объём последней свечи в 5 раз больше среднего за последние 10, то помечает эту свечу жёлтым символом над или под свечой в зависимости от направления свечи.
BTCUSD with adjustable sl,tpThis strategy is designed for swing traders who want to enter long positions on pullbacks after a short-term trend shift, while also allowing immediate short entries when conditions favor downside movement. It combines SMA crossovers, a fixed-percentage retracement entry, and adjustable risk management parameters for optimal trade execution.
Key Features:
✅ Trend Confirmation with SMA Crossover
The 10-period SMA crossing above the 25-period SMA signals a bullish trend shift.
The 10-period SMA crossing below the 25-period SMA signals a bearish trend shift.
Short trades are only taken if the price is below the 150 EMA, ensuring alignment with the broader trend.
📉 Long Pullback Entry Using Fixed Percentage Retracement
Instead of entering immediately on the SMA crossover, the strategy waits for a retracement before going long.
The pullback entry is defined as a percentage retracement from the recent high, allowing for an optimized entry price.
The retracement percentage is fully adjustable in the settings (default: 1%).
A dynamic support level is plotted on the chart to visualize the pullback entry zone.
📊 Short Entry Rules
If the SMA(10) crosses below the SMA(25) and price is below the 150 EMA, a short trade is immediately entered.
Risk Management & Exit Strategy:
🚀 Take Profit (TP) – Fully customizable profit target in points. (Default: 1000 points)
🛑 Stop Loss (SL) – Adjustable stop loss level in points. (Default: 250 points)
🔄 Break-Even (BE) – When price moves in favor by a set number of points, the stop loss is moved to break-even.
📌 Extra Exit Condition for Longs:
If the SMA(10) crosses below SMA(25) while the price is still below the EMA150, the strategy force-exits the long position to avoid reversals.
How to Use This Strategy:
Enable the strategy on your TradingView chart (recommended for stocks, forex, or indices).
Customize the settings – Adjust TP, SL, BE, and pullback percentage for your risk tolerance.
Observe the plotted retracement levels – When the price touches and bounces off the level, a long trade is triggered.
Let the strategy manage the trade – Break-even protection and take-profit logic will automatically execute.
Ideal Market Conditions:
✅ Trending Markets – The strategy works best when price follows strong trends.
✅ Stocks, Indices, or Forex – Can be applied across multiple asset classes.
✅ Medium-Term Holding Period – Suitable for swing trades lasting days to weeks.
Equity Curve with Trend Indicator (Long & Short) - SimulationOverview:
Market Regime Detector via Virtual Equity Curve is a unique indicator that simulates the performance of a trend-following trading system—incorporating both long and short trades—to help you identify prevailing market regimes. By generating a “virtual equity” curve based on simple trend signals and applying trend analysis directly on that curve, this indicator visually differentiates trending regimes from mean-reverting (or sideways) periods. The result is an intuitive display where green areas indicate a trending (bullish) regime (i.e., where trend-following strategies are likely to perform well) and red areas indicate a mean-reverting (bearish) regime.
Features:
Simulated Trade Performance:
Uses a built-in trend-following logic (a simple 10/50 SMA crossover example) to simulate both long and short trades. This simulation creates a virtual equity curve that reflects the cumulative performance of the system over time.
Equity Trend Analysis:
Applies an Exponential Moving Average (EMA) to the simulated equity curve to filter short-term noise. The EMA acts as a trend filter, enabling the indicator to determine if the equity curve is in an upward (trending) or downward (mean-reverting) phase.
Dynamic Visual Regime Detection:
Fills the area between the equity curve and its EMA with green when the equity is above the EMA (indicating a healthy trending regime) and red when below (indicating a mean-reverting or underperforming regime).
Customizable Parameters:
Easily adjust the initial capital, the length of the equity EMA, and other settings to tailor the simulation and visual output to your trading style and market preferences.
How It Works:
Trade Simulation:
The indicator generates trading signals using a simple SMA crossover:
When the 10-period SMA is above the 50-period SMA, it simulates a long entry.
When the 10-period SMA is below the 50-period SMA, it simulates a short entry. The virtual equity is updated bar-by-bar based on these simulated positions.
Equity Trend Filtering:
An EMA is calculated on the simulated equity curve to smooth out fluctuations. The relative position of the equity curve versus its EMA is then used as a proxy for the market regime:
Bullish Regime: Equity is above its EMA → fill area in green.
Bearish Regime: Equity is below its EMA → fill area in red.
Visualization:
The indicator plots:
A gray line representing the simulated equity curve.
An orange line for the EMA of the equity curve.
A dynamic fill between the two lines, colored green or red based on the prevailing regime.
Inputs & Customization:
Initial Capital: Set your starting virtual account balance (default: 10,000 USD).
Equity EMA Length: Specify the lookback period for the EMA applied to the equity curve (default: 30).
Trend Signal Logic:
The current implementation uses a simple SMA crossover for demonstration purposes. Users can modify or replace this logic with their own trend-following indicator to tailor the simulation further.
Smart Scalper Indicator🎯 How the Smart Scalper Indicator Works
1. EMA (Exponential Moving Average)
EMA 10 (Blue Line):
Shows the short-term trend.
If the price is above this line, the trend is bullish; if below, bearish.
EMA 20 (Orange Line):
Displays the longer-term trend.
If EMA 10 is above EMA 20, it indicates a bullish trend (Buy signal).
2. SuperTrend
Green Line:
Represents support levels.
If the price is above the green line, the market is considered bullish.
Red Line:
Represents resistance levels.
If the price is below the red line, the market is considered bearish.
3. VWAP (Volume Weighted Average Price)
Purple Line:
Indicates the average price considering volume.
If the price is above the VWAP, the market is strong (Buy signal).
If the price is below the VWAP, the market is weak (Sell signal).
4. ATR (Average True Range)
Used to measure market volatility.
An increasing ATR indicates higher market activity, enhancing the reliability of signals.
ATR is not visually displayed but is factored into the signal conditions.
⚡ Entry Signals
Green Up Arrow (Buy):
EMA 10 is above EMA 20.
The price is above the SuperTrend green line.
The price is above the VWAP.
Volatility (ATR) is increasing.
Red Down Arrow (Sell):
EMA 10 is below EMA 20.
The price is below the SuperTrend red line.
The price is below the VWAP.
Volatility (ATR) is increasing.
🔔 Alerts
"Buy Alert" — Notifies when a Buy condition is met.
"Sell Alert" — Notifies when a Sell condition is met.
✅ How to Use the Indicator:
Add the indicator to your TradingView chart.
Enable alerts to stay updated on signal triggers.
Check the signal:
A green arrow suggests a potential Buy.
A red arrow suggests a potential Sell.
Set Stop-Loss:
Below the SuperTrend line or based on ATR levels.
Take Profit:
Target 1-2% for short-term trades.
US Yield Curve (2-10yr)US Yield Curve (2-10yr) by oonoon
2-10Y US Yield Curve and Investment Strategies
The 2-10 year US Treasury yield spread measures the difference between the 10-year and 2-year Treasury yields. It is a key indicator of economic conditions.
Inversion (Spread < 0%): When the 2-year yield exceeds the 10-year yield, it signals a potential recession. Investors may shift to long-term bonds (TLT, ZROZ), gold (GLD), or defensive stocks.
Steepening (Spread widening): A rising 10-year yield relative to the 2-year suggests economic expansion. Investors can benefit by shorting bonds (TBT) or investing in financial stocks (XLF). The Amundi US Curve Steepening 2-10Y ETF can be used to profit from this trend.
Monitoring the curve: Traders can track US10Y-US02Y on TradingView for real-time insights and adjust portfolios accordingly.
Vertical Lines at Specific Times### **Script Description**
This **Pine Script v6** indicator for **TradingView** plots **vertical dotted lines** at user-specified times, marking key time ranges during the day. It is designed to help traders visually track market movements within specific timeframes.
#### **Features:**
✔ **Custom Timeframes:**
- Two separate time ranges can be defined:
- **Morning Session:** (Default: 9 AM - 10 AM, New York Time)
- **Evening Session:** (Default: 9 PM - 10 PM, New York Time)
✔ **Adjustable Line Properties:**
- **Line Width:** Users can change the thickness of the vertical lines.
- **Line Colors:** Users can select different colors for morning and evening session lines.
✔ **New York Local Time Support:**
- Ensures that the vertical lines appear correctly based on **Eastern Time (ET)**.
✔ **Full-Height Vertical Lines:**
- Lines extend across the **entire chart**, from the highest high to the lowest low, for clear visibility.
- Uses **dotted line style** to avoid cluttering the chart.
#### **How It Works:**
1. The script retrieves the **current date** (year, month, day) in **New York time**.
2. Converts the **user-defined input times** into **timestamps** for accurate placement.
3. When the current time matches a specified session time, a **dotted vertical line** is drawn.
4. The script **repeats this process daily**, ensuring automatic updates.
#### **Customization Options (Inputs):**
- **Morning Start & End Time** (Default: 9 AM - 10 AM)
- **Evening Start & End Time** (Default: 9 PM - 10 PM)
- **Line Width** (Default: 2)
- **Morning Line Color** (Default: Blue)
- **Evening Line Color** (Default: Green)
#### **Use Case Scenarios:**
📈 Marking market **open & close** hours.
📊 Highlighting **key trading sessions** for day traders.
🔎 Identifying time-based **price action patterns**.
Enhanced Volume Profile█ OVERVIEW
The Enhanced Volume Profile (EVP) is an indicator designed to plot a volume profile on the chart based on either the visible chart range or a fixed lookback period. The script helps analyze the distribution of volume at different price levels over time, providing insights into areas of high trading activity and potential support/resistance zones.
█ KEY FEATURES
1. Visible Chart Range vs. Fixed Lookback Depth
Visible Chart Range
- Default analysis mode
- Calculates profile based on visible portion of the chart
- Dynamically updates with chart view changes
Fixed Lookback Depth
- Optional alternative to visible range
- Uses specified number of bars (10-3000)
- Provides consistent analysis depth
- Independent of chart view
2. Custom Resolution
Auto-Resolution Mode
Automatically selects timeframes based on chart's current timeframe:
≤ 1 minute: Uses 1-minute resolution
≤ 5 minutes: Uses 1-minute resolution
≤ 15 minutes: Uses 5-minute resolution
≤ 1 hour: Uses 5-minute resolution
≤ 4 hours: Uses 15-minute resolution
≤ 12 hours: Uses 15-minute resolution
≤ 1 day: Uses 1-hour resolution
≤ 3 days: Uses 2-hours resolution
≤ 1 week: Uses 4-hours resolution
Custom Resolution Override
Optional override of auto-resolution system
Provides control over data granularity
Must be lower than or equal to chart's timeframe
Falls back to auto-resolution if validation fails
3. Volume Profile Resolution
Adjustable number of points (10-400)
Controls profile granularity
Higher resolution provides more detail
Balance between precision and performance
4. Point of Control (PoC)
Identifies price level with highest traded volume
Optional display with customizable appearance
Adjustable line thickness (1-30)
Configurable color
5. Value Area (VA)
Shows price range of majority trading volume
Adjustable coverage (5-95%), default is 68%
Customizable boundary lines
Configurable lines color and thickness (1-20)
█ INPUT PARAMETERS
Lookback Settings
Use Visible Chart Range
- Default: true
- Calculates profile based on visible bars
- Ideal for focused analysis
Fixed Lookback Bars
- Range: 10-3000
- Default: 200
- Used when visible range is disabled
Resolution Settings
Enable Custom Resolution
- Default: false
- Overrides auto-resolution
Custom Resolution
- Default: 1-minute
- Changes automatically when "Enable Custom Resolution" is disabled
Volume Profile Appearance
Profile Resolution
- Range: 10-400
- Default: 200
- Controls detail level
Profile Width Scale
- Range: 1-50
- Default: 15
- Adjusts profile width
Right Offset
- Range: 0-500
- Default: 20
- Controls spacing from price bars
Profile Fill Color
- Default: #5D606B (70% transparency)
Point of Control Settings
Show Point of Control
- Default: true
- Toggles PoC visibility
PoC Line Thickness
- Range: 1-30
- Default: 1
PoC Line Color
- Default: Red
Value Area Settings
Show Value Area
- Default: true
- Toggles VA lines
Value Area Coverage
- Range: 5-95%
- Default: 68%
Value Area Line Color
- Default: Blue
Value Area Line Thickness
- Range: 1-20
- Default: 1
█ TECHNICAL IMPLEMENTATION DETAILS
Exceeding Bars Management
The script dynamically adjusts the number of bars used in the volume profile calculation based on the selected timeframe and the maximum allowed bars (max_bars_back).
If the total number of bars exceeds the predefined threshold (6000 bars), the script reduces the lookback period (lookback_bars) by trimming some of the historical data, ensuring the chart does not become overloaded with data.
The adjustment is made based on the ratio of bars per candle (bars_per_candle), ensuring that the volume profile remains computationally efficient while maintaining its relevance.
█ EXAMPLE USE CASES
1. Visible Range Mode
For analyzing a recent trend and focusing on only the visible part of the chart, enabling the "Use Visible Chart Range" option calculates the profile based on the current view, without considering historical data outside the visible area.
2. Fixed Lookback Depth
For analyzing a specific period in the past (e.g., the last 200 bars), disabling the visible range and setting a fixed lookback depth of 200 bars ensures the profile always considers the last 200 bars, regardless of the visible range.
3. Custom Resolution
If there’s a need for greater control over the timeframe used for volume profile calculations (e.g., using a 5-minute resolution on a 15-minute chart), enabling custom resolution and setting the desired timeframe provides this control.
HAPPY TRADING ✌️
The Final Countdown//Credit to ©SamRecio for the original indicator that this is based on, which is called, "HTF Bar Close Countdown".
Here are the key differences between the two indicators (That a user would care about):
1.) 10 timeframe slots (double the original number).
2.) Many more timeframe options ('1', '3', '5', '10', '15', '30', '45', '1H', '2H', '4H', '6H', '8H', '12H', 'D', 'W').
3.) Ability to structure timeframes however you want (Higher up top descending, vice versa, or just randomly.).
4.) Support for hour-based timeframes (1H, 2H, etc.).
5.) Displays minutes as numbers, hours with a number followed by H (ex. 1H), and anything above with a letter (D for day, W for week).
6.) Dynamic colors based on remaining time percentage (green->yellow->red) with two user-defined thresholds.
7.) Alerts for when timeframes are close to closing (yellow->red).
8.) More granular timeframe selection options.
9.) Background colors for an additional visual alert.
------Colors background the selected color for each timeframe (Default is all timeframes are blue with 80% transparency).
------This does not repaint, so the color will persist once the red condition is over.
------As soon as you leave the timeframe though, it will be erased and the new timeframe will begin tracking red conditions.
------It always starts from the current bar, so it is not applicable to historical bars unless you leave it running for an extended period of time.
------Do note that since this is not actual paint or colored pencils, the colors do not blend.
------The most recent timeframe to enter a red condition will be the background that you see unless you leave the timeframe and return.
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Now for the description and instructions....
IT'S THE FINAL COUNTDOWN!
This indicator helps shorter-timeframe traders track multiple timeframe closings simultaneously, providing visual, audio and notification alerts when bars are nearing their close. It's particularly useful for traders who want to prepare for potential price action around bar closings across different timeframes. If you're a HODL till you're broke kind of trader, you don't need this.
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Multi-Timeframe Tracking
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- Monitors up to 10 different timeframes simultaneously
- Supports various timeframes from 1 minute to weekly (1m, 3m, 5m, 10m, 15m, 30m, 45m, 1H, 2H, 4H, 6H, 8H, 12H, Daily, Weekly)
- Timeframes can be arranged in any order (ascending, descending, or custom)
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Visual Display
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- Shows a countdown timer for each selected timeframe
- Dynamic color changes based on time remaining:
Green: More than 15% of bar time remaining
Yellow: Between 15% and 5% remaining
Red: Less than 5% remaining
- Customizable background colors appear when timeframes enter their red zone
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Alert System
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- Built-in alerts trigger when any timeframe enters its red zone
- Each timeframe can have its alerts toggled independently
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- Setup Instructions -
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Timeframe Selection
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- Choose up to 10 timeframes to monitor
- Each timeframe has its own toggle switch to turn it on/off
- Default configuration starts from 5m and goes up to 12H
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Visual Customization
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- Adjust the table size, position
- Customize frame and border colors
- Modify the yellow and red threshold percentages
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Background Color Settings
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- Enable/disable background colors for each timeframe
- Choose custom colors for each timeframe's background
- Default setting is blue (with a fixed 80% transparency)
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Usage Tips
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- Use the countdown table to prepare for multiple timeframe closes as big moves (especially reversals) tend to begin come after higher timeframe changes (sometimes to the second).
- Watch for color changes to anticipate important closing periods to avoid getting trapped in bad trade (please always use stop losses if trading, in general).
- Set up alerts for critical timeframes that require immediate attention (2H, 4H, etc.).
- Use background colors as an additional visual cue for timeframe closes.
- Position the table where it won't interfere with your chart analysis.
BBSS+This Pine Script implements a custom indicator overlaying Bollinger Bands with additional features for trend analysis using Exponential Moving Averages (EMAs). Here's a breakdown of its functionality:
Bollinger Bands:
The script calculates the Bollinger Bands using a 20-period Simple Moving Average (SMA) as the basis and a multiplier of 2 for the standard deviation.
It plots the Upper Band and Lower Band in red.
EMA Calculations:
Three EMAs are calculated for the close price with periods of 5, 10, and 40.
The EMAs are plotted in green (5-period), cyan (10-period), and orange (40-period) to distinguish between them.
Trend Detection:
The script determines bullish or bearish EMA alignments:
Bullish Order: EMA 5 > EMA 10 > EMA 40.
Bearish Order: EMA 5 < EMA 10 < EMA 40.
Entry Signals:
Long Entry: Triggered when:
The close price crosses above the Upper Bollinger Band.
The Upper Band is above its 5-period SMA (indicating momentum).
The EMAs are in a bullish order.
Short Entry: Triggered when:
The close price crosses below the Lower Bollinger Band.
The Lower Band is below its 5-period SMA.
The EMAs are in a bearish order.
Trend State Tracking:
A variable tracks whether the market is in a Long or Short trend based on conditions:
A Long trend continues unless conditions for a Short Entry are met or the Upper Band dips below its average.
A Short trend continues unless conditions for a Long Entry are met or the Lower Band rises above its average.
Visual Aids:
Signal Shapes:
Triangle-up shapes indicate Long Entry points below the bar.
Triangle-down shapes indicate Short Entry points above the bar.
Bar Colors:
Green bars indicate a Long trend.
Red bars indicate a Short trend.
This script combines Bollinger Bands with EMA crossovers to generate entry signals and visualize market trends, making it a versatile tool for identifying momentum and trend reversals.
