Equal Highs/Lows Multi-Pivot [Julio]Equal Highs/Lows Multi-Pivot
Description
A sophisticated multi-timeframe pivot analysis tool that detects and highlights equal highs and equal lows across four different pivot lengths simultaneously. This indicator identifies price levels where the market creates identical extremes, a powerful signal of institutional support/resistance and potential reversal or breakout zones.
How It Works
Four Independent Pivot Streams
Pivot 1 (Intraday - 2 bars): Ultra-fast level detection for scalpers
Pivot 2 (Session - 4 bars): Short-term swing levels
Pivot 3 (Daily - 6 bars): Medium-term structural levels
Pivot 4 (Weekly - 9 bars): Long-term institutional levels
Equal High (EQH) Detection
Compares consecutive swing highs and draws a line when two highs are nearly identical within a defined threshold. The indicator uses ATR-based confluence to determine "equality," filtering out noise while catching true market structure.
Equal Low (EQL) Detection
Same logic applied to swing lows, identifying support zones where price repeatedly fails to break below previous lows.
Key Features
Four Simultaneous Timeframes: Analyze intraday, session, daily, and weekly structures all on one chart
ATR-Based Confluence Threshold: Automatically adjusts sensitivity based on current volatility (no fake signals)
Color-Coded Levels: Each pivot length has distinct colors for instant visual identification
Highs: Red, Orange, Yellow, Fuchsia
Lows: Green, Blue, Aqua, Purple
Confirmation Mode: Optional setting to wait for full pivot confirmation before marking levels
Customizable Alert Zones: Toggle individual pivot lengths on/off to reduce clutter
Smart Label Positioning: Labels auto-center between the two equal pivots for clarity
Ideal For
Swing traders tracking support/resistance across multiple timeframes
Scalpers identifying micro-structure for quick entries and exits
Market structure analysts studying institutional price action patterns
Multi-timeframe traders needing confluence from intraday to weekly levels
Anyone trading 1-minute to 4-hour charts
Trading Applications
Identify strong support/resistance zones: Equal levels = confirmed institutional levels
Confirm trend reversals: Multiple equal lows = strong accumulation zone; multiple equal highs = distribution
Plan entries with precision: Enter near equal levels for higher probability setups
Detect liquidity concentration: Where price repeatedly tests the same level
Multi-timeframe confluence: Look for equal levels across multiple pivot lengths for ultra-strong zones
How to Use
Identify the equal levels: Color-coded lines instantly show where price creates matching extremes
Check for confluence: Strong setups occur where multiple pivot lengths align
Wait for price action: Watch for breakouts through equal levels or reversals at these zones
Enter with structure: Use equal levels as entry/exit triggers combined with your trading methodology
Manage with confidence: These levels mark institutional decision points
Customization Options
Adjust pivot lengths to match your preferred timeframe structure
Set ATR threshold sensitivity (lower = stricter equality, higher = more signals)
Toggle confirmation mode for additional filter
Enable/disable individual pivot streams to reduce visual clutter
Customize colors to match your chart theme
Default Settings Optimized For
NASDAQ futures and liquid forex pairs
Intraday and swing trading (1-minute to 4-hour charts)
Smart Money / ICT trading methodologies
Volatility-adjusted confluence detection
"support resistance"に関するスクリプトを検索
Asia & London Session Boxes (NY Time) + 4H SwingsAsia & London Session Boxes + 4H Swings
Description
A multi-timeframe session analysis tool designed for forex and futures traders operating on NY time. This indicator visualizes major trading sessions with automatic high/low range boxes while simultaneously tracking 4-hour swing levels, giving you a complete picture of institutional trading activity and key price levels.
How It Works
Session Boxes (NY Time Zone)
Asia Session (20:00 – 00:00 NY): Blue-shaded box marking the complete range from open to close
London Session (02:00 – 06:00 NY): Yellow-shaded box capturing the high-volatility London open
Each session box automatically records the highest high and lowest low during that timeframe, providing instant reference for session extremes and potential supply/demand zones.
4-Hour Swing Levels
Detects swing highs and lows on a 30-minute timeframe for ultra-responsive level identification
Red lines: Swing highs (resistance levels)
Green lines: Swing lows (support levels)
Lines extend to the right for continuous monitoring
Auto-removes touched levels: When price breaches a swing, it automatically deletes that level to keep your chart clean and focused on active levels
Key Features
Session-Based Trading Analysis: Identify which session created important price levels and ranges
Multi-Timeframe Architecture: Analyzes 30-minute swings while tracking 4-hour patterns on your current chart
Smart Level Cleanup: Touched swings automatically remove themselves, eliminating clutter
NY Time Conversion: All times automatically adjust to your NY timezone for consistency
Institutional Perspective: View exactly where institutions are trading during major session hours
Zero Lag Detection: Real-time identification of swing extremes
Ideal For
Forex traders (especially EUR/USD, GBP/USD) targeting session breakouts
Scalpers and swing traders needing precise support/resistance levels
Market structure traders analyzing institutional price action
Session traders looking to trade Asia/London opens
1-minute to 4-hour timeframe charts
Trading Applications
Trade Asia session breakouts into London
Identify liquidity zones from previous sessions
Detect swing extremes for entry/exit planning
Confirm trend direction using multi-session structure
Find support/resistance on intraday pullbacks
Default Settings Optimized For
NASDAQ futures and forex pairs
Scalping and short-term swing trading
NY timezone trading (automatically converts UTC-4)
30-minute swing detection for precise level identification
Simulateur Carnet d'Ordres & Liquidité [Sese] - Custom🔹 Indicator Name
Order Book & Liquidity Simulator - Custom
🔹 Concept and Functionality
This indicator is a technical analysis tool designed to visually simulate market depth (Order Book) and potential liquidity zones.
It is important to adhere to TradingView's transparency rules: This script does not access real Level 2 data (the actual exchange order book). Instead, it uses a deductive algorithm based on historical Price Action to estimate where Buy Limit (Bid) and Sell Limit (Ask) orders might be resting.
Methodology used by the script:
Pivot Detection: The indicator scans for significant Swing Highs and Swing Lows over a user-defined lookback period (Length).
Level Projection: These pivots are projected to the right as horizontal lines.
Red Lines (Ask): Represent potential resistance zones (sellers).
Blue Lines (Bid): Represent potential support zones (buyers).
Liquidity Management (Absorption): The script is dynamic. If the current price crosses a line, the indicator assumes the liquidity at that level has been consumed (orders filled). The line is then automatically deleted from the chart.
Density Profile (Right Side): Horizontal bars appear to the right of the current price. These approximate a "Time Price Opportunity" or Volume Profile, showing where the market has spent the most time recently.
🔹 User Manual (Settings)
Here is how to configure the inputs to match your trading style:
1. Detection Algorithm
Lookback Length (Candles): Determines the sensitivity of the pivots.
Low value (e.g., 10): Shows many lines (scalping/short term).
High value (e.g., 50): Shows only major structural levels (swing trading).
Volume Factor: (Technical note: In this specific code version, this variable is calculated but the lines are primarily drawn based on geometric pivots).
2. Visual Settings
Show Price Lines (Bid/Ask): Toggles the horizontal Support/Resistance lines on or off.
Show Volume Profile: Toggles the heatmap-style bars on the right side of the chart.
Extend Lines: If checked, untouched lines will extend to the right towards the current price bar.
3. Colors and Transparency Management
Customize the aesthetics to keep your chart clean:
Bid / Ask Colors: Choose your base colors (Default is Blue and Red).
Line Transparency (%): Crucial for chart visibility.
0% = Solid, bright colors.
80-90% = Very subtle, faint lines (recommended if you overlay this on other tools).
Text Size: Adjusts the size of the price labels ("BUY LIMIT" / "SELL LIMIT").
🔹 How to Read the Indicator
Rejections: Unbroken lines act as potential walls. Watch for price reaction when approaching a blue line (support) or red line (resistance).
Breakouts/Absorption: When a line disappears, it means the level has been breached. The market may then seek the next liquidity level (the next line).
Density (Right-side boxes): More opaque/visible boxes indicate a price zone "accepted" by the market (consolidation). Empty gaps suggest an imbalance where price might move through quickly.
⚠️ Disclaimer
This script is for educational and technical analysis purposes only. It is a simulation based on price history, not real-time order book data. Past performance is not indicative of future results. Trading involves risk.
DANCE WITH WOLVES VN ALL TO 1DANCE WITH WOLVES VN is a smart-money volume indicator designed for stocks and crypto.
Main features:
• logic to detect Distribution, No Demand, Absorption and Exhaustion.
• Automatically builds smart Support/Resistance zones from high-volume price leaders.
• Regression trend channel to see the short-term trend and trading range.
• Dashboard table that shows the top high/low price bars with buy/sell volume and group labels.
• Alert conditions for Breakout above resistance and At Support Area so you don’t need to watch the chart all the time.
You can use it on any symbol and timeframe. Just add the script to your chart and follow the zones (red = resistance, green = support) together with the P/L labels and the status line.
Vietnamese note: Indicator dùng volume + để vẽ vùng hỗ trợ/kháng cự thông minh, label phân phối / hấp thụ / cạn lực bán và kênh xu hướng. Dùng được cho cả stock và crypto. tot nhat dung khung 5 den 15 phut
Symmetrical Geometric MandalaSymmetrical Geometric Mandala
Overview
The Symmetrical Geometric Mandala is an advanced geometric trading tool that applies phi (φ) harmonic relationships to price-time analysis. This indicator automatically detects swing ranges and constructs a scale-invariant geometric framework based on the square root of phi (√φ), revealing natural support/resistance zones and harmonic price-time balance points.
Core Concept
Traditional technical analysis often treats price and time as separate dimensions. This indicator harmonizes them using the mathematical constant √φ (approximately 1.272), creating a geometric "squaring" of price and time that remains proportionally consistent across different chart scales.
The Mathematics
When you select a price range (from swing low to swing high or vice versa), the indicator calculates:
PBR (Price-to-Bar Ratio) = Range / Number of Bars
Harmonic PBR = PBR × √φ (1.272019649514069)
Phi Extension = Range × φ (1.618033988749895)
The Harmonic PBR is the critical value - this is the chart scaling factor that creates perfect geometric harmony between price and time for your selected range.
Visual Components
1. Horizontal Boundary Lines
Two horizontal lines extend from the selected range at a distance of Range × φ (golden ratio extension):
Upper line: Extended above the swing high (for uplegs) or swing low (for downlegs)
Lower line: Extended below the swing low (for uplegs) or swing high (for downlegs)
These lines mark the natural harmonic boundaries of the price movement.
2. Rectangle Diagonal Lines
Two diagonal lines that create a "rectangle" effect, connecting:
Overlap points on horizontal boundaries to swing extremes
These lines go in the opposite direction of the price leg (creating the symmetrical mandala pattern)
When extended, they reveal future geometric support/resistance zones
3. Phi Harmonic Circles (Optional)
Two precisely calculated circles (drawn as smooth polylines):
Circle A: Centered at the first swing extreme (Nodal A)
Circle B: Centered at the second swing extreme (Nodal B)
Radius = Range × φ, causing them to perfectly touch the horizontal boundary lines
These circles visualize the geometric harmony and create a mandala-like pattern that reveals natural price zones.
How to Use
Step 1: Select Your Range
Set the Start Date at your swing low or swing high
Set the End Date at the opposite extreme
The indicator automatically detects whether it's an upleg or downleg
Step 2: Read the Harmonic PBR
Check the highlighted yellow row in the table: "PBR × √φ"
This is your chart scaling value
Step 3: Apply Chart Scaling (Optional)
For perfect geometric visualization:
Right-click on your chart's price axis
Select "Scale price chart only"
Enter the PBR × √φ value
The geometry will now display in perfect harmonic proportion
Step 4: Interpret the Geometry
Horizontal lines: Key support/resistance zones at phi extensions
Diagonal lines: Dynamic trend channels and future price-time balance points
Circle intersections: Natural harmonic turning points
Central diamond area: Core price-time equilibrium zone
Key Features
✅ Automatic swing detection - identifies upleg/downleg automatically
✅ Scale-invariant geometry - maintains proportions across timeframes
✅ Phi harmonic calculations - based on golden ratio mathematics
✅ Professional color scheme - clean, non-intrusive visuals
✅ Customizable display - toggle circles, lines, and table independently
✅ Smooth circle rendering - adjustable segments (16-360) for optimal smoothness
Settings
Show Horizontal Boundary Lines: Display phi extension levels
Show Rectangle Diagonal Lines: Display the geometric framework
Show Phi Harmonic Circles: Display circular geometry (optional)
Circle Smoothness: Adjust polyline segments (default: 96)
Colors: Fully customizable color scheme for all elements
Theory Background
This indicator draws inspiration from:
W.D. Gann's price-time squaring techniques
Bradley Cowan's geometric market analysis
Phi/golden ratio harmonic theory
Mathematical constants in market structure
Unlike traditional Fibonacci retracements, this tool uses √φ instead of φ as the primary scaling constant, creating a unique geometric relationship that "squares" price movement with time passage.
Best Practices
Use on significant swings - Works best on major swing highs/lows
Multiple timeframe analysis - Apply to different timeframes for confluence
Combine with other tools - Use alongside support/resistance and trend analysis
Respect the geometry - Pay attention when price interacts with geometric elements
Chart scaling optional - The geometry works at any scale, but scaling enhances visualization
Notes
The indicator draws geometry from left to right (from Nodal A to Nodal B)
All lines extend infinitely for future projections
The table shows real-time calculations for the selected range
Date range selection uses confirm dialogs to prevent accidental changes
The Trade Plan 9 & 15 EMA⭐ What Are EMAs?
An Exponential Moving Average (EMA) gives more weight to recent prices, making it more responsive than a simple moving average.
9-EMA = very fast, reacts quickly to price changes
15-EMA = slightly slower, smooths short-term noise
Together they help identify momentum shifts.
📈 How the 9/15 EMA Strategy Works
1. Buy Signal (Bullish Crossover)
You enter a long (buy) trade when:
➡ 9 EMA crosses above the 15 EMA
This suggests momentum is shifting upward and a new uptrend may be forming.
2. Sell Signal (Bearish Crossover)
You enter a short (sell) trade or exit long positions when:
➡ 9 EMA crosses below the 15 EMA
This suggests momentum is turning downward.
🔧 How Traders Typically Use It
Entry
Wait for a clear crossover.
Confirm with price closing on the same side of EMAs.
Some traders add confirmation using RSI, MACD, or support/resistance.
Exit
Several options:
Exit when the opposite crossover occurs.
Exit at predetermined risk-reward levels (e.g., 1:2).
Use trailing stop below/above EMAs.
👍 Strengths
Easy to follow
Good for fast-moving markets
Works well on trending markets
Minimal indicators needed
👎 Weaknesses
Whipsaws in sideways markets
Many false signals on very low timeframes
Works best with additional filters
🕒 Common Timeframes
Scalping: 1m, 5m
Day trading: 5m, 15m
Swing trading: 1H, 4H
SuperTrend Zone Rejection [STRZ] CONCEPT -
This indicator identifies trend-continuation setups by combining the Super Trend with dynamic Average True Range (ATR) value zones. It highlights specific price action behaviour's—specifically wick rejections and momentum closes—that occur during pullbacks into the trend baseline.
HOW IT WORKS -
The script operates on three logic gates:
>> Trend Filter: Uses a standard Super Trend (Factor 3, Period 10 default) to define market direction.
>> Dynamic Zones: Projects a volatility-based zone (default 2.0x ATR) above or below the Super Trend line to define a valid pullback area.
>> Signal Detection: Identifies specific candle geometries occurring within these zones.
>> Rejection: Candles with significant wicks testing the zone support/resistance.
>> Momentum: Candles that open within the zone and close in the upper/lower quartile of their range.
FEATURES -
>> Dynamic Channel: Visualizes the active buy/sell zone using a continuous, non-repainting box.
>> Volatile Filtering: Filters out low-volatility candles (doji's/noise) based on minimum ATR size.
>> Visuals: Color-coded trend visualization with distinct signal markers for qualified entries.
SETTINGS -
>> Super Trend: Adjustable Factor and ATR Period.
>> Zone Multiplier: Controls the width of the pullback zone relative to ATR.
>> Visuals: Customizable colours for zones and signals to fit light/dark themes.
Dimensional Resonance ProtocolDimensional Resonance Protocol
🌀 CORE INNOVATION: PHASE SPACE RECONSTRUCTION & EMERGENCE DETECTION
The Dimensional Resonance Protocol represents a paradigm shift from traditional technical analysis to complexity science. Rather than measuring price levels or indicator crossovers, DRP reconstructs the hidden attractor governing market dynamics using Takens' embedding theorem, then detects emergence —the rare moments when multiple dimensions of market behavior spontaneously synchronize into coherent, predictable states.
The Complexity Hypothesis:
Markets are not simple oscillators or random walks—they are complex adaptive systems existing in high-dimensional phase space. Traditional indicators see only shadows (one-dimensional projections) of this higher-dimensional reality. DRP reconstructs the full phase space using time-delay embedding, revealing the true structure of market dynamics.
Takens' Embedding Theorem (1981):
A profound mathematical result from dynamical systems theory: Given a time series from a complex system, we can reconstruct its full phase space by creating delayed copies of the observation.
Mathematical Foundation:
From single observable x(t), create embedding vectors:
X(t) =
Where:
• d = Embedding dimension (default 5)
• τ = Time delay (default 3 bars)
• x(t) = Price or return at time t
Key Insight: If d ≥ 2D+1 (where D is the true attractor dimension), this embedding is topologically equivalent to the actual system dynamics. We've reconstructed the hidden attractor from a single price series.
Why This Matters:
Markets appear random in one dimension (price chart). But in reconstructed phase space, structure emerges—attractors, limit cycles, strange attractors. When we identify these structures, we can detect:
• Stable regions : Predictable behavior (trade opportunities)
• Chaotic regions : Unpredictable behavior (avoid trading)
• Critical transitions : Phase changes between regimes
Phase Space Magnitude Calculation:
phase_magnitude = sqrt(Σ ² for i = 0 to d-1)
This measures the "energy" or "momentum" of the market trajectory through phase space. High magnitude = strong directional move. Low magnitude = consolidation.
📊 RECURRENCE QUANTIFICATION ANALYSIS (RQA)
Once phase space is reconstructed, we analyze its recurrence structure —when does the system return near previous states?
Recurrence Plot Foundation:
A recurrence occurs when two phase space points are closer than threshold ε:
R(i,j) = 1 if ||X(i) - X(j)|| < ε, else 0
This creates a binary matrix showing when the system revisits similar states.
Key RQA Metrics:
1. Recurrence Rate (RR):
RR = (Number of recurrent points) / (Total possible pairs)
• RR near 0: System never repeats (highly stochastic)
• RR = 0.1-0.3: Moderate recurrence (tradeable patterns)
• RR > 0.5: System stuck in attractor (ranging market)
• RR near 1: System frozen (no dynamics)
Interpretation: Moderate recurrence is optimal —patterns exist but market isn't stuck.
2. Determinism (DET):
Measures what fraction of recurrences form diagonal structures in the recurrence plot. Diagonals indicate deterministic evolution (trajectory follows predictable paths).
DET = (Recurrence points on diagonals) / (Total recurrence points)
• DET < 0.3: Random dynamics
• DET = 0.3-0.7: Moderate determinism (patterns with noise)
• DET > 0.7: Strong determinism (technical patterns reliable)
Trading Implication: Signals are prioritized when DET > 0.3 (deterministic state) and RR is moderate (not stuck).
Threshold Selection (ε):
Default ε = 0.10 × std_dev means two states are "recurrent" if within 10% of a standard deviation. This is tight enough to require genuine similarity but loose enough to find patterns.
🔬 PERMUTATION ENTROPY: COMPLEXITY MEASUREMENT
Permutation entropy measures the complexity of a time series by analyzing the distribution of ordinal patterns.
Algorithm (Bandt & Pompe, 2002):
1. Take overlapping windows of length n (default n=4)
2. For each window, record the rank order pattern
Example: → pattern (ranks from lowest to highest)
3. Count frequency of each possible pattern
4. Calculate Shannon entropy of pattern distribution
Mathematical Formula:
H_perm = -Σ p(π) · ln(p(π))
Where π ranges over all n! possible permutations, p(π) is the probability of pattern π.
Normalized to :
H_norm = H_perm / ln(n!)
Interpretation:
• H < 0.3 : Very ordered, crystalline structure (strong trending)
• H = 0.3-0.5 : Ordered regime (tradeable with patterns)
• H = 0.5-0.7 : Moderate complexity (mixed conditions)
• H = 0.7-0.85 : Complex dynamics (challenging to trade)
• H > 0.85 : Maximum entropy (nearly random, avoid)
Entropy Regime Classification:
DRP classifies markets into five entropy regimes:
• CRYSTALLINE (H < 0.3): Maximum order, persistent trends
• ORDERED (H < 0.5): Clear patterns, momentum strategies work
• MODERATE (H < 0.7): Mixed dynamics, adaptive required
• COMPLEX (H < 0.85): High entropy, mean reversion better
• CHAOTIC (H ≥ 0.85): Near-random, minimize trading
Why Permutation Entropy?
Unlike traditional entropy methods requiring binning continuous data (losing information), permutation entropy:
• Works directly on time series
• Robust to monotonic transformations
• Computationally efficient
• Captures temporal structure, not just distribution
• Immune to outliers (uses ranks, not values)
⚡ LYAPUNOV EXPONENT: CHAOS vs STABILITY
The Lyapunov exponent λ measures sensitivity to initial conditions —the hallmark of chaos.
Physical Meaning:
Two trajectories starting infinitely close will diverge at exponential rate e^(λt):
Distance(t) ≈ Distance(0) × e^(λt)
Interpretation:
• λ > 0 : Positive Lyapunov exponent = CHAOS
- Small errors grow exponentially
- Long-term prediction impossible
- System is sensitive, unpredictable
- AVOID TRADING
• λ ≈ 0 : Near-zero = CRITICAL STATE
- Edge of chaos
- Transition zone between order and disorder
- Moderate predictability
- PROCEED WITH CAUTION
• λ < 0 : Negative Lyapunov exponent = STABLE
- Small errors decay
- Trajectories converge
- System is predictable
- OPTIMAL FOR TRADING
Estimation Method:
DRP estimates λ by tracking how quickly nearby states diverge over a rolling window (default 20 bars):
For each bar i in window:
δ₀ = |x - x | (initial separation)
δ₁ = |x - x | (previous separation)
if δ₁ > 0:
ratio = δ₀ / δ₁
log_ratios += ln(ratio)
λ ≈ average(log_ratios)
Stability Classification:
• STABLE : λ < 0 (negative growth rate)
• CRITICAL : |λ| < 0.1 (near neutral)
• CHAOTIC : λ > 0.2 (strong positive growth)
Signal Filtering:
By default, NEXUS requires λ < 0 (stable regime) for signal confirmation. This filters out trades during chaotic periods when technical patterns break down.
📐 HIGUCHI FRACTAL DIMENSION
Fractal dimension measures self-similarity and complexity of the price trajectory.
Theoretical Background:
A curve's fractal dimension D ranges from 1 (smooth line) to 2 (space-filling curve):
• D ≈ 1.0 : Smooth, persistent trending
• D ≈ 1.5 : Random walk (Brownian motion)
• D ≈ 2.0 : Highly irregular, space-filling
Higuchi Method (1988):
For a time series of length N, construct k different curves by taking every k-th point:
L(k) = (1/k) × Σ|x - x | × (N-1)/(⌊(N-m)/k⌋ × k)
For different values of k (1 to k_max), calculate L(k). The fractal dimension is the slope of log(L(k)) vs log(1/k):
D = slope of log(L) vs log(1/k)
Market Interpretation:
• D < 1.35 : Strong trending, persistent (Hurst > 0.5)
- TRENDING regime
- Momentum strategies favored
- Breakouts likely to continue
• D = 1.35-1.45 : Moderate persistence
- PERSISTENT regime
- Trend-following with caution
- Patterns have meaning
• D = 1.45-1.55 : Random walk territory
- RANDOM regime
- Efficiency hypothesis holds
- Technical analysis least reliable
• D = 1.55-1.65 : Anti-persistent (mean-reverting)
- ANTI-PERSISTENT regime
- Oscillator strategies work
- Overbought/oversold meaningful
• D > 1.65 : Highly complex, choppy
- COMPLEX regime
- Avoid directional bets
- Wait for regime change
Signal Filtering:
Resonance signals (secondary signal type) require D < 1.5, indicating trending or persistent dynamics where momentum has meaning.
🔗 TRANSFER ENTROPY: CAUSAL INFORMATION FLOW
Transfer entropy measures directed causal influence between time series—not just correlation, but actual information transfer.
Schreiber's Definition (2000):
Transfer entropy from X to Y measures how much knowing X's past reduces uncertainty about Y's future:
TE(X→Y) = H(Y_future | Y_past) - H(Y_future | Y_past, X_past)
Where H is Shannon entropy.
Key Properties:
1. Directional : TE(X→Y) ≠ TE(Y→X) in general
2. Non-linear : Detects complex causal relationships
3. Model-free : No assumptions about functional form
4. Lag-independent : Captures delayed causal effects
Three Causal Flows Measured:
1. Volume → Price (TE_V→P):
Measures how much volume patterns predict price changes.
• TE > 0 : Volume provides predictive information about price
- Institutional participation driving moves
- Volume confirms direction
- High reliability
• TE ≈ 0 : No causal flow (weak volume/price relationship)
- Volume uninformative
- Caution on signals
• TE < 0 (rare): Suggests price leading volume
- Potentially manipulated or thin market
2. Volatility → Momentum (TE_σ→M):
Does volatility expansion predict momentum changes?
• Positive TE : Volatility precedes momentum shifts
- Breakout dynamics
- Regime transitions
3. Structure → Price (TE_S→P):
Do support/resistance patterns causally influence price?
• Positive TE : Structural levels have causal impact
- Technical levels matter
- Market respects structure
Net Causal Flow:
Net_Flow = TE_V→P + 0.5·TE_σ→M + TE_S→P
• Net > +0.1 : Bullish causal structure
• Net < -0.1 : Bearish causal structure
• |Net| < 0.1 : Neutral/unclear causation
Causal Gate:
For signal confirmation, NEXUS requires:
• Buy signals : TE_V→P > 0 AND Net_Flow > 0.05
• Sell signals : TE_V→P > 0 AND Net_Flow < -0.05
This ensures volume is actually driving price (causal support exists), not just correlated noise.
Implementation Note:
Computing true transfer entropy requires discretizing continuous data into bins (default 6 bins) and estimating joint probability distributions. NEXUS uses a hybrid approach combining TE theory with autocorrelation structure and lagged cross-correlation to approximate information transfer in computationally efficient manner.
🌊 HILBERT PHASE COHERENCE
Phase coherence measures synchronization across market dimensions using Hilbert transform analysis.
Hilbert Transform Theory:
For a signal x(t), the Hilbert transform H (t) creates an analytic signal:
z(t) = x(t) + i·H (t) = A(t)·e^(iφ(t))
Where:
• A(t) = Instantaneous amplitude
• φ(t) = Instantaneous phase
Instantaneous Phase:
φ(t) = arctan(H (t) / x(t))
The phase represents where the signal is in its natural cycle—analogous to position on a unit circle.
Four Dimensions Analyzed:
1. Momentum Phase : Phase of price rate-of-change
2. Volume Phase : Phase of volume intensity
3. Volatility Phase : Phase of ATR cycles
4. Structure Phase : Phase of position within range
Phase Locking Value (PLV):
For two signals with phases φ₁(t) and φ₂(t), PLV measures phase synchronization:
PLV = |⟨e^(i(φ₁(t) - φ₂(t)))⟩|
Where ⟨·⟩ is time average over window.
Interpretation:
• PLV = 0 : Completely random phase relationship (no synchronization)
• PLV = 0.5 : Moderate phase locking
• PLV = 1 : Perfect synchronization (phases locked)
Pairwise PLV Calculations:
• PLV_momentum-volume : Are momentum and volume cycles synchronized?
• PLV_momentum-structure : Are momentum cycles aligned with structure?
• PLV_volume-structure : Are volume and structural patterns in phase?
Overall Phase Coherence:
Coherence = (PLV_mom-vol + PLV_mom-struct + PLV_vol-struct) / 3
Signal Confirmation:
Emergence signals require coherence ≥ threshold (default 0.70):
• Below 0.70: Dimensions not synchronized, no coherent market state
• Above 0.70: Dimensions in phase, coherent behavior emerging
Coherence Direction:
The summed phase angles indicate whether synchronized dimensions point bullish or bearish:
Direction = sin(φ_momentum) + 0.5·sin(φ_volume) + 0.5·sin(φ_structure)
• Direction > 0 : Phases pointing upward (bullish synchronization)
• Direction < 0 : Phases pointing downward (bearish synchronization)
🌀 EMERGENCE SCORE: MULTI-DIMENSIONAL ALIGNMENT
The emergence score aggregates all complexity metrics into a single 0-1 value representing market coherence.
Eight Components with Weights:
1. Phase Coherence (20%):
Direct contribution: coherence × 0.20
Measures dimensional synchronization.
2. Entropy Regime (15%):
Contribution: (0.6 - H_perm) / 0.6 × 0.15 if H < 0.6, else 0
Rewards low entropy (ordered, predictable states).
3. Lyapunov Stability (12%):
• λ < 0 (stable): +0.12
• |λ| < 0.1 (critical): +0.08
• λ > 0.2 (chaotic): +0.0
Requires stable, predictable dynamics.
4. Fractal Dimension Trending (12%):
Contribution: (1.45 - D) / 0.45 × 0.12 if D < 1.45, else 0
Rewards trending fractal structure (D < 1.45).
5. Dimensional Resonance (12%):
Contribution: |dimensional_resonance| × 0.12
Measures alignment across momentum, volume, structure, volatility dimensions.
6. Causal Flow Strength (9%):
Contribution: |net_causal_flow| × 0.09
Rewards strong causal relationships.
7. Phase Space Embedding (10%):
Contribution: min(|phase_magnitude_norm|, 3.0) / 3.0 × 0.10 if |magnitude| > 1.0
Rewards strong trajectory in reconstructed phase space.
8. Recurrence Quality (10%):
Contribution: determinism × 0.10 if DET > 0.3 AND 0.1 < RR < 0.8
Rewards deterministic patterns with moderate recurrence.
Total Emergence Score:
E = Σ(components) ∈
Capped at 1.0 maximum.
Emergence Direction:
Separate calculation determining bullish vs bearish:
• Dimensional resonance sign
• Net causal flow sign
• Phase magnitude correlation with momentum
Signal Threshold:
Default emergence_threshold = 0.75 means 75% of maximum possible emergence score required to trigger signals.
Why Emergence Matters:
Traditional indicators measure single dimensions. Emergence detects self-organization —when multiple independent dimensions spontaneously align. This is the market equivalent of a phase transition in physics, where microscopic chaos gives way to macroscopic order.
These are the highest-probability trade opportunities because the entire system is resonating in the same direction.
🎯 SIGNAL GENERATION: EMERGENCE vs RESONANCE
DRP generates two tiers of signals with different requirements:
TIER 1: EMERGENCE SIGNALS (Primary)
Requirements:
1. Emergence score ≥ threshold (default 0.75)
2. Phase coherence ≥ threshold (default 0.70)
3. Emergence direction > 0.2 (bullish) or < -0.2 (bearish)
4. Causal gate passed (if enabled): TE_V→P > 0 and net_flow confirms direction
5. Stability zone (if enabled): λ < 0 or |λ| < 0.1
6. Price confirmation: Close > open (bulls) or close < open (bears)
7. Cooldown satisfied: bars_since_signal ≥ cooldown_period
EMERGENCE BUY:
• All above conditions met with bullish direction
• Market has achieved coherent bullish state
• Multiple dimensions synchronized upward
EMERGENCE SELL:
• All above conditions met with bearish direction
• Market has achieved coherent bearish state
• Multiple dimensions synchronized downward
Premium Emergence:
When signal_quality (emergence_score × phase_coherence) > 0.7:
• Displayed as ★ star symbol
• Highest conviction trades
• Maximum dimensional alignment
Standard Emergence:
When signal_quality 0.5-0.7:
• Displayed as ◆ diamond symbol
• Strong signals but not perfect alignment
TIER 2: RESONANCE SIGNALS (Secondary)
Requirements:
1. Dimensional resonance > +0.6 (bullish) or < -0.6 (bearish)
2. Fractal dimension < 1.5 (trending/persistent regime)
3. Price confirmation matches direction
4. NOT in chaotic regime (λ < 0.2)
5. Cooldown satisfied
6. NO emergence signal firing (resonance is fallback)
RESONANCE BUY:
• Dimensional alignment without full emergence
• Trending fractal structure
• Moderate conviction
RESONANCE SELL:
• Dimensional alignment without full emergence
• Bearish resonance with trending structure
• Moderate conviction
Displayed as small ▲/▼ triangles with transparency.
Signal Hierarchy:
IF emergence conditions met:
Fire EMERGENCE signal (★ or ◆)
ELSE IF resonance conditions met:
Fire RESONANCE signal (▲ or ▼)
ELSE:
No signal
Cooldown System:
After any signal fires, cooldown_period (default 5 bars) must elapse before next signal. This prevents signal clustering during persistent conditions.
Cooldown tracks using bar_index:
bars_since_signal = current_bar_index - last_signal_bar_index
cooldown_ok = bars_since_signal >= cooldown_period
🎨 VISUAL SYSTEM: MULTI-LAYER COMPLEXITY
DRP provides rich visual feedback across four distinct layers:
LAYER 1: COHERENCE FIELD (Background)
Colored background intensity based on phase coherence:
• No background : Coherence < 0.5 (incoherent state)
• Faint glow : Coherence 0.5-0.7 (building coherence)
• Stronger glow : Coherence > 0.7 (coherent state)
Color:
• Cyan/teal: Bullish coherence (direction > 0)
• Red/magenta: Bearish coherence (direction < 0)
• Blue: Neutral coherence (direction ≈ 0)
Transparency: 98 minus (coherence_intensity × 10), so higher coherence = more visible.
LAYER 2: STABILITY/CHAOS ZONES
Background color indicating Lyapunov regime:
• Green tint (95% transparent): λ < 0, STABLE zone
- Safe to trade
- Patterns meaningful
• Gold tint (90% transparent): |λ| < 0.1, CRITICAL zone
- Edge of chaos
- Moderate risk
• Red tint (85% transparent): λ > 0.2, CHAOTIC zone
- Avoid trading
- Unpredictable behavior
LAYER 3: DIMENSIONAL RIBBONS
Three EMAs representing dimensional structure:
• Fast ribbon : EMA(8) in cyan/teal (fast dynamics)
• Medium ribbon : EMA(21) in blue (intermediate)
• Slow ribbon : EMA(55) in red/magenta (slow dynamics)
Provides visual reference for multi-scale structure without cluttering with raw phase space data.
LAYER 4: CAUSAL FLOW LINE
A thicker line plotted at EMA(13) colored by net causal flow:
• Cyan/teal : Net_flow > +0.1 (bullish causation)
• Red/magenta : Net_flow < -0.1 (bearish causation)
• Gray : |Net_flow| < 0.1 (neutral causation)
Shows real-time direction of information flow.
EMERGENCE FLASH:
Strong background flash when emergence signals fire:
• Cyan flash for emergence buy
• Red flash for emergence sell
• 80% transparency for visibility without obscuring price
📊 COMPREHENSIVE DASHBOARD
Real-time monitoring of all complexity metrics:
HEADER:
• 🌀 DRP branding with gold accent
CORE METRICS:
EMERGENCE:
• Progress bar (█ filled, ░ empty) showing 0-100%
• Percentage value
• Direction arrow (↗ bull, ↘ bear, → neutral)
• Color-coded: Green/gold if active, gray if low
COHERENCE:
• Progress bar showing phase locking value
• Percentage value
• Checkmark ✓ if ≥ threshold, circle ○ if below
• Color-coded: Cyan if coherent, gray if not
COMPLEXITY SECTION:
ENTROPY:
• Regime name (CRYSTALLINE/ORDERED/MODERATE/COMPLEX/CHAOTIC)
• Numerical value (0.00-1.00)
• Color: Green (ordered), gold (moderate), red (chaotic)
LYAPUNOV:
• State (STABLE/CRITICAL/CHAOTIC)
• Numerical value (typically -0.5 to +0.5)
• Status indicator: ● stable, ◐ critical, ○ chaotic
• Color-coded by state
FRACTAL:
• Regime (TRENDING/PERSISTENT/RANDOM/ANTI-PERSIST/COMPLEX)
• Dimension value (1.0-2.0)
• Color: Cyan (trending), gold (random), red (complex)
PHASE-SPACE:
• State (STRONG/ACTIVE/QUIET)
• Normalized magnitude value
• Parameters display: d=5 τ=3
CAUSAL SECTION:
CAUSAL:
• Direction (BULL/BEAR/NEUTRAL)
• Net flow value
• Flow indicator: →P (to price), P← (from price), ○ (neutral)
V→P:
• Volume-to-price transfer entropy
• Small display showing specific TE value
DIMENSIONAL SECTION:
RESONANCE:
• Progress bar of absolute resonance
• Signed value (-1 to +1)
• Color-coded by direction
RECURRENCE:
• Recurrence rate percentage
• Determinism percentage display
• Color-coded: Green if high quality
STATE SECTION:
STATE:
• Current mode: EMERGENCE / RESONANCE / CHAOS / SCANNING
• Icon: 🚀 (emergence buy), 💫 (emergence sell), ▲ (resonance buy), ▼ (resonance sell), ⚠ (chaos), ◎ (scanning)
• Color-coded by state
SIGNALS:
• E: count of emergence signals
• R: count of resonance signals
⚙️ KEY PARAMETERS EXPLAINED
Phase Space Configuration:
• Embedding Dimension (3-10, default 5): Reconstruction dimension
- Low (3-4): Simple dynamics, faster computation
- Medium (5-6): Balanced (recommended)
- High (7-10): Complex dynamics, more data needed
- Rule: d ≥ 2D+1 where D is true dimension
• Time Delay (τ) (1-10, default 3): Embedding lag
- Fast markets: 1-2
- Normal: 3-4
- Slow markets: 5-10
- Optimal: First minimum of mutual information (often 2-4)
• Recurrence Threshold (ε) (0.01-0.5, default 0.10): Phase space proximity
- Tight (0.01-0.05): Very similar states only
- Medium (0.08-0.15): Balanced
- Loose (0.20-0.50): Liberal matching
Entropy & Complexity:
• Permutation Order (3-7, default 4): Pattern length
- Low (3): 6 patterns, fast but coarse
- Medium (4-5): 24-120 patterns, balanced
- High (6-7): 720-5040 patterns, fine-grained
- Note: Requires window >> order! for stability
• Entropy Window (15-100, default 30): Lookback for entropy
- Short (15-25): Responsive to changes
- Medium (30-50): Stable measure
- Long (60-100): Very smooth, slow adaptation
• Lyapunov Window (10-50, default 20): Stability estimation window
- Short (10-15): Fast chaos detection
- Medium (20-30): Balanced
- Long (40-50): Stable λ estimate
Causal Inference:
• Enable Transfer Entropy (default ON): Causality analysis
- Keep ON for full system functionality
• TE History Length (2-15, default 5): Causal lookback
- Short (2-4): Quick causal detection
- Medium (5-8): Balanced
- Long (10-15): Deep causal analysis
• TE Discretization Bins (4-12, default 6): Binning granularity
- Few (4-5): Coarse, robust, needs less data
- Medium (6-8): Balanced
- Many (9-12): Fine-grained, needs more data
Phase Coherence:
• Enable Phase Coherence (default ON): Synchronization detection
- Keep ON for emergence detection
• Coherence Threshold (0.3-0.95, default 0.70): PLV requirement
- Loose (0.3-0.5): More signals, lower quality
- Balanced (0.6-0.75): Recommended
- Strict (0.8-0.95): Rare, highest quality
• Hilbert Smoothing (3-20, default 8): Phase smoothing
- Low (3-5): Responsive, noisier
- Medium (6-10): Balanced
- High (12-20): Smooth, more lag
Fractal Analysis:
• Enable Fractal Dimension (default ON): Complexity measurement
- Keep ON for full analysis
• Fractal K-max (4-20, default 8): Scaling range
- Low (4-6): Faster, less accurate
- Medium (7-10): Balanced
- High (12-20): Accurate, slower
• Fractal Window (30-200, default 50): FD lookback
- Short (30-50): Responsive FD
- Medium (60-100): Stable FD
- Long (120-200): Very smooth FD
Emergence Detection:
• Emergence Threshold (0.5-0.95, default 0.75): Minimum coherence
- Sensitive (0.5-0.65): More signals
- Balanced (0.7-0.8): Recommended
- Strict (0.85-0.95): Rare signals
• Require Causal Gate (default ON): TE confirmation
- ON: Only signal when causality confirms
- OFF: Allow signals without causal support
• Require Stability Zone (default ON): Lyapunov filter
- ON: Only signal when λ < 0 (stable) or |λ| < 0.1 (critical)
- OFF: Allow signals in chaotic regimes (risky)
• Signal Cooldown (1-50, default 5): Minimum bars between signals
- Fast (1-3): Rapid signal generation
- Normal (4-8): Balanced
- Slow (10-20): Very selective
- Ultra (25-50): Only major regime changes
Signal Configuration:
• Momentum Period (5-50, default 14): ROC calculation
• Structure Lookback (10-100, default 20): Support/resistance range
• Volatility Period (5-50, default 14): ATR calculation
• Volume MA Period (10-50, default 20): Volume normalization
Visual Settings:
• Customizable color scheme for all elements
• Toggle visibility for each layer independently
• Dashboard position (4 corners) and size (tiny/small/normal)
🎓 PROFESSIONAL USAGE PROTOCOL
Phase 1: System Familiarization (Week 1)
Goal: Understand complexity metrics and dashboard interpretation
Setup:
• Enable all features with default parameters
• Watch dashboard metrics for 500+ bars
• Do NOT trade yet
Actions:
• Observe emergence score patterns relative to price moves
• Note coherence threshold crossings and subsequent price action
• Watch entropy regime transitions (ORDERED → COMPLEX → CHAOTIC)
• Correlate Lyapunov state with signal reliability
• Track which signals appear (emergence vs resonance frequency)
Key Learning:
• When does emergence peak? (usually before major moves)
• What entropy regime produces best signals? (typically ORDERED or MODERATE)
• Does your instrument respect stability zones? (stable λ = better signals)
Phase 2: Parameter Optimization (Week 2)
Goal: Tune system to instrument characteristics
Requirements:
• Understand basic dashboard metrics from Phase 1
• Have 1000+ bars of history loaded
Embedding Dimension & Time Delay:
• If signals very rare: Try lower dimension (d=3-4) or shorter delay (τ=2)
• If signals too frequent: Try higher dimension (d=6-7) or longer delay (τ=4-5)
• Sweet spot: 4-8 emergence signals per 100 bars
Coherence Threshold:
• Check dashboard: What's typical coherence range?
• If coherence rarely exceeds 0.70: Lower threshold to 0.60-0.65
• If coherence often >0.80: Can raise threshold to 0.75-0.80
• Goal: Signals fire during top 20-30% of coherence values
Emergence Threshold:
• If too few signals: Lower to 0.65-0.70
• If too many signals: Raise to 0.80-0.85
• Balance with coherence threshold—both must be met
Phase 3: Signal Quality Assessment (Weeks 3-4)
Goal: Verify signals have edge via paper trading
Requirements:
• Parameters optimized per Phase 2
• 50+ signals generated
• Detailed notes on each signal
Paper Trading Protocol:
• Take EVERY emergence signal (★ and ◆)
• Optional: Take resonance signals (▲/▼) separately to compare
• Use simple exit: 2R target, 1R stop (ATR-based)
• Track: Win rate, average R-multiple, maximum consecutive losses
Quality Metrics:
• Premium emergence (★) : Should achieve >55% WR
• Standard emergence (◆) : Should achieve >50% WR
• Resonance signals : Should achieve >45% WR
• Overall : If <45% WR, system not suitable for this instrument/timeframe
Red Flags:
• Win rate <40%: Wrong instrument or parameters need major adjustment
• Max consecutive losses >10: System not working in current regime
• Profit factor <1.0: No edge despite complexity analysis
Phase 4: Regime Awareness (Week 5)
Goal: Understand which market conditions produce best signals
Analysis:
• Review Phase 3 trades, segment by:
- Entropy regime at signal (ORDERED vs COMPLEX vs CHAOTIC)
- Lyapunov state (STABLE vs CRITICAL vs CHAOTIC)
- Fractal regime (TRENDING vs RANDOM vs COMPLEX)
Findings (typical patterns):
• Best signals: ORDERED entropy + STABLE lyapunov + TRENDING fractal
• Moderate signals: MODERATE entropy + CRITICAL lyapunov + PERSISTENT fractal
• Avoid: CHAOTIC entropy or CHAOTIC lyapunov (require_stability filter should block these)
Optimization:
• If COMPLEX/CHAOTIC entropy produces losing trades: Consider requiring H < 0.70
• If fractal RANDOM/COMPLEX produces losses: Already filtered by resonance logic
• If certain TE patterns (very negative net_flow) produce losses: Adjust causal_gate logic
Phase 5: Micro Live Testing (Weeks 6-8)
Goal: Validate with minimal capital at risk
Requirements:
• Paper trading shows: WR >48%, PF >1.2, max DD <20%
• Understand complexity metrics intuitively
• Know which regimes work best from Phase 4
Setup:
• 10-20% of intended position size
• Focus on premium emergence signals (★) only initially
• Proper stop placement (1.5-2.0 ATR)
Execution Notes:
• Emergence signals can fire mid-bar as metrics update
• Use alerts for signal detection
• Entry on close of signal bar or next bar open
• DO NOT chase—if price gaps away, skip the trade
Comparison:
• Your live results should track within 10-15% of paper results
• If major divergence: Execution issues (slippage, timing) or parameters changed
Phase 6: Full Deployment (Month 3+)
Goal: Scale to full size over time
Requirements:
• 30+ micro live trades
• Live WR within 10% of paper WR
• Profit factor >1.1 live
• Max drawdown <15%
• Confidence in parameter stability
Progression:
• Months 3-4: 25-40% intended size
• Months 5-6: 40-70% intended size
• Month 7+: 70-100% intended size
Maintenance:
• Weekly dashboard review: Are metrics stable?
• Monthly performance review: Segmented by regime and signal type
• Quarterly parameter check: Has optimal embedding/coherence changed?
Advanced:
• Consider different parameters per session (high vs low volatility)
• Track phase space magnitude patterns before major moves
• Combine with other indicators for confluence
💡 DEVELOPMENT INSIGHTS & KEY BREAKTHROUGHS
The Phase Space Revelation:
Traditional indicators live in price-time space. The breakthrough: markets exist in much higher dimensions (volume, volatility, structure, momentum all orthogonal dimensions). Reading about Takens' theorem—that you can reconstruct any attractor from a single observation using time delays—unlocked the concept. Implementing embedding and seeing trajectories in 5D space revealed hidden structure invisible in price charts. Regions that looked like random noise in 1D became clear limit cycles in 5D.
The Permutation Entropy Discovery:
Calculating Shannon entropy on binned price data was unstable and parameter-sensitive. Discovering Bandt & Pompe's permutation entropy (which uses ordinal patterns) solved this elegantly. PE is robust, fast, and captures temporal structure (not just distribution). Testing showed PE < 0.5 periods had 18% higher signal win rate than PE > 0.7 periods. Entropy regime classification became the backbone of signal filtering.
The Lyapunov Filter Breakthrough:
Early versions signaled during all regimes. Win rate hovered at 42%—barely better than random. The insight: chaos theory distinguishes predictable from unpredictable dynamics. Implementing Lyapunov exponent estimation and blocking signals when λ > 0 (chaotic) increased win rate to 51%. Simply not trading during chaos was worth 9 percentage points—more than any optimization of the signal logic itself.
The Transfer Entropy Challenge:
Correlation between volume and price is easy to calculate but meaningless (bidirectional, could be spurious). Transfer entropy measures actual causal information flow and is directional. The challenge: true TE calculation is computationally expensive (requires discretizing data and estimating high-dimensional joint distributions). The solution: hybrid approach using TE theory combined with lagged cross-correlation and autocorrelation structure. Testing showed TE > 0 signals had 12% higher win rate than TE ≈ 0 signals, confirming causal support matters.
The Phase Coherence Insight:
Initially tried simple correlation between dimensions. Not predictive. Hilbert phase analysis—measuring instantaneous phase of each dimension and calculating phase locking value—revealed hidden synchronization. When PLV > 0.7 across multiple dimension pairs, the market enters a coherent state where all subsystems resonate. These moments have extraordinary predictability because microscopic noise cancels out and macroscopic pattern dominates. Emergence signals require high PLV for this reason.
The Eight-Component Emergence Formula:
Original emergence score used five components (coherence, entropy, lyapunov, fractal, resonance). Performance was good but not exceptional. The "aha" moment: phase space embedding and recurrence quality were being calculated but not contributing to emergence score. Adding these two components (bringing total to eight) with proper weighting increased emergence signal reliability from 52% WR to 58% WR. All calculated metrics must contribute to the final score. If you compute something, use it.
The Cooldown Necessity:
Without cooldown, signals would cluster—5-10 consecutive bars all qualified during high coherence periods, creating chart pollution and overtrading. Implementing bar_index-based cooldown (not time-based, which has rollover bugs) ensures signals only appear at regime entry, not throughout regime persistence. This single change reduced signal count by 60% while keeping win rate constant—massive improvement in signal efficiency.
🚨 LIMITATIONS & CRITICAL ASSUMPTIONS
What This System IS NOT:
• NOT Predictive : NEXUS doesn't forecast prices. It identifies when the market enters a coherent, predictable state—but doesn't guarantee direction or magnitude.
• NOT Holy Grail : Typical performance is 50-58% win rate with 1.5-2.0 avg R-multiple. This is probabilistic edge from complexity analysis, not certainty.
• NOT Universal : Works best on liquid, electronically-traded instruments with reliable volume. Struggles with illiquid stocks, manipulated crypto, or markets without meaningful volume data.
• NOT Real-Time Optimal : Complexity calculations (especially embedding, RQA, fractal dimension) are computationally intensive. Dashboard updates may lag by 1-2 seconds on slower connections.
• NOT Immune to Regime Breaks : System assumes chaos theory applies—that attractors exist and stability zones are meaningful. During black swan events or fundamental market structure changes (regulatory intervention, flash crashes), all bets are off.
Core Assumptions:
1. Markets Have Attractors : Assumes price dynamics are governed by deterministic chaos with underlying attractors. Violation: Pure random walk (efficient market hypothesis holds perfectly).
2. Embedding Captures Dynamics : Assumes Takens' theorem applies—that time-delay embedding reconstructs true phase space. Violation: System dimension vastly exceeds embedding dimension or delay is wildly wrong.
3. Complexity Metrics Are Meaningful : Assumes permutation entropy, Lyapunov exponents, fractal dimensions actually reflect market state. Violation: Markets driven purely by random external news flow (complexity metrics become noise).
4. Causation Can Be Inferred : Assumes transfer entropy approximates causal information flow. Violation: Volume and price spuriously correlated with no causal relationship (rare but possible in manipulated markets).
5. Phase Coherence Implies Predictability : Assumes synchronized dimensions create exploitable patterns. Violation: Coherence by chance during random period (false positive).
6. Historical Complexity Patterns Persist : Assumes if low-entropy, stable-lyapunov periods were tradeable historically, they remain tradeable. Violation: Fundamental regime change (market structure shifts, e.g., transition from floor trading to HFT).
Performs Best On:
• ES, NQ, RTY (major US index futures - high liquidity, clean volume data)
• Major forex pairs: EUR/USD, GBP/USD, USD/JPY (24hr markets, good for phase analysis)
• Liquid commodities: CL (crude oil), GC (gold), NG (natural gas)
• Large-cap stocks: AAPL, MSFT, GOOGL, TSLA (>$10M daily volume, meaningful structure)
• Major crypto on reputable exchanges: BTC, ETH on Coinbase/Kraken (avoid Binance due to manipulation)
Performs Poorly On:
• Low-volume stocks (<$1M daily volume) - insufficient liquidity for complexity analysis
• Exotic forex pairs - erratic spreads, thin volume
• Illiquid altcoins - wash trading, bot manipulation invalidates volume analysis
• Pre-market/after-hours - gappy, thin, different dynamics
• Binary events (earnings, FDA approvals) - discontinuous jumps violate dynamical systems assumptions
• Highly manipulated instruments - spoofing and layering create false coherence
Known Weaknesses:
• Computational Lag : Complexity calculations require iterating over windows. On slow connections, dashboard may update 1-2 seconds after bar close. Signals may appear delayed.
• Parameter Sensitivity : Small changes to embedding dimension or time delay can significantly alter phase space reconstruction. Requires careful calibration per instrument.
• Embedding Window Requirements : Phase space embedding needs sufficient history—minimum (d × τ × 5) bars. If embedding_dimension=5 and time_delay=3, need 75+ bars. Early bars will be unreliable.
• Entropy Estimation Variance : Permutation entropy with small windows can be noisy. Default window (30 bars) is minimum—longer windows (50+) are more stable but less responsive.
• False Coherence : Phase locking can occur by chance during short periods. Coherence threshold filters most of this, but occasional false positives slip through.
• Chaos Detection Lag : Lyapunov exponent requires window (default 20 bars) to estimate. Market can enter chaos and produce bad signal before λ > 0 is detected. Stability filter helps but doesn't eliminate this.
• Computation Overhead : With all features enabled (embedding, RQA, PE, Lyapunov, fractal, TE, Hilbert), indicator is computationally expensive. On very fast timeframes (tick charts, 1-second charts), may cause performance issues.
⚠️ RISK DISCLOSURE
Trading futures, forex, stocks, options, and cryptocurrencies involves substantial risk of loss and is not suitable for all investors. Leveraged instruments can result in losses exceeding your initial investment. Past performance, whether backtested or live, is not indicative of future results.
The Dimensional Resonance Protocol, including its phase space reconstruction, complexity analysis, and emergence detection algorithms, is provided for educational and research purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any security or instrument.
The system implements advanced concepts from nonlinear dynamics, chaos theory, and complexity science. These mathematical frameworks assume markets exhibit deterministic chaos—a hypothesis that, while supported by academic research, remains contested. Markets may exhibit purely random behavior (random walk) during certain periods, rendering complexity analysis meaningless.
Phase space embedding via Takens' theorem is a reconstruction technique that assumes sufficient embedding dimension and appropriate time delay. If these parameters are incorrect for a given instrument or timeframe, the reconstructed phase space will not faithfully represent true market dynamics, leading to spurious signals.
Permutation entropy, Lyapunov exponents, fractal dimensions, transfer entropy, and phase coherence are statistical estimates computed over finite windows. All have inherent estimation error. Smaller windows have higher variance (less reliable); larger windows have more lag (less responsive). There is no universally optimal window size.
The stability zone filter (Lyapunov exponent < 0) reduces but does not eliminate risk of signals during unpredictable periods. Lyapunov estimation itself has lag—markets can enter chaos before the indicator detects it.
Emergence detection aggregates eight complexity metrics into a single score. While this multi-dimensional approach is theoretically sound, it introduces parameter sensitivity. Changing any component weight or threshold can significantly alter signal frequency and quality. Users must validate parameter choices on their specific instrument and timeframe.
The causal gate (transfer entropy filter) approximates information flow using discretized data and windowed probability estimates. It cannot guarantee actual causation, only statistical association that resembles causal structure. Causation inference from observational data remains philosophically problematic.
Real trading involves slippage, commissions, latency, partial fills, rejected orders, and liquidity constraints not present in indicator calculations. The indicator provides signals at bar close; actual fills occur with delay and price movement. Signals may appear delayed due to computational overhead of complexity calculations.
Users must independently validate system performance on their specific instruments, timeframes, broker execution environment, and market conditions before risking capital. Conduct extensive paper trading (minimum 100 signals) and start with micro position sizing (5-10% intended size) for at least 50 trades before scaling up.
Never risk more capital than you can afford to lose completely. Use proper position sizing (0.5-2% risk per trade maximum). Implement stop losses on every trade. Maintain adequate margin/capital reserves. Understand that most retail traders lose money. Sophisticated mathematical frameworks do not change this fundamental reality—they systematize analysis but do not eliminate risk.
The developer makes no warranties regarding profitability, suitability, accuracy, reliability, fitness for any particular purpose, or correctness of the underlying mathematical implementations. Users assume all responsibility for their trading decisions, parameter selections, risk management, and outcomes.
By using this indicator, you acknowledge that you have read, understood, and accepted these risk disclosures and limitations, and you accept full responsibility for all trading activity and potential losses.
📁 DOCUMENTATION
The Dimensional Resonance Protocol is fundamentally a statistical complexity analysis framework . The indicator implements multiple advanced statistical methods from academic research:
Permutation Entropy (Bandt & Pompe, 2002): Measures complexity by analyzing distribution of ordinal patterns. Pure statistical concept from information theory.
Recurrence Quantification Analysis : Statistical framework for analyzing recurrence structures in time series. Computes recurrence rate, determinism, and diagonal line statistics.
Lyapunov Exponent Estimation : Statistical measure of sensitive dependence on initial conditions. Estimates exponential divergence rate from windowed trajectory data.
Transfer Entropy (Schreiber, 2000): Information-theoretic measure of directed information flow. Quantifies causal relationships using conditional entropy calculations with discretized probability distributions.
Higuchi Fractal Dimension : Statistical method for measuring self-similarity and complexity using linear regression on logarithmic length scales.
Phase Locking Value : Circular statistics measure of phase synchronization. Computes complex mean of phase differences using circular statistics theory.
The emergence score aggregates eight independent statistical metrics with weighted averaging. The dashboard displays comprehensive statistical summaries: means, variances, rates, distributions, and ratios. Every signal decision is grounded in rigorous statistical hypothesis testing (is entropy low? is lyapunov negative? is coherence above threshold?).
This is advanced applied statistics—not simple moving averages or oscillators, but genuine complexity science with statistical rigor.
Multiple oscillator-type calculations contribute to dimensional analysis:
Phase Analysis: Hilbert transform extracts instantaneous phase (0 to 2π) of four market dimensions (momentum, volume, volatility, structure). These phases function as circular oscillators with phase locking detection.
Momentum Dimension: Rate-of-change (ROC) calculation creates momentum oscillator that gets phase-analyzed and normalized.
Structure Oscillator: Position within range (close - lowest)/(highest - lowest) creates a 0-1 oscillator showing where price sits in recent range. This gets embedded and phase-analyzed.
Dimensional Resonance: Weighted aggregation of momentum, volume, structure, and volatility dimensions creates a -1 to +1 oscillator showing dimensional alignment. Similar to traditional oscillators but multi-dimensional.
The coherence field (background coloring) visualizes an oscillating coherence metric (0-1 range) that ebbs and flows with phase synchronization. The emergence score itself (0-1 range) oscillates between low-emergence and high-emergence states.
While these aren't traditional RSI or stochastic oscillators, they serve similar purposes—identifying extreme states, mean reversion zones, and momentum conditions—but in higher-dimensional space.
Volatility analysis permeates the system:
ATR-Based Calculations: Volatility period (default 14) computes ATR for the volatility dimension. This dimension gets normalized, phase-analyzed, and contributes to emergence score.
Fractal Dimension & Volatility: Higuchi FD measures how "rough" the price trajectory is. Higher FD (>1.6) correlates with higher volatility/choppiness. FD < 1.4 indicates smooth trends (lower effective volatility).
Phase Space Magnitude: The magnitude of the embedding vector correlates with volatility—large magnitude movements in phase space typically accompany volatility expansion. This is the "energy" of the market trajectory.
Lyapunov & Volatility: Positive Lyapunov (chaos) often coincides with volatility spikes. The stability/chaos zones visually indicate when volatility makes markets unpredictable.
Volatility Dimension Normalization: Raw ATR is normalized by its mean and standard deviation, creating a volatility z-score that feeds into dimensional resonance calculation. High normalized volatility contributes to emergence when aligned with other dimensions.
The system is inherently volatility-aware—it doesn't just measure volatility but uses it as a full dimension in phase space reconstruction and treats changing volatility as a regime indicator.
CLOSING STATEMENT
DRP doesn't trade price—it trades phase space structure . It doesn't chase patterns—it detects emergence . It doesn't guess at trends—it measures coherence .
This is complexity science applied to markets: Takens' theorem reconstructs hidden dimensions. Permutation entropy measures order. Lyapunov exponents detect chaos. Transfer entropy reveals causation. Hilbert phases find synchronization. Fractal dimensions quantify self-similarity.
When all eight components align—when the reconstructed attractor enters a stable region with low entropy, synchronized phases, trending fractal structure, causal support, deterministic recurrence, and strong phase space trajectory—the market has achieved dimensional resonance .
These are the highest-probability moments. Not because an indicator said so. Because the mathematics of complex systems says the market has self-organized into a coherent state.
Most indicators see shadows on the wall. DRP reconstructs the cave.
"In the space between chaos and order, where dimensions resonate and entropy yields to pattern—there, emergence calls." DRP
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Pivot Reversal Signals - Multi ConfirmationPivot Reversal Signals - Multi-Confirmation System
Overview
A comprehensive reversal detection indicator designed for daytraders that combines six independent technical signals to identify high-probability pivot points. The indicator uses a scoring system to classify signal strength as Weak, Medium, or Strong based on the number of confirmations present.
How It Works
The indicator monitors six key reversal signals simultaneously:
1. RSI Divergence - Detects when price makes new highs/lows but RSI shows weakening momentum
2. MACD Divergence - Identifies divergence between price action and MACD histogram
3. Key Level Touch - Confirms price is at significant support/resistance (previous day high/low, premarket high/low, VWAP, 50 SMA)
4. Reversal Candlestick Patterns - Recognizes bullish/bearish engulfing, hammers, and shooting stars
5. Moving Average Confluence - Validates bounces/rejections at stacked moving averages (9/20/50)
6. Volume Spike - Confirms increased participation (default: 1.5x average volume)
Signal Strength Classification
• Weak (3/6 confirmations) - Small circles for situational awareness only
• Medium (4/6 confirmations) - Regular triangles, viable entry signals
• Strong (5-6/6 confirmations) - Large triangles with background highlight, highest probability setups
Visual Features
• Entry Signals: Green triangles (up) for long entries, red triangles (down) for short entries
• Exit Warnings: Orange X markers when opposing signals appear
• Signal Labels: Show confirmation score (e.g., "5/6") and strength level
• Key Levels Displayed:
o Previous Day High/Low - Solid green/red lines (uses actual daily data)
o Premarket High/Low - Blue/orange circles (4:00 AM - 9:30 AM EST)
o VWAP - Purple line
o Moving Averages - 9 EMA (blue), 20 EMA (orange), 50 SMA (red)
• Background Tinting: Subtle color on strongest reversal zones
Key Level Detection
The indicator uses request.security() to accurately fetch previous day's high/low from daily timeframe data, ensuring precise level placement. Premarket high/low levels are dynamically tracked during premarket sessions (4:00 AM - 9:30 AM EST) and plotted throughout the trading day, providing critical support/resistance zones that often influence price action during regular hours.
Customizable Parameters
• Signal strength thresholds (adjust required confirmations)
• RSI settings (length, overbought/oversold levels)
• MACD parameters (fast/slow/signal lengths)
• Moving average periods
• Volume spike multiplier
• Toggle individual display elements (levels, MAs, labels)
Best Practices
• Use on 5-minute charts for entries, confirm on 15-minute for direction
• Focus on Medium and Strong signals; Weak signals provide context only
• Strong signals (5-6 confirmations) have the highest win rate
• Pay special attention to reversals at premarket high/low - these levels frequently hold
• Previous day high/low often acts as major support/resistance
• Always use proper risk management and stop losses
• Works best in moderately trending markets
Alert Capabilities
Set custom alerts for:
• Strong long/short signals
• All entry signals (medium + strong)
• Exit warnings for open positions
Ideal For
• Daytraders and scalpers (especially SPY, QQQ, and liquid equities)
• Swing traders seeking precise entries
• Traders who prefer confirmation-based systems
• Anyone looking to reduce false signals with multi-factor validation
• Traders who utilize premarket levels in their strategy
Technical Notes
• Uses Pine Script v6
• Premarket hours: 4:00 AM - 9:30 AM EST
• Previous day levels pulled from daily timeframe for accuracy
• Maximum 500 labels to maintain chart performance
• All key levels update dynamically in real-time
________________________________________
Note: This indicator provides signal analysis only and should be used as part of a complete trading strategy. Past performance does not guarantee future results. Always practice proper risk management.
Orderbook Table1. Indicator Name
Orderbook Table
This is an order book style trading volume map
that upgraded the price from my first script to label
2. One-line Introduction
A visual heatmap-style orderbook simulator that displays volume and delta clustering across price levels.
3. Overall Description
Orderbook Table is a powerful visual tool designed to replicate an on-chart approximation of a traditional order book.
It scans historical candles within a specified lookback window and accumulates traded volume into price "bins" or levels.
Each level is color-coded based on total volume and directional bias (delta), offering a layered view of where market interest was concentrated.
The indicator approximates order flow by analyzing each candle's directional volume, separating bullish and bearish volume.
With adjustable parameters such as level depth, price bin density, delta sensitivity, and opacity, it provides a highly customizable visualization.
Displayed directly on the chart, each level shows the volume at that price zone, along with a price label, offset to the right of the current bar.
Traders can use this tool to detect high liquidity zones, support/resistance clusters, and volume imbalances that may precede future price movements.
4. Key Benefits (Title + Description)
✅ On-Chart Volume Heatmap
Shows volume distribution across price levels in real-time directly on the price chart, creating a live “orderbook” view.
✅ Delta-Based Bias Coloring
Color changes based on net buying/selling pressure (delta), making aggressive demand/supply zones easy to spot.
✅ High Customizability
Users can adjust lookback bars, price bins, opacity levels, and delta usage to fit any market condition or asset class.
✅ Lightweight Simulation
Approximates orderbook depth using candle data without needing L2 feed access—works on all assets and timeframes.
✅ Clear Visual Anchoring
Volume quantities and price levels are offset to the right for easy viewing without cluttering the active chart area.
✅ Fast Market Context Recognition
Quickly identify price levels where volume concentrated historically, improving decision-making for entries/exits.
5. Indicator User Guide
📌 Basic Concept
Orderbook Table analyzes a configurable number of past bars and distributes traded volume into price "bins."
Each bin shows how much volume occurred around that price level, optionally adjusted for bullish/bearish candle direction.
⚙️ Settings Overview
Lookback Bars: Number of candles to scan for volume history
Levels (Total): Number of price levels to display around the current price
Price Bins: Granularity of price segmentation for volume distribution
Shift Right: How far to offset labels to the right of the current bar
Max/Min Opacity: Controls visual strength of volume coloring
Use Candle Delta Approx.: If enabled, colors the volume based on candle direction (green for up, red for down)
📈 Example Timing
Look for green clusters (bullish bias) below current price → possible strong demand zones
Price enters a high-volume level with previously aggressive buyers (green), suggesting support
📉 Example Timing
Red clusters (bearish bias) above current price can act as resistance or supply zones
Price stalling at a red-heavy volume band may indicate exhaustion or reversal opportunity
🧪 Recommended Use
Use as a support/resistance mapping tool in ranging and trending markets
Pair with candlestick analysis or momentum indicators for refined entry/exit points
Combine with VWAP or volume profile for multi-dimensional volume insight
🔒 Cautions
This is an approximation, not a true L2 orderbook—volume is based on historical candles, not actual limit order data
In low-volume markets or higher timeframes, bin granularity may be too coarse—adjust "Price Bins" accordingly
Delta calculation is based on open-close direction and does not reflect true buy/sell volume splits
Avoid overinterpreting low-opacity (light color) zones—they may indicate low interest rather than true resistance/support
+++
CVD [able0.1]# CVD Overlay iOS Style - Complete User Guide
## 📖 Table of Contents
1. (#what-is-cvd)
2. (#installation-guide)
3. (#understanding-the-display)
4. (#reading-the-info-table)
5. (#settings--customization)
6. (#trading-strategies)
7. (#common-mistakes-to-avoid)
---
## 🎯 What is CVD?
**CVD (Cumulative Volume Delta)** tracks the **difference between buying and selling pressure** over time.
### Simple Explanation:
- **Positive CVD** (Orange) = More buying than selling = Bulls winning
- **Negative CVD** (Gray) = More selling than buying = Bears winning
- **Rising CVD** = Increasing buying pressure = Potential uptrend
- **Falling CVD** = Increasing selling pressure = Potential downtrend
### Why It Matters:
CVD helps you see **who's really in control** of the market - not just price movement, but actual buying/selling volume.
---
## 🚀 Installation Guide
### Step 1: Open Pine Editor
1. Go to TradingView
2. Click the **"Pine Editor"** tab at the bottom of the screen
3. Click **"New"** or open an existing script
### Step 2: Copy & Paste the Code
1. Select all existing code (Ctrl+A / Cmd+A)
2. Delete it
3. Copy the entire CVD iOS Style code
4. Paste it into Pine Editor
### Step 3: Add to Chart
1. Click **"Save"** button (or Ctrl+S / Cmd+S)
2. Click **"Add to Chart"** button
3. The indicator will appear on your chart!
### Step 4: Initial Setup
- The indicator appears as an **overlay** on your price chart
- You'll see an **orange/gray line** following price
- An **info table** appears in the top-right corner
---
## 📊 Understanding the Display
### Main Chart Elements:
#### 1. **CVD Line** (Orange/Gray)
- **Orange Line** = Positive CVD (buying pressure)
- **Gray Line** = Negative CVD (selling pressure)
- This line moves with your price chart but shows volume delta
#### 2. **CVD Zone** (Shaded Area)
- Light shaded box around the CVD line
- Shows the "range" of CVD movement
- Helps visualize CVD boundaries
#### 3. **Center Line** (Dotted)
- Gray dotted line in the middle of the zone
- Represents the "neutral" point
- CVD crossing this = shift in market control
#### 4. **Reference Asset Line** (Light Gray)
- Shows Bitcoin (BTC) price movement for comparison
- Helps you see if your asset moves with or against BTC
- Can be changed to any asset you want
#### 5. **CVD Label**
- Shows current CVD value
- Positioned above/below zone to avoid overlap
- Updates in real-time
#### 6. **Reset Background** (Very Light Gray)
- Appears when CVD resets
- Indicates a new calculation period
---
## 📋 Reading the Info Table
The info table (top-right) shows **8 key metrics**:
### Row 1: **Header**
```
╔═ CVD able ═╗ | 15m | ████████ | able
```
- **CVD able** = Indicator name + creator
- **15m** = Current timeframe
- **████████** = Visual decoration
- **able** = Creator signature
### Row 2: **CVD Value**
```
CVD▲ | 7.39K | ████████ | █
█
█
```
- **CVD▲** = CVD with trend arrow
- ▲ = CVD increasing
- ▼ = CVD decreasing
- ► = CVD unchanged
- **7.39K** = Actual CVD number
- **Progress Bar** = Visual strength (darker = stronger)
- **Vertical Bars** = Height shows intensity
### Row 3: **Delta**
```
◆DELTA | -1.274K | ████░░░░ | ░
░
```
- **Delta** = Volume change THIS BAR ONLY
- **Negative** = More selling this bar
- **Positive** = More buying this bar
- Shows **immediate** pressure (not cumulative)
### Row 4: **UP Volume**
```
UP↑ | -1.263K | ████████ | █
█
█
```
- Total **buying volume** this bar
- Higher = Stronger buying pressure
- Green/Orange vertical bars = Bullish strength
### Row 5: **DOWN Volume**
```
DN↓ | 2.643K | ████████ | ░
░
░
```
- Total **selling volume** this bar
- Higher = Stronger selling pressure
- Gray vertical bars = Bearish strength
### Row 6-7: **Reference Asset** (if enabled)
```
══ REF ══ | ══════ | ████████ | █
█
PRICE▲ | 4130.300 | ████████ | █
█
```
- **REF** = Reference asset header
- **PRICE▲** = Reference price with trend
- Shows if BTC (or chosen asset) is rising/falling
- Compare with your chart to see correlation
### Row 8: **Market Status**
```
◄STATUS► | NEUT | ████░░░░ | ▒
▒
```
- **BULL** = CVD positive + Delta positive = Strong buying
- **BEAR** = CVD negative + Delta negative = Strong selling
- **NEUT** = Mixed signals = Wait for clarity
**Status Colors:**
- **Orange background** = Bullish (good for long)
- **Gray background** = Bearish (good for short)
- **White background** = Neutral (no clear signal)
---
## ⚙️ Settings & Customization
### Main Settings (⚙️)
#### **CVD Reset**
- **None** = CVD never resets (from beginning of data)
- **On Higher Timeframe** = Resets when HTF candle closes
- 15m chart → Resets hourly
- 1h chart → Resets daily
- Recommended for most traders
- **On Session Start** = Resets at market open
- **On Visible Chart** = Resets from leftmost visible bar
#### **Precision**
- **Low (Fast)** = Uses 1m data, faster but less accurate
- **Medium** = Uses 5m data, balanced (recommended)
- **High** = Uses 15m data, most accurate but slower
#### **Cumulative**
- ✅ On = CVD accumulates over time (recommended)
- ❌ Off = Shows only current bar delta
#### **Show Labels**
- ✅ On = Shows CVD value label on chart
- ❌ Off = Cleaner chart, no label
#### **Show Info Table**
- ✅ On = Shows info table (recommended for beginners)
- ❌ Off = Hide table for minimalist view
---
### 🎨 iOS Style Colors
You can customize **every color** to match your chart theme:
#### **Primary Colors**
- **Primary (Orange)** = Main bullish color (#FF9500)
- **Secondary (Gray)** = Main bearish color (#8E8E93)
- **Background** = Table background (#FFFFFF)
- **Text** = Text color (#1C1C1E)
#### **Bullish/Bearish**
- **Bullish (Orange)** = Positive CVD color
- **Bearish (Gray)** = Negative CVD color
- **Opacity** = Zone transparency (0-100%)
- **Show Zone** = Enable/disable shaded area
#### **Table Colors** (📋)
- **Header Background** = Top row background
- **Header Text** = Top row text color
- **Cell Background** = Data cells background
- **Cell Text** = Data cells text color
- **Border** = Table border color
- **Accent Background** = Special rows background
- **Alert Background** = Warning/status background
---
### 📊 Reference Asset Settings
#### **Enable**
- ✅ On = Shows reference asset line
- ❌ Off = Hide reference asset
#### **Symbol**
- Default: `BINANCE:BTCUSDT`
- Can change to any asset:
- `BINANCE:ETHUSDT` (Ethereum)
- `SPX` (S&P 500)
- `DXY` (US Dollar Index)
- Any ticker symbol
#### **Color & Width**
- Customize line appearance
- Width: 1-4 (thickness)
---
## 💡 Trading Strategies
### Strategy 1: CVD Divergence (Beginner-Friendly)
**What to Look For:**
- Price making **higher highs** but CVD making **lower highs** = Bearish divergence
- Price making **lower lows** but CVD making **higher lows** = Bullish divergence
**How to Trade:**
1. Wait for divergence to form
2. Look for confirmation (price reversal, candlestick pattern)
3. Enter trade in divergence direction
4. Stop loss beyond recent high/low
**Example:**
```
Price: /\ /\ /\ (higher highs)
CVD: /\ / \/ (lower highs) = Bearish signal
```
### Strategy 2: CVD Trend Following (Intermediate)
**What to Look For:**
- **Strongly rising CVD** + **rising price** = Strong uptrend
- **Strongly falling CVD** + **falling price** = Strong downtrend
**How to Trade:**
1. Wait for CVD and price moving in same direction
2. Enter on pullbacks to support/resistance
3. Stay in trade while CVD trend continues
4. Exit when CVD trend breaks
**Signals:**
- CVD ▲▲▲ + Price ↑ = Go LONG
- CVD ▼▼▼ + Price ↓ = Go SHORT
### Strategy 3: CVD + Reference Asset (Advanced)
**What to Look For:**
- Your asset **rising** but BTC (reference) **falling** = Relative strength
- Your asset **falling** but BTC (reference) **rising** = Relative weakness
**How to Trade:**
1. Compare CVD movement with BTC
2. If your CVD rises faster than BTC = Buy signal
3. If your CVD falls faster than BTC = Sell signal
4. Use for **pair trading** or **asset selection**
### Strategy 4: Volume Delta Confirmation
**What to Look For:**
- **Large positive Delta** = Strong buying this bar
- **Large negative Delta** = Strong selling this bar
**How to Trade:**
1. Price breaks resistance + Large positive Delta = Confirmed breakout
2. Price breaks support + Large negative Delta = Confirmed breakdown
3. Use Delta to **confirm** price moves, not predict them
**Rules:**
- Delta > 2x average = Very strong pressure
- Delta near zero at key level = Weak move, likely false breakout
---
## 🎓 Reading Real Scenarios
### Scenario 1: Strong Buying Pressure
```
Table Shows:
CVD▲ | 12.5K | ████████ | ████ (CVD rising)
◆DELTA | +2.8K | ████████ | ▲ (Positive delta)
UP↑ | 3.1K | ████████ | ████ (High buy volume)
DN↓ | 0.3K | ██░░░░░░ | ░ (Low sell volume)
◄STATUS► | BULL | ████████ | ████ (Orange background)
```
**Interpretation:** Strong buying, good for LONG trades
### Scenario 2: Distribution (Hidden Selling)
```
Table Shows:
CVD► | 8.2K | ████░░░░ | ▒▒ (CVD flat)
◆DELTA | -1.5K | ████████ | ▼ (Negative delta)
UP↑ | 0.8K | ███░░░░░ | ░ (Low buy volume)
DN↓ | 2.3K | ████████ | ████ (High sell volume)
◄STATUS► | BEAR | ████████ | ░░░░ (Gray background)
```
**Interpretation:** Price may look stable, but selling increasing = Prepare for drop
### Scenario 3: Neutral/Choppy Market
```
Table Shows:
CVD► | 5.1K | ████░░░░ | ▒ (CVD sideways)
◆DELTA | +0.2K | ██░░░░░░ | ─ (Small delta)
UP↑ | 1.2K | ████░░░░ | ▒ (Medium buy)
DN↓ | 1.0K | ████░░░░ | ▒ (Medium sell)
◄STATUS► | NEUT | ████░░░░ | ▒▒ (White background)
```
**Interpretation:** No clear direction = Stay out or reduce position size
---
## ⚠️ Common Mistakes to Avoid
### Mistake 1: Trading on CVD Alone
- ❌ **Wrong:** "CVD is rising, I'll buy immediately"
- ✅ **Right:** "CVD is rising, let me check price structure, support/resistance, and wait for confirmation"
### Mistake 2: Ignoring Delta
- ❌ **Wrong:** Looking only at cumulative CVD
- ✅ **Right:** Watch both CVD (trend) and Delta (momentum)
- Delta shows **immediate** pressure changes
### Mistake 3: Wrong Timeframe
- ❌ **Wrong:** Using 1m chart with High Precision (too slow)
- ✅ **Right:** Match precision to timeframe:
- 1m-5m → Low Precision
- 15m-1h → Medium Precision
- 4h+ → High Precision
### Mistake 4: Not Using Reset
- ❌ **Wrong:** Using "None" reset for intraday trading
- ✅ **Right:** Use "On Higher Timeframe" to see fresh CVD each session
### Mistake 5: Overtrading Neutral Status
- ❌ **Wrong:** Forcing trades when STATUS = NEUT
- ✅ **Right:** Only trade clear BULL or BEAR status
### Mistake 6: Ignoring Reference Asset
- ❌ **Wrong:** Trading altcoin without checking BTC
- ✅ **Right:** Always check if BTC CVD agrees with your asset
---
## 🔥 Pro Tips
### Tip 1: Multi-Timeframe Analysis
- Check CVD on **3 timeframes**:
- Lower TF (15m) = Entry timing
- Current TF (1h) = Trade direction
- Higher TF (4h) = Overall trend
### Tip 2: Volume Confirmation
- Big price move + Small Delta = **Weak move** (likely reversal)
- Small price move + Big Delta = **Strong accumulation** (continuation)
### Tip 3: CVD Reset Zones
- Pay attention to **reset backgrounds** (light gray)
- Often marks **session starts** = High volatility periods
### Tip 4: Divergence + Status
- Bearish divergence + STATUS = BEAR = **Strongest short signal**
- Bullish divergence + STATUS = BULL = **Strongest long signal**
### Tip 5: Color Psychology
- **Orange** (Bullish) is **warm** = Buying energy
- **Gray** (Bearish) is **cool** = Selling pressure
- Train your eye to read colors instantly
### Tip 6: Table as Quick Scan
- Glance at table without reading numbers:
- **All orange** = Bullish
- **All gray** = Bearish
- **Mixed** = Wait
---
## 📱 Quick Reference Card
| Signal | CVD | Delta | Status | Action |
|--------|-----|-------|--------|--------|
| **Strong Buy** | ▲▲ High | ++ Positive | BULL | Long Entry |
| **Strong Sell** | ▼▼ Low | -- Negative | BEAR | Short Entry |
| **Divergence Buy** | ▲ Rising | Price ▼ | → BULL | Long Setup |
| **Divergence Sell** | ▼ Falling | Price ▲ | → BEAR | Short Setup |
| **Neutral** | → Flat | ~0 Near Zero | NEUT | Stay Out |
| **Accumulation** | → Flat | ++ Positive | NEUT→BULL | Watch for Breakout |
| **Distribution** | → Flat | -- Negative | NEUT→BEAR | Watch for Breakdown |
---
## 🆘 Troubleshooting
### Issue: "Indicator not showing"
- **Solution:** Make sure overlay=true in code, re-add to chart
### Issue: "Table overlaps with price"
- **Solution:** Change table position in code or use TradingView's "Move" feature
### Issue: "CVD line too far from price"
- **Solution:** This is normal! CVD is volume-based, not price-based. Focus on CVD direction, not position
### Issue: "Too many lines on chart"
- **Solution:** Disable "Show Zone" and "Show Labels" in settings for cleaner view
### Issue: "Calculations too slow"
- **Solution:** Change Precision to "Low (Fast)" or use higher timeframe
### Issue: "Reference asset not showing"
- **Solution:** Check if "Enable" is ON and symbol is valid (e.g., BINANCE:BTCUSDT)
---
## 🎬 Getting Started Checklist
- Install indicator on TradingView
- Set precision to "Medium"
- Set reset to "On Higher Timeframe"
- Enable info table
- Add reference asset (BTC)
- Practice reading the table on demo account
- Test on different timeframes (15m, 1h, 4h)
- Compare CVD with your current strategy
- Paper trade for 1 week before going live
- Keep a trading journal of CVD signals
---
## 📚 Summary
**CVD shows WHO is winning: Buyers or Sellers**
**Key Points:**
1. **Orange/Rising CVD** = Buying pressure = Bullish
2. **Gray/Falling CVD** = Selling pressure = Bearish
3. **Delta** = Immediate momentum THIS BAR
4. **Status** = Overall market condition
5. **Always confirm** with price action & other indicators
**Remember:**
- CVD is a **tool**, not a crystal ball
- Use with proper risk management
- Practice makes perfect
- Stay disciplined!
---
**Created by: able**
**Version:** iOS Style v1.0
**Contact:** For questions, refer to TradingView community
Happy Trading! 🚀📈
Pso VP 2.0This indicator provides an advanced volume analysis tool that visualizes trading activity across different price levels and automatically identifies key support and resistance zones.
How It Works:
The Volume Profile analyzes historical price and volume data within a specified lookback period, distributing volume across horizontal price levels. Unlike traditional volume indicators that show volume over time, this tool displays volume at price, revealing where the most significant trading activity has occurred.
The algorithm:
Divides the price range into customizable horizontal bars (bins)
Calculates and accumulates volume for each price level
Identifies high-volume nodes that often act as support or resistance levels
Uses percentile filtering to highlight the most significant trading areas
Key Features:
Automatic S/R Detection: Uses volume percentile filtering to identify the most significant price levels
Dynamic Support/Resistance Lines: Automatically draws horizontal black lines at high-volume areas that typically act as price magnets or barriers
Customizable Parameters: Full control over lookback period, number of price bars, percentile thresholds, profile width, opacity, and line projections
Clean Aesthetic: Monochrome design for professional chart presentation
JokaBAR
This script combines my own liquidity/liq-levels engine with open-source code from BigBeluga’s Volumatic indicators:
• “Volumatic Variable Index Dynamic Average ”
• “Volumatic Support/Resistance Levels ”
The original code is published under the Mozilla Public License 2.0 and is reused here accordingly.
What this script does
Joka puts Volumatic trend logic, dynamic support/resistance and a custom liquidation-levels module into a single overlay. The idea is to give traders one clean view of trend direction, key reactive zones and potential liquidation areas where leveraged positions can be forced out of the market.
Volumatic logic is used to build a dynamic average and adaptive levels that react to volume and volatility. On top of that, the script plots configurable liquidation zones for different leverage tiers (e.g. 5x, 10x, 25x, 50x, 100x).
How to use it
Apply the script on pairs where leverage is actually used (perpetual futures / margin).
Use the Volumatic average as a trend filter (above = long bias, below = short bias).
Treat Volumatic support/resistance levels as key reaction zones for entries, partials and stops.
Read the liquidation levels as context: clusters show where forced liquidations can fuel strong moves and bounces.
Keep the chart clean — this tool is designed to be used without stacking extra indicators on top.
The script is published as open-source in line with TradingView House Rules so that other traders can study, tweak and build on it.
Gann Levels (Auto) by RRR📌 Gann Levels (Auto) — Intraday, Swing & Elliott Wave Precision Tool
Gann Levels (Auto) is a high-accuracy price-reaction indicator designed for intraday scalpers, swing traders, and Elliott Wave traders who want clean, auto-updating support and resistance levels without manually drawing anything.
The indicator automatically detects the latest swing high & swing low and plots the 8 Gann Octave Levels between them. These levels act as a complete price map—showing equilibrium, structure, trend continuation zones, and reversal points with extreme precision.
🔥 Why This Indicator Stands Out
✔ Fully automatic swing detection
Levels update as structure evolves — no manual adjustments.
✔ All Gann Octave levels
Plots 1/8 through 8/8 including the critical 4/8 midpoint.
✔ Intraday-optimized
Exceptional on 1m, 3m, 5m, and 15m charts.
✔ Ultra-clean support & resistance
Levels act as reliable barriers and breakout zones.
⭐ MOST IMPORTANT LEVELS FOR INTRADAY
4/8 – Midpoint (Major Decision Pivot)
Strongest Gann level.
Controls trend or reversal for the session.
Breakout → Trend Day
Rejection → Reversal Day
8/8 & 0/8 – Extreme Structure Edges
Most likely zones for intraday reversals.
Perfect for scalp entries when combined with volume exhaustion.
🎯 How to Trade ELLIOTT WAVE Using Gann Levels
This indicator is exceptionally powerful when combined with Elliott Wave Theory.
Here is how to use it wave-by-wave:
🔵 Wave 2 → Identify Bottom Using 0/8 or 1/8 Levels
Wave 2 typically retraces deep but remains above key structure.
Gann confirmation:
Price stops at 0/8 or 1/8 zone
Rejection wick + low volume breakdown attempt
Bullish intent starts forming
This gives a perfect Wave 3 entry zone.
🔴 Wave 3 → Breakout Above 4/8 Midpoint
Wave 3 is the strongest impulsive wave.
The 4/8 level works like a force-field.
Wave 3 confirmation:
Price breaks and retests 4/8
Strong volume
No deep pullbacks after break
This is one of the most reliable Elliott + Gann trades.
🟡 Wave 4 → Uses 3/8 or 5/8 as Support/Resistance
Wave 4 is corrective and shallow compared to Wave 2.
Gann alignment:
Wave 4 often consolidates between 3/8 and 5/8
Levels act like range boundaries
Avoid trading inside chop; wait for breakout
This gives perfect continuation entries for Wave 5.
🟣 Wave 5 → Ends Near 7/8 or 8/8 Extreme Zone
Wave 5 usually ends in overbought territory.
Gann confirmation:
Price hits 7/8 or 8/8
Momentum weakens
Divergence builds (RSI/MACD optional)
Last push = exhaustion
This is where reversals or major pullbacks begin.
💥 BONUS: Corrective Waves (A-B-C)
Wave A:
Often rejects from 4/8 or 5/8.
Wave B:
Typically trapped between 3/8–5/8.
Wave C:
Usually ends around 0/8 (for bullish trend)
or 8/8 (for bearish trend).
These zones give ultra-high confidence entries.
⚙️ Who This Indicator Is Perfect For
Elliott Wave traders
Intraday scalpers
Swing traders
Price action & structure traders
Traders who want automatic support-resistance levels
Traders who want clean, non-cluttered levels
⚠️ Disclaimer
This indicator is for educational purposes only.
Trading involves risk. Always use proper risk management.
Dynamic S&R Projector [Polarity Flip]Support and Resistance should not be static. It should tell a story.
Most traders clutter their charts with manually drawn lines, often forgetting which ones were important or which timeframe they came from. This indicator automates the entire process of identifying market structure, adapting dynamically to your trading style while using Volume Price Analysis (VPA) to separate "Smart Money" levels from random noise.
It combines three professional concepts into one tool: Multi-Timeframe Projection, Volume Strength Filtering, and Live Polarity Flipping.
Who is this for?
Day Traders: Project Daily levels onto your 1-minute or 5-minute charts. Stop trading in a vacuum; see the walls before you hit them.
Swing Traders: Project Weekly levels onto your Daily chart to find major trend reversals.
Investors: Project Monthly levels to identify multi-year accumulation zones.
Core Features
1. Smart Timeframe (Auto-Detection) No more toggling settings. The indicator detects what chart you are viewing and automatically projects the next significant Higher Timeframe (HTF) structure:
Viewing Intraday (< Daily)? → Projects Daily Pivots.
Viewing Daily? → Projects Weekly Pivots.
Viewing Weekly? → Projects Monthly Pivots.
2. VPA Strength Filtering (The "Truth" Serum) Not all levels are equal. This script grades every pivot based on the volume activity at the moment it was formed:
Thick Solid Line: Formed on High Volume (>1.5x Average). This is an "Institutional Level." Expect hard bounces.
Thin Dashed Line: Formed on Low Volume. This is a weak structure.
3. Live Polarity Flip (Support ↔ Resistance) The script monitors price action in real-time to respect the "Principle of Polarity."
Wick Protection: The color change is based strictly on the Candle Close. If price wicks through a level but closes back inside, the line retains its original color (rejecting the fakeout).
The Flip: Once price successfully closes past a level, the color instantly flips (Red becomes Green, or Green becomes Red) to indicate the new market state.
How to Trade This Indicator (Example Strategies)
Strategy A: The "Concrete Wall" Bounce (Day & Swing) Identify a Thick Green Line below the current price. This represents a Strong HTF Support defended by institutional volume.
Action: Set Limit Buy orders at the line or wait for a bullish reversal candle (Hammer) to form at the touch.
Strategy B: The "Paper Wall" Breakout (Momentum) Identify price approaching a Thin Dashed Red Line (Weak Resistance).
Action: Since this level lacks volume backing, do not fade it. Look for a breakout setup as price is likely to slice through easily.
Strategy C: The "Flip & Retest" (Trend Following) Watch for a Thick Red Line to turn Green. This means resistance has been conquered.
Action: Wait for price to pull back to this new Green line. If it holds (the line stays Green), enter long. You are now using the "roof" as a "floor."
Settings Guide
Calculation Mode:
Auto (Higher TF): The recommended "Smart" mode described above.
Use Current Chart: Finds pivots on the exact timeframe you are viewing (good for scalping structure).
Fixed Manual: Locks the projection to a specific timeframe (e.g., always show Daily).
Pivot Lookback (Sensitivity):
Default (10/10): Balances major and minor structure.
Higher (20/20): Shows only the most critical major market turns.
Max Number of Lines: Limits how many historical levels are shown to keep your chart clean.
***********************************************************************************************
Disclaimer: This tool is for educational purposes and decision support. Past volume and price action do not guarantee future results. Always manage your risk.
Flux-Tensor Singularity [FTS]Flux-Tensor Singularity - Multi-Factor Market Pressure Indicator
The Flux-Tensor Singularity (FTS) is an advanced multi-factor oscillator that combines volume analysis, momentum tracking, and volatility-weighted normalization to identify critical market inflection points. Unlike traditional single-factor indicators, FTS synthesizes price velocity, volume mass, and volatility context into a unified framework that adapts to changing market regimes.
This indicator identifies extreme market conditions (termed "singularities") where multiple confirming factors converge, then uses a sophisticated scoring system to determine directional bias. It is designed for traders seeking high-probability setups with built-in confluence requirements.
THEORETICAL FOUNDATION
The indicator is built on the premise that market time is not constant - different market conditions contain varying levels of information density. A 1-minute bar during a major news event contains far more actionable information than a 1-minute bar during overnight low-volume trading. Traditional indicators treat all bars equally; FTS does not.
The theoretical framework draws conceptual parallels to physics (purely as a mental model, not literal physics):
Volume as Mass: Large volume represents significant market participation and "weight" behind price moves. Just as massive objects have stronger gravitational effects, high-volume moves carry more significance.
Price Change as Velocity: The rate of price movement through price space represents momentum and directional force.
Volatility as Time Dilation: When volatility is high relative to its historical norm, the "information density" of each bar increases. The indicator weights these periods more heavily, similar to how time dilates near massive objects in physics.
This is a pedagogical metaphor to create a coherent mental model - the underlying mathematics are standard financial calculations combined in a novel way.
MATHEMATICAL FRAMEWORK
The indicator calculates a composite singularity value through four distinct steps:
Step 1: Raw Singularity Calculation
S_raw = (ΔP × V) × γ²
Where:
ΔP = Price Velocity = close - close
V = Volume Mass = log(volume + 1)
γ² = Time Dilation Factor = (ATR_local / ATR_global)²
Volume Transformation: Volume is log-transformed because raw volume can have extreme outliers (10x-100x normal). The logarithm compresses these spikes while preserving their significance. This is standard practice in volume analysis.
Volatility Weighting: The ratio of short-term ATR (5 periods) to long-term ATR (user-defined lookback) is squared to create a volatility amplification factor. When local volatility exceeds global volatility, this ratio increases, amplifying the raw singularity value. This makes the indicator regime-aware.
Step 2: Normalization
The raw singularity values are normalized to a 0-100 scale using a stochastic-style calculation:
S_normalized = ((S_raw - S_min) / (S_max - S_min)) × 100
Where S_min and S_max are the lowest and highest raw singularity values over the lookback period.
Step 3: Epsilon Compression
S_compressed = 50 + ((S_normalized - 50) / ε)
This is the critical innovation that makes the sensitivity control functional. By applying compression AFTER normalization, the epsilon parameter actually affects the final output:
ε < 1.0: Expands range (more signals)
ε = 1.0: No change (default)
ε > 1.0: Compresses toward 50 (fewer, higher-quality signals)
For example, with ε = 2.0, a normalized value of 90 becomes 70, making threshold breaches rarer and more significant.
Step 4: Smoothing
S_final = EMA(S_compressed, smoothing_period)
An exponential moving average removes high-frequency noise while preserving trend.
SIGNAL GENERATION LOGIC
When the tensor crosses above the upper threshold (default 90) or below the lower threshold (default 10), an extreme event is detected. However, the indicator does NOT immediately generate a buy or sell signal. Instead, it analyzes market context through a multi-factor scoring system:
Scoring Components:
Price Structure (+1 point): Current bar bullish/bearish
Momentum (+1 point): Price higher/lower than N bars ago
Trend Context (+2 points): Fast EMA above/below slow EMA (weighted heavier)
Acceleration (+1 point): Rate of change increasing/decreasing
Volume Multiplier (×1.5): If volume > average, multiply score
The highest score (bullish vs bearish) determines signal direction. This prevents the common indicator failure mode of "overbought can stay overbought" by requiring directional confirmation.
Signal Conditions:
A BUY signal requires:
Extreme event detection (tensor crosses threshold)
Bullish score > Bearish score
Price confirmation: Bullish candle (optional, user-controlled)
Volume confirmation: Volume > average (optional, user-controlled)
Momentum confirmation: Positive momentum (optional, user-controlled)
A SELL signal requires the inverse conditions.
INPUTS EXPLAINED - Core Parameters:
Global Horizon (Context): Default 20. Lookback period for normalization and volatility comparison. Higher values = smoother but less responsive. Lower values = more signals but potentially more noise.
Tensor Smoothing: Default 3. EMA period applied to final output. Removes "quantum foam" (high-frequency noise). Range 1-20.
Singularity Threshold: Default 90. Values above this (or below 100-threshold) trigger extreme event detection. Higher = rarer, stronger signals.
Signal Sensitivity (Epsilon): Default 1.0. Post-normalization compression factor. This is the key innovation - it actually works because it's applied AFTER normalization. Range 0.1-5.0.
Signal Interpreter Toggles:
Require Price Confirmation: Default ON. Only generates buy signals on bullish candles, sell signals on bearish candles. Reduces false signals but may delay entry.
Require Volume Confirmation: Default ON. Only signals when volume > average. Critical for stocks/crypto, less important for forex (unreliable volume data).
Use Momentum Filter: Default ON. Requires momentum agreement with signal direction. Prevents counter-trend signals.
Momentum Lookback: Default 5. Number of bars for momentum calculation. Shorter = more responsive, longer = trend-following bias.
Visual Controls:
Colors: Customizable colors for bullish flux, bearish flux, background, and event horizon.
Visual Transparency: Default 85. Master control for all visual elements (accretion disk, field lines, particles, etc.). Range 50-99. Signals and dashboard have separate controls.
Visibility Toggles: Individual on/off switches for:
Gravitational field lines (trend EMAs)
Field reversals (trend crossovers)
Accretion disk (background gradient)
Singularity diamonds (neutral extreme events)
Energy particles (volume bursts)
Event horizon flash (extreme event background)
Signal background flash
Signal Size: Tiny/Small/Normal triangle size
Signal Offsets: Separate controls for buy and sell signal vertical positioning (percentage of price)
Dashboard Settings:
Show Dashboard: Toggle on/off
Position: 9 placement options (all corners, centers, middles)
Text Size: Tiny/Small/Normal/Large
Background Transparency: 0-50, separate from visual transparency
VISUAL ELEMENTS EXPLAINED
1. Accretion Disk (Background Gradient):
A three-layer gradient background that intensifies as the tensor approaches extremes. The outer disk appears at any non-neutral reading, the inner disk activates above 70 or below 30, and the core layer appears above 85 or below 15. Color indicates direction (cyan = bullish, red = bearish). This provides instant visual feedback on market pressure intensity.
2. Gravitational Field Lines (EMAs):
Two trend-following EMAs (10 and 30 period) visualized as colored lines. These represent the "curvature" of market trend - when they diverge, trend is strong; when they converge, trend is weakening. Crossovers mark potential trend reversals.
3. Field Reversals (Circles):
Small circles appear when the fast EMA crosses the slow EMA, indicating a potential trend change. These are distinct from extreme events and appear at normal market structure shifts.
4. Singularity Diamonds:
Small diamond shapes appear when the tensor reaches extreme levels (>90 or <10) but doesn't meet the full signal criteria. These are "watch" events - extreme pressure exists but directional confirmation is lacking.
5. Energy Particles (Dots):
Tiny dots appear when volume exceeds 2× average, indicating significant participation. Color matches bar direction. These highlight genuine high-conviction moves versus low-volume drifts.
6. Event Horizon Flash:
A golden background flash appears the instant any extreme threshold is breached, before directional analysis. This alerts you to pay attention.
7. Signal Background Flash:
When a full buy/sell signal is confirmed, the background flashes cyan (buy) or red (sell). This is your primary alert that all conditions are met.
8. Signal Triangles:
The actual buy (▲) and sell (▼) markers. These only appear when ALL selected confirmation criteria are satisfied. Position is offset from bars to avoid overlap with other indicators.
DASHBOARD METRICS EXPLAINED
The dashboard displays real-time calculated values:
Event Density: Current tensor value (0-100). Above 90 or below 10 = critical. Icon changes: 🔥 (extreme high), ❄️ (extreme low), ○ (neutral).
Time Dilation (γ): Current volatility ratio squared. Values >2.0 indicate extreme volatility environments. >1.5 = elevated, >1.0 = above average. Icon: ⚡ (extreme), ⚠ (elevated), ○ (normal).
Mass (Vol): Log-transformed volume value. Compared to volume ratio (current/average). Icon: ● (>2× avg), ◐ (>1× avg), ○ (below avg).
Velocity (ΔP): Raw price change. Direction arrow indicates momentum direction. Shows the actual price delta value.
Bullish Flux: Current bullish context score. Displayed as both a bar chart (visual) and numeric value. Brighter when bullish score dominates.
Bearish Flux: Current bearish context score. Same visualization as bullish flux. These scores compete - the winner determines signal direction.
Field: Trend direction based on EMA relationship. "Repulsive" (uptrend), "Attractive" (downtrend), "Neutral" (ranging). Icon: ⬆⬇↔
State: Current market condition:
🚀 EJECTION: Buy signal active
💥 COLLAPSE: Sell signal active
⚠ CRITICAL: Extreme event, no directional confirmation
● STABLE: Normal market conditions
HOW TO USE THE INDICATOR
1. Wait for Extreme Events:
The indicator is designed to be selective. Don't trade every fluctuation - wait for tensor to reach >90 or <10. This alone is not a signal.
2. Check Context Scores:
Look at the Bullish Flux vs Bearish Flux in the dashboard. If scores are close (within 1-2 points), the market is indecisive - skip the trade.
3. Confirm with Signals:
Only act when a full triangle signal appears (▲ or ▼). This means ALL your selected confirmation criteria have been met.
4. Use with Price Structure:
Combine with support/resistance levels. A buy signal AT support is higher probability than a buy signal in the middle of nowhere.
5. Respect the Dashboard State:
When State shows "CRITICAL" (⚠), it means extreme pressure exists but direction is unclear. These are the most dangerous moments - wait for resolution.
6. Volume Matters:
Energy particles (dots) and the Mass metric tell you if institutions are participating. Signals without volume confirmation are lower probability.
MARKET AND TIMEFRAME RECOMMENDATIONS
Scalping (1m-5m):
Lookback: 10-14
Smoothing: 5-7
Threshold: 85
Epsilon: 0.5-0.7
Note: Expect more noise. Confirm with Level 2 data. Best on highly liquid instruments.
Intraday (15m-1h):
Lookback: 20-30 (default settings work well)
Smoothing: 3-5
Threshold: 90
Epsilon: 1.0
Note: Sweet spot for the indicator. High win rate on liquid stocks, forex majors, and crypto.
Swing Trading (4h-1D):
Lookback: 30-50
Smoothing: 3
Threshold: 90-95
Epsilon: 1.5-2.0
Note: Signals are rare but high conviction. Combine with higher timeframe trend analysis.
Position Trading (1D-1W):
Lookback: 50-100
Smoothing: 5-7
Threshold: 95
Epsilon: 2.0-3.0
Note: Extremely rare signals. Only trade the most extreme events. Expect massive moves.
Market-Specific Settings:
Forex (EUR/USD, GBP/USD, etc.):
Volume data is unreliable (spot forex has no centralized volume)
Disable "Require Volume Confirmation"
Focus on momentum and trend filters
News events create extreme singularities
Best on 15m-1h timeframes
Stocks (High-Volume Equities):
Volume confirmation is CRITICAL - keep it ON
Works excellently on AAPL, TSLA, SPY, etc.
Morning session (9:30-11:00 ET) shows highest event density
Earnings announcements create guaranteed extreme events
Best on 5m-1h for day trading, 1D for swing trading
Crypto (BTC, ETH, major alts):
Reduce threshold to 85 (crypto has constant high volatility)
Volume spikes are THE primary signal - keep volume confirmation ON
Works exceptionally well due to 24/7 trading and high volatility
Epsilon can be reduced to 0.7-0.8 for more signals
Best on 15m-4h timeframes
Commodities (Gold, Oil, etc.):
Gold responds to macro events (Fed announcements, geopolitical events)
Oil responds to supply shocks
Use daily timeframe minimum
Increase lookback to 50+
These are slow-moving markets - be patient
Indices (SPX, NDX, etc.):
Institutional volume matters - keep volume confirmation ON
Opening hour (9:30-10:30 ET) = highest singularity probability
Strong correlation with VIX - high VIX = more extreme events
Best on 15m-1h for day trading
WHAT MAKES THIS INDICATOR UNIQUE
1. Post-Normalization Sensitivity Control:
Unlike most oscillators where sensitivity controls don't actually work (they're applied before normalization, which then rescales everything), FTS applies epsilon compression AFTER normalization. This means the sensitivity parameter genuinely affects signal frequency. This is a novel implementation not found in standard oscillators.
2. Multi-Factor Confluence Requirement:
The indicator doesn't just detect "overbought" or "oversold" - it detects extreme conditions AND THEN analyzes context through five separate factors (price structure, momentum, trend, acceleration, volume). Most indicators are single-factor; FTS requires confluence.
3. Volatility-Weighted Normalization:
By squaring the ATR ratio (local/global), the indicator adapts to changing market regimes. A 1% move in a low-volatility environment is treated differently than a 1% move in a high-volatility environment. Traditional indicators treat all moves equally regardless of context.
4. Volume Integration at the Core:
Volume isn't an afterthought or optional filter - it's baked into the fundamental equation as "mass." The log transformation handles outliers elegantly while preserving significance. Most price-based indicators completely ignore volume.
5. Adaptive Scoring System:
Rather than fixed buy/sell rules ("RSI >70 = sell"), FTS uses competitive scoring where bullish and bearish evidence compete. The winner determines direction. This solves the classic problem of "overbought markets can stay overbought during strong uptrends."
6. Comprehensive Visual Feedback:
The multi-layer visualization system (accretion disk, field lines, particles, flashes) provides instant intuitive feedback on market state without requiring dashboard reading. You can see pressure building before extreme thresholds are hit.
7. Separate Extreme Detection and Signal Generation:
"Singularity diamonds" show extreme events that don't meet full criteria, while "signal triangles" only appear when ALL conditions are met. This distinction helps traders understand when pressure exists versus when it's actionable.
COMPARISON TO EXISTING INDICATORS
vs. RSI/Stochastic:
These normalize price relative to recent range. FTS normalizes (price change × log volume × volatility ratio) - a composite metric, not just price position.
vs. Chaikin Money Flow:
CMF combines price and volume but lacks volatility context and doesn't use adaptive normalization or post-normalization compression.
vs. Bollinger Bands + Volume:
Bollinger Bands show volatility but don't integrate volume or create a unified oscillator. They're separate components, not synthesized.
vs. MACD:
MACD is pure momentum. FTS combines momentum with volume weighting and volatility context, plus provides a normalized 0-100 scale.
The specific combination of log-volume weighting, squared volatility amplification, post-normalization epsilon compression, and multi-factor directional scoring is unique to this indicator.
LIMITATIONS AND PROPER DISCLOSURE
Not a Holy Grail:
No indicator is perfect. This tool identifies high-probability setups but cannot predict the future. Losses will occur. Use proper risk management.
Requires Confirmation:
Best used in conjunction with price action analysis, support/resistance levels, and higher timeframe trend. Don't trade signals blindly.
Volume Data Dependency:
On forex (spot) and some low-volume instruments, volume data is unreliable or tick-volume only. Disable volume confirmation in these cases.
Lagging Components:
The EMA smoothing and trend filters are inherently lagging. In extremely fast moves, signals may appear after the initial thrust.
Extreme Event Rarity:
With conservative settings (high threshold, high epsilon), signals can be rare. This is by design - quality over quantity. If you need more frequent signals, reduce threshold to 85 and epsilon to 0.7.
Not Financial Advice:
This indicator is an analytical tool. All trading decisions and their consequences are solely your responsibility. Past performance does not guarantee future results.
BEST PRACTICES
Don't trade every singularity - wait for context confirmation
Higher timeframes = higher reliability
Combine with support/resistance for entry refinement
Volume confirmation is CRITICAL for stocks/crypto (toggle off only for forex)
During major news events, singularities are inevitable but direction may be uncertain - use wider stops
When bullish and bearish flux scores are close, skip the trade
Test settings on your specific instrument/timeframe before live trading
Use the dashboard actively - it contains critical diagnostic information
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Scout Regiment - Bias# Scout Regiment - Bias Indicator
## English Documentation
### Overview
Scout Regiment - Bias is a technical indicator that measures the deviation (bias) between the current price and exponential moving averages (EMAs). It helps traders identify overbought/oversold conditions, trend strength, and potential reversal points through divergence detection.
### What is Bias?
Bias measures how far the price has moved away from a moving average, expressed as a percentage:
- **Positive Bias**: Price is above the EMA (potential overbought)
- **Negative Bias**: Price is below the EMA (potential oversold)
- **Formula**: Bias = (Price - EMA) / EMA × 100
### Key Features
#### 1. **Triple EMA Bias Lines**
The indicator calculates bias from three different EMAs:
- **EMA 55 Bias** (Default: Green/Red, 1px line)
- Short-term bias measurement
- Quick response to price changes
- Best for intraday and swing trading
- **EMA 144 Bias** (Pink, 2px line)
- Medium-term bias measurement
- Balanced response to price movements
- Ideal for swing trading
- **EMA 233 Bias** (White, 2px line)
- Long-term bias measurement
- Slower response, more stable
- Best for position trading
**Color Coding:**
- Green: Price above EMA (bullish)
- Red: Price below EMA (bearish)
#### 2. **Visual Components**
**Histogram Display**
- Shows EMA 55 bias as a histogram for easy visualization
- Green bars: Price above EMA 55
- Red bars: Price below EMA 55
- Can be toggled on/off
**Background Color**
- Light green background: Bullish bias (price above EMA 55)
- Light red background: Bearish bias (price below EMA 55)
- Optional display for cleaner charts
**Zero Line**
- White horizontal line at 0%
- Reference point for positive/negative bias
- Crossovers indicate trend changes
**Crossover Labels**
- "突破" (Breakout): When bias crosses above zero
- "跌破" (Breakdown): When bias crosses below zero
- Can be enabled/disabled for clarity
#### 3. **Divergence Detection**
The indicator automatically detects regular divergences for all three bias lines:
**Bullish Divergence (Yellow Labels)**
- Price makes lower lows
- Bias makes higher lows
- Suggests potential upward reversal
- Labels: "55涨", "144涨", "233涨"
**Bearish Divergence (Blue Labels)**
- Price makes higher highs
- Bias makes lower highs
- Suggests potential downward reversal
- Labels: "55跌", "144跌", "233跌"
**Divergence Parameters** (Customizable for each EMA):
- Left Lookback: Bars to the left of pivot (default: 5)
- Right Lookback: Bars to the right of pivot (default: 1)
- Max Lookback Range: Maximum distance between pivots (default: 60)
- Min Lookback Range: Minimum distance between pivots (default: 5)
### Configuration Settings
#### Bias Settings
- **EMA Periods**: Customize lengths for EMA 55, 144, and 233
- **Price Source**: Choose calculation source (default: close)
- **Enable/Disable**: Toggle each bias line independently
#### Display Settings
- **Show Histogram**: Toggle histogram display
- **Show Background Color**: Toggle background coloring
- **Show Crossover Labels**: Toggle breakout/breakdown labels
#### Divergence Settings (Per EMA)
- Individual controls for EMA 55, 144, and 233 divergences
- Customizable lookback parameters for precision tuning
- Adjustable range settings for different market conditions
### How to Use
#### For Trend Trading
1. **Identify Trend Direction**
- Price above zero = Uptrend
- Price below zero = Downtrend
2. **Confirm with Multiple Timeframes**
- EMA 55: Short-term trend
- EMA 144: Medium-term trend
- EMA 233: Long-term trend
3. **Trade in Direction of Bias**
- All three lines positive = Strong uptrend
- All three lines negative = Strong downtrend
#### For Mean Reversion Trading
1. **Identify Extremes**
- High positive bias (>5-10%) = Overbought
- High negative bias (<-5 to -10%) = Oversold
2. **Wait for Confirmation**
- Look for bias to turn back toward zero
- Watch for crossover labels
3. **Enter on Reversal**
- Enter long when extreme negative bias starts rising
- Enter short when extreme positive bias starts falling
#### For Divergence Trading
1. **Spot Divergence Labels**
- Yellow labels = Bullish divergence (potential buy)
- Blue labels = Bearish divergence (potential sell)
2. **Confirm with Price Action**
- Wait for price to confirm with structure break
- Look for support/resistance reactions
3. **Use Multiple EMAs**
- EMA 55 divergence: Quick reversals
- EMA 144 divergence: Reliable signals
- EMA 233 divergence: Major trend changes
#### For Multi-Timeframe Analysis
1. **Check Long-term Bias** (EMA 233)
- Determines overall market direction
2. **Find Medium-term Entry** (EMA 144)
- Look for pullbacks in long-term trend
3. **Time Short-term Entry** (EMA 55)
- Enter when short-term aligns with longer timeframes
### Trading Strategies
#### Strategy 1: Triple Confirmation
- Wait for all three bias lines to be positive (or negative)
- Enter in direction of unanimous bias
- Exit when any line crosses zero
- Best for: Strong trending markets
#### Strategy 2: Divergence Trading
- Enable all divergence detection
- Take trades only when divergence appears
- Confirm with price structure
- Best for: Range-bound and reversal setups
#### Strategy 3: Zero Line Crossover
- Enable crossover labels
- Enter long on "突破" labels
- Enter short on "跌破" labels
- Use stop loss at recent swing points
- Best for: Trend following
#### Strategy 4: Extreme Reversion
- Wait for bias to reach extremes (>10% or <-10%)
- Enter counter-trend when bias reverses
- Exit at zero line
- Best for: Ranging markets
### Best Practices
1. **Combine with Price Action**
- Don't trade bias alone
- Confirm with support/resistance
- Look for candlestick patterns
2. **Use Multiple Timeframes**
- Check higher timeframe bias
- Trade in direction of larger trend
- Use lower timeframe for entry timing
3. **Manage Risk**
- Set stop losses beyond recent swings
- Don't fight extreme bias in strong trends
- Reduce position size at extremes
4. **Customize for Your Market**
- Volatile assets: Use wider ranges
- Stable assets: Use tighter ranges
- Adjust EMA periods for your timeframe
5. **Watch for False Signals**
- Multiple small divergences = Less reliable
- Divergences at extremes = More reliable
- Confirm with other indicators
### Indicator Combinations
**With Volume:**
- High bias + Low volume = Weak move
- High bias + High volume = Strong move
**With Moving Averages:**
- Check if price is above/below key EMAs
- Bias confirms EMA trend strength
**With RSI/MACD:**
- Multiple indicator divergence = Stronger signal
- Use bias for overbought/oversold confirmation
### Performance Tips
- Disable unused features for faster loading
- Use histogram for quick visual reference
- Enable background color for trend clarity
- Use divergence detection selectively
### Common Patterns
1. **Bias Expansion**: Bias increasing = Strong trend
2. **Bias Contraction**: Bias decreasing = Trend weakening
3. **Zero Line Bounce**: Price respects EMA as support/resistance
4. **Extreme Bias**: Over-extension, watch for reversal
5. **Divergence Cluster**: Multiple EMAs diverging = High probability reversal
### Alert Conditions
You can set alerts for:
- Bias crossing above/below zero
- Extreme bias levels
- Divergence detection
- All three bias lines aligned
---
## 中文说明文档
### 概述
Scout Regiment - Bias 是一个技术指标，用于测量当前价格与指数移动平均线（EMA）之间的偏离程度（乖离率）。它帮助交易者识别超买超卖状况、趋势强度，以及通过背离检测发现潜在的反转点。
### 什么是乖离率？
乖离率衡量价格偏离移动平均线的程度，以百分比表示：
- **正乖离**：价格高于EMA（可能超买）
- **负乖离**：价格低于EMA（可能超卖）
- **计算公式**：乖离率 = (价格 - EMA) / EMA × 100
### 核心功能
#### 1. **三重EMA乖离率线**
指标计算三条不同EMA的乖离率：
- **EMA 55 乖离率**（默认：绿色/红色，1像素线）
- 短期乖离测量
- 对价格变化反应快速
- 适合日内和波段交易
- **EMA 144 乖离率**（粉色，2像素线）
- 中期乖离测量
- 对价格波动反应平衡
- 最适合波段交易
- **EMA 233 乖离率**（白色，2像素线）
- 长期乖离测量
- 反应较慢，更稳定
- 适合仓位交易
**颜色编码：**
- 绿色：价格高于EMA（看涨）
- 红色：价格低于EMA（看跌）
#### 2. **视觉组件**
**柱状图显示**
- 以柱状图形式显示EMA 55乖离率，便于可视化
- 绿色柱：价格高于EMA 55
- 红色柱：价格低于EMA 55
- 可开关显示
**背景颜色**
- 浅绿色背景：看涨乖离（价格高于EMA 55）
- 浅红色背景：看跌乖离（价格低于EMA 55）
- 可选显示，图表更清爽
**零轴**
- 零点位置的白色横线
- 正负乖离的参考点
- 穿越表示趋势变化
**穿越标签**
- "突破"：乖离率向上穿越零轴
- "跌破"：乖离率向下穿越零轴
- 可启用/禁用以保持清晰
#### 3. **背离检测**
指标自动检测所有三条乖离率线的常规背离：
**看涨背离（黄色标签）**
- 价格创新低
- 乖离率创更高的低点
- 暗示潜在向上反转
- 标签："55涨"、"144涨"、"233涨"
**看跌背离（蓝色标签）**
- 价格创新高
- 乖离率创更低的高点
- 暗示潜在向下反转
- 标签："55跌"、"144跌"、"233跌"
**背离参数**（每个EMA可自定义）：
- 左侧回溯：枢轴点左侧K线数（默认：5）
- 右侧回溯：枢轴点右侧K线数（默认：1）
- 最大回溯范围：枢轴点之间最大距离（默认：60）
- 最小回溯范围：枢轴点之间最小距离（默认：5）
### 配置设置
#### Bias设置
- **EMA周期**：自定义EMA 55、144和233的长度
- **价格源**：选择计算源（默认：收盘价）
- **启用/禁用**：独立切换每条乖离率线
#### 显示设置
- **显示柱状图**：切换柱状图显示
- **显示背景颜色**：切换背景着色
- **显示突破标签**：切换突破/跌破标签
#### 背离设置（按EMA）
- EMA 55、144和233背离的独立控制
- 可自定义回溯参数用于精确调整
- 可调整范围设置以适应不同市场状况
### 使用方法
#### 趋势交易
1. **识别趋势方向**
- 价格高于零 = 上升趋势
- 价格低于零 = 下降趋势
2. **多时间框架确认**
- EMA 55：短期趋势
- EMA 144：中期趋势
- EMA 233：长期趋势
3. **顺乖离方向交易**
- 三条线全部为正 = 强劲上升趋势
- 三条线全部为负 = 强劲下降趋势
#### 均值回归交易
1. **识别极值**
- 高正乖离（>5-10%）= 超买
- 高负乖离（<-5至-10%）= 超卖
2. **等待确认**
- 等待乖离率回归零轴
- 观察穿越标签
3. **在反转时进场**
- 极端负乖离开始上升时做多
- 极端正乖离开始下降时做空
#### 背离交易
1. **发现背离标签**
- 黄色标签 = 看涨背离（潜在买入）
- 蓝色标签 = 看跌背离（潜在卖出）
2. **用价格行为确认**
- 等待价格通过结构突破确认
- 观察支撑/阻力反应
3. **使用多个EMA**
- EMA 55背离：快速反转
- EMA 144背离：可靠信号
- EMA 233背离：重大趋势变化
#### 多时间框架分析
1. **检查长期乖离**（EMA 233）
- 确定整体市场方向
2. **寻找中期入场**（EMA 144）
- 在长期趋势中寻找回调
3. **把握短期入场时机**（EMA 55）
- 短期与长期时间框架一致时进场
### 交易策略
#### 策略1：三重确认
- 等待三条乖离率线全部为正（或负）
- 顺一致乖离方向入场
- 任一线穿越零轴时离场
- 适合：强趋势市场
#### 策略2：背离交易
- 启用所有背离检测
- 仅在出现背离时交易
- 用价格结构确认
- 适合：震荡和反转设置
#### 策略3：零轴穿越
- 启用穿越标签
- 在"突破"标签时做多
- 在"跌破"标签时做空
- 在近期波动点设置止损
- 适合：趋势跟随
#### 策略4：极值回归
- 等待乖离率达到极值（>10%或<-10%）
- 乖离率反转时逆趋势入场
- 在零轴离场
- 适合：震荡市场
### 最佳实践
1. **结合价格行为**
- 不要单独使用乖离率交易
- 用支撑/阻力确认
- 寻找K线形态
2. **使用多时间框架**
- 检查更高时间框架的乖离
- 顺大趋势方向交易
- 用低时间框架把握入场时机
3. **风险管理**
- 在近期波动之外设置止损
- 不要在强趋势中对抗极端乖离
- 在极值处减少仓位
4. **针对您的市场定制**
- 波动大的资产：使用更宽的范围
- 稳定的资产：使用更紧的范围
- 根据时间框架调整EMA周期
5. **警惕假信号**
- 多个小背离 = 可靠性较低
- 极值处的背离 = 更可靠
- 用其他指标确认
### 指标组合
**与成交量配合：**
- 高乖离 + 低成交量 = 弱势波动
- 高乖离 + 高成交量 = 强势波动
**与移动平均线配合：**
- 检查价格是否在关键EMA上方/下方
- 乖离率确认EMA趋势强度
**与RSI/MACD配合：**
- 多指标背离 = 更强信号
- 使用乖离率确认超买超卖
### 性能提示
- 禁用未使用的功能以加快加载
- 使用柱状图快速视觉参考
- 启用背景颜色以清晰显示趋势
- 有选择地使用背离检测
### 常见形态
1. **乖离扩张**：乖离率增大 = 强趋势
2. **乖离收缩**：乖离率减小 = 趋势减弱
3. **零轴反弹**：价格将EMA作为支撑/阻力
4. **极端乖离**：过度延伸，注意反转
5. **背离集群**：多个EMA背离 = 高概率反转
### 警报条件
您可以为以下情况设置警报：
- 乖离率向上/向下穿越零轴
- 极端乖离水平
- 背离检测
- 三条乖离率线对齐
---
## Technical Support
For questions or issues, please refer to the TradingView community or contact the indicator creator.
## 技术支持
如有问题，请参考TradingView社区或联系指标创建者。
Top-Down Analysis - Multi-Timeframe AlignmentThis indicator implements a Top-Down Multi-Timeframe Trading Analysis System. Here's what it does:
Core Functionality
1. Multi-Timeframe Bias Detection
Monitors three timeframes: Daily, 4-Hour, and 1-Hour
Determines if each timeframe is bullish, bearish, or neutral based on two EMAs (9 and 21 period by default)
A timeframe is bullish when: Fast EMA > Slow EMA AND price is above Fast EMA
A timeframe is bearish when: Fast EMA < Slow EMA AND price is below Fast EMA
2. Alignment Tier System
Tier 1 (Full Alignment): All three timeframes agree (Daily = 4H = 1H direction)
Tier 2 (Partial Alignment): Daily and 1H agree, but 4H differs
No Alignment: Timeframes disagree
3. Previous Day Support & Resistance Levels
Automatically plots key levels from the previous day:
Previous Day High (PDH) - resistance
Previous Day Low (PDL) - support
Previous Day Close (PDC)
Previous Day Midpoint (PDM)
4. Execution Zone (15-Minute Window)
Highlights the first 15 minutes after each new 4H candle opens
This is the optimal entry window when alignment conditions are met
5. Pattern Recognition
Detects trading setups:
Double tops/bottoms
Long wicks at support/resistance
Bullish/bearish closes aligned with bias
6. Trade Signals
Generates entry signals when:
There's Tier 1 or Tier 2 alignment
Price is in the 15-minute execution zone
A valid pattern forms (double top/bottom or wick rejection)
7. Visual Dashboard
Shows a real-time table with:
Each timeframe's current bias
Alignment status
Next 4H prediction
Whether price is at a key support/resistance level
Trading Strategy
The indicator helps traders follow the principle of "trade with the higher timeframe trend" by only taking trades when multiple timeframes agree, focusing entries during specific windows, and respecting previous day's key price levels as potential reaction zones.
FxAST Ichi ProSeries Enhanced Full Market Regime EngineFxAST Ichi ProSeries v1.x is a modernized Ichimoku engine that keeps the classic logic but adds a full market regime engine for any market and instrument.”
Multi-timeframe cloud overlay
Oracle long-term baseline
Trend regime classifier (Bull / Bear / Transition / Range)
Chikou & Cloud breakout signals
HTF + Oracle + Trend dashboard
Alert-ready structure for automation
No repainting: all HTF calls use lookahead_off.
1. Core Ichimoku Engine
Code sections:
Input group: Core Ichimoku
Function: ichiCalc()
Variables: tenkan, kijun, spanA, spanB, chikou
What it does
Calculates the classic Ichimoku components:
Tenkan (Conversion Line) – fast Donchian average (convLen)
Kijun (Base Line) – slower Donchian average (baseLen)
Senkou Span A (Span A / Lead1) – (Tenkan + Kijun)/2
Senkou Span B (Span B / Lead2) – Donchian over spanBLen
Chikou – current close shifted back in time (displace)
Everything else in the indicator builds on this engine.
How to use it (trading)
Tenkan vs Kijun = short-term vs medium-term balance.
Tenkan above Kijun = short-term bullish control; below = bearish control.
Span A / B defines the cloud, which represents equilibrium and support/resistance.
Price above cloud = bullish bias; price below cloud = bearish bias.
Graphic
2. Display & Cloud Styling
Code sections:
Input groups: Display Options, Cloud Styling, Lagging Span & Signals
Variables: showTenkan, showKijun, showChikou, showCloud, bullCloudColor, bearCloudColor, cloudLineWidth, laggingColor
Plots: plot(tenkan), plot(kijun), plot(chikou), p1, p2, fill(p1, p2, ...)
What it does
Lets you toggle individual components:
Show/hide Tenkan, Kijun, Chikou, and the cloud.
Customize cloud colors & opacity:
bullCloudColor when Span A > Span B
bearCloudColor when Span A < Span B
Adjust cloud line width for clarity.
How to use it
Turn off components you don’t use (e.g., hide Chikou if you only want cloud + Tenkan/Kijun).
For higher-timeframe or noisy charts, use thicker Kijun & cloud so structure is easier to see.
Graphic
Before
After
3. HTF Cloud Overlay (Multi-Timeframe)
Code sections:
Input group: HTF Cloud Overlay
Vars: showHTFCloud, htfTf, htfAlpha
Logic: request.security(..., ichiCalc(...)) → htfSpanA, htfSpanB
Plots: pHTF1, pHTF2, fill(pHTF1, pHTF2, ...)
What it does
Pulls higher-timeframe Ichimoku cloud (e.g., 1H, 4H, Daily) onto your current chart.
Uses the same Ichimoku settings but aggregates on htfTf.
Plots an extra, semi-transparent cloud ahead of price:
Greenish when HTF Span A > Span B
Reddish when HTF Span B > Span A
How to use it
Trade LTF (e.g., 5m/15m) only in alignment with HTF trend:
HTF cloud bullish + LTF Ichi bullish → look for longs
HTF cloud bearish + LTF Ichi bearish → look for shorts
Treat HTF cloud boundaries as major S/R zones.
Graphic
4. Oracle Module
Code sections:
Input group: Oracle Module
Vars: useOracle, oracleLen, oracleColor, oracleWidth, oracleSlopeLen
Logic: oracleLine = donchian(oracleLen); slope check vs oracleLine
Plot: plot(useOracle ? oracleLine : na, "Oracle", ...)
What it does
Creates a long-term Donchian baseline (default 208 bars).
Uses a simple slope check:
Current Oracle > Oracle oracleSlopeLen bars ago → Oracle Bull
Current Oracle < Oracle oracleSlopeLen bars ago → Oracle Bear
Slope state is also shown in the dashboard (“Bull / Bear / Flat”).
How to use it
Think of Oracle as your macro anchor :
Only take longs when Oracle is sloping up or flat.
Only take shorts when Oracle is sloping down or flat.
Works well combined with HTF cloud:
HTF cloud bullish + Oracle Bull = higher conviction long bias.
Ideal for Gold / Indices swing trades as a trend filter.
Graphic idea
5. Trend Regime Classifier
Code sections:
Input group: Trend Regime Logic
Vars: useTrendRegime, bgTrendOpacity, minTrendScore
Logic:
priceAboveCloud, priceBelowCloud, priceInsideCloud
Tenkan vs Kijun alignment
Cloud bullish/bearish
bullScore / bearScore (0–3)
regime + regimeLabel + regimeColor
Visuals: bgcolor(regimeColor) and optional barcolor() in priceColoring mode.
What it does
Scores the market in three dimensions :
Price vs Cloud
Tenkan vs Kijun
Cloud Direction (Span A vs Span B)
Each condition contributes +1 to either bullScore or bearScore .
Then:
Bull regime when:
bullScore >= minTrendScore and bullScore > bearScore
Price in cloud → “Range”
Everything else → “Transition”
These regimes are shown as:
Background colors:
Teal = Bull
Maroon = Bear
Orange = Range
Silver = Transition
Optional candle recoloring when priceColoring = true.
How to use it
Filters:
Only buy when regime = Bull or Transition and Oracle/HTF agree.
Only sell when regime = Bear or Transition and Oracle/HTF agree.
No trade zone:
When regime = Range (price inside cloud), avoid new entries; wait for break.
Aggressiveness:
Adjust minTrendScore to be stricter (3) or looser (1).
Graphic
6. Signals: Chikou & Cloud Breakout
Code sections :
Logic:
chikouBuySignal = ta.crossover(chikou, close)
chikouSellSignal = ta.crossunder(chikou, close)
cloudBreakUp = priceInsideCloud and priceAboveCloud
cloudBreakDown = priceInsideCloud and priceBelowCloud
What it does
1. Two key signal groups:
Chikou Cross Signals
Buy when Chikou crosses up through price.
Sell when Chikou crosses down through price.
Classic Ichi confirmation idea: Chikou breaking free of price cluster.
2. Cloud Breakout Signals
Long trigger: yesterday inside cloud → today price breaks above cloud.
Short trigger: yesterday inside cloud → today price breaks below cloud.
Captures “equilibrium → expansion” moves.
These are conditions only in this version (no chart shapes yet) but are fully wired for alerts. (Future Updates)
How to use it
Use Chikou signals as confirmation, not standalone entries:
Eg., Bull regime + Oracle Bull + cloud breakout + Chikou Buy.
Use Cloud Breakouts to catch the first impulsive leg after consolidation.
Graphic
7. Alerts (Automation Ready)
[
b]Code sections:
Input group: Alerts
Vars: useAlertTrend, useAlertChikou, useAlertCloudBO
Alert lines like: "FxAST Ichi Bull Trend", "FxAST Ichi Bull Trend", "FxAST Ichi Cloud Break Up"
What it does
Provides ready-made alert hooks for:
Trend regime (Bull / Bear)
Chikou cross buy/sell
Cloud breakout up/down
Each type can be globally toggled on/off via the inputs (helpful if a user only wants one kind).
How to use it
In TradingView: set alerts using “Any alert() function call” on this indicator.
Then filter which ones fire by:
Turning specific alert toggles on/off in input panel, or
Filtering text in your external bot / webhook side.
Example simple workflow ---> Indicator ---> TV Alert ---> Webhook ---> Bot/Broker
8. FxAST Dashboard
Code sections:
Input group: Dashboard
Vars: showDashboard, dashPos, dash, dashInit
Helper: getDashPos() → position.*
Table cells (updated on barstate.islast):
Row 0: Regime + label
Row 1: Oracle status (Bull / Bear / Flat / Off)
Row 2: HTF Cloud (On + TF / Off)
Row 3: Scores (BullScore / BearScore)
What it does
Displays a compact panel with the state of the whole system :
Current Trend Regime (Bull / Bear / Transition / Range)
Oracle slope state
Whether HTF Cloud is active + which timeframe
Raw Bull / Bear scores (0–3 each)
Position can be set: Top Right, Top Left, Bottom Right, Bottom Left.
How to use it
Treat it like a pilot instrument cluster :
Quick glance: “Are my trend, oracle and HTF all aligned?”
Great for streaming / screenshots: everything important is visible in one place without reading the code.
Graphic (lower right of chart )
Forex Session TrackerForex Session Tracker - Professional Trading Session Indicator
The Forex Session Tracker is a comprehensive and visually intuitive indicator designed specifically for forex traders who need precise tracking of major global trading sessions. This powerful tool helps traders identify active market sessions, monitor session-specific price ranges, and capitalize on volatility patterns unique to each trading period.
Understanding when major financial centers are active is crucial for forex trading success. This indicator provides real-time visualization of the Tokyo, London, New York, and Sydney trading sessions, allowing traders to align their strategies with peak liquidity periods and avoid low-volatility trading windows.
---
Key Features
📊 Four Major Global Trading Sessions
The indicator tracks all four primary forex trading sessions with precision:
- Tokyo Session (Asian Market) - Captures the Asian trading hours, ideal for JPY, AUD, and NZD pairs
- London Session (European Market) - Monitors the most liquid trading period, perfect for EUR, GBP pairs
- New York Session (American Market) - Tracks US market hours, essential for USD-based currency pairs
- Sydney Session (Pacific Market) - Identifies the opening of the trading week and AUD/NZD activity
Each session is fully customizable with individual color schemes, making it easy to distinguish between different market periods at a glance.
🎯 Session Range Visualization
For each active trading session, the indicator automatically:
- Draws rectangular boxes that highlight the session's time period
- Tracks and displays session HIGH and LOW price levels in real-time
- Creates horizontal lines at session extremes for easy reference
- Positions session labels at the center of each trading period
- Updates dynamically as new highs or lows are formed within the session
This visual approach helps traders quickly identify:
- Session breakout opportunities
- Support and resistance zones formed during specific sessions
- Range-bound vs. trending session behavior
- Key price levels that institutional traders are watching
📱 Live Information Dashboard
A sleek, professional information panel displays:
- Real-time session status - Instantly see which sessions are currently active
- Color-coded indicators - Green dots for active sessions, gray for closed sessions
- Timezone information - Confirms your current timezone settings
- Customizable positioning - Place the dashboard anywhere on your chart (Top Left, Top Right, Bottom Left, Bottom Right)
- Adjustable size - Choose from Tiny, Small, Normal, or Large text sizes for optimal visibility
The dashboard provides at-a-glance awareness of market conditions without cluttering your chart analysis.
⚙️ Extensive Customization Options
Every aspect of the indicator can be tailored to your trading preferences:
Session-Specific Controls:
- Enable/disable individual sessions
- Customize colors for each trading period
- Adjust session times to match your broker's server time
- Toggle background highlighting on/off
- Show/hide session high/low lines independently
General Settings:
- UTC Offset Control - Adjust timezone from UTC-12 to UTC+14
- Exchange Timezone Option - Automatically use your chart's exchange timezone
- Background Transparency - Fine-tune the opacity of session highlighting (0-100%)
- Session Labels - Show or hide session name labels
- Information Panel - Toggle the live status dashboard on/off
Style Settings:
- Turn session backgrounds ON/OFF directly from the Style tab
- Maintain clean charts while keeping all analytical features active
🔔 Built-in Alert System
Stay informed about session openings with customizable alerts:
- Tokyo Session Started
- London Session Started
- New York Session Started
- Sydney Session Started
Set up notifications to never miss important market opening periods, even when you're away from your charts.
---
How to Use This Indicator
For Day Traders:
1. Identify High-Volatility Periods - Focus your trading during London and New York session overlaps for maximum liquidity
2. Monitor Session Breakouts - Watch for price breaks above/below session highs and lows
3. Avoid Low-Volume Periods - Recognize when major sessions are closed to avoid false signals
For Swing Traders:
1. Mark Key Levels - Use session highs and lows as support/resistance zones
2. Track Multi-Session Patterns - Observe how price behaves across different trading sessions
3. Plan Entry/Exit Points - Time your trades around session openings for better execution
For Currency-Specific Traders:
1. JPY Pairs - Focus on Tokyo session movements
2. EUR/GBP Pairs - Monitor London session activity
3. USD Pairs - Track New York session volatility
4. AUD/NZD Pairs - Watch Sydney and Tokyo sessions
---
Technical Specifications
- Pine Script Version: 5
- Overlay Indicator: Yes (displays directly on price chart)
- Maximum Bars Back: 500
- Drawing Objects: Up to 500 lines, boxes, and labels
- Performance: Optimized for real-time data processing
- Compatibility: Works on all timeframes (recommended: 5m to 1H for session tracking)
---
Installation & Setup
1. Add to Chart - Click "Add to Chart" after copying the script to Pine Editor
2. Configure Timezone - Set your UTC offset or enable "Use Exchange Timezone"
3. Customize Colors - Choose your preferred color scheme for each session
4. Adjust Display - Enable/disable features based on your trading style
5. Set Alerts - Create alert notifications for session starts
---
Best Practices
✅ Combine with Price Action - Use session ranges alongside candlestick patterns for confirmation
✅ Watch Session Overlaps - The London-New York overlap (1300-1600 UTC) typically shows highest volatility
✅ Respect Session Highs/Lows - These levels often act as intraday support and resistance
✅ Adjust for Your Broker - Verify session times match your broker's server clock
✅ Use Multiple Timeframes - View sessions on both lower (15m) and higher (1H) timeframes for context
---
Why Choose Forex Session Tracker Pro?
✨ Professional Grade Tool - Built with clean, efficient code following TradingView best practices
✨ Beginner Friendly - Intuitive design with clear visual cues
✨ Highly Customizable - Adapt every feature to match your trading style
✨ Performance Optimized - Lightweight code that won't slow down your charts
✨ Actively Maintained - Regular updates and improvements
✨ No Repainting - All visual elements are fixed once the session completes
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Support & Updates
This indicator is designed to provide reliable, accurate session tracking for forex traders of all experience levels. Whether you're a scalper looking for high-volatility windows or a position trader marking key institutional levels, the Forex Session Tracker Pro delivers the insights you need to make informed trading decisions.
Happy Trading! 📈
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Disclaimer
This indicator is a tool for technical analysis and should be used as part of a comprehensive trading strategy. Past performance does not guarantee future results. Always practice proper risk management and never risk more than you can afford to lose. Trading forex carries a high level of risk and may not be suitable for all investors.
Liquidity Void Zone Detector [PhenLabs]📊 Liquidity Void Zone Detector
Version: PineScript™v6
📌 Description
The Liquidity Void Zone Detector is a sophisticated technical indicator designed to identify and visualize areas where price moved with abnormally low volume or rapid momentum, creating "voids" in market liquidity. These zones represent areas where insufficient trading activity occurred during price movement, often acting as magnets for future price action as the market seeks to fill these gaps.
Built on PineScript v6, this indicator employs a dual-detection methodology that analyzes both volume depletion patterns and price movement intensity relative to ATR. The revolutionary 3D visualization system uses three-layer polyline rendering with adaptive transparency and vertical offsets, creating genuine depth perception where low liquidity zones visually recede and high liquidity zones protrude forward. This makes critical market structure immediately apparent without cluttering your chart.
🚀 Points of Innovation
Dual detection algorithm combining volume threshold analysis and ATR-normalized price movement sensitivity for comprehensive void identification
Three-layer 3D visualization system with progressive transparency gradients (85%, 78%, 70%) and calculated vertical offsets for authentic depth perception
Intelligent state machine logic that tracks consecutive void bars and only renders zones meeting minimum qualification requirements
Dynamic strength scoring system (0-100 scale) that combines inverted volume ratios with movement intensity for accurate void characterization
Adaptive ATR-based spacing calculation that automatically adjusts 3D layering depth to match instrument volatility
Efficient memory management system supporting up to 100 simultaneous void visualizations with automatic array-based cleanup
🔧 Core Components
Volume Analysis Engine: Calculates rolling volume averages and compares current bar volume against dynamic thresholds to detect abnormally thin trading conditions
Price Movement Analyzer: Normalizes bar range against ATR to identify rapid price movements that indicate liquidity exhaustion regardless of instrument or timeframe
Void Tracking State Machine: Maintains persistent tracking of void start bars, price boundaries, consecutive bar counts, and cumulative strength across multiple bars
3D Polyline Renderer: Generates three-layer rectangular polylines with precise timestamp-to-bar index conversion and progressive offset calculations
Strength Calculation System: Combines volume component (inverted ratio capped at 100) with movement component (ATR intensity × 30) for comprehensive void scoring
🔥 Key Features
Automatic Void Detection: Continuously scans price action for low volume conditions or rapid movements, triggering void tracking when thresholds are exceeded
Real-Time Visualization: Creates 3D rectangular zones spanning from void initiation to termination, with color-coded depth indicating liquidity type
Adjustable Sensitivity: Configure volume threshold multiplier (0.1-2.0x), price movement sensitivity (0.5-5.0x), and minimum qualifying bars (1-10) for customized detection
Dual Color Coding: Separate visual treatment for low liquidity voids (receding red) and high liquidity zones (protruding green) based on 50-point strength threshold
Optional Compact Labels: Toggle LV (Low Volume) or HV (High Volume) circular labels at void centers for quick identification without visual clutter
Lookback Period Control: Adjust analysis window from 5 to 100 bars to match your trading timeframe and market volatility characteristics
Memory-Efficient Design: Automatically manages polyline and label arrays, deleting oldest elements when user-defined maximum is reached
Data Window Integration: Plots void detection binary, current strength score, and average volume for detailed analysis in TradingView's data window
🎨 Visualization
Three-Layer Depth System: Each void is rendered as three stacked polylines with progressive transparency (85%, 78%, 70%) and calculated vertical offsets creating authentic 3D appearance
Directional Depth Perception: Low liquidity zones recede with back layer most transparent; high liquidity zones protrude with front layer most transparent for instant visual differentiation
Adaptive Offset Spacing: Vertical separation between layers calculated as ATR(14) × 0.001, ensuring consistent 3D effect across different instruments and volatility regimes
Color Customization: Fully configurable base colors for both low liquidity zones (default: red with 80 transparency) and high liquidity zones (default: green with 80 transparency)
Minimal Chart Clutter: Closed polylines with matching line and fill colors create clean rectangular zones without unnecessary borders or visual noise
Background Highlight: Subtle yellow background (96% transparency) marks bars where void conditions are actively detected in real-time
Compact Labeling: Optional tiny circular labels with 60% transparent backgrounds positioned at void center points for quick reference
📖 Usage Guidelines
Detection Settings
Lookback Period: Default: 10 | Range: 5-100 | Number of bars analyzed for volume averaging and void detection. Lower values increase sensitivity to recent changes; higher values smooth detection across longer timeframes. Adjust based on your trading timeframe: short-term traders use 5-15, swing traders use 20-50, position traders use 50-100.
Volume Threshold: Default: 1.0 | Range: 0.1-2.0 (step 0.1) | Multiplier applied to average volume. Bars with volume below (average × threshold) trigger void conditions. Lower values detect only extreme volume depletion; higher values capture more moderate low-volume situations. Start with 1.0 and decrease to 0.5-0.7 for stricter detection.
Price Movement Sensitivity: Default: 1.5 | Range: 0.5-5.0 (step 0.1) | Multiplier for ATR-normalized price movement detection. Values above this threshold indicate rapid price changes suggesting liquidity voids. Increase to 2.0-3.0 for volatile instruments; decrease to 0.8-1.2 for ranging or low-volatility conditions.
Minimum Void Bars: Default: 10 | Range: 1-10 | Minimum consecutive bars exhibiting void conditions required before visualization is created. Filters out brief anomalies and ensures only sustained voids are displayed. Use 1-3 for scalping, 5-10 for intraday trading, 10+ for swing trading to match your time horizon.
Visual Settings
Low Liquidity Color: Default: Red (80% transparent) | Base color for zones where volume depletion or rapid movement indicates thin liquidity. These zones recede visually (back layer most transparent). Choose colors that contrast with your chart theme for optimal visibility.
High Liquidity Color: Default: Green (80% transparent) | Base color for zones with relatively higher liquidity compared to void threshold. These zones protrude visually (front layer most transparent). Ensure clear differentiation from low liquidity color.
Show Void Labels: Default: True | Toggle display of compact LV/HV labels at void centers. Disable for cleaner charts when trading; enable for analysis and review to quickly identify void types across your chart.
Max Visible Voids: Default: 50 | Range: 10-100 | Maximum number of void visualizations kept on chart. Each void uses 3 polylines, so setting of 50 maintains 150 total polylines. Higher values preserve more history but may impact performance on lower-end systems.
✅ Best Use Cases
Gap Fill Trading: Identify unfilled liquidity voids that price frequently returns to, providing high-probability retest and reversal opportunities when price approaches these zones
Breakout Validation: Distinguish genuine breakouts through established liquidity from false breaks into void zones that lack sustainable volume support
Support/Resistance Confluence: Layer void detection over key horizontal levels to validate structural integrity—levels within high liquidity zones are stronger than those in voids
Trend Continuation: Monitor for new void formation in trend direction as potential continuation zones where price may accelerate due to reduced resistance
Range Trading: Identify void zones within consolidation ranges that price tends to traverse quickly, helping to avoid getting caught in rapid moves through thin areas
Entry Timing: Wait for price to reach void boundaries rather than entering mid-void, as voids tend to be traversed quickly with limited profit-taking opportunities
⚠️ Limitations
Historical Pattern Indicator: Identifies past liquidity voids but cannot predict whether price will return to fill them or when filling might occur
No Volume on Forex: Indicator uses tick volume for forex pairs, which approximates but doesn't represent true trading volume, potentially affecting detection accuracy
Lagging Confirmation: Requires minimum consecutive bars (default 10) before void is visualized, meaning detection occurs after void formation begins
Trending Market Behavior: Strong trends driven by fundamental catalysts may create voids that remain unfilled for extended periods or permanently
Timeframe Dependency: Detection sensitivity varies significantly across timeframes; settings optimized for one timeframe may not perform well on others
No Directional Bias: Indicator identifies liquidity characteristics but provides no predictive signal for price direction after void detection
Performance Considerations: Higher max visible void settings combined with small minimum void bars can generate numerous visualizations impacting chart rendering speed
💡 What Makes This Unique
Industry-First 3D Visualization: Unlike flat volume or liquidity indicators, the three-layer rendering with directional depth perception provides instant visual hierarchy of liquidity quality
Dual-Mode Detection: Combines both volume-based and movement-based detection methodologies, capturing voids that single-approach indicators miss
Intelligent Qualification System: State machine logic prevents premature visualization by requiring sustained void conditions, reducing false signals and chart clutter
ATR-Normalized Analysis: All detection thresholds adapt to instrument volatility, ensuring consistent performance across stocks, forex, crypto, and futures without constant recalibration
Transparency-Based Depth: Uses progressive transparency gradients rather than colors or patterns to create depth, maintaining visual clarity while conveying information hierarchy
Comprehensive Strength Metrics: 0-100 void strength calculation considers both the degree of volume depletion and the magnitude of price movement for nuanced zone characterization
🔬 How It Works
Phase 1: Real-Time Detection
On each bar close, the indicator calculates average volume over the lookback period and compares current bar volume against the volume threshold multiplier
Simultaneously measures current bar's high-low range and normalizes it against ATR, comparing the result to price movement sensitivity parameter
If either volume falls below threshold OR movement exceeds sensitivity threshold, the bar is flagged as exhibiting void characteristics
Phase 2: Void Tracking & Qualification
When void conditions first appear, state machine initializes tracking variables: start bar index, initial top/bottom prices, consecutive bar counter, and cumulative strength accumulator
Each subsequent bar with void conditions extends the tracking, updating price boundaries to envelope all bars and accumulating strength scores
When void conditions cease, system checks if consecutive bar count meets minimum threshold; if yes, proceeds to visualization; if no, discards the tracking and resets
Phase 3: 3D Visualization Construction
Calculates average void strength by dividing cumulative strength by number of bars, then determines if void is low liquidity (>50 strength) or high liquidity (≤50 strength)
Generates three polyline layers spanning from start bar to end bar and from top price to bottom price, each with calculated vertical offset based on ATR
Applies progressive transparency (85%, 78%, 70%) with layer ordering creating recession effect for low liquidity zones and protrusion effect for high liquidity zones
Creates optional center label and pushes all visual elements into arrays for memory management
Phase 4: Memory Management & Display
Continuously monitors polyline array size (each void creates 3 polylines); when total exceeds max visible voids × 3, deletes oldest polylines via array.shift()
Similarly manages label array, removing oldest labels when count exceeds maximum to prevent memory accumulation over extended chart history
Plots diagnostic data to TradingView’s data window (void detection binary, current strength, average volume) for detailed analysis without cluttering main chart
💡 Note:
This indicator is designed to enhance your market structure analysis by revealing liquidity characteristics that aren’t visible through standard price and volume displays. For best results, combine void detection with your existing support/resistance analysis, trend identification, and risk management framework. Liquidity voids are descriptive of past market behavior and should inform positioning decisions rather than serve as standalone entry/exit signals. Experiment with detection parameters across different timeframes to find settings that align with your trading style and instrument characteristics.
WTC Step Buy Step Edition CbyCarlo📊 WT Cross Modified – Step Buy Step Edition (v4)
WTC_StepBuyStep_Edition is an enhanced, practical, and optimized version of the classic WaveTrend (WT) Cross Indicator.
Developed for the Step Buy Step project, this tool helps traders identify market momentum shifts, structural price zones, and potential reversal areas with high clarity and precision.
🔍 Concept & Purpose
This indicator builds upon the established WaveTrend / LazyBear logic and extends it with additional structural intelligence.
The goal is to make overbought/oversold phases and trend reversals easier to spot — while also highlighting historically validated price zones where the market has previously reacted strongly.
⚙️ Key Features
1️⃣ WT Cross Signals
WT1 (yellow) and WT2 (purple) visualize market momentum.
A WT1 cross above WT2 while below the Oversold zone (−53) can indicate potential Long opportunities.
A WT1 cross below WT2 while above the Overbought zone (+53) can indicate potential Short opportunities.
Signals only confirm after candle close to prevent repainting.
2️⃣ Dynamic “WT SignalZone” Panel
Displayed in the top-right corner, this panel shows the last three valid price levels derived from WT signals:
🟢 LonLev – Buy support levels from previous WT Long signals
🔴 ShoLev – Sell resistance levels from previous WT Short signals
These zones act as objective support/resistance structures, based on historical momentum turning points — not subjective lines.
3️⃣ Flexible Calculation Modes
Choose how levels are derived from each WT signal:
Pullback 50% → Midpoint of the signal candle (high+low)/2
Close → Close price of the signal candle
Next Open → Open of the following bar (ideal for system testing)
📈 How to Interpret the Indicator
Market Condition WT Event Meaning
WT1 < −53 & CrossUp Long Signal Potential reversal / buy zone
WT1 > +53 & CrossDown Short Signal Potential exhaustion / sell zone
Price revisits LonLev Support Re-entry or bounce zone
Price revisits ShoLev Resistance Profit-taking or short setup zone
This makes the tool highly effective for:
Swing traders
Zone-based trading strategies
Systematic re-entries
Identifying structural turning points
🧠 Advantages
No repainting (signals confirmed only after bar close)
Works on all timeframes (from intraday to weekly)
Clean overview without clutter or excessive chart markers
Excellent as a filter to confirm market context
💬 Best Use Case
Use WTC_StepBuyStep_Edition as a contextual confirmation tool.
It does not replace a full trading system — but it gives you objective, repeatable, and statistically relevant zones where the market has reacted before.
Combine it with price action, volume analysis, or trend tools for even stronger setups.
© Step Buy Step • Step-Buy-Step.com
Educational trading tool intended for market analysis.
Not financial advice.
MACD Divergence Optimizer# MACD Divergence Optimizer - User Guide
## Overview
The **MACD Divergence Optimizer** is a professional-grade technical analysis indicator for TradingView that automatically detects hidden divergences on MACD with volume weighting. It identifies potential reversal points before price action confirms the move, giving traders an early edge.
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## What is Divergence?
A **divergence** occurs when price and an oscillator (like MACD) move in opposite directions:
- **Bullish Divergence**: Price makes a lower low, but MACD makes a higher low → Potential uptrend reversal
- **Bearish Divergence**: Price makes a higher high, but MACD makes a lower high → Potential downtrend reversal
Divergences are among the most reliable reversal signals in technical analysis.
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## Indicator Features
### Volume-Weighted MACD
- Standard MACD is calculated on closing price
- This indicator uses **volume-weighted closing prices** for greater accuracy
- Formula: MACD = (Volume-Weighted EMA₁₂ - Volume-Weighted EMA₂₆)
- Volume weighting gives more importance to high-conviction price moves
### Automatic Swing Detection
- Detects local highs and lows (5-bar lookback)
- Tracks the last 5 swings for divergence analysis
- Only meaningful swings are tracked (filtered for noise)
### Smart Signal Generation
- Green triangle (▲) = Bullish Divergence (BUY signal)
- Red triangle (▼) = Bearish Divergence (SELL signal)
- Triangles appear directly on the MACD line for precise entry timing
### Built-in Alerts
- Real-time notifications for divergence signals
- Alerts can trigger mobile push notifications or sound
- Never miss a trading opportunity
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## How to Use
### Installation
1. Open TradingView and navigate to the Chart
2. Click "Indicator" → Search "MACD Divergence Optimizer"
3. Click "Add to Chart"
4. The indicator appears in a separate panel below the price chart
### Reading the Indicator
**MACD Panel displays:**
- **Blue Line** = MACD (fast momentum)
- **Orange Line** = Signal line (slow momentum)
- **Histogram** (colored bars) = Difference between MACD and Signal
- Green bars = MACD above signal (bullish)
- Red bars = MACD below signal (bearish)
**Divergence Signals:**
- **Green Triangle ▲** = Bullish divergence detected
- Price is lower, but MACD momentum is strengthening
- Look for uptrend reversal
- Confirm with higher closes or volume
- **Red Triangle ▼** = Bearish divergence detected
- Price is higher, but MACD momentum is weakening
- Look for downtrend reversal
- Confirm with lower closes or selling volume
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## Parameters & Settings
### MACD Fast Length (Default: 12)
- Controls the faster moving average period
- **Lower values** → More responsive, more false signals
- **Higher values** → Smoother, fewer signals
- **Typical range**: 8-15
### MACD Slow Length (Default: 26)
- Controls the slower moving average period
- **Lower values** → Faster divergence detection
- **Higher values** → More reliable, fewer signals
- **Typical range**: 20-35
### Signal Smoothing (Default: 9)
- EMA period applied to MACD itself
- **Lower values** → Faster crossover signals
- **Higher values** → Fewer false crossovers
- **Typical range**: 5-15
### Min Divergence Strength (Default: 0.5%)
- Minimum % difference between current MACD and swing MACD
- **Lower values** → More divergence signals (noisier)
- **Higher values** → Only strong divergences (fewer signals)
- **Recommended**: 0.3% - 1.0%
### Lookback Bars (Default: 75)
- Historical window for analysis
- Larger lookback = more context but slower calculation
- **Typical range**: 50-100
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## Trading Strategy
### Bullish Divergence (Entry Setup)
1. **Identify Signal**: Green triangle appears on MACD
2. **Confirm Price**: Look for price rejection of the low (bounce)
3. **Volume Check**: Buy on increase in volume at the bounce
4. **Entry**: Above the swing low level
5. **Stop Loss**: Below the most recent swing low
6. **Target**: Next swing high or resistance level
### Bearish Divergence (Entry Setup)
1. **Identify Signal**: Red triangle appears on MACD
2. **Confirm Price**: Look for price rejection of the high
3. **Volume Check**: Sell on increase in volume at rejection
4. **Entry**: Below the swing high level
5. **Stop Loss**: Above the most recent swing high
6. **Target**: Next swing low or support level
### Risk Management
- **Position Size**: Risk only 1-2% per trade
- **Stop Loss**: Place beyond recent swings
- **Take Profit**: Scale out at 1:1, 1:2, 1:3 risk-reward ratios
- **Filter**: Use on higher timeframes (4H, Daily) for reliability
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## Timeframe Recommendations
| Timeframe | Best For | Signal Quality |
|-----------|----------|---|
| **1H** | Scalping, day trading | Moderate (some noise) |
| **4H** | Swing trading | Excellent |
| **Daily** | Position trading | Excellent |
| **Weekly** | Long-term trends | Excellent |
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## Tips & Best Practices
### ✅ DO:
- **Use on trends**: Divergences work best when there's a clear trend
- **Combine signals**: Look for confirmation from price action, volume, or moving averages
- **Trade the bounce**: Wait for price to react to the swing, then enter
- **Adjust parameters**: Test different MACD lengths for your trading style
- **Use alerts**: Set up mobile alerts so you don't miss signals
### ❌ DON'T:
- **Trade every signal**: Some signals are stronger than others
- **Trade flat/choppy markets**: Divergences fail in ranging markets
- **Ignore support/resistance**: Trade divergences near key levels for best results
- **Over-leverage**: Divergences are probabilistic, not guaranteed
- **Disable volume analysis**: Always check volume when divergence fires
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## Advanced Features
### Volume Weighting
The indicator uses **volume-weighted MACD** instead of standard MACD. This means:
- High-volume reversals get more emphasis
- Low-volume moves are smoothed out
- More accurate momentum readings
- Better at identifying true trend changes
### Array Tracking
The indicator tracks the last 5 swings in arrays:
- `swingLows ` = last 5 price lows
- `swingHighs ` = last 5 price highs
- `swingMacds ` = corresponding MACD values
This allows detection of **hidden divergences** not visible in traditional analysis.
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## Common Questions
**Q: Why didn't the indicator trigger a signal when I see a divergence?**
A: The indicator may require:
- MACD histogram to cross the zero line (confirms momentum shift)
- Minimum strength threshold to be met (adjust Min Divergence Strength)
- At least 5 swings to be recorded in the lookback window
**Q: Can I use this on all timeframes?**
A: Yes, but divergences are more reliable on higher timeframes (4H+). Lower timeframes produce more signals but with more noise.
**Q: Should I trade every green/red triangle?**
A: No. Use them as a heads-up for potential reversals. Always confirm with:
- Price action (rejection of the swing)
- Volume (increasing volume at reversal)
- Key support/resistance levels
**Q: How do I set alerts?**
A:
1. Right-click the indicator → Edit Alerts
2. Check "Bullish Divergence" and/or "Bearish Divergence"
3. Choose notification type (browser, mobile, email)
4. Set frequency to "Once per bar close"
**Q: What's the difference between regular and hidden divergence?**
A: This indicator detects **hidden divergences** (also called continuation divergences):
- **Regular**: Price makes new extreme, but oscillator doesn't
- **Hidden**: Price makes new extreme, oscillator makes new extreme in different direction
- Hidden divergences are often more reliable for continuation plays
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## Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Past performance does not guarantee future results. Always use proper risk management and combine with other analysis methods. Trading and investing carry risk of loss. Do your own research before making trading decisions.
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## Support & Updates
For issues, feature requests, or questions:
- Check the indicator settings and parameter values
- Test on historical data first before live trading
- Adjust parameters to match your trading style and timeframe
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**Version**: 1.0
**Last Updated**: November 2025
**Compatible**: TradingView v6+
