@DARKPOOL Magnet - MEMEDescription:
The @DARKPOOL Magnet indicator identifies and displays significant price levels where institutional buying and selling activity has created persistent support and resistance zones. The indicator focuses on three primary types of institutional footprints:
Pin Zone Detection: Identifies price levels where multiple pin bars (high volume, narrow range candles) have clustered within a specified tolerance, indicating repeated institutional defense of those levels.
Whale Footprint Detection: Detects absorption events where significant volume occurs with minimal net price movement, suggesting large institutional orders being filled without allowing substantial directional movement.
Dark Pool Detection: Identifies potential dark pool prints characterized by unexplained price gaps that occur without visible tape activity, indicating off-exchange institutional transactions.
The indicator draws horizontal lines at these identified institutional price levels and highlights areas where multiple detection methods converge, creating confluence zones that represent higher probability support and resistance levels.
Confluence lines are displayed when multiple independently identified institutional levels occur within a user-specified proximity, providing visual emphasis on price levels with the strongest institutional interest.
Buscar en scripts para "gaps"
SMB Master Hub Pro1 Bull Flag Strong uptrend, small consolidation, breakout above flag high
2 Range Breakout Consolidation range, breakout with volume
3 VWAP Reclaim Price crosses above VWAP after being below
4 EMA9 Bounce Price bounces off EMA9 in uptrend
5 Pre-market Gap Stock gaps up or down with momentum, looks for continuation
Hybrid Flow Master📊 Hybrid Flow Master - Professional Trading Indicator
Overview
Hybrid Flow Master is an advanced all-in-one trading indicator that combines Smart Money Concepts, institutional order flow analysis, and multi-timeframe confluence scoring to identify high-probability trade setups. Designed for both scalpers and swing traders across all markets (Forex, Crypto, Stocks, Indices).
🎯 Key Features
1. Intelligent Confluence System (0-100% Scoring) Proprietary scoring algorithm that weighs multiple factors Only signals when minimum confidence threshold is met
Real-time probability calculations for each setup Signal quality grading: A+, A, B, C ratings
2. Smart Money Concepts (SMC)
Automatic Order Block detection (bullish/bearish) Fair Value Gap (FVG) identification
Market structure analysis (Higher Highs, Lower Lows) Swing high/low tracking with visual markers
3. Multi-Timeframe Analysis
Higher timeframe trend filter for confluence Customizable HTF periods (1H, 4H, Daily, etc.)
Prevents counter-trend trades Aligns entries with major trends
4. Volume Flow Analysis
Volume spike detection with customizable thresholds Volume delta calculations (buying vs selling pressure) Institutional footprint identification Background highlighting for high-volume bars
5. Advanced Risk Management
ATR-based stop loss calculation Automatic take profit levels Customizable risk/reward ratios (1:1, 1:2, 1:3+) Visual SL/TP lines on chart Position sizing guidance
6. Professional Dashboard
Real-time HUD displaying:
Market bias (Bullish/Bearish/Neutral)
Higher timeframe trend status
Current confluence percentage
Volume status (Normal/High)
RSI reading with color coding
ATR volatility measure
Signal quality grade
7. Smart Alert System
Bullish confluence signals
Bearish confluence signals
Volume spike notifications
Customizable alert messages
Works with mobile app notifications
📈 What Makes It Unique?
✅ No Repainting - All signals are confirmed and final
✅ Probability-Based - Shows confidence level, not just binary signals
✅ Multi-Factor Confluence - Combines structure, volume, momentum, and HTF analysis
✅ Clean Interface - Toggle individual components on/off
✅ Works on All Timeframes - From 1-minute scalping to daily swing trading
✅ Universal Markets - Forex, Crypto, Stocks, Indices, Commodities
🎨 Customization Options
Adjustable swing detection length
Volume threshold settings
Minimum confluence score filter
Custom color schemes
Dashboard position (4 corners)
Show/hide individual components
Risk/reward ratio adjustment
ATR multiplier for stops
📊 Best Used For:
✔️ Scalping (1m - 15m charts)
✔️ Day Trading (15m - 1H charts)
✔️ Swing Trading (4H - Daily charts)
✔️ Trend Following
✔️ Reversal Trading
✔️ Breakout Trading
💡 How to Use:
Add indicator to chart - Works immediately with default settings Set your timeframe - Choose your trading style Wait for signals - Green BUY or Red SELL labels with confidence %
Check confluence score - Higher % = better quality setup Review dashboard - Confirm market bias and HTF trend Manage risk - Use provided SL/TP levels or adjust to your preference
Set alerts - Get notified of high-probability setups
⚙️ Recommended Settings:
For Scalping (1m-5m):
Swing Length: 5-7
Min Confluence: 70%
HTF: 15m or 1H
For Day Trading (15m-1H):
Swing Length: 10-15
Min Confluence: 60%
HTF: 4H or Daily
For Swing Trading (4H-Daily):
Swing Length: 15-20
Min Confluence: 50-60%
HTF: Weekly
📚 Indicator Components:
✦ Market Structure Detection
✦ Order Block Identification
✦ Fair Value Gaps (FVG)
✦ Volume Analysis
✦ RSI (14)
✦ MACD (12, 26, 9)
✦ ATR (14)
✦ Multi-Timeframe Trend
✦ Confluence Scoring Algorithm
🚀 Performance Notes:
Optimized for speed and efficiency Minimal CPU usage Clean chart presentation
Limited drawing objects (no chart clutter) Works on all TradingView plans
⚠️ Important Notes:
This indicator is a tool to assist trading decisions, not financial advice Always use proper risk management (1-2% per trade recommended) Backtest on your preferred market and timeframe
Combine with your own analysis and strategy Past performance does not guarantee future results
🔔 Alert Setup:
Right-click indicator name → "Add Alert" → Choose:
"Bullish Confluence Signal" for buy setups
"Bearish Confluence Signal" for sell setups
"Volume Spike Alert" for unusual activity
💬 Support:
For questions, suggestions, or custom modifications, feel free to message me directly through TradingView.
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.
Josh FXJoshFX Multi-Timeframe Levels & Fair Value Gap Indicator
This powerful TradingView indicator provides a comprehensive view of key market levels and trends across multiple timeframes. Designed for traders who want precise entries and market context, it includes:
Previous Daily Levels: Automatically marks the previous day’s High, Low, and 50% midpoint.
Multi-Timeframe Trend: Displays the trend direction for 5-minute, 15-minute, 1-hour, and 4-hour charts directly on your current chart.
Daily Candle Display: Shows the current daily candle for quick visual reference.
Pivot Points: Accurately marks technical highs and lows (pivot points) to the exact unit on the chart.
Fair Value Gaps (FVGs): Highlights areas of imbalance for potential high-probability trade setups.
JoshFX Telegram Watermark: Includes branding for the JoshFX community.
This all-in-one tool is perfect for traders combining price action, liquidity concepts, and multi-timeframe analysis to find high-quality setups efficiently.
BifaneiroSinaleiro V3 ULTIMATEBifaneiroSinaleiro V3 ULTIMATE - Complete ICT Analysis System & Signal Generator
This isn't just an indicator - it's your 24/7 ICT analyst that does the manual work for you.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🔥 WHAT IT DOES FOR YOU:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
✅ Marks ALL ICT Concepts Automatically:
- Fair Value Gaps (LTF + HTF with priority)
- Market Structure (BOS/CHoCH in real-time)
- Breaker Blocks (validated with volume + killzone)
- Liquidity Sweeps (Asian High/Low runs)
- Premium/Discount Arrays + OTE Zones
- Institutional Sessions (London, NY Silver Bullets)
✅ Advanced Pattern Recognition:
- Turtle Soup (sweep + reversal)
- Unicorn Model (sweep → BOS → FVG)
- SMT Divergences (monitors correlated pairs)
- PO3/AMD Phases (Accumulation → Manipulation → Distribution)
✅ Intelligent Scoring System:
- 12+ confluence factors analyzed
- Minimum score 12 for signals (configurable)
- Score 20+ = EXTREME (enables 2nd trade in session)
- Visual score display on every signal
✅ Professional Trade Management:
- 1 trade per session (London, NY AM, NY PM) = max 3/day
- EXTREME mode: 2 trades per session = max 6/day
- Automatic stop loss (session range-based)
- Dynamic take profit (score-adjusted multiplier)
- Auto breakeven after 2.5x move
- EOD close (23:59) with P&L label
- Weekend close (Fri 23:55) with P&L label
✅ 100% ICT Pure Methodology:
- NO EMAs, NO ATR, NO lagging indicators
- Pure price action: High/Low/Range only
- HTF confirmation via Premium/Discount (not EMAs!)
- Stop loss via Asian Range (not ATR!)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚡ WHY IT'S DIFFERENT:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Traditional indicators show 1-2 concepts. This shows 10+ simultaneously.
Manual ICT takes 2-3 hours per session. This does it in milliseconds.
Other systems guess. This scores with objective confluence.
You save hours daily. You trade better. You profit more consistently.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📊 WHAT YOU GET:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
- Real-time dashboard (scores, confluences, structure)
- Precision signals (only in killzones, only with confluences)
- Trade tracking (win rate, RR, P&L by session)
- Multi-timeframe analysis (automatic)
- News block filter (configurable)
- Full customization (colors, thresholds, sessions)
- Comprehensive alerts (8+ types)
Works on: Forex, Indices, Commodities, Crypto
Best on: 1m-5m for execution, 15m+ for swing
Timezone: Configured for CET (UTC+1), easily adjustable
⚠️ This is a professional tool requiring ICT/SMC understanding.
Not magic - it's methodology, automated.
🚀 Stop drawing. Start trading. Add to chart now.
(CRT) MTF Candle Range Theory Model# 🚀 **CASH Pro MTF – Candle Range Theory (CRT) Indicator**
**The Smart Money ICT Setup Detector** 🔥
Hey Traders!
Here is the **ultimate Pine Script indicator** that automatically detects one of the most powerful Smart Money / ICT setups: **Candle Range Theory (CRT)**
---
### What is Candle Range Theory – CRT?
**CRT** is a high-probability price action model based on **liquidity grabs** and **range expansion**.
Price loves to:
1️⃣ Raid the low/high of the previous candle (take stop-losses)
2️⃣ Then reverse and run to the opposite side of the range (or beyond)
When this happens near a **key higher-timeframe level**, magic happens!
### Bullish CRT Model
- Price touches a **strong HTF support**
- Previous candle closes near that support
- Next candle **sweeps the low** (grabs liquidity)
- Current candle **closes above the raided low AND breaks the high** of the sweep candle
**Result → Aggressive bullish move expected!**
**Entry:** On close above the high (or on retest + MSS)
**Stop Loss:** Below the swept low
**Take Profit:** CRT High or next liquidity pool
### Bearish CRT Model
- Price touches a **strong HTF resistance**
- Previous candle closes near resistance
- Next candle **sweeps the high** (grabs buy stops)
- Current candle **closes below the raided high AND breaks the low** of the sweep candle
**Result → Strong bearish expansion!**
**Entry:** On close below the low
**Stop Loss:** Above the swept high
**Take Profit:** CRT Low or next downside liquidity
This whole setup can form in **just 3 candles**… or sometimes more if price consolidates after the sweep.
---
### Why This Indicator is Special
This is **NOT** a simple 3-candle pattern scanner!
This is a **true CRT + MTF confluence beast** with:
- **Multi-Timeframe Confirmation** (default 4H – fully customizable)
- **Built-in RSI Filter** (avoid fake moves in overbought/oversold)
- **Day-2 High/Low Levels** automatically drawn (the exact CRT range!)
- **Clean “LONG” / “SHORT” labels** right on the candle (no ugly arrows or offset)
- **Background highlight** on signal
- **Fully grouped inputs** – super clean settings panel
---
### Features at a Glance
| Feature | Included |
|--------------------------------|----------|
| Higher Timeframe Confirmation | Yes |
| RSI Overbought/Oversold Filter | Yes |
| Day-2 High/Low Lines + Labels | Yes |
| Clean Text Signals (no offset) | Yes |
| Background Highlight | Yes |
| Fully Customizable Colors & Text| Yes |
| Works on All Markets & TFs | Yes |
---
### How to Use
1. Add the indicator to your chart
2. Wait for a **LONG** or **SHORT** label to appear
3. Confirm price is near a **key HTF level** (order block, FVG, etc.)
4. Enter on close or retest (your choice)
5. Manage risk with the drawn Day-2 levels
**Pro Tip:** Combine with ICT Market Structure Shift (MSS) or Fair Value Gaps for even higher accuracy!
Chop + MSS/FVG Retest (Ace v1.6) – IndicatorWhat this indicator does
Name: Chop + MSS/FVG Retest (Ace v1.6) – Indicator
This is an entry model helper, not just a BOS/MSS marker.
It looks for clean trend-side setups by combining:
MSS (Market Structure Shift) using swing highs/lows
3-bar ICT Fair Value Gaps (FVG)
First retest back into the FVG
A built-in chop / trend filter based on ATR and a moving average
When everything lines up, it plots:
L below the candle = Long candidate
S above the candle = Short candidate
You pair this with a higher-timeframe filter (like the Chop Meter 1H/30M/15M) to avoid pressing the button in garbage environments.
How it works (simple explanation)
Chop / Trend filter
Computes ATR and compares each bar’s range to ATR.
If the bar is small vs ATR → more likely CHOP.
If the bar is big vs ATR → more likely TREND.
Uses a moving average:
Above MA + TREND → trendLong zone
Below MA + TREND → trendShort zone
MSS (Market Structure Shift)
Uses swing highs/lows (left/right bars) to track the last significant high/low.
Bullish MSS: close breaks above last swing high with displacement.
Bearish MSS: close breaks below last swing low with displacement.
Those events are marked as tiny triangles (MSS up/down).
A MSS only stays “valid” for a certain number of bars (Bars after MSS allowed).
3-bar ICT FVG
Bullish FVG: low > high
→ gap between bar 3 high and bar 2 low.
Bearish FVG: high < low
→ gap between bar 3 low and bar 2 high.
The indicator stores the FVG boundaries (top/bottom).
Retest of FVG
Watches for price to trade back into that gap (first touch).
That retest is the “entry zone” after the MSS.
Final Long / Short condition
Long (L) prints when:
Recent bullish MSS
Bullish FVG has formed
Price retests the bullish FVG
Environment = trendLong (ATR + above MA)
Not CHOP
Short (S) prints when:
Recent bearish MSS
Bearish FVG has formed
Price retests the bearish FVG
Environment = trendShort (ATR + below MA)
Not CHOP
So the L/S markers are “model-approved entry candles”, not just any random BOS.
Inputs / Settings
Key inputs you’ll see:
ATR length (chop filter)
How many bars to use for ATR in the chop / trend filter.
Lower = more sensitive, twitchy
Higher = smoother, slower to change
Max chop ratio
If barRange / ATR is below this → treat as CHOP.
Min trend ratio
If barRange / ATR is above this → treat as TREND.
Hide MSS/BOS marks in CHOP?
ON = MSS triangles disappear when the bar is classified as CHOP
Keeps your chart cleaner in consolidation
Swing left / right bars
Controls how tight or wide the swing highs/lows are for MSS:
Smaller = more sensitive, more MSS points
Larger = fewer, more significant swings
Bars after MSS allowed
How many bars after a MSS the indicator will still allow FVG entries.
Small value (e.g. 10) = MSS must deliver quickly or it’s ignored.
Larger (e.g. 20) = MSS idea stays “in play” longer.
Visual RR (for info only)
Just for plotting relative risk-reward in your head.
This is not a strategy tester; it doesn’t manage positions.
What you see on the chart
Small green triangle up = Bullish MSS
Small red triangle down = Bearish MSS
“L” triangle below a bar = Long idea (MSS + FVG retest + trendLong + not chop)
“S” triangle above a bar = Short idea (MSS + FVG retest + trendShort + not chop)
Faint circle plots on price:
When the filter sees CHOP
When it sees Trend Long zone
When it sees Trend Short zone
You do not have to trade every L or S.
They’re there to show “this is where the model would have considered an entry.”
How to use it in your trading
1. Use it with a higher-timeframe filter
Best practice:
Use this with the Chop Meter 1H/30M/15M or some other HTF filter.
Only consider L/S when:
Chop Meter = TRADE / NORMAL, and
This indicator prints L or S in the right location (premium/discount, near OB/FVG, etc.)
If higher-timeframe says NO TRADE, you ignore all L/S.
2. Location > Signal
Treat L/S as confirmation, not the whole story.
For shorts (S):
Look for premium zones (previous highs, OBs, fair value ranges above mid).
Want purge / raid of liquidity + MSS down + bearish FVG retest → then S.
For longs (L):
Look for discount zones (previous lows, OBs/FVGs below mid).
Want stop raid / purge low + MSS up + bullish FVG retest → then L.
If you see L/S firing in the middle of a bigger range, that’s where you skip and let it go.
3. Instrument presets (example)
You can tune the ATR/chop settings per instrument:
MNQ (noisy, 1m chart):
ATR length: 21
Max chop ratio: 0.90
Min trend ratio: 1.40
Bars after MSS allowed: 10
GOLD (cleaner, 3m chart):
ATR length: 14
Max chop ratio: 0.80
Min trend ratio: 1.30
Bars after MSS allowed: 20
You can save those as presets in the TV settings for quick switching.
4. How to practice with it
Open replay on a couple of days.
Check Chop Meter → if NO TRADE, just observe.
When Chop Meter says TRADE:
Mark where L/S printed.
Ask:
Was this in premium/discount?
Was there SMT / purge on HTF?
Did the move actually deliver, or did it die?
Screenshot the A+ L/S and the ugly ones; refine:
ATR length
Chop / trend thresholds
MSS lookback
Your goal is to get it to where:
The L/S marks show up mostly in the same places your eye already likes,
and you ignore the rest.
Astro's MG Detector (Ultra Sensitive V2)This indicator helps you find micro gaps on the cash session meaning when there is an imbalance of price found on the 5-minute chart between candles this should detect them. IYKYK
Astros MG DetectorIFKYK this indicator auto detects micro gaps where price has not yet been after an imbalance on said candles has been created.
Dobrusky Pressure CoreWhat it does & who it’s for
Dobrusky Pressure Core is a volume by time replacement for traders who care about which side actually controls each bar. Instead of just plotting total volume, it splits each bar into estimated buy vs sell pressure and overlays a custom, session-aware volume baseline. It’s built for discretionary traders who want more nuanced volume context for entries, breakouts, and pullbacks.
Core ideas
Buy/sell pressure split: Each bar’s volume is broken into estimated buying and selling pressure.
Dominant side highlighting: The dominant side (buy or sell) is always displayed starting from the bottom of the bar, so you can quickly see who “owned” that bar.
Median-based baseline: Uses the median of the last N bars (50 by default) to build a robust volume baseline that’s less sensitive to one-off spikes.
Session-aware behavior: Baseline is calculated from Regular Trading Hours (RTH) by default, with an option to include Extended Hours (ETH) and a control to force Regular data on higher timeframes.
Volume regimes: Three multipliers (1x, 1.5x, 2x by default) show normal, high, and extreme volume regions.
Flexible display: Baseline can be shown as lines or as columns behind the volume, with full color customization.
How the pressure logic works
For each bar, the script:
Adjusts the range for gaps relative to the prior close so the “true” traded range is more consistent.
Computes buy pressure as a proportion of the adjusted range from low to close.
Defines sell pressure as: total volume minus buy pressure.
Marks the bar as buy-dominant if buy pressure ≥ sell pressure, otherwise sell-dominant, and colors the dominant side from the bottom to at least the midpoint using the selected buy/sell colors.
In practice, this turns basic volume columns into bars where the internal split and dominant side are clearly visible, helping you judge whether aggressive buyers or sellers truly controlled the bar instead of just looking at the price action.
Volume baseline & session logic
The script builds a session-aware baseline from recent volume:
Baseline length: A rolling window (default 50 bars) is used to compute a median volume value instead of a simple moving average.
RTH-only by default: By default, the baseline is built from Regular Trading Hours bars only. During extended hours, the baseline effectively “freezes” at the last RTH-derived value unless you choose to include extended session data.
Extended mode: If you select Extended mode, the script builds separate rolling baselines for RTH and ETH trading, using the appropriate one depending on the current session.
Force Regular Above Timeframe: On timeframes equal to or higher than your chosen threshold, the baseline automatically uses Regular session data, even if Extended is selected.
Multipliers: Three adjustable multipliers (1x, 1.5x, 2x by default) create normal, high, and extreme volume bands for quick identification.
This lets you choose whether you want a pure RTH reference or a baseline that adapts to extended-session activity.
Example ways to use it
1. Replace standard volume bars
Add Dobrusky Pressure Core to your volume pane and hide the default volume if you prefer a clean look.
Use the colors and split to see at a glance whether buyers or sellers were dominant on each bar.
2. Pressure confirmation for entries
For longs (example concept; adapt to your own rules):
Require that the entry bar’s buy pressure is greater than the previous bar’s sell pressure , or
If the entry and prior bar are both buy-dominant, require that the entry bar has more buy pressure than the prior bar.
This helps avoid taking a long when buying pressure is clearly fading relative to what sellers recently showed. A mirrored idea can be used for short setups with sell pressure.
3. Context from baseline multipliers
Use ~1x baseline as “normal” volume.
Watch for bars at or above 1.5x baseline when you want to see increased participation.
Treat 2x baseline and above as “extreme” volume zones that may mark climactic or especially important bars.
In practice, the baseline and multipliers are best used as context and filters, not as rigid rules.
Settings overview
Display
- Show Volume Baseline: toggle the baseline and its levels on or off.
- Baseline Display: choose between Line or Bars for the baseline visualization.
Baseline Calculation
- Length: lookback for the median baseline (default 50, configurable).
- Baseline Session Data: choose Regular or Extended to control which session data feeds the baseline.
Session Controls
- Regular Session (Local to TZ): define your RTH window (e.g., 0930-1600).
- Session Time Zone: choose the time zone used for that window.
- Force Regular Above Timeframe: on higher timeframes, force the baseline to use Regular session data only.
Baseline Levels
- Show Level x Multiplier 1/2/3: toggle each volume regime level.
- Multiplier 1/2/3: define what you consider normal, high, and extreme volume (defaults: 1.0, 1.5, 2.0).
Colors
- Buy Volume / Sell Volume: choose colors for buy and sell pressure.
- Baseline Bars (Base / x2 / x3): colors when the baseline is drawn as columns.
- Baseline Line (Base / x2 / x3): colors when the baseline is drawn as lines.
Limitations & best practices
This is a decision-support and visualization tool, not a buy/sell signal generator.
Best suited to markets where volume data is meaningful (e.g., index futures, liquid equities, liquid crypto).
The usefulness of any volume-based metric depends on the underlying data feed and instrument structure.
Always combine pressure and baseline context with your own strategy, risk management, and testing.
Originality
Most volume tools either show total volume only or compare it to a simple moving average. Dobrusky Pressure Core combines:
An intrabar buy/sell pressure split based on a gap-adjusted price range.
A median-based, configurable baseline built from session-specific data.
Session-aware behavior that keeps the baseline focused on Regular hours by default, with the option to incorporate Extended hours and force Regular data on higher timeframes.
The goal is to give traders a richer, session-aware view of participation and pressure that standard volume bars and simple SMA overlays don’t provide, while keeping everything transparent and open-source so users can review and adapt the logic.
FVG HTF# FVG HTF — Higher‑Timeframe Fair Value Gaps
## Summary
- Plots higher‑timeframe Fair Value Gap (FVG) zones directly on your current chart.
- Tracks fill progress using four methods: Any Touch, Midpoint Reached, Wick Sweep, Body Beyond.
- Shows optional labels with timeframe source and live fill percentage; label text color is configurable.
- Designed for clean overlays and efficient rendering with limits on graphics and bars processed.
## What It Does
- Detects bullish and bearish FVGs from a chosen timeframe (or the chart timeframe) and renders:
- Zone Top/Bottom lines and a dotted midpoint line
- Semi‑transparent area fill between the edges
- Optional label at the midpoint with a tooltip showing zone prices
- Continuously updates zones forward and removes them when the selected fill condition is met.
## Inputs
- `Enable FVG` (`fvgSH2`): Toggle detection/plotting on/off.
- `Timeframe` (`fvgTF2`): Choose `Chart` or HTFs (`5 Minutes`, `15 Minutes`, `1 Hour`, `4 Hours`, `1 Day`, `1 Week`, `1 Month`).
- `Fill Method` (`fvgFill2`):
- Any Touch — wick or body touches any part of the zone
- Midpoint Reached — price reaches at least the 50% of the zone
- Wick Sweep — wick fully travels past the far edge and back inside (conceptually stricter than touch)
- Body Beyond — candle body closes beyond the opposite edge (strong confirmation)
- `Zones` colors (`fvgCb2`, `fvgCs2`): Bullish/Bearish zone colors.
- `Labels` (`fvgLB2`): Show/Hide on‑chart labels.
- `Label Color` (`fvgLBc2`): Color picker for label text (default: white).
- `Max Bars Back` (`maxBars2`): Limits processing to recent bars for performance.
## Timeframe Rules
- The helper `htfTF` prevents selecting a timeframe lower than the chart. If an invalid lower TF is chosen, it falls back to `timeframe.period`.
- Supports minute, daily, weekly, and monthly aggregations that are safe for intraday/daily/weekly charts.
## Detection Logic
- Uses rolling higher‑timeframe bars constructed on the fly and checks 3‑bar displacement patterns:
- Bullish FVG: current HTF low above the high two bars ago AND previous HTF close above that high, with no direct gap condition.
- Bearish FVG: current HTF high below the low two bars ago AND previous HTF close below that low, with no direct gap condition.
- On detection, the script creates an FVG object with:
- Top/Bottom lines (`lnTop`, `lnBtm`) and midpoint line (`lnAvg`)
- Midpoint label (`lbTxt`) showing source timeframe and updating fill percentage
- Semi‑transparent fill (`linefill`) for visual clarity
## Fill Tracking
- Fill threshold depends on selected method:
- Any Touch: opposite edge
- Midpoint Reached: zone’s midpoint
- Wick Sweep: stricter condition conceptually (implemented as an opposite‑edge threshold)
- Body Beyond: requires close beyond the opposite edge
- Each bar updates label x‑position and line endpoints forward; the label text shows the best fill ratio achieved.
- When the threshold is reached, the FVG (label, lines, fill) is removed from the chart.
## Best Practices
- Start with `Any Touch` to visualize broad repairs; switch to `Body Beyond` for conservative confirmations.
- Use `1 Hour` or `4 Hours` overlays on 5m–15m charts for context; `1 Day` on 1H charts; `1 Week` on daily charts.
- Keep labels on when monitoring fills intraday; hide labels for clean higher‑level context.
- Adjust `Max Bars Back` if performance is impacted by many zones.
## Repainting Notes
- HTF zones are computed on `timeframe.change(tf)` and therefore confirm on HTF bar closes.
- Label endpoints extend each bar; detection itself avoids lookahead bias. For strict confirmation, align entries with HTF closes.
## Limitations
- “Wick Sweep” is treated as a stricter touch to the far edge; it does not enforce a separate “return inside” bar state.
- Label text color applies uniformly to bull/bear labels. If you need separate colors per side, contact the author.
## Credits & Version
- Pine Script v6; © rithsilanew2020
## Quick Start
1. Enable FVG and choose your HTF (e.g., `1 Hour`).
2. Pick a Fill Method (start with `Any Touch`).
3. Select zone colors and label text color.
4. Set `Max Bars Back` as needed for performance.
5. Use labels/tooltip values (Top/Mid/Bottom) to plan entries and manage risk.
MTF Checklist DashboardMTF Checklist Dashboard
Overview
The MTF Checklist Dashboard is an advanced multi-timeframe analysis tool that provides traders with a comprehensive visual dashboard to analyze market conditions across six customizable timeframes simultaneously. This indicator combines multiple technical analysis methods, including Opening Range Breakouts (ORB), VWAP, EMAs, and daily price levels, to generate high-probability confluence-based trading signals.
Unlike traditional single-timeframe indicators, this dashboard displays all critical information in one organized table, allowing traders to instantly identify when multiple timeframes align for optimal entry and exit opportunities.
Key Features
Multi-Timeframe Analysis
Analyzes up to 6 timeframes simultaneously (default: 1m, 5m, 15m, 30m, 1h, 4h)
Fully customizable timeframe selection via comma-separated input
Color-coded cells for instant visual recognition (green=bullish, red=bearish, yellow=neutral)
Technical Indicators Tracked
Current and previous candle direction
Opening Range Breakout (ORB) positioning with custom period
VWAP relationship (above/below)
200 EMA positioning
Daily and previous day high/low proximity
EMA crossovers (9 vs 21, both vs 200)
Advanced Signal Filtering System
Confluence scoring: Requires multiple timeframes to align (3-6 timeframes)
Higher timeframe confirmation: Ensures 30m/1h/4h agreement
Volume filter: Confirms signals with above-average volume (1.5x default)
ATR volatility filter: Validates sufficient market movement
Session timing: Restricts signals to optimal trading hours (EST)
Momentum confirmation: Requires recent directional strength
Range positioning: Blocks signals near daily extremes
Candle strength: Validates strong directional candles (60%+ body ratio)
Visual Signals
Optional entry arrows (above/below bars)
Background color highlighting
Organized dashboard with real-time price levels
ORB range, current day, and previous day summary rows
Alert Conditions
JSON-formatted alerts for automated trading integration
Separate alerts for long entry, short entry, long exit, and short exit
Compatible with webhook automation systems
How To Use
Dashboard Interpretation
The dashboard displays a color-coded table with the following columns:
TF: Timeframe being analyzed
C: Current candle (Green=bullish, Red=bearish)
P: Previous candle (Green=bullish, Red=bearish)
ORB: Opening Range Breakout position (A=Above, B=Below, W=Within)
VWAP: Price vs VWAP (A=Above, B=Below)
E200: Price vs 200 EMA (A=Above, B=Below)
D Hi/Lo: Proximity to current day high/low (Hi/Lo/Mid)
PD Hi/Lo: Proximity to previous day high/low (Hi/Lo/Mid)
9 vs 21: EMA 9 vs EMA 21 relationship (A=9 above 21, B=9 below 21)
9&21 v200: Both EMAs vs 200 EMA (>>=both above, <<=both below, <>=mixed)
Signal Generation
Long Entry Signal triggers when:
Minimum number of timeframes show bullish alignment (default: 5 of 6)
Higher timeframes (30m/1h/4h) confirm direction (default: 2 of 3)
Price breaks above ORB high with sufficient distance
Volume exceeds average by specified multiplier
ATR shows adequate volatility
Trade occurs during optimal session hours
Recent momentum is upward
Price not too close to daily high
Strong bullish candle forms
Short Entry Signal uses opposite conditions
Exit Signals trigger when opposing timeframe confluence reaches threshold (default: 3 timeframes)
Recommended Workflow
Select your asset and primary trading timeframe
Observe the dashboard - Look for rows showing mostly green (bullish) or red (bearish)
Wait for alignment - The indicator will show arrows when confluence requirements are met
Check the bottom rows - Review ORB levels and daily ranges for context
Set alerts - Enable TradingView alerts using the built-in alert conditions
Manage risk - Use appropriate position sizing and stop losses based on ORB range or daily ATR
Settings Guide
Basic Settings
Timeframes: Enter comma-separated values (e.g., "1,5,15,30,60,240")
Show Header: Toggle column headers on/off
ORB Minutes: Set opening range period (default: 15 minutes)
Near % for daily highs/lows: Define proximity threshold (default: 0.20%)
Use close for comparisons: Compare using close vs current price
Dashboard Position: Choose from 9 screen positions
Confluence Filters
Minimum Timeframes Aligned: Set required confluence (3-6, default: 5)
Require Higher Timeframe Confirmation: Toggle HTF requirement on/off
Min Higher Timeframes: Specify HTF agreement needed (1-3, default: 2)
Volume Filter
Volume Confirmation: Enable/disable volume filtering
Volume vs Average: Set multiplier threshold (default: 1.5x)
Volume Average Length: Period for volume average (default: 20 bars)
Volatility Filter (ATR)
Volatility Filter: Enable/disable ATR confirmation
ATR Length: Calculation period (default: 14)
Min ATR vs Average: Required ATR level (default: 0.5x = 50%)
ORB Filters
ORB Breakout Distance Required: Toggle distance requirement
Min Breakout % Beyond ORB: Additional breakout threshold (default: 0.10%)
Session Filter
Trade Only During Best Hours: Enable time-based filtering
Session 1: First trading window (default: 0930-1130 EST)
Session 2: Second trading window (default: 1400-1530 EST)
Momentum Filter
Recent Momentum Required: Enable directional momentum check
Lookback Bars: Period for momentum comparison (default: 3 bars)
Daily Range Filter
Block Signals Near Daily Extremes: Prevent entries at extremes
Distance from High/Low %: Minimum distance required (default: 2.0%)
Candle Filter
Strong Directional Candle: Require candle strength
Min Candle Body %: Body-to-range ratio threshold (default: 60%)
Visual Signals
Show Entry Signals: Master toggle for visual signals
Show Arrows: Display entry arrows on chart
Background Color: Enable background highlighting
Best Practices
Start with default settings and adjust based on your trading style and asset volatility
Higher confluence requirements (5-6 timeframes) produce fewer but higher-quality signals
Enable all filters for conservative trading; disable some for more frequent signals
Use the dashboard as confirmation alongside your existing trading strategy
Backtest on your specific instruments before live trading
Consider market conditions—trending vs ranging markets may require different settings
Alerts
This indicator includes four alert conditions with JSON formatting for webhook integration:
Long Entry Signal: Triggers when all long conditions are met
Short Entry Signal: Triggers when all short conditions are met
Long Exit Signal: Triggers when opposing confluence reaches exit threshold
Short Exit Signal: Triggers when opposing confluence reaches exit threshold
Alert messages include ticker symbol, action (buy/sell), price, and quantity for automated trading systems.
Important Notes
This indicator works best on liquid instruments with clear price action
Highly volatile markets may require adjusted ATR and ORB distance settings
Session times are in EST timezone—adjust if trading non-US markets
The ORB calculation requires sufficient price history for the day
Signals are generated in real-time but should be confirmed at candle close
Limitations
Maximum of 6 timeframes can be analyzed due to TradingView's security call limits
ORB calculations may not work correctly on instruments with gaps or irregular sessions
The indicator is most effective during regular market hours when volume and volatility are adequate
Lower timeframes (1m, 5m) may produce more false signals in choppy conditions
License
Mozilla Public License 2.0 (MPL-2.0)
This indicator is licensed under the Mozilla Public License 2.0. You are free to use, modify, and distribute this code under the terms of the MPL-2.0. The full license text is available at mozilla.org
Key license provisions:
You may use this code commercially
You may modify and distribute modified versions
Modified versions must be released under the same license
You must include the original license notice in any distributions
No trademark rights are granted
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice, and past performance does not guarantee future results. Trading involves substantial risk of loss. Always:
Practice proper risk management
Test thoroughly on paper/demo accounts before live trading
Use appropriate position sizing
Never risk more than you can afford to lose
Consult with a financial advisor for personalized advice
The creator assumes no liability for trading losses incurred using this indicator.
Version: 2.0
Pine Script Version: v6
Author: © EliasVictor
MP Universal FVG Detector🇺🇸 English Description
MP Universal FVG Detector
A clean and powerful indicator that automatically detects classic ICT 3-candle Fair Value Gaps on any market and any timeframe.
It highlights bullish and bearish imbalances with clear colored boxes, helping you quickly spot inefficient price zones where liquidity is likely to return.
Perfect for:
• Smart Money Concepts
• ICT/Inner Circle Trader setups
• Breaker / OB / Displacement traders
• Scalpers, day traders, swing traders
The indicator works with all assets: crypto, forex, stocks, indices, commodities — and on all timeframes.
🇺🇦 Опис українською
MP Universal FVG Detector
Чистий і потужний індикатор, який автоматично визначає класичні 3-свічкові Fair Value Gap (FVG) у стилі ICT на будь-якому ринку та будь-якому таймфреймі.
Він підсвічує бичачі та ведмежі дисбаланси кольоровими боксами, щоб ти легко бачив неефективні зони ціни, куди з великою ймовірністю повернеться ліквідність.
Підходить для:
• Smart Money Concepts
• ICT/Inner Circle Trader структур
• Breaker / Order Block / Displacement трейдерів
• Скальпінгу, внутрідеяльної та свінг-торгівлі
Працює з усіма активами: крипта, форекс, акції, індекси, товари — і на всіх таймфреймах.
Ross Cameron 5 Pillars FilterFirst, I am not Ross Cameron. This indicator is based on his five pillars of stock selection.
ROSS CAMERON 5 PILLARS MOMENTUM FILTER
🎯 OVERVIEW
This indicator automatically checks if the current symbol meets Ross Cameron's famous "5 Pillars" stock selection criteria from Warrior Trading - a proven methodology for identifying high-probability momentum day trading setups.
📊 ROSS CAMERON'S 5 PILLARS
1️⃣ RELATIVE VOLUME ≥5x (Automated ✅)
• Compares current volume to 30-day average
• Minimum 5x confirms institutional/retail interest
• High RVol = high liquidity and momentum potential
2️⃣ DAILY % CHANGE ≥10% (Automated ✅)
• Stock must already be showing momentum
• Default threshold: 10% up from previous close
• Confirms demand is already present
3️⃣ NEWS CATALYST (Manual Check ⚠️)
• Breaking news justifies the price movement
• Look for: earnings, FDA approvals, partnerships, contracts
• 🔥 icon flags stocks with ≥15% momentum (likely news-driven)
4️⃣ PRICE RANGE $1-$20 (Automated ✅)
• Sweet spot for retail trader momentum
• Highly volatile small-cap stocks
• Accessible price range for position building
5️⃣ FLOAT <10 MILLION SHARES (Automated ✅)
• Low float creates supply/demand imbalances
• Enables explosive 50-100%+ intraday moves
• Automatically checked when data available
• Shows actual float with ✅/❌ indicator
🚀 KEY FEATURES
✅ GREEN BACKGROUND HIGHLIGHT
• Visual alert when ALL automated criteria are met
• Instantly identify potential setups while scanning watchlist
📋 DETAILED BREAKDOWN TABLE
• Shows pass/fail status for each pillar
• Displays actual values (RVol, %, Float, etc.)
• Color-coded for quick interpretation
🔥 STRONG MOMENTUM INDICATOR
• Highlights stocks ≥15% (likely have news catalyst)
• Helps prioritize which stocks to research first
🔔 BUILT-IN ALERTS
• "Ross Cameron Criteria Met" - All automated criteria pass
• "Strong Momentum Alert" - Stock showing explosive movement
⚙️ FULLY CUSTOMIZABLE
• Adjust all thresholds to your trading style
• Configurable table position and display
• Toggle volume spike filter on/off
💡 HOW TO USE
BEST WORKFLOW:
1. Build a watchlist of small-cap stocks using TradingView's Stock Screener
2. Add this indicator to your charts
3. Flip through your watchlist - look for GREEN BACKGROUNDS
4. Check the table for detailed breakdown of each pillar
5. VERIFY NEWS CATALYST (required for Pillar 3)
6. If float shows N/A, verify manually on Finviz
7. Execute your trading plan with proper risk management
OPTIMAL TIMING:
• Pre-Market (8:00-9:30 AM ET) - Identify gap-up candidates
• Morning Session (9:30 AM-12:00 PM ET) - Prime momentum window
• Avoid lunch hour (12:00-2:00 PM ET) - Low volume, choppy
ALERT SETUP:
1. Click "Create Alert" on your chart
2. Select "Ross Cameron Criteria Met" condition
3. Get notified when new setups appear real-time
⚙️ CUSTOMIZABLE SETTINGS
PILLAR 1 - RELATIVE VOLUME:
• Min RVol: 5.0x (Ross's minimum, increase for more selective)
• RVol Period: 30 days (industry standard)
PILLAR 2 - MOMENTUM:
• Min Daily %: 10% (increase to 15% for stronger setups)
PILLAR 3 - CATALYST:
• Strong Momentum %: 15% (threshold for 🔥 indicator)
PILLAR 4 - PRICE RANGE:
• Min Price: $1.00 (adjust based on account size)
• Max Price: $20.00 (Ross's sweet spot)
PILLAR 5 - FLOAT:
• Max Float: 10M shares (ultra-aggressive traders use 5M)
ADDITIONAL FILTERS:
• Volume Spike: 2x (Warrior Trading standard)
• Confirms intraday momentum continuation
📈 INTERPRETATION GUIDE
✅ GREEN BACKGROUND = GO!
• All automated criteria are met
• Check news catalyst before trading
• Verify setup on chart (not overextended)
• Follow your risk management plan
❌ NO GREEN BACKGROUND = WAIT
• At least one criterion failed
• Check table to see which pillar(s) failed
• May become valid later if momentum increases
🔥 FLAME ICON = HIGH PRIORITY
• Stock showing very strong momentum (≥15%)
• Likely has significant news catalyst
• Research news IMMEDIATELY
• Often the best setups of the day
⚠️ N/A FOR FLOAT = MANUAL CHECK
• TradingView doesn't have float data for this symbol
• Verify on Finviz.com or similar
• If float >10M, setup is invalid per Ross's criteria
📚 RECOMMENDED STRATEGIES
GAP AND GO:
• Stock gaps up 10%+ on news
• Enters above gap high with volume
• Targets: 20-50% gains
VWAP BOUNCE:
• Pullback to VWAP support
• Enters on bounce with volume confirmation
• Tight stop below VWAP
HIGH OF DAY BREAKOUT:
• New HOD with volume surge
• Momentum continuation play
• Trail stop as it runs
ABCD PATTERN:
• Classic reversal pattern
• Enters on D-point breakout
• Target: A-B distance from C
⚠️ RISK WARNINGS
• DAY TRADING IS HIGHLY RISKY - Most day traders lose money
• This indicator finds setups - YOUR EXECUTION determines success
• Always use proper risk management (1-2% risk per trade)
• Never trade without stop losses
• Paper trade extensively before using real money
• Past performance does not guarantee future results
🔧 TECHNICAL DETAILS
• Pine Script v6
• Works on any timeframe (calculates daily metrics automatically)
• Compatible with TradingView Free, Pro, Premium
• No repainting - all calculations based on confirmed data
• Efficient code - minimal lag
📊 DATA SOURCES
• Relative Volume: Calculated from 30-day volume average
• Daily %: Previous day's close vs current price
• Float: TradingView's shares_outstanding_float data
• Volume Spike: 20-period volume moving average
🎯 WHO THIS IS FOR
IDEAL FOR:
✅ Day traders focused on momentum strategies
✅ Traders who follow Ross Cameron/Warrior Trading methodology
✅ Small-cap stock traders ($1-$20 range)
✅ Scalpers and swing traders seeking high-volatility setups
NOT IDEAL FOR:
❌ Long-term investors
❌ Large-cap stock traders
❌ Options-only traders
❌ Traders who don't monitor news catalysts
💬 USAGE TIPS
1. COMBINE WITH OTHER TOOLS
• Use alongside your charting/technical analysis
• Verify pattern setups (bull flags, ABCD, etc.)
• Check Level 2 / Time & Sales for confirmation
2. MAINTAIN A WATCHLIST
• Update daily with fresh small-cap movers
• Use Finviz Gap Scanner as starting point
• Focus on sectors with momentum
3. RISK MANAGEMENT IS KEY
• Never risk more than 1-2% per trade
• Use 2:1 minimum profit/loss ratio
• Cut losses quickly, let winners run
• Position size based on volatility (ATR)
4. TRACK YOUR RESULTS
• Keep a trading journal
• Note which setups work best for you
• Refine criteria based on your data
• Continuous improvement mindset
📝 DISCLAIMER
This indicator is for EDUCATIONAL PURPOSES ONLY. It is not investment advice, a recommendation to buy/sell securities, or a guarantee of profits. Trading involves substantial risk of loss. Always:
• Conduct your own research and due diligence
• Consult with a licensed financial advisor
• Never risk money you cannot afford to lose
• Understand that most day traders lose money
• Practice in a simulator before trading real money
The creator of this indicator is not affiliated with Ross Cameron or Warrior Trading. This is an independent implementation of publicly available trading methodology.
📈 SUPPORT & FEEDBACK
If you find this indicator helpful, please:
• Give it a thumbs up 👍
• Leave a comment with your experience
• Share with other momentum traders
• Follow for updates and new indicators
For questions or suggestions, leave a comment below!
---
🏆 HAPPY TRADING! Remember: The indicator finds opportunities, but YOUR discipline, risk management, and execution determine your success.
#DayTrading #Momentum #RossCameron #WarriorTrading #SmallCaps #GapAndGo #Scalping #StockScreener
Consolidation Tracker🧭 Consolidation Tracker — Visualize Market Reversals in Real Time
The Consolidation Tracker is a minimalist yet powerful tool designed to map the anatomy of market reversals and trend transitions. It highlights the structural evolution of price through four key phases, helping traders anticipate shifts with clarity and confidence.
🔄 The Four Stages of a Market Reversal:
Failure to Displace — Price fails to break beyond recent highs or lows, signaling potential exhaustion of the current trend.
Consolidation (CAMP) — A range-bound phase where price compresses between a dynamic high and low. These zones are shaded gray, representing indecision and balance.
Engulfing (ENGULF) — A decisive candle closes beyond the CAMP high or low, suggesting a directional shift. These are highlighted in orange.
Fair Value Gap (FVG) — A three-candle pattern forms a price imbalance. If this FVG also engulfs the CAMP range, it confirms the reversal and resets the CAMP. Bullish FVGs are shaded green, bearish FVGs in red.
🔁 From Reversal to Trend:
Once a reversal is confirmed via an FVG, the market often transitions into a trend cycle characterized by:
Displacement — Strong directional movement away from the prior range.
Fair Value Gaps — Continuation imbalances that offer high-probability entries on retracements.
🧠 How It Works:
The indicator dynamically tracks CAMP highs and lows, updating only when a candle engulfs the range or a valid FVG forms.
FVGs are detected when a three-candle sequence creates a gap between candle 2 and 0, and the middle candle (candle 1) breaks the CAMP boundary.
CAMP levels are plotted as horizontal lines, while background colors narrate the evolving structure in real time.
This tool is ideal for traders who value market structure, price efficiency, and narrative clarity. Whether you're anticipating reversals or riding trends, the Consolidation Tracker offers a clean, actionable lens into price behavior.
Volume Pressure and PercentVPP Volume Pressure and Percentage Indicator with a Volume Trendline that indicates which side is driving the flow.
Features:
1. Buy/Sell Pressure Bars (Core Volume Split)
The indicator separates each candle’s volume into buy volume (green) above the zero line and sell volume (red) below it. This gives you a real-time visualization of which side is more aggressive within the current bar. Instead of waiting for prices to move or candles to close, you can instantly see whether buyers or sellers are stepping in.
2. Dynamic Total Volume (Invisible Histogram + Status Line Color)
The total volume of each bar is tracked behind the scenes and displayed in the pinned status line using a dynamic color—green when buyers dominate, red when sellers dominate. The histogram for total volume is invisible to keep the chart clean, but the total volume figure stays visible and changes color based on who is in control. This gives you instant confirmation of whether institutional-sized volume supports the direction shown by the buy/sell pressure, which is especially valuable when evaluating the risk or conviction behind a potential entry.
3. Percentage Mode (% of Bar Volume)
When toggled on, the indicator converts each bar into percent buy vs percent sell, normalizing all flow to a 0–100% scale. This mode is incredibly useful when comparing pressure across different times of day, gaps, or varying volume conditions—such as early morning spikes versus lunchtime chop. By removing absolute volume from the equation, you gain a clean look at the actual imbalance between buyers and sellers.
4. 70% Pressure Band (Imbalance Threshold Zone)
In percentage mode, the indicator displays a subtle 70% band (a light gray zone) above and below the zero line, showing where buy or sell pressure reaches extreme dominance (≥70%). When a bar’s buy or sell percentage enters this zone, it highlights moments of exhaustion, acceleration, or potential reversal. The band acts like a real-time overbought/oversold gauge specifically for volume imbalance, not price.
5. Trend Line (Net Pressure Trend / Reversal Detector)
The trend line smooths out the net volume pressure (buy volume minus sell volume or its percentage equivalent) and shows the overall direction of order flow. When the line slopes upward, buyers are gaining control; when it slopes downward, sellers are taking over. This trend line acts as a real-time momentum indicator based directly on flow rather than price. Because it reacts quickly to intrabar shifts in buy/sell pressure, it often turns before price does—giving you a measurable timing edge.
6. Auto-Selecting Trend Source (Volume Net, Percent Net, or CVD)
The indicator lets you choose how the trend line is calculated: Volume Net (buy minus sell volume), Percent Net (normalized imbalance), or CVD (Cumulative Volume Delta) for long-term flow bias. The default “Auto” mode automatically switches between Volume Net and Percent Net depending on which view you’re using. This flexibility allows the trend line to remain meaningful whether you’re analyzing raw volume or normalized percentage data.
7. Pinned (Status Line) Totals in K/M/B Format
Regardless of whether you’re in volume or percentage mode, the indicator always displays Total Volume, Buy Volume, and Sell Volume in the status line using abbreviated K, M, B formatting. These values update in real time and are color-coded: green for bullish dominance, red for bearish. This gives you a concise snapshot of order flow strength on every bar.
---------------------
How To Use:
Support Level Zones
• Watch for Buy bars increasing + Trend line flipping up right at or slightly below support.
• This often signals absorption — market makers filling large buy orders before reversal.
• Confirmation: Price reclaims VWAP ... enter calls / longs.
Resistance Level Zones
• Watch for Sell bars increasing + Trend line flattening/turning down near resistance.
• This signals distribution or stop runs.
• Confirmation: Price rejects VWAP ... enter puts / shorts.
Breakout Traps
• Sometimes you’ll see price break a level, but the flow doesn’t confirm (buy volume doesn’t expand).
• That’s a false breakout — fade it with options opposite the move.
Liquidity Void Detector + Pro SignalsWhat This Indicator Does
This indicator detects “liquidity voids”—large displacement candles with very high body-to-wick ratios and size significantly above recent ATR—where price moved rapidly and left untested areas.
It automatically draws shaded boxes for new, non-overlapping voids, shows a moveable dashboard (void fill probabilities), and provides one clean, actionable long/short signal per void when price action and momentum confirm.
How It Works
Void Detection: Candles with a body/wick ratio and size above user threshold trigger a potential liquidity void.
Box Drawing: Each new void is drawn as a shaded box (yellow/orange) that never overlaps other active voids.
Signal Confirmation: A “LONG” or “SHORT” label appears at the first bar within each valid void if momentum and candlestick structure align.
Dashboard: User-selectable dashboard shows up-to-date stats on remaining unfilled, partially filled, and fully filled voids.
Alerts: Built-in alerts fire when a new high-probability long/short signal is detected (user must add alerts manually).
Key Features
No overlap, no clutter: Only the latest set of boxes and a single signal per event are drawn. Oldest boxes are pruned automatically.
Momentum filter: Signals combine void and trend strength for higher conviction, filtering out weak/fake moves.
Non-repainting: Signals, boxes, and logic only use confirmed bar data—no repaint or future leaks.
Adjustable settings: Every threshold (body/wick ratio, ATR size, maximum boxes, dashboard location, signal label size) is user-configurable.
Efficient for all timeframes and asset classes.
How to Use
Add to your chart:
Click "Add to Chart" or search “Liquidity Void Detector” in the indicator search panel.
Tune your inputs:
Adjust the Body/Wick Ratio and Min Size vs ATR for your market or timeframe.
Set the Void Box Length (how many bars the box displays), signal sensitivity, and maximum concurrent voids.
Move the dashboard as needed for your chart layout.
What to look for:
Yellow/orange boxes highlight recent liquidity voids—untested price gaps where future reactions may occur.
LONG/SHORT signals appear only where a fresh void coincides with confirmed momentum in that direction.
Dashboard tracks probability of voids remaining unfilled, being partially filled, or fully refilled by price.
Trading logic and best use:
Traders may use void boxes to anticipate where price might react, reverse, or trend continuation can resume.
Combine signals with additional price action confirmation such as S/R levels, order blocks, wick rejections, volume spikes, or patterns (e.g., pin bars, engulfing).
Use signal alerts in conjunction with order flow, session profile, or support/resistance tools for increased confluence.
Always backtest and demo trade before live use.
Important Compliance & Disclaimer
No advice: This tool provides visual context only. All trading and risk decisions are the user’s responsibility.
No repainting, original source: The code is fully open-source, uses only native Pine Script, and never repaints.
No spam, no links, no 3rd-party promotion: 100% TradingView House Rules compliant.
If you find this useful, please consider leaving a positive review, and remember to always confirm with your own analysis.
EMA Dynamic Crossover Detector with Real-Time Signal TableDescriptionWhat This Indicator Does:This indicator monitors all possible crossovers between four key exponential moving averages (20, 50, 100, and 200 periods) and displays them both visually on the chart and in an organized data table. Unlike standard EMA indicators that only plot the lines, this tool actively detects every crossover event, marks the exact crossover point with a circle, records the precise price level, and maintains a running log of all crossovers during the trading session. It's designed for traders who want comprehensive EMA crossover analysis without manually watching multiple moving average pairs.Key Features:
Four Essential EMAs: Plots 20, 50, 100, and 200-period exponential moving averages with color-coded thin lines for clean chart presentation
Complete Crossover Detection: Monitors all 6 possible EMA pair combinations (20×50, 20×100, 20×200, 50×100, 50×200, 100×200) in both directions
Precise Price Marking: Places colored circles at the exact average price where crossovers occur (not just at candle close)
Real-Time Signal Table: Displays up to 10 most recent crossovers with timestamp, direction, exact price, and signal type
Session Filtering: Only records crossovers during active trading hours (10:00-18:00 Istanbul time) to avoid noise from low-liquidity periods
Automatic Daily Reset: Clears the signal table at the start of each new trading day for fresh analysis
Built-In Alerts: Two alert conditions (bullish and bearish crossovers) that can be configured to send notifications
How It Works:The indicator calculates four exponential moving averages using the standard EMA formula, then continuously monitors for crossover events using Pine Script's ta.crossover() and ta.crossunder() functions:Bullish Crossovers (Green ▲):
When a faster EMA crosses above a slower EMA, indicating potential upward momentum:
20 crosses above 50, 100, or 200
50 crosses above 100 or 200
100 crosses above 200 (Golden Cross when it's the 50×200)
Bearish Crossovers (Red ▼):
When a faster EMA crosses below a slower EMA, indicating potential downward momentum:
20 crosses below 50, 100, or 200
50 crosses below 100 or 200
100 crosses below 200 (Death Cross when it's the 50×200)
Price Calculation:
Instead of marking crossovers at the candle's close price (which might not be where the actual cross occurred), the indicator calculates the average price between the two crossing EMAs, providing a more accurate representation of the crossover point.Signal Table Structure:The table in the top-right corner displays four columns:
Saat (Time): Exact time of crossover in HH:MM format
Yön (Direction): Arrow indicator (▲ green for bullish, ▼ red for bearish)
Fiyat (Price): Calculated average price at the crossover point
Durum (Status): Signal classification ("ALIŞ" for buy signals, "SATIŞ" for sell signals) with color-coded background
The table shows up to 10 most recent crossovers, automatically updating as new signals appear. If no crossovers have occurred during the session within the time filter, it displays "Henüz kesişim yok" (No crossovers yet).EMA Color Coding:
EMA 20 (Aqua/Turquoise): Fastest-reacting, most sensitive to recent price changes
EMA 50 (Green): Short-term trend indicator
EMA 100 (Yellow): Medium-term trend indicator
EMA 200 (Red): Long-term trend baseline, key support/resistance level
How to Use:For Day Traders:
Monitor 20×50 crossovers for quick entry/exit signals within the day
Use the time filter (10:00-18:00) to focus on high-volume trading hours
Check the signal table throughout the session to track momentum shifts
Look for confirmation: if 20 crosses above 50 and price is above EMA 200, bullish bias is stronger
For Swing Traders:
Focus on 50×200 crossovers (Golden Cross/Death Cross) for major trend changes
Use higher timeframes (4H, Daily) for more reliable signals
Wait for price to close above/below the crossover point before entering
Combine with support/resistance levels for better entry timing
For Position Traders:
Monitor 100×200 crossovers on daily/weekly charts for long-term trend changes
Use as confirmation of major market shifts
Don't react to every crossover—wait for sustained movement after the cross
Consider multiple timeframe analysis (if crossovers align on weekly and daily, signal is stronger)
Understanding EMA Hierarchies:The indicator becomes most powerful when you understand EMA relationships:Bullish Hierarchy (Strongest to Weakest):
All EMAs ascending (20 > 50 > 100 > 200): Strong uptrend
20 crosses above 50 while both are above 200: Pullback ending in uptrend
50 crosses above 200 while 20/50 below: Early trend reversal signal
Bearish Hierarchy (Strongest to Weakest):
All EMAs descending (20 < 50 < 100 < 200): Strong downtrend
20 crosses below 50 while both are below 200: Rally ending in downtrend
50 crosses below 200 while 20/50 above: Early trend reversal signal
Trading Strategy Examples:Pullback Entry Strategy:
Identify major trend using EMA 200 (price above = uptrend, below = downtrend)
Wait for pullback (20 crosses below 50 in uptrend, or above 50 in downtrend)
Enter when 20 re-crosses 50 in the trend direction
Place stop below/above the recent swing point
Exit when 20 crosses 50 against the trend again
Golden Cross/Death Cross Strategy:
Wait for 50×200 crossover (appears in the signal table)
Verify: Check if crossover occurs with increasing volume
Entry: Enter in the direction of the cross after a pullback
Stop: Place stop below/above the 200 EMA
Target: Swing high/low or when opposite crossover occurs
Multi-Crossover Confirmation:
Watch for multiple crossovers in the same direction within a short period
Example: 20×50 crossover followed by 20×100 = strengthening momentum
Enter after the second confirmation crossover
More crossovers = stronger signal but also means you're entering later
Time Filter Benefits:The 10:00-18:00 Istanbul time filter prevents recording crossovers during:
Pre-market volatility and gaps
Low-volume overnight sessions (for 24-hour markets)
After-hours erratic movements
Bull/Bear FVG Density RatioThis indicator tracks the directional frequency of Fair Value Gaps (FVGs) over a configurable lookback window, offering a clean, responsive measure of market imbalance.
🔍 What It Does:
Detects bullish and bearish FVGs using a 3-bar displacement logic
Calculates the ratio of FVGs to candles over the last N bars
Plots separate density curves for bullish and bearish FVGs
Includes a threshold line to help identify regime shifts (e.g., drought vs spate)
📈 How to Use:
Use rising density to confirm trend strength or breakout momentum
Watch for crossovers above the threshold to signal active imbalance regimes
Combine with price action or volume overlays for high-confluence setups
⚙️ Inputs:
Lookback Window: Number of candles used to calculate FVG density
Threshold: Visual guide for regime classification (default: 0.2)
This tool is ideal for traders who want to move beyond symptomatic signals and model structural causality. It pairs well with lifecycle scoring, retest velocity, and HTF overlays.
Filled Fair Value GapsThese are filled fvgs it only shows filled fvgs so you can see where price is retracing to and don't have 50 fvgs on your screen
XenoSmooth Predictive Candles - Advanced Heikin Ashi CandlesXenoSmooth Predictive Candles
Summary in one paragraph
A synthetic candle engine for crypto, FX, equities, and futures on intraday to swing timeframes. It reduces noise and flip delay so structure is easier to read. The core novelty is a predictive open with inertia plus slope lead fused with a zero lag body filter and an overshoot based wick model normalized by the real range and capped by ATR. Add it to a clean chart, hide regular candles if desired, and tune lengths. Shapes can move while the bar is open and settle on close. For conservative workflows read on bar close.
Scope and intent
• Markets. Major FX pairs, index futures, large cap equities, liquid crypto
• Timeframes. One minute to daily
• Purpose. Faster and smoother visual structure than Heikin Ashi while keeping causality and realistic wicks
Originality and usefulness
• Unique concept. Predictive open with inertia and slope lead plus selectable zero lag body filter and ATR capped wick overshoot in percent of real range
• Failure mode addressed. Late flips in chop and unreal long wicks from raw extremes
• Testability. Every control is an input. Users can toggle body method, lengths, clipping, and percent modeling
• Portable yardstick. ATR based wick cap and percent of bar range scale across symbols
Method overview in plain language
Build a robust base price from O, H, L, and extra weight on Close. Smooth it with a chosen filter to produce the synthetic close. Drive a predictive open that follows the synthetic close with tunable inertia and a small lead from the last bar slope. Model wicks as the portion of the real extremes that extends beyond the synthetic body, smooth that overshoot, normalize by the bar range if selected, then cap by ATR to avoid tail spikes. Clamp synthetic values to the real high and low if enabled.
Base measures
• Range basis. True Range for the ATR cap and High minus Low for percent normalization
• Return basis. Not used
Components
• Body Base Blend. Weighted O H L with a close bias to stabilize the base
• Zero Lag Body Filter. ZLEMA or Super Smoother or WMA to set the synthetic close
• Predictive Open. Inertial follow of the synthetic close plus a slope lead term
• Wick Overshoot Model. Smoothed extension beyond the body, optional percent of real range, ATR cap
• Clamp Option. Keeps synthetic open and close inside the real bar range
Fusion rule
• Synthetic close equals filtered base
• Synthetic open equals previous open plus inertia times distance to synthetic close plus slope lead
• Wicks equal smoothed overshoot above and below the body, optionally percent of range then converted back to price and capped by ATR
Inputs with guidance
Setup
• Signal timeframe. Uses the chart timeframe
• Invert direction. Not applicable
• Session windows. Not applicable
Logic
• Body length. Core smoothing length for the synthetic close. Typical 6 to 14. Higher gives smoother and slower. Lower gives faster flips
• Body method. ZLEMA or Super Smoother or WMA. ZLEMA is fastest. Super Smoother is calmest
• Close weight in base. 0 to 1. Higher gives stronger emphasis on close and less noise
• Open inertia. 0 to 1. Higher makes the open follow the close more tightly
• Lead gain. 0 to 1. Higher adds more phase lead. Keep modest to avoid overshoot
• Clamp body to real range. On keeps synthetic body inside high and low
• Wick smooth length. Typical 4 to 10. Higher reduces jitter
• Overshoot as percent. On stabilizes wicks across regimes
• ATR length. Typical 10 to 20 for the cap
• Max wick equals ATR times. 0 disables. 1.0 to 2.0 contains extreme tails
Filters
• Efficiency or trend filter. Not used
• Micro versus macro range relation. Not used
• Location filter. Not used
Realism and responsible publication
• No performance claims
• Intrabar motion reminder. Shapes can move while a bar forms and settle on close
• Strategies must use standard candles for signals and orders
Honest limitations and failure modes
• High impact releases and thin liquidity can distort wicks and produce gaps that any smoother cannot predict
• Very quiet regimes can reduce contrast. Consider longer body length
• Session time on the chart controls the definition of each bar
Liquidity + Order-Flow Exhaustion (Smart-Money Logic)Liquidity + Order-Flow Exhaustion (Smart-Money Logic) is a visual tool that helps traders recognize where big market participants (“smart money”) are likely accumulating or distributing positions.
It identifies liquidity sweeps (stop-hunts above or below previous swing levels) and market structure shifts (reversals confirmed by price closing back in the opposite direction).
In simple terms, it shows where price “tricks” retail traders into chasing breakouts — right before reversing.
How it works:
The script scans recent highs and lows to find when price breaks them and quickly rejects — a sign of stop-hunts or liquidity grabs.
It then checks for a close back inside the previous range to confirm a possible Market Structure Shift (MSS).
When this happens, the chart highlights the zone and optionally adds directional labels (🔹 or 🔸) to mark where the liquidity event occurred.
How to read the signals:
🟢 Bullish shift — Price takes out a previous low, then closes higher. This often marks the end of a short-term down-move.
🔴 Bearish shift — Price sweeps a previous high, then closes lower. This often marks the end of a short-term rally.
Colored backgrounds and labels help visualize these key reversals directly on the chart.
How to use it:
Apply to any timeframe; 15-minute to 4-hour charts work best.
Use it to confirm reversals near major swing points or liquidity zones.
Combine with volume spikes, displacement candles, or Fair-Value Gaps (FVGs) for stronger confirmation.
What makes it original:
Simple, self-contained logic inspired by Smart Money Concepts (SMC).
Automatically detects both liquidity sweeps and the subsequent structural shift.
Visual and alert-ready design — perfect for discretionary or algorithmic strategies.
Tip: For even better accuracy, align detected shifts with higher-timeframe bias or VWAP deviations.
