Index Top 5 Heavyweight Analyzer## 🎯 Overview
This advanced Pine Script indicator applies the **Pareto Principle** to Nifty 50 trading: the top 5 heavyweights control 40%+ of the index's movement. Instead of watching all 50 stocks, this tool monitors the "Kings" that actually drive the index direction.
Professional traders don't trade the index in isolation - they look "under the hood" at heavyweight constituents. This indicator does exactly that, providing real-time analysis of HDFC Bank, Reliance, ICICI Bank, Bharti Airtel, and TCS to predict Nifty movements before they happen.
## 🔥 Key Features
### 1️⃣ Four-Quadrant OI Cycle Analysis
Identifies which cycle each heavyweight is in using Open Interest from continuous futures contracts:
- **Long Buildup** (Price ↑ + OI ↑): Institutions buying aggressively → Bullish driver
- **Short Covering** (Price ↑ + OI ↓): Bears trapped and exiting → Fast bullish spike
- **Short Buildup** (Price ↓ + OI ↑): Big money shorting → Bearish drag
- **Long Unwinding** (Price ↓ + OI ↓): Buyers giving up → Index weakness
### 2️⃣ Alignment Score System
Counts how many of the top 5 stocks are bullish/bearish/neutral. When 3+ heavyweights align in the same direction with sufficient weightage (15%+), the indicator generates high-conviction trade signals for the Nifty index.
### 3️⃣ Cost of Carry (Basis) Analysis
Compares Future vs Spot prices to gauge institutional sentiment:
- **Rising Premium**: Aggressive institutional buying
- **Discount (Backwardation)**: Extreme bearishness
### 4️⃣ Divergence Detection
Warns when the index move contradicts heavyweight signals - identifying "fake moves" that professional traders fade.
### 5️⃣ Actionable Trade Signals
- **Strong Bullish**: Buy Index Calls / Long Nifty Future
- **Strong Bearish**: Buy Index Puts / Short Nifty Future
- **Neutral/Choppy**: Iron Condor / Avoid Directional trades
## 📈 What Makes This Different?
Unlike basic index indicators, this tool:
- Fetches real Open Interest data from continuous futures (RELIANCE1!, HDFCBANK1!, etc.)
- Applies weighted analysis - top 3 stocks matter most
- Provides professional trade recommendations based on constituent alignment
- Uses dark theme optimized colors for extended screen time
- Displays comprehensive dashboard with price, OI, OI change %, cycle status, and basis
## 💡 How to Use
1. **Add to any Nifty 50 or Bank Nifty chart**
2. **Watch the dashboard** in the top-right corner showing all 5 heavyweights
3. **Check the ALIGNMENT row**:
- 🔼 Bull Count | 🔽 Bear Count | ➖ Neutral Count
- Weighted Bull/Bear scores
4. **Read the INDEX SIGNAL row** for trade recommendations
5. **Look for divergence warnings** (⚠️) indicating fake moves
6. **Use the histogram plot** to visualize signal strength over time
## ⚙️ Customizable Settings
- **Constituents**: Modify ticker symbols and weightages
- **Signal Thresholds**: Adjust minimum alignment required (default: 3 out of 5)
- **Display Options**: Toggle table, signals, and basis calculations
- **Timeframe**: Works on all timeframes (intraday and daily)
## 🎨 Dark Theme Optimized
Designed specifically for TradingView's dark mode with:
- High-contrast colors that reduce eye strain
- Bright lime green (#00E676) for bullish signals
- Bright red (#FF5252) for bearish signals
- Electric colors for easy pattern recognition
## 📊 Best Used For
- **Nifty 50 Options Trading**: Know whether to buy calls or puts
- **Index Futures Trading**: Identify high-probability directional moves
- **Risk Management**: Avoid trading when heavyweights show divergence
- **Market Timing**: Enter when top stocks align (3+ in same direction)
## 🚀 Pro Tips
- **"Double Engine" Signal**: When Reliance shows Long Buildup AND HDFC Bank shows Short Covering → Extremely bullish for Nifty
- **Sector Rotation**: If Banks are strong but Tech is weak (or vice versa) → Expect choppy, range-bound index
- **Rollover Analysis**: Near expiry, watch for high OI with rising basis → Bulls/Bears carrying positions forward with confidence
## ⚠️ Important Notes
- Requires TradingView Premium for multiple `request.security()` calls
- OI data available only for stocks with active futures
- Best used on NSE exchange during market hours
- Combine with your own risk management strategy
## 📝 Credits
Based on professional institutional trading methodologies that analyze index constituents rather than the index itself. Implements the Pareto Principle: focus on the 20% (top 5 stocks) that drives 80% of the index movement.
***
## 🔔 Alerts Available
- Strong Bullish Signal (3+ stocks aligned bullish)
- Strong Bearish Signal (3+ stocks aligned bearish)
- Divergence Warning (fake index moves)
**Made for serious traders who want to trade like institutions - by watching what the "smart money" is doing in the heavyweights.**
***
*Optimize your Nifty trading by monitoring the stocks that actually matter. Stop watching all 50 - focus on the 5 Kings!* 👑
***
**Tags**: Nifty, Open Interest, OI Analysis, Heavyweight Analysis, Index Trading, Options Trading, Futures Trading, Institutional Analysis, Smart Money, Pareto Principle
ค้นหาในสคริปต์สำหรับ "bear"
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.
Market Momentum in Premium & Discount-Delta @MaxMaserati 3.0Market Delta Momentum in Premium & Discount-Delta @MaxMaserati 3.0
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Overview
The MMPD 3.0 indicator is an advanced momentum oscillator that combines market structure analysis with institutional order flow concepts. It transforms price action into a normalized 0-100 scale, identifying premium and discount zones where institutional traders typically operate, while simultaneously tracking momentum through specialized body close candles and multi-timeframe synchronization.
This indicator is designed for traders who want to:
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Identify high-probability reversal zones using premium/discount analysis
Track momentum divergence between price and the MMPD oscillator
Recognize institutional rejection and acceptance zones
Synchronize multiple timeframes for confluence-based trading decisions
Core Methodology
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MMPD Calculation
The Market Delta Momentum indicator uses a proprietary calculation that:
Normalizes price position within a specific period range (0-100 scale)
Applies double smoothing to filter noise
Calculates a balance line (similar to a moving average) to determine bullish/bearish momentum
The relationship between the MMPD line and balance line creates directional candles
Key Zones:
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90-100: Extreme Premium (Institutional Selling Zone)
80-90: High Premium (Caution Zone)
65-80: Premium (Bullish Bias)
50-65: Light Premium (Neutral-Bullish)
35-50: Light Discount (Neutral-Bearish)
20-35: Discount (Bearish Bias)
10-20: High Discount (Institutional Buying Zone)
0-10: Extreme Discount (High Probability Buy Zone)
MMM 3.0 Body Close Logic BC and the MMPD 3.0 Body Close Logic MBC
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1️⃣ Body Close Analysis (BC & MBC)
Price Body Close (BC)
Bullish BC: Price closes above the previous high AND closes above its open (green candle showing aggressive buying)
Bearish BC: Price closes below the previous low AND closes below its open (red candle showing aggressive selling)
No Body Close (NBC): All other candles - representing consolidation, pause, or loss of momentum
MMPD Body Close (MBC)
Bullish MBC: MMPD closes higher than previous MMPD structure (continuation or reversal momentum)
Bearish MBC: MMPD closes lower than previous MMPD structure (continuation or reversal momentum)
MNBC: MMPD No Body Close - weak or ranging MMPD momentum
BC + MBC Confirmation
When Price BC and MMPD MBC align in the same direction, it signals high-conviction momentum:
Deep Green: Bullish BC + Bullish MBC (Strongest Bullish Signal)
Pale Green: Bullish BC only (Moderate Bullish Signal)
Deep Red: Bearish BC + Bearish MBC (Strongest Bearish Signal)
Pale Pink: Bearish BC only (Moderate Bearish Signal)
2️⃣ Momentum Synchronization System
The indicator compares MBC (MMPD Body Close) momentum against BC (Price Body Close) momentum to identify divergence and synchronization:
Synchronized States:
BULLISH+: High volatility bullish synchronization (BC+MBC aligned, high ATR)
BULLISH-: Low volatility bullish synchronization (BC+MBC aligned, low ATR)
BEARISH+: High volatility bearish synchronization (BC+MBC aligned, high ATR)
BEARISH-: Low volatility bearish synchronization (BC+MBC aligned, low ATR)
SYNCHRONIZED: Both MMPD and Price moving together (standard bullish or bearish move)
Divergence States (Reversal Warnings):
MMPD FAST | PRICE SLOW: MMPD showing strong directional MBC candles while Price shows NBC (pause/consolidation) - Reversal Warning!
If MMPD is bullish MBC but Price is NBC → Potential Bearish Reversal
If MMPD is bearish MBC but Price is NBC → Potential Bullish Reversal
Status Indicators:
BULL / BEAR: Standard synchronized moves
BULL+ / BEAR+: High volatility synchronized moves (aggressive trending)
BULL- / BEAR-: Low volatility synchronized moves (grinding trends)
POT. BULL / POT. BEAR: Potential reversal zones (divergence detected)
BALANCED: Neutral conditions, no clear momentum alignment which is price efficiency
3️⃣ Premium/Discount Breakout Markers
🔴 Red Circle Dots (Premium Exit)
Appears when MMPD closes below 80 after being completely in the 80-100 extreme premium zone
Signals institutional distribution complete, potential reversal or correction
🟢 Green Circle Dots (Discount Exit)
Appears when MMPD closes above 20 after being completely in the 0-20 extreme discount zone
Signals institutional accumulation complete, potential rally or reversal
🔴 Red Squares (Premium Rejection)
Appears on the first candle that fails to touch 80-100 after a Bullish MBC touched that zone
Indicates rejection of premium pricing, bearish signal
🟢 Green Squares (Discount Rejection)
Appears on the first candle that fails to touch 0-20 after a Bearish MBC touched that zone
Indicates rejection of discount pricing, bullish signal
🔻 Red Triangles Down (Bearish Midline Rejection)
Signals potential bearish Resumption
🔺 Green Triangles Up (Bullish Midline Bounce)
Signals potential Bullish Resumption
4️⃣ Multi-Timeframe Dashboard with Candle time to close
The MTF table displays:
6 customizable timeframes (default: 5min, 15min, 1H, 4H, Daily, Weekly)
Premium/Discount Status with color-coded zones for each timeframe
Time to Close (T2C): Live countdown timer for each timeframe candle close
Red warning color when the candle closing time is imminent
4H timeframe auto-detects exchange-specific session starts (ES, NQ, CL, GC, etc.)
Momentum Sync Status: Shows the current synchronization state between MMPD and Price across the chart timeframe
Color Coding:
Premium zones: Green/Cyan colors
Discount zones: Purple/Magenta colors
Intensity increases with extremeness (darker = more extreme)
5️⃣ Delta MMPD Alternative View
Toggle between two oscillator calculations:
MMPD: Original MMPD
Delta MMPD: Volume-weighted delta calculation emphasizing buying/selling pressure
TIPS
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Use Multi-Timeframe Confluence: The strongest signals occur when multiple timeframes align in premium/discount zones
Wait for Body Close Confirmation: BC+MBC alignment = highest probability setups
Respect Momentum Sync Warnings: "MMPD FAST | PRICE SLOW" is a critical reversal warning
Trade Premium → Discount or Discount → Premium: Mean reversion from extremes offers best risk/reward
Combine with Price Action: MMPD is a momentum oscillator - always confirm with price structure (support/resistance, trendlines, chart patterns)
Educational Notes
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What is Premium/Discount Pricing?
Institutional traders operate based on value zones:
Premium: Price is expensive relative to recent range - institutions distribute (sell)
Discount: Price is cheap relative to recent range - institutions accumulate (buy)
Fair Value (50 line): Equilibrium pricing where institutions pause
MMM 3.0 Body Close Approach Importance
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BC (Body Close): Shows price commitment and aggressivity
NBC (No Body Close): Shows indecision, consolidation, or loss of momentum
Consecutive BC candles = strong momentum
NBC candles breaking BC sequence = momentum loss → potential reversal
Momentum Synchronization Theory
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When MMPD (momentum) moves aggressively but Price shows NBC (pause), it indicates:
Momentum exhaustion
Smart money distribution/accumulation
Imminent reversal as retail traders get trapped
⚠️ Disclaimer
This indicator is for educational purposes only. Past performance does not guarantee future results. Always practice proper risk management and never risk more than you can afford to lose. Trading involves substantial risk of loss. The creator assumes no responsibility for trading losses incurred using this indicator.
Smart Money Precision Structure [BullByte]Smart Money Precision Structure
Advanced Market Structure Analysis Using Institutional Order Flow Concepts
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OVERVIEW
Smart Money Precision Structure (SMPS) is a comprehensive market analysis indicator that combines six analytical frameworks to identify high-probability market structure patterns. The indicator uses multi-dimensional scoring algorithms to evaluate market conditions through institutional order flow concepts, providing traders with professional-grade market analysis.
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PURPOSE AND ORIGINALITY
Why This Indicator Was Developed
• Addresses the gap between retail and institutional analysis methods
• Consolidates multiple analysis techniques that professionals use separately
• Automates complex market structure evaluation into actionable insights
• Eliminates the need for multiple indicators by providing comprehensive analysis
What Makes SMPS Original
• Six-Layer Confluence System - Unique combination of market regime, structure, volume flow, momentum, price action, and adaptive filtering
• Institutional Pattern Recognition - Identifies smart money accumulation and distribution patterns
• Adaptive Intelligence - Parameters automatically adjust based on detected market conditions
• Real-Time Market Scoring - Proprietary algorithm rates market quality from 0-100%
• Structure Break Detection - Advanced pivot analysis identifies trend reversals early
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HOW IT WORKS - TECHNICAL METHODOLOGY
1. Market Regime Analysis Engine
The indicator evaluates five core market dimensions:
• Volatility Score - Measures current volatility against 50-period historical baseline
• Trend Score - Analyzes alignment between 8, 21, and 50-period EMAs
• Momentum Score - Combines RSI divergence with MACD signal alignment
• Structure Score - Evaluates pivot point formation clarity
• Efficiency Score - Calculates directional movement efficiency ratio
These scores combine to classify markets into five regimes:
• TRENDING - Strong directional movement with aligned indicators
• RANGING - Sideways movement with mixed directional signals
• VOLATILE - Elevated volatility with unpredictable price swings
• QUIET - Low volatility consolidation periods
• TRANSITIONAL - Market shifting between different regimes
2. Market Structure Analysis
Advanced pivot point analysis identifies:
• Higher Highs and Higher Lows for bullish structure
• Lower Highs and Lower Lows for bearish structure
• Structure breaks when established patterns fail
• Dynamic support and resistance from recent pivot points
• Key level proximity detection using ATR-based buffers
3. Volume Flow Decoding
Institutional activity detection through:
• Volume surge identification when volume exceeds 2x average
• Buy versus sell pressure analysis using price-volume correlation
• Flow strength measurement through directional volume consistency
• Divergence detection between volume and price movements
• Institutional threshold alerts when unusual volume patterns emerge
4. Multi-Period Momentum Synthesis
Weighted momentum calculation across four timeframes:
• 1-period momentum weighted at 40%
• 3-period momentum weighted at 30%
• 5-period momentum weighted at 20%
• 8-period momentum weighted at 10%
Result smoothed with 6-period EMA for noise reduction.
5. Price Action Quality Assessment
Each bar evaluated for:
• Range quality relative to 20-period average
• Body-to-range ratio for directional conviction
• Wick analysis for rejection pattern identification
• Pattern recognition including engulfing and hammer formations
• Sequential price movement analysis
6. Adaptive Parameter System
Parameters automatically adjust based on detected regime:
• Trending markets reduce sensitivity and confirmation requirements
• Volatile markets increase filtering and require additional confirmations
• Ranging markets maintain neutral settings
• Transitional markets use moderate adjustments
---
COMPLETE SETTINGS GUIDE
Section 1: Core Analysis Settings
Analysis Sensitivity (0.3-2.0)
• Default: 1.0
• Lower values require stronger price movements
• Higher values detect more subtle patterns
• Scalpers use 0.8-1.2, swing traders use 1.5-2.0
Noise Reduction Level (2-7)
• Default: 4
• Controls filtering of false patterns
• Higher values reduce pattern frequency
• Increase in volatile markets
Minimum Move % (0.05-0.50)
• Default: 0.15%
• Sets minimum price movement threshold
• Adjust based on instrument volatility
• Forex: 0.05-0.10%, Stocks: 0.15-0.25%, Crypto: 0.20-0.50%
High Confirmation Mode
• Default: True (Enabled)
• Requires all technical conditions to align
• Reduces frequency but increases reliability
• Disable for more aggressive pattern detection
Section 2: Market Regime Detection
Enable Regime Analysis
• Default: True (Enabled)
• Activates market environment evaluation
• Essential for adaptive features
• Keep enabled for best results
Regime Analysis Period (20-100)
• Default: 50 bars
• Determines regime calculation lookback
• Shorter for responsive, longer for stable
• Scalping: 20-30, Swing: 75-100
Minimum Market Clarity (0.2-0.8)
• Default: 0.4
• Quality threshold for pattern generation
• Higher values require clearer conditions
• Lower for more patterns, higher for quality
Adaptive Parameter Adjustment
• Default: True (Enabled)
• Enables automatic parameter optimization
• Adjusts based on market regime
• Highly recommended to keep enabled
Section 3: Market Structure Analysis
Enable Structure Validation
• Default: True (Enabled)
• Validates patterns against support/resistance
• Confirms trend structure alignment
• Essential for reliability
Structure Analysis Period (15-50)
• Default: 30 bars
• Period for structure pattern analysis
• Affects support/resistance calculation
• Match to your trading timeframe
Minimum Structure Alignment (0.3-0.8)
• Default: 0.5
• Required structure score for valid patterns
• Higher values need stronger structure
• Balance with desired frequency
Section 4: Analysis Configuration
Minimum Strength Level (3-5)
• Default: 4
• Minimum confirmations for pattern display
• 5 = Maximum reliability, 3 = More patterns
• Beginners should use 4-5
Required Technical Confirmations (4-6)
• Default: 5
• Number of aligned technical factors
• Higher = fewer but better patterns
• Works with High Confirmation Mode
Pattern Separation (3-20 bars)
• Default: 8 bars
• Minimum bars between patterns
• Prevents clustering and overtrading
• Increase for cleaner charts
Section 5: Technical Filters
Momentum Validation
• Default: True (Enabled)
• Requires momentum alignment
• Filters counter-trend patterns
• Essential for trend following
Volume Confluence Analysis
• Default: True (Enabled)
• Requires volume confirmation
• Identifies institutional participation
• Critical for reliability
Trend Direction Filter
• Default: True (Enabled)
• Only shows patterns with trend
• Reduces counter-trend signals
• Disable for reversal hunting
Section 6: Volume Flow Analysis
Institutional Activity Threshold (1.2-3.5)
• Default: 2.0
• Multiplier for unusual volume detection
• Lower finds more institutional activity
• Stock: 2.0-2.5, Forex: 1.5-2.0, Crypto: 2.5-3.5
Volume Surge Multiplier (1.8-4.5)
• Default: 2.5
• Defines significant volume increases
• Adjust per instrument characteristics
• Higher for stocks, lower for forex
Volume Flow Period (12-35)
• Default: 18 bars
• Smoothing for volume analysis
• Shorter = responsive, longer = smooth
• Match to timeframe used
Section 7: Analysis Frequency Control
Maximum Analysis Points Per Hour (1-5)
• Default: 3
• Limits pattern frequency
• Prevents overtrading
• Scalpers: 4-5, Swing traders: 1-2
Section 8: Target Level Configuration
Target Calculation Method
• Default: Market Adaptive
• Three modes available:
- Fixed: Uses set point distances
- Dynamic: ATR-based calculations
- Market Adaptive: Structure-based levels
Minimum Target/Risk Ratio (1.0-3.0)
• Default: 1.5
• Minimum acceptable reward vs risk
• Higher filters lower probability setups
• Professional standard: 1.5-2.0
Fixed Mode Settings:
• Fixed Target Distance: 50 points default
• Fixed Invalidation Distance: 30 points default
• Use for consistent instruments
Dynamic Mode Settings:
• Dynamic Target Multiplier: 1.8x ATR default
• Dynamic Invalidation Multiplier: 1.0x ATR default
• Adapts to volatility automatically
Market Adaptive Settings:
• Use Structure Levels: True (default)
• Structure Level Buffer: 0.1% default
• Places levels at actual support/resistance
Section 9: Visual Display Settings
Color Theme Options
• Professional (Teal/Red)
- Bullish: Teal (#26a69a)
- Bearish: Red (#ef5350)
- Neutral: Gray (#78909c)
- Best for: Traditional traders, clean appearance
• Dark (Neon Green/Pink)
- Bullish: Neon Green (#00ff88)
- Bearish: Hot Pink (#ff0044)
- Neutral: Dark Gray (#333333)
- Best for: Dark theme users, high contrast
• Light (Green/Red Classic)
- Bullish: Green (#4caf50)
- Bearish: Red (#f44336)
- Neutral: Light Gray (#9e9e9e)
- Best for: Light backgrounds, traditional colors
• Vibrant (Cyan/Magenta)
- Bullish: Cyan (#00ffff)
- Bearish: Magenta (#ff00ff)
- Neutral: Medium Gray (#888888)
- Best for: High visibility, modern appearance
Dashboard Position
• Options: Top Left, Top Right, Bottom Left, Bottom Right, Middle Left, Middle Right
• Default: Top Right
• Choose based on chart layout preference
Dashboard Size
• Full: Complete information display (desktop)
• Mobile: Compact view for small screens
• Default: Full
Analysis Display Style
• Arrows : Simple directional markers
• Labels : Detailed text information
• Zones : Colored areas showing pattern regions
• Default: Labels (most informative)
Display Options:
• Display Analysis Strength: Shows star rating
• Display Target Levels: Shows target/invalidation lines
• Display Market Regime: Shows regime in pattern labels
---
HOW TO USE SMPS - DETAILED GUIDE
Understanding the Dashboard
Top Row - Header
• SMPS Dashboard title
• VALUE column: Current readings
• STATUS column: Condition assessments
Market Regime Row
• Shows: TRENDING, RANGING, VOLATILE, QUIET, or TRANSITIONAL
• Color coding: Green = Favorable, Red = Caution
• Status: FAVORABLE or CAUTION trading conditions
Market Score Row
• Percentage from 0-100%
• Above 60% = Strong conditions
• 40-60% = Moderate conditions
• Below 40% = Weak conditions
Structure Row
• Direction: BULLISH, BEARISH, or NEUTRAL
• Status: INTACT or BREAK
• Orange BREAK indicates structure failure
Volume Flow Row
• Direction: BUYING or SELLING
• Intensity: STRONG or WEAK
• Color indicates dominant pressure
Momentum Row
• Numerical momentum value
• Positive = Upward pressure
• Negative = Downward pressure
Volume Status Row
• INST = Institutional activity detected
• HIGH = Above average volume
• NORM = Normal volume levels
Adaptive Mode Row
• ACTIVE = Parameters adjusting
• STATIC = Fixed parameters
• Shows required confirmations
Analysis Level Row
• Minimum strength level setting
• Pattern separation in bars
Market State Row
• Current analysis: BULLISH, BEARISH, NEUTRAL
• Shows analysis price level when active
T:R Ratio Row
• Current target to risk ratio
• GOOD = Meets minimum requirement
• LOW = Below minimum threshold
Strength Row
• BULL or BEAR dominance
• Numerical strength value 0-100
Price Row
• Current price
• Percentage change
Last Analysis Row
• Previous pattern direction
• Bars since last pattern
Reading Pattern Signals
Bullish Structure Pattern
• Upward triangle or "Bullish Structure" label
• Star rating shows strength (★★★★★ = strongest)
• Green line = potential target level
• Red dashed line = invalidation level
• Appears below price bars
Bearish Structure Pattern
• Downward triangle or "Bearish Structure" label
• Star rating indicates reliability
• Green line = potential target level
• Red dashed line = invalidation level
• Appears above price bars
Pattern Strength Interpretation
• ★★★★★ = 6 confirmations (exceptional)
• ★★★★☆ = 5 confirmations (strong)
• ★★★☆☆ = 4 confirmations (moderate)
• ★★☆☆☆ = 3 confirmations (minimum)
• Below minimum = filtered out
Visual Elements on Chart
Lines and Levels:
• Gray Line = 21 EMA trend reference
• Green Stepline = Dynamic support level
• Red Stepline = Dynamic resistance level
• Green Solid Line = Active target level
• Red Dashed Line = Active invalidation level
Pattern Markers:
• Triangles = Arrow display mode
• Text Labels = Label display mode
• Colored Boxes = Zone display mode
Target Completion Labels:
• "Target" = Price reached target level
• "Invalid" = Pattern invalidated by price
---
RECOMMENDED USAGE BY TIMEFRAME
1-Minute Charts (Scalping)
• Sensitivity: 0.8-1.2
• Noise Reduction: 3-4
• Pattern Separation: 3-5 bars
• High Confirmation: Optional
• Best for: Quick intraday moves
5-Minute Charts (Precision Intraday)
• Sensitivity: 1.0 (default)
• Noise Reduction: 4 (default)
• Pattern Separation: 8 bars
• High Confirmation: Enabled
• Best for: Day trading
15-Minute Charts (Short Swing)
• Sensitivity: 1.0-1.5
• Noise Reduction: 4-5
• Pattern Separation: 10-12 bars
• High Confirmation: Enabled
• Best for: Intraday swings
30-Minute to 1-Hour (Position Trading)
• Sensitivity: 1.5-2.0
• Noise Reduction: 5-7
• Pattern Separation: 15-20 bars
• Regime Period: 75-100
• Best for: Multi-day positions
Daily Charts (Swing Trading)
• Sensitivity: 1.8-2.0
• Noise Reduction: 6-7
• Pattern Separation: 20 bars
• All filters enabled
• Best for: Long-term analysis
---
MARKET-SPECIFIC SETTINGS
Forex Pairs
• Minimum Move: 0.05-0.10%
• Institutional Threshold: 1.5-2.0
• Volume Surge: 1.8-2.2
• Target Mode: Dynamic or Market Adaptive
Stock Indices (ES, NQ, YM)
• Minimum Move: 0.10-0.15%
• Institutional Threshold: 2.0-2.5
• Volume Surge: 2.5-3.0
• Target Mode: Market Adaptive
Individual Stocks
• Minimum Move: 0.15-0.25%
• Institutional Threshold: 2.0-2.5
• Volume Surge: 2.5-3.5
• Target Mode: Dynamic
Cryptocurrency
• Minimum Move: 0.20-0.50%
• Institutional Threshold: 2.5-3.5
• Volume Surge: 3.0-4.5
• Target Mode: Dynamic
• Increase noise reduction
---
PRACTICAL APPLICATION EXAMPLES
Example 1: Strong Trending Market
Dashboard Reading:
• Market Regime: TRENDING
• Market Score: 75%
• Structure: BULLISH, INTACT
• Volume Flow: BUYING, STRONG
• Momentum: +0.45
Interpretation:
• Strong uptrend environment
• Institutional buying present
• Look for bullish patterns as continuation
• Higher probability of success
• Consider using lower sensitivity
Example 2: Range-Bound Conditions
Dashboard Reading:
• Market Regime: RANGING
• Market Score: 35%
• Structure: NEUTRAL
• Volume Flow: SELLING, WEAK
• Momentum: -0.05
Interpretation:
• No clear direction
• Low opportunity environment
• Patterns are less reliable
• Consider waiting for regime change
• Or switch to a range-trading approach
Example 3: Structure Break Alert
Dashboard Reading:
• Previous: BULLISH structure
• Current: Structure BREAK
• Volume: INST flag active
• Momentum: Shifting negative
Interpretation:
• Trend reversal potentially beginning
• Institutional participation detected
• Watch for bearish pattern confirmation
• Adjust bias accordingly
• Increase caution on long positions
Example 4: Volatile Market
Dashboard Reading:
• Market Regime: VOLATILE
• Market Score: 45%
• Adaptive Mode: ACTIVE
• Confirmations: Increased to 6
Interpretation:
• Choppy conditions
• Parameters auto-adjusted
• Fewer but higher quality patterns
• Wider stops may be needed
• Consider reducing position size
Below are a few chart examples of the Smart Money Precision Structure (SMPS) indicator in action.
• Example 1 – Bullish Structure Detection on SOLUSD 5m
• Example 2 – Bearish Structure Detected with Strong Confluence on SOLUSD 5m
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TROUBLESHOOTING GUIDE
No Patterns Appearing
Check these settings:
• High Confirmation Mode may be too restrictive
• Minimum Strength Level may be too high
• Market Clarity threshold may be too high
• Regime filter may be blocking patterns
• Try increasing sensitivity
Too Many Patterns
Adjust these settings:
• Enable High Confirmation Mode
• Increase Minimum Strength Level to 5
• Increase Pattern Separation
• Reduce Sensitivity below 1.0
• Enable all technical filters
Dashboard Shows "CAUTION"
This indicates:
• Market conditions are unfavorable
• Regime is RANGING or QUIET
• Market score is low
• Consider waiting for better conditions
• Or adjust expectations accordingly
Patterns Not Reaching Targets
Consider:
• Market may be choppy
• Volatility may have changed
• Try Dynamic target mode
• Reduce target/risk ratio requirement
• Check if regime is VOLATILE
---
ALERTS CONFIGURATION
Alert Message Format
Alerts include:
• Pattern type (Bullish/Bearish)
• Strength rating
• Market regime
• Analysis price level
• Target and invalidation levels
• Strength percentage
• Target/Risk ratio
• Educational disclaimer
Setting Up Alerts
• Click Alert button on TradingView
• Select SMPS indicator
• Choose alert frequency
• Customize message if desired
• Alerts fire on pattern detection
---
DATA WINDOW INFORMATION
The Data Window displays:
• Market Regime Score (0-100)
• Market Structure Bias (-1 to +1)
• Bullish Strength (0-100)
• Bearish Strength (0-100)
• Bull Target/Risk Ratio
• Bear Target/Risk Ratio
• Relative Volume
• Momentum Value
• Volume Flow Strength
• Bull Confirmations Count
• Bear Confirmations Count
---
BEST PRACTICES AND TIPS
For Beginners
• Start with default settings
• Use High Confirmation Mode
• Focus on TRENDING regime only
• Paper trade first
• Learn one timeframe thoroughly
For Intermediate Users
• Experiment with sensitivity settings
• Try different target modes
• Use multiple timeframes
• Combine with price action analysis
• Track pattern success rate
For Advanced Users
• Customize per instrument
• Create setting templates
• Use regime information for bias
• Combine with other indicators
• Develop systematic rules
---
IMPORTANT DISCLAIMERS
• This indicator is for educational and informational purposes only
• Not financial advice or a trading system
• Past performance does not guarantee future results
• Trading involves substantial risk of loss
• Always use appropriate risk management
• Verify patterns with additional analysis
• The author is not a registered investment advisor
• No liability accepted for trading losses
---
VERSION NOTES
Version 1.0.0 - Initial Release
• Six-layer confluence system
• Adaptive parameter technology
• Institutional volume detection
• Market regime classification
• Structure break identification
• Real-time dashboard
• Multiple display modes
• Comprehensive settings
## My Final Thoughts
Smart Money Precision Structure represents an advanced approach to market analysis, bringing institutional-grade techniques to retail traders through intelligent automation and multi-dimensional evaluation. By combining six analytical frameworks with adaptive parameter adjustment, SMPS provides comprehensive market intelligence that single indicators cannot achieve.
The indicator serves as an educational tool for understanding how professional traders analyze markets, while providing practical pattern detection for those seeking to improve their technical analysis. Remember that all trading involves risk, and this tool should be used as part of a complete analysis approach, not as a standalone trading system.
- BullByte
Six Meridian Divine Swords [theUltimator5]The Six Meridian Divine Sword is a legendary martial arts technique in the classic wuxia novel “Demi-Gods and Semi-Devils” (天龙八部) by Jin Yong (金庸). The technique uses powerful internal energy (qi) to shoot invisible sword-like energy beams from the six meridians of the hand. Each of the six fingers/meridians corresponds to a “sword,” giving six different sword energies.
The Six Meridian Divine Swords indicator is a compact “signal dashboard” that fuses six classic indicators (fingers)—MACD, KDJ, RSI, LWR (Williams %R), BBI, and MTM—into one pane. Each row is a traffic-light dot (green/bullish, red/bearish, gray/neutral). When all six align, the script draws a confirmation line (“All Bullish” or “All Bearish”). It’s designed for quick consensus reads across trend, momentum, and overbought/oversold conditions.
How to Read the Dashboard
The pane has 6 horizontal rows (explained in depth later):
MACD
KDJ
RSI
LWR (Larry Williams %R)
BBI (Bull & Bear Index)
MTM (Momentum)
Each tick in the row is a dot, with sentiment identified by a color.
Green = bullish condition met
Red = bearish condition met
Gray = inside a neutral band (filtering chop), shown when Use Neutral (Gray) Colors is ON
There are two lines that track the dots on the top or bottom of the pane.
All Bullish Signal Line: appears only if all 6 are strongly bullish (default color = white)
All Bearish Signal Line: appears only if all 6 are strongly bearish (default color = fuchsia)
The Six Meridians (Indicators) — What They Mean:
1) MACD — Trend & Momentum
What it is: A trend-following momentum indicator based on the relationship between two moving averages (typically 12-EMA and 26-EMA)
Logic used: Classic MACD line (EMA12−EMA26) vs its 9-EMA signal.
Bullish: MACD > Signal and |MACD−Signal| > Neutral Threshold
Bearish: MACD < Signal and |diff| > threshold
Neutral: |diff| ≤ threshold
Why: Small crosses can whipsaw. The neutral band ignores tiny separations to reduce noise.
Inputs: Fast/Slow/Signal lengths, Neutral Threshold.
2) KDJ — Stochastic with J-line boost
What it is: A variation of the stochastic oscillator popular in Chinese trading systems
Logic used: K = SMA(Stochastic, smooth), D = SMA(K, smooth), J = 3K − 2D.
Bullish: K > D and |K−D| > 2
Bearish: K < D and |K−D| > 2
Neutral: |K−D| ≤ 2
Why: K–D separation filters tiny wiggles; J offers an “extreme” early-warning context in the value label.
Inputs: Length, Smoothing.
3) RSI — Momentum balance (0–100)
What it is: A momentum oscillator measuring speed and magnitude of price changes (0–100)
Logic used: RSI(N).
Bullish: RSI > 50 + Neutral Zone
Bearish: RSI < 50 − Neutral Zone
Neutral: Between those bands
Why: Centerline/adaptive bands (around 50) give a directional bias without relying on fixed 70/30.
Inputs: Length, Neutral Zone (± around 50).
4) LWR (Williams %R) — Overbought/Oversold
What it is: An oscillator similar to stochastic, measuring how close the close is to the high-low range over N periods
Logic used: %R over N bars (0 to −100).
Bullish: %R > −50 + Neutral Zone
Bearish: %R < −50 − Neutral Zone
Neutral: Between those bands
Why: Uses a centered band around −50 instead of only −20/−80, making it act like a directional filter.
Inputs: Length, Neutral Zone (± around −50).
5) BBI (Bull & Bear Index) — Smoothed trend bias
What it is: A composite moving average, essentially the average of several different moving averages (often 3, 6, 12, 24 periods)
Logic used: Average of 4 SMAs (3/6/12/24 by default):
BBI = (MA3 + MA6 + MA12 + MA24) / 4
Bullish: Close > BBI and |Close−BBI| > 0.2% of BBI
Bearish: Close < BBI and |diff| > threshold
Neutral: |diff| ≤ threshold
Why: Multiple MAs blended together reduce single-MA whipsaw. A dynamic 0.2% band ignores tiny drift.
Inputs: 4 lengths (default 3/6/12/24). Threshold is auto-scaled at 0.2% of BBI.
6) MTM (Momentum) — Rate of change in price
What it is: A simple measure of rate of change
Logic used: MTM = Close − Close
Bullish: MTM > 0.5% of Close
Bearish: MTM < −0.5% of Close
Neutral: |MTM| ≤ threshold
Why: A percent-based gate adapts across prices (e.g., $5 vs $500) and mutes insignificant moves.
Inputs: Length. Threshold auto-scaled to 0.5% of current Close.
Display & Inputs You Can Tweak
🎨 Use Neutral (Gray) Colors
ON (default): 3-color mode with clear “no-trade”/“weak” states.
OFF: classic binary (green/red) without neutral filtering.
Linton Price Targets(R)Linton Price Targets
A groundbreaking new way of projecting price targets and when they will be met in the future.
Point and figure charts have largely fallen out of favour in recent decades with the birth of personal computing and electronic data services. Few software systems calculate them correctly, and the technique is seen as outdated and difficult for the newcomer to technical analysis to understand. Linton Price Targets takes the point and figure methodology for producing vertical count targets and applies them to time-based charts that are much more widely used for technical analysis.
To place Point and figure price targets on a time-based chart, we first need to relate the conditions that produce the vertical count targets. Vertical Targets are only generated with uninterrupted moves off a high or a low point in prices. A pullback of at least 3 boxes locks the thrust column and therefore the price target. A move of at least one box above (in the case of an upside target off a low) or one box below (downside off a high) ‘activates’ the price target. Here the buyers and sellers respectively are confirmed. Conversely a move below the base of an upside target column, or above the top of a downside column ‘negates’ the vertical target. In this case, the buyers and sellers have been superseded by subsequent events.
Projecting Price
The price projection following the point and figure 3-Box method is relatively straightforward. The standard projection used is twice the original move from the top of the initial thrust level. This derives from the 3-Box construction devised by Cohen, whereby the initial thrust count is a third of the overall price count projection. But there is no reason to limit the Target Price Factor to the value to 2. A value of 1 could be used in the case of consolidation patten where the move out of the pattern is roughly equivalent to the move into the pattern. A value of 1.618 could be used for Fibonacci Retracements or Extensions or a value of 2 x log, can be used to deal with increasing box (unit) sizes as price changes.
Projecting Time
Projecting a potential price target with is relatively straight forward. Determining a time in the future when such a price target will be met is more of a challenge. This has been seen as one of the major drawbacks of point and figure charts for decades. Because there is no time axis on a Point and figure chart, there is no saying when a count projection target will be met.
For the Time to Target, we need to consider potential methodologies such as:
1. Price to Time Ratio – t units of price for every x units of time – ie $1 every 2 days
2. Thrust Angle Factor – a factor x the initial trust angle for the target angle
3. Time to Activation Factor – time to target is x the time taken for a target to activate
4. Follow the Price – track prices as the progress to target and adjust time to target accordingly
5. Historical Average Slope – historical average price time average for last n targets
Considering the Price to Time Ratio method, Chart 1 below shows a chart of the price targets for the US stock Applied Materials with a Unit size of $1. The targets are projected Log Scale 2x the initial thrust. From this chart we see that the target prices are reached later than the projection predicted. This means that we need to consider a lesser slope. Chart 2 below shows the same chart with the slope now adjusted to $1 every three days. This chart shows that recent targets for Applied Materials have been approximately met with this slope. Therefore, this is a better slope to use in this instance.
Chart 1 - Applied Materials (unit size $1) - target projection slope $1 every 2 days
Chart 2 - Applied Materials (unit size $1) - target projection slope $1 every 3 days
Chart 3 - Applied Materials (unit size $1) - target projection slope 1/2 initial thrust slope
The second method of projecting price targets assumes the time that a price target will be reached is directly related to the speed of the initial thrust, which generates the target. Chart 3 shows the same security as in the previous examples but using this method with an angle of slope which is half the initial thrust angle. The factor can also be altered with this method to best fit the data. In the previous examples (Charts 1 & 2) we see the slope of each of the targets is constant. Using the Thrust Angle Factor method, different buying and selling thrust angles produces different target slopes.
A third possible projection method assumes that the longer a price target takes to activate, the longer it takes for a target to be reached. The argument goes that the pullback from the initial thrust is more of a consolidation phase rather than a sharp reaction and therefore, the potential overall move will take longer. Chart 4 shows this method. Again, we see that, due to the varying times of price targets to activate, the slopes of the targets are not uniform as in Method 1 which uses a consistent price to time slope.
Chart 4: Applied Materials (unit size $1) – target projection x times the time taken for target to activate.
Chart 5: Applied Materials (unit size $1) – target projection readjusts with new price information
A fourth method for predicting when in the future that a price target might be met adjusts the slope of the targets from the activation point as new price information arrives. With multiple targets activated at different points on the chart, this method also produces price targets of different slopes. Because targets are readjusted with every new price, it is best to set this method to ignore the last x bars in order to spot any divergence from the targets. Chart 5 shows this methodology.
Chart 6 shows a method where the average slope of price over time is taken for the previous n targets that are achieved and used as the slope for projecting targets into the future. While the slopes for upward and downward targets can be separately adjusted with the previous methods mentioned, this method automatically calculates the different slope speeds of upside and downside targets.
Chart 6: Applied Materials (unit size $1) – target projection based on the average slope of the last x targets.
Multiple Price Targets
As with Point and figure count targets, multiple price targets point to the same price or price level increases the likelihood of price targets being met. This is known as ‘clustering’. Now with the ability to project price targets to a future date on a chart, it is not only possible to see clustering of the price of multiple targets, but also clustering of times targets may be met. This can lead to a ‘cluster zone’, an area of price and time in the future that multiple targets may be met. Chart 7 shows an example of this.
Chart 7: Applied Materials (unit size $1) – target zone of future price and time of multiple targets
Achievement and Non-Achievement of Price Targets and Prevailing Trend
Point and figure targets are approximate and are more often than not, not met precisely. They are regularly not achieved or exceeded, but this provides valuable information in itself. Upside price targets that are achieved or exceeded shows bullish confirmation, whereas these targets not being achieved indicates a degree of bearishness. Conversely, downside price targets achieved or exceeded is bearish confirmation and such targets not achieved is an indication of inherent bullishness.
Unsurprisingly, price targets are normally achieved or exceeded in line with the prevailing trend. Upside price targets should be given more weight in uptrends, while downside ones may only serve as a temporary moment for caution, because they are counter-trend. Downside Targets will carry more weight in downtrends. It is also often the case that the last target in line with the prevailing trend is never met as the trend changes and a new set of targets in the opposite direction are generated with the new reversal of trend. Active price targets in both directions are often an early sign of this. This is particularly true with multiple targets in the new trend direction verses one lone target in the previous trend direction. This lone target is likely to be negated, clearly signalling the new trend direction is taking hold.
Activation and Negation of Price Targets
An upside price target is only activated when prices rise a further than a full price unit above the top of the initial uninterrupted buying thrust in prices from a low. A low is defined by a price level at least one full price unit below a previous recent low. The pullback downwards of at least three price units ‘locks’ the initial thrust that generates the upside price target. Here the bulls buying from the bottom have been confirmed.
A downside price target is only activated when prices fall further than a full price unit below the bottom of the initial uninterrupted selling thrust in prices from a high. A high is defined by a price level at least one full price unit above a previous recent high. The pullback upwards of at least three price units ‘locks’ the initial thrust that generates the downside price target. Here the bears selling from the top have been confirmed.
A target is valid once the column is locked with the pullback of at least three units, but it should not be considered as active until the price breaks through the activation level. An unactivated target serves as advance notice that a target is in place and will become active once the activation price level is broken.
An upside price target is negated if prices fall below the bottom of the initial uninterrupted buying thrust in prices. In this instance the bulls have been beaten by the bears. Conversely, a downside price target is negated if prices rise above the top of the initial uninterrupted Selling thrust in prices. Here the bears selling from the top have been beaten by the bulls.
It is important to note the difference between a target that is activated first and then negated and a target that was never activated and negated first. Research shows that normally more than half of all negated targets were never activated and wouldn’t have been taken. Taking the prevailing trend into account further reduces the number of negated targets that would have been taken at the activation point.
Evaluating a Target as Price Progress
Because Linton Price targets can be evaluated with subsequent new price information with the passage of time, it becomes possible to see more easily, than on a point and figure chart, when a target might be failing. The ideas of activation, negation, and achievement of price targets are understood in point and figure charting and apply similarly here to time-based charts. But the ability to now see prices diverging from the target path presents us with some potential new states of a target. In the case of an upside target, if prices fall away or wander sideways from a target path this alerts us to the fact that the prices on their way to the target may be ‘exhausting’. If we fall or wander back below the target activation level, this implies the previous resistance level off the thrust high has not managed to become a new support level for the price. Consequently, we may consider that the target has been ‘de-activated’. If we fall further below the low of the pullback low point, this previous support level also failed to hold and this is providing us with an early warning that the target is quite possibly ‘failing.’ If prices are moving towards the target as expected, we can say the target is ‘in train.’ This is particularly appropriate for multiple targets that run parallel using the first price/time slope prediction method where the targets look like ‘train tracks.’
Improbable Targets
Occasionally an improbable target a long way from the price will be generated. This is particularly true using a log scale projection. Beware of a target that points to a very large change in price. This is especially true of a lone target. It is also quite likely that the unit size has been set too small where a bigger unit size may not produce a target at all.
Longer term charts
Point and figure charts have always meant to be constructed with tick data. The point and figure methodology reduces this down to just the ticks that create a new box on the chart. Long tick data price histories are typically expensive and hard to come by. This can also be an overwhelming amount data to store and analyse, particularly in the case of very liquid instruments such as a major currency pair. For intraday charts, one minute data will normally suffice. But these histories may not be long enough either and it may be necessary to use a 60-minute chart.
It is also possible to construct point and figure charts using high/low data or even open-high-low-close data making some assumptions based on a rising or falling candle, on which came first, the high or the low. The targets will be impacted accordingly.
When it comes to longer term charts such as weekly or monthly charts it is unlikely that these time frames would be used for point and figure charts. The construction method already filters the data. But when it comes to long-term time based charts it becomes necessary to look at weekly or monthly data.
You will also see that long term price upside targets are generated that are not on the daily chart. This is because daily the movements will not provide the same uninterrupted buying thrusts as with the monthly data. The daily pullbacks are effectively ignored when using monthly data. The other advantage is the unit size is now months so we can say that the target slope equates to 1% of price every month for a 1 to 1 slope for example. Using weekly or monthly data to construct the price targets is a significant departure from the traditional point and figure charting method.
Time-Based Charts Are Easier to Understand Than Point and Figure Charts
In recent years, the vast majority of people carrying out technical analysis of charts do not use the point and figure charts. This is partly because very few software systems draw them correctly and do not calculate the price targets. Newcomers to technical analysis find point and figure charts hard to understand.
Combining With Other Techniques
Using point and figure charts has also often meant the need to switch between different chart types for the same instrument. Time-based charts allow for a vast set of technical analysis time-series based techniques to be married with Linton Price Targets. Having different sets of analysis on the same chart can increase the power of the analysis without having to swap between different chart types.
Linton Price Targets builds on the technical analysis body of knowledge developed over the past 100 years by bringing an old, largely lost, technique into the modern age.
The main advantages of Linton Price Targets are:
• The ability to have price targets on time-based charts.
• It is now possible to ascertain when in the future a price target may be met.
• With the passage of time, it becomes clearer if a target track is being followed.
• The targets can be applied to longer-term time-based charts.
• Time-series based analysis techniques can be used on the same chart as the targets.
• The targets are much easier to understand for the newcomer to technical analysis.
BVB dominance bars
Hello everyone, this is my first indicator. these candles shows you who's in control. I like to think its some what close to heikin ashi candles as it shows you the Trend but doesn't average it out. also shows you when there is indecision. please read the instructions on how it works. its not a stand alone strategy. but adds value to your own strategy.
📖 How It Works
The BvB Dominance Bars indicator is a visual tool that colors candles based on market control—whether bulls or bears are in charge. It uses a custom metric comparing the price's relationship to a smoothed moving average (EMA), then normalizes that difference over time to express relative bullish or bearish pressure.
Here’s the breakdown:
Bulls vs Bears Logic:
A short-term EMA (default: 14-period) is used to establish a midpoint reference.
Bull Pressure is calculated as how far the high is above this EMA.
Bear Pressure is how far the low is below this EMA.
These are normalized over a lookback period (default: 120 bars) to produce percentile scores (0–100) for both bulls and bears.
Dominance & Color Coding:
The indicator compares normalized bull and bear scores.
Candles are color-coded based on:
Bright Lime: Strong Bull Dominance (with high confidence)
Soft Lime/Yellow: Moderate Bull Control
Bright Red: Strong Bear Dominance
Soft Red/Yellow: Moderate Bear Control
Gray: Neutral/Low conviction
Optional Live Label:
A small floating label shows who has control: “Bull Control,” “Bear Control,” or “Neutral.”
🧠 How to Use It (Example Strategy)
The BvB Dominance Bars indicator is not a standalone buy/sell signal but a market sentiment overlay. It’s most effective when combined with your own strategy, like price action or trend-following tools.
Here’s an example use case:
🧪 Reversal Confirmation Strategy
Objective: Catch high-probability reversals during key kill zones or supply/demand levels.
Setup:
Mark your key support/resistance zones using your standard method (e.g., FVGs, liquidity sweeps, or ICT PD arrays).
Wait for price to reach one of these zones.
Watch candle colors from the BvB Dominance Bars:
If you expect a bullish reversal, wait for a transition from red/gray candles to lime green or bright lime (bullish dominance taking over).
If you expect a bearish reversal, look for a change from green/gray to red or bright red.
Entry Filter:
Only enter if the dominant color holds for 2+ candles.
Avoid trades when candles are gray or yellow (indecision/neutral).
Exit Option:
Exit if dominance shifts against you (e.g., from lime to red), or use structure-based stops.
⚙️ Settings You Can Adjust:
BvB Period: Controls how fast EMA responds.
Bars Back: Determines how long the normalization looks back.
Thresholds: Influence how strong the dominance must be to change candle color.
✅ Best Used When:
You already have a bias and just want a confirmation of sentiment.
You're trading intraday and want a feel for shifting momentum without relying on noisy indicators.
You want a clean, color-coded overlay to help filter out fakeouts and indecision.
Multiple (12) Strong Buy/Sell Signals + Momentum
Indicator Manual: "Multiple (12) Strong Buy/Sell Signals + Momentum"
This indicator is designed to identify strong buy and sell signals based on 12 configurable conditions, which include a variety of technical analysis methods such as trend-following indicators, pattern recognition, volume analysis, and momentum oscillators. It allows for customizable alerts and visual cues on the chart. The indicator helps traders spot potential entry and exit points by displaying buy and sell signals based on the selected conditions.
Key Observations:
• The script integrates multiple indicators and pattern recognition methods to provide comprehensive buy/sell signals.
• Trend-based indicators like EMAs and MACD are combined with pattern recognition (flags, triangles) and momentum-based signals (RSI, ADX, and volume analysis).
• User customization is a core feature, allowing adjustments to the conditions and thresholds for more tailored signals.
• The script is designed to be responsive to market conditions, with multiple conditions filtering out noise to generate reliable signals.
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Key Features:
1. 12 Combined Buy/Sell Signal Conditions: This indicator incorporates a diverse set of conditions based on trend analysis, momentum, and price patterns.
2. Minimum Conditions Input: You can adjust the threshold of conditions that need to be met for the buy/sell signals to appear.
3. Alert Customization: Set alert thresholds for both buy and sell signals.
4. Dynamic Visualization: Buy and sell signals are shown as triangles on the chart, with momentum signals highlighted as circles.
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Detailed Description of the 12 Conditions:
1. Exponential Moving Averages (EMA):
o Conditions: The indicator uses EMAs with periods 3, 8, and 13 for quick trend-following signals.
o Bullish Signal: EMA3 > EMA8 > EMA13 (Bullish stack).
o Bearish Signal: EMA3 < EMA8 < EMA13 (Bearish stack).
o Reversal Signal: The crossing over or under of these EMAs can signify trend reversals.
2. MACD (Moving Average Convergence Divergence):
o Fast MACD (2, 7, 3) is used to confirm trends quickly.
o Bullish Signal: When the MACD line crosses above the signal line.
o Bearish Signal: When the MACD line crosses below the signal line.
3. Donchian Channel:
o Tracks the highest high and lowest low over a given period (default 20).
o Breakout Signal: Price breaking above the upper band is bullish; breaking below the lower band is bearish.
4. VWAP (Volume-Weighted Average Price):
o Above VWAP: Bullish condition (price above VWAP).
o Below VWAP: Bearish condition (price below VWAP).
5. EMA Stacking & Reversal:
o Tracks the order of EMAs (3, 8, 13) to confirm strong trends and reversals.
o Bullish Reversal: EMA3 < EMA8 < EMA13 followed by a crossing to bullish.
o Bearish Reversal: EMA3 > EMA8 > EMA13 followed by a crossing to bearish.
6. Bull/Bear Flags:
o Bull Flag: Characterized by a strong price movement (flagpole) followed by a pullback and breakout.
o Bear Flag: Similar to Bull Flag but in the opposite direction.
7. Triangle Patterns (Ascending and Descending):
o Detects ascending and descending triangles using pivot highs and lows.
o Ascending Triangle: Higher lows and flat resistance.
o Descending Triangle: Lower highs and flat support.
8. Volume Sensitivity:
o Identifies price moves with significant volume increases.
o High Volume: When current volume is significantly above the moving average volume (set to 1.2x of the average).
9. Momentum Indicators:
o RSI (Relative Strength Index): Confirms overbought and oversold levels with thresholds set at 65 (overbought) and 35 (oversold).
o ADX (Average Directional Index): Confirms strong trends when ADX > 28.
o Momentum Up: Momentum is upward with strong volume and bullish RSI/ADX conditions.
o Momentum Down: Momentum is downward with strong volume and bearish RSI/ADX conditions.
10. Bollinger & Keltner Squeeze:
o Squeeze Condition: A contraction in both Bollinger Bands and Keltner Channels indicates low volatility, signaling a potential breakout.
o Squeeze Breakout: Price breaking above or below the squeeze bands.
11. 3 Consecutive Candles Condition:
o Bullish: Price rises for three consecutive candles with higher highs and lows.
o Bearish: Price falls for three consecutive candles with lower highs and lows.
12. Williams %R and Stochastic RSI:
o Williams %R: A momentum oscillator with signals when the line crosses certain levels.
o Stochastic RSI: Provides overbought/oversold levels with smoother signals.
o Combined Signals: You can choose whether to require both WPR and StochRSI to signal a buy/sell.
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User Inputs (Inputs Tab):
1. Minimum Conditions for Buy/Sell:
o min_conditions: Number of conditions required to trigger a buy/sell signal on the chart (1 to 12).
o Alert_min_conditions: User-defined alert threshold (how many conditions must be met before an alert is triggered).
2. Donchian Channel Settings:
o Show Donchian: Toggle visibility of the Donchian channel.
o Donchian Length: The length of the Donchian Channel (default 20).
3. Bull/Bear Flag Settings:
o Bull Flag Flagpole Strength: ATR multiplier to define the strength of the flagpole.
o Bull Flag Pullback Length: Length of pullback for the bull flag pattern.
o Bull Flag EMA Length: EMA length used to confirm trend during bull flag pattern.
Similar settings exist for Bear Flag patterns.
4. Momentum Indicators:
o RSI Length: Period for calculating the RSI (default 9).
o RSI Overbought: Overbought threshold for the RSI (default 65).
o RSI Oversold: Oversold threshold for the RSI (default 35).
5. Bollinger/Keltner Squeeze Settings:
o Squeeze Width Threshold: The maximum width of the Bollinger and Keltner Bands for squeeze conditions.
6. Stochastic RSI Settings:
o Stochastic RSI Length: The period for calculating the Stochastic RSI.
7. WPR Settings:
o WPR Length: Period for calculating Williams %R (default 14).
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User Inputs (Style Tab):
1. Signal Plotting:
o Control the display and colors of the buy/sell signals, momentum indicators, and pattern signals on the chart.
o Buy/Sell Signals: Can be customized with different colors and shapes (triangle up for buys, triangle down for sells).
o Momentum Signals: Custom circle placement for momentum-up or momentum-down signals.
2. Donchian Channel:
o Show Donchian: Toggle visibility of the Donchian upper, lower, and middle bands.
o Band Colors: Choose the color for each band (upper, lower, middle).
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How to Use the Indicator:
1. Adjust Minimum Conditions: Set the minimum number of conditions that must be met for a signal to appear. For example, set it to 5 if you want only stronger signals.
2. Set Alert Threshold: Define the number of conditions needed to trigger an alert. This can be different from the minimum conditions for visual signals.
3. Customize Appearance: Modify the colors and styles of the signals to match your preferences.
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Conclusion:
This comprehensive trading indicator uses a combination of trend-following, pattern recognition, and momentum-based conditions to help you spot potential buy and sell opportunities. By adjusting the input settings, you can fine-tune it to match your specific trading strategy, making it a versatile tool for different market conditions.
Signal Reliability Based on Condition Count
The reliability of the buy/sell signals increases as more conditions are met. Here's a breakdown of the probabilities:
1. 1-3 Conditions Met: Lower Probability
o Signals that meet only 1-3 conditions tend to have lower reliability and are considered less probable. These signals may represent false positives or weaker market movements, and traders should approach them with caution.
2. 4 Conditions Met: More Reliable Signal
o When 4 conditions are met, the signal becomes more reliable. This indicates that multiple indicators or market patterns are aligning, increasing the likelihood of a valid buy/sell opportunity. While not foolproof, it's a stronger indication that the market may be moving in a particular direction.
3. 5-6 Conditions Met: Strong Signal
o A signal meeting 5-6 conditions is considered a strong signal. This indicates a well-confirmed move, with several technical indicators and market factors aligning to suggest a higher probability of success. These are the signals that traders often prioritize.
4. 7+ Conditions Met: Rare and High-Confidence Signal
o Signals that meet 7 or more conditions are rare and should be considered high-confidence signals. These represent a significant alignment of multiple factors, and while they are less frequent, they are highly reliable when they do occur. Traders can be more confident in acting on these signals, but they should still monitor market conditions for confirmation.
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You can adjust the number of conditions as needed, but this breakdown should give a clear structure on how the signal strength correlates with the number of conditions met!
BTC Markup/Markdown Zones by Koenigsegg📈 BTC Markup/Markdown Zones
A handcrafted indicator designed to mark Bitcoin's most critical High Time Frame (HTF) structure shifts. This tool overlays true institutional-level Markup and Markdown Zones, selected manually after deep market review. Whether you're testing strategies or actively trading, this tool gives you the bigger picture at all times.
🔍 Key Features:
✅ HTF Markup & Markdown Zones
Every zone is manually selected — no indicators, no repainting. Just raw market history and real structure.
✅ Two Display Modes
• Background Zones — soft overlays with low opacity for visual context — with the option to increase opacity manually if desired.
• Start Candle Highlight — sharply highlighted candle marking the final pivot before a macro reversal.
✅ Custom Color Controls (Style Tab)
All visual styling lives in the Style tab, with clearly labeled fields:
• Markup Zone
• Markdown Zone
• Start Candle Highlight Markup
• Start Candle Highlight Markdown
✅ Minimal Input Section
Just one toggle: display mode. Everything else is kept clean and intuitive.
🧠 Purpose:
This script is made for any timeframe:
• Zoom into lower timeframes to know whether you're trading inside a Markup or Markdown
• Use it during strategy testing for true structural awareness
📅 Handpicked Macro Turning Points:
Each zone originates from a manually confirmed candle — the last meaningful candle before a shift in control between bulls and bears:
• FRI 19 AUG 2011 12PM – MARK DOWN
• THU 20 OCT 2011 12AM – MARK UP
• WED 10 APR 2013 12PM – MARK DOWN
• FRI 12 APR 2013 12PM – MARK UP
• SAT 30 NOV 2013 12AM – MARK DOWN
• WED 14 JAN 2015 12PM – MARK UP
• SUN 17 DEC 2017 12PM – MARK DOWN
• SAT 15 DEC 2018 12PM – MARK UP
• WED 14 APR 2021 4AM – MARK DOWN
• TUE 22 JUN 2021 12PM – MARK UP
• WED 10 NOV 2021 12PM – MARK DOWN
• MON 21 NOV 2022 8PM – MARK UP
• THU 14 MAR 2024 4AM – MARK DOWN
• MON 5 AUG 2024 12PM – MARK UP
• MON 20 JAN 2025 4AM – MARK DOWN
💡 Zones are manually updated by me after each new confirmed Markup or Markdown.
🧬 Fractal Structure for MTF Systems
Price is fractal — meaning the same principles of structure repeat across all timeframes. In Version 2, this tool evolves by introducing manually selected sub-zones inside each High Time Frame (HTF) Markup or Markdown. These sub-zones reflect Medium Timeframe (MTF) structure shifts, offering precision for traders who operate on both intraday and swing levels.
This makes the indicator ideal for low timeframe (LTF) Markup/Markdown awareness — whether you're managing 15m entries or building multi-timeframe confluence systems.
No auto-zones. No guesswork. Just clean, intentional structure division within the broader trend, handpicked for maximum clarity and edge.
💡 Pro Tip:
When price is inside a Markup Zone, shorting becomes riskier — you're trading against a macro bullish structure.
When inside a Markdown Zone, longing becomes riskier — you're fighting against confirmed bearish momentum.
Use this tool to stay aligned with the broader move, especially when zoomed into smaller timeframes or managing entries/exits during intraday setups.
📈 Markup Phase – Bullish Sentiment
Definition: A period where price makes higher highs and higher lows — the uptrend is in full force.
Why sentiment is bullish:
- Institutions and smart money are already positioned long.
- Public/institutional demand drives prices up.
- Momentum is supported by positive news, breakouts, and FOMO.
- Higher highs confirm buyers are in control.
📉 Markdown Phase – Bearish Sentiment
Definition: A period where price makes lower lows and lower highs — clear downtrend.
Why sentiment is bearish:
- Distribution has already occurred, and supply outweighs demand.
- Smart money is short or sidelined, waiting for deeper prices.
- Panic selling or trend-following traders add downside momentum.
- Lower lows confirm sellers are in control.
❌ Trading Against the Trend — Consequences:
-Reduced Probability of Success
-You’re fighting the dominant flow. Most participants are pushing in the opposite direction.
-Drawdowns & Stop-Outs
-Countertrend trades often get wicked or flushed before any meaningful move, especially without structure-based entries.
-Low Risk-Reward Ratio
-Trends offer sustained moves. Countertrend trades may have small take-profit zones or chop.
-Mental Drain & Doubt
-Fighting momentum causes anxiety, second-guessing, and emotional reactions.
-Missed Opportunities
-Focusing on fighting the trend makes you blind to the high-probability setups with the trend.
-Increased Transaction Costs
-More stop-outs and re-entries mean more fees, more friction.
-FOMO from Watching the Trend Run
-Entering countertrend means you might watch the trend explode without you.
-Confirmation Bias & Stubbornness
-Countertrend traders often look for reasons to justify staying in the wrong direction — leading to bigger losses.
🧠 Summary
In markup = bulls dominate → you swim with the current.
In markdown = bears dominate → going long is like pushing a rock uphill.
Trading with the trend is not just safer, it's smarter. The edge lives in momentum — not ego.
⚠️ Disclaimer
This indicator is for educational and analytical use only. It is not financial advice and should not be relied on for decision-making without personal analysis.
This is not a predictive tool. No indicator can forecast upcoming price movements.
What you see here is based purely on past market behavior — specifically, historical tops and bottoms that marked the start of confirmed reversals.
This script does not know where the next reversal begins, nor can it determine where a new Markup or Markdown starts or ends. It is designed to provide context, not prediction.
Always trade with responsibility and perform your own due diligence.
Uptrick: Oscillator SpectrumUptrick: Oscillator Spectrum is a versatile trading tool designed to bring together multiple aspects of technical analysis—oscillators, momentum signals, divergence checks, correlation insights, and more—into one script. It includes customizable overlays and alert conditions intended to address a wide range of market conditions and trading styles.
Developed in Pine Script™, Uptrick: Oscillator Spectrum represents an extended version of the classic Ultimate Oscillator concept. It consolidates short-, medium-, and long-term momentum readings, applies correlation analysis across different symbols, and offers optional table-based metrics to provide traders with a more structured overview of potential trade setups. Whether used alongside your existing charts or as a standalone toolkit, it aims to build on and enhance the functionality of the standard Ultimate Oscillator.
### A Few Key Features
- Momentum Insights: Multiple timeframes for oscillators, plus buy/sell signal modes for flexible identification of overbought/oversold situations or crossovers.
- Divergence Detection: Automated checks for bullish/bearish divergences, aiming to help traders spot potential shifts in momentum.
- Correlation Meter: A visual histogram summarizing how selected assets are collectively trending. It is useful for tracking the bigger market picture.
- Gradient Overlays & Bar Coloring: Dynamic color transitions designed to emphasize changes in momentum, trend shifts, and overall sentiment without cluttering the chart.
- Money Flow Tracker: Tracks the flow of money into and out of the market using a smoothed Money Flow Index (MFI). Highlights overbought/oversold conditions with dynamic bar coloring and visual gradient fills, helping traders assess volume-driven sentiment shifts.
- Advanced Table Metrics: An optional table showing return on investment (ROI), collateral risk, and other contextual metrics for supported assets.
- Alerts & Automation: Configurable alerts covering divergence events, crossing of critical levels, and more, helping to keep traders informed of developments in real time.
### Intended Usage
- For Multiple Markets: Works on various markets (cryptocurrencies, forex pairs, stocks) to deliver a consistent view of momentum, potential entry/exit signals, and correlation.
- Adaptable Trading Styles: With customizable input settings, you can enable or disable specific features to align with your preferred strategies—intraday scalping, swing trading, or position holding.
By combining these elements under one indicator, Uptrick: Oscillator Spectrum allows traders to streamline analysis workflows, helping them stay focused on interpreting market moves and making informed decisions rather than juggling multiple scripts.
Purpose
Purpose of the “Uptrick: Oscillator Spectrum” Indicator
The “Uptrick: Oscillator Spectrum” indicator is intended to bring together several technical analysis elements into one tool. It combines oscillator-based momentum readings across different lookback periods, checks for potential divergences, provides optional buy/sell signal triggers, and offers correlation-based insights across multiple symbols. Additionally, it includes features such as bar coloring, gradient visualization, and user-configurable alerts to help highlight various market conditions.
By consolidating these functions, the script aims to help users systematically observe changing momentum, identify when prices reach user-defined overbought or oversold levels, detect when oscillator movements diverge from price, and examine whether different assets are aligning or diverging in their trends. The indicator also allows for optional advanced metric tables, which can supply further context on risk, ROI calculations, or other factors for supported assets. Overall, the script’s purpose is to organize multiple layers of technical analysis so that users have a structured way to evaluate potential trade opportunities and market behavior.
## Usage Guide
Below is an outline of how you can utilize the various components and features of Uptrick: Oscillator Spectrum in your charting workflow.
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### 1. Using the Core Oscillator
- Basic View: By default, the script calculates a multi-timeframe oscillator (commonly displayed as the “Ultimate Oscillator”). This oscillator combines short-, medium-, and long-term measurements of buying pressure and true range.
- Overbought/Oversold Zones: You can configure thresholds (e.g., 70 for overbought, 30 for oversold) to help identify potential turning points. When the oscillator crosses these levels, it may indicate that price is extended in one direction.
- You can use the colors of the main oscillator to help you take short-term trades as well: cyan : Buy , red: Sell
- Alerts: If you enable alerts, the indicator can notify you when the oscillator crosses above or below your chosen overbought/oversold boundaries or when you get buy/sell signals.
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### 2. Buy/Sell Signals in Overlay Modes
Uptrick: Oscillator Spectrum provides several signal modes and a choice between overlay true and overlay false or both. Additionally, you can pick which “line” (data source) the script uses to generate signals. This is set in the “Line to Analyze” dropdown, which includes Oscillator, HMA of Oscillator, and Moving Average. The following sections describe how each piece fits together.
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#### Line to Analyze - Overlay Flase: Oscillator / HMA of Oscillator / Moving Average
1. Oscillator
- The core momentum reading, reflecting short-, medium-, and long-term periods combined.
2. HMA of Oscillator
- Applies a Hull Moving Average to the oscillator, creating a smoother but still responsive curve.
- Signals will be derived from this smoothed line. Some traders find it filters out minor fluctuations while remaining quicker to react than standard averages.
3. Moving Average
- Uses a user-selected MA type (SMA, EMA, WMA, etc.) over the oscillator values, rather than the raw oscillator itself.
- Tends to be more stable than the raw oscillator, but might delay signals more depending on the chosen MA settings.
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#### Signal Modes
Regardless of which line you choose to analyze, you can use one of the following seven signal modes in overlay being true:
1. Overbought/Oversold (Pyramiding)
- What It Does:
- Buy signal when the chosen line crosses below the oversold threshold.
- Sell signal when it crosses above the overbought threshold.
- Pyramiding:
- Allows multiple triggers within the same overbought/oversold event.
2. Overbought/Oversold (Non Pyramiding)
- What It Does:
- Same thresholds but only one signal per oversold or overbought event.
- Use Case:
- Prevents repeated signals and chart clutter.
3. Smoothed MA Middle Crossover
- What It Does:
- Uses an MA defined by the user.
- Buy when crossing above the midpoint (50), Sell when crossing below.
- Use Case:
- Generates fewer signals, focusing on broader momentum shifts. There is no pyramiding.
In this image ,for example, the VWMA is used with length of 14 to identify buy sell signals.
4. Crossing Above Overbought/Below Oversold (Non Pyramiding)
- What It Does:
- Buy occurs if the line exits oversold territory by crossing back above it.
- Sell occurs if the line exits overbought territory by crossing back below it.
- Non Pyramiding:
- Restricts repeated signals until conditions reset.
5. Crossing Above Overbought/Below Oversold (Pyramiding)
- What It Does:
- Same thresholds, but allows multiple signals if the line repeatedly dips in and out of overbought or oversold.
- Use Case:
- More frequent entries/exits for active traders.
6. Divergence (Non Pyramiding)
- What It Does:
- Identifies bullish or bearish divergences using the chosen line vs. price.
- Buy for bullish divergence (higher low on the line vs. lower low on price), Sell for bearish divergence.
- Single Trigger:
- Only one signal per identified divergence event. (non pyramiding)
7. Divergence (Pyramiding)
- What It Does:
- Same divergence logic but triggers multiple times if the script sees repeated divergence in the same direction.
- Use Case:
- Could suit traders who layer positions during sustained divergence scenarios.
#### Overlay Modes: True vs. False
1. Overlay True
- Buy/sell arrows or labels plot directly on the main price chart, often at or near candlesticks.
- Bar Coloring:
- Can turn the candlestick bars green (buy) or red (sell), with intensity reflecting signal recency if bar coloring is enabled for this mode. (read below.)
- Advantage:
- Everything (price, signals, bar colors) is in one spot, making it straightforward to associate signals with current market action. You can adjust the periods of the main oscillator or lookback periods of divergences or overbought/oversold thresholds, to play around with your signals.
2. Overlay False
- Signal Placement:
- Signals appear in a sub-window or oscillator panel, leaving the main price chart uncluttered.
- Bar Coloring:
- You may still enable bar colors on the main chart (green for buy, red for sell) if desired.
- Alternatively, you can keep them neutral if you prefer a completely separate display of signals.
- Advantage:
- Clear separation of price action from signals, useful for cleaner charts or if using multiple overlay-based tools.
At the bottom are the signals for overlay being false and on the chart are the signals for overlay being true:
#### Bar Color Adjustments
1. Coloring Logic
- Bars typically go green on buy signals, red on sell signals.
- The opacity or brightness can vary to indicate signal freshness. When a new signal is formed, the color gets brighter. When there is no signal for a longer period of time, then the color slowly fades.
2. Enabling Bar Coloring
- In the indicator’s settings, turn on Bar Coloring.
- Choose “Signals Overlay True” or “Signals Overlay False” from the “Color should depend on:” dropdown, depending on which overlay approach you want to drive your bar colors. You can also chose the cloud fill in overlay false, correlation meter and smoothed HMA to color bars. Read more below:
### Bar Color Options:
When you enable bar coloring in Uptrick: Oscillator Spectrum, you can select which component or signal logic drives the color changes. Below are the five available choices:
---
#### Option 1: Overlay True Signals
- What It Does:
- Uses signals generated under the Overlay True mode to color the bars on your main chart.
- If a buy signal is triggered, bars turn green. If a sell signal occurs, bars turn red.
- Color Intensity:
- Bars appear brighter (more opaque) immediately after a new signal fires, then gradually fade over subsequent bars if no new signal appears.
---
#### Option 2: Overlay False Signals
- What It Does:
- Links bar coloring to signals generated when Overlay False mode is active.
- Buy/sell labels typically plot in a separate sub-window instead of the main chart, but your price bars can still change color based on these signals.
- Color Intensity:
- Similar to Overlay True, new buy/sell signals yield stronger color intensity, which fades over time.
- Use Case:
- Helps maintain a clean main chart (with signals off-chart) while still providing an immediate color-coded indication of a buy or sell state.
- Particularly useful if you prefer less clutter from signal markers on your price chart yet still want a visual representation of signal timing.
In this example normal divergence Pyramiding Signals are used in the overlay being true and the signals in overlay false are signals that analyze the HMA. This can help clear out noise (using a combo of both).
Option 3: Money Flow Tracker
What It Does:
The Money Flow Tracker uses the Money Flow Index (MFI), a volume-weighted oscillator, to measure the strength of money flowing into or out of an asset. The script smooths the raw MFI data using an EMA for a more responsive and visually intuitive output.
The feature also includes dynamic color gradients and bar coloring that highlight whether money flow is positive or negative.
Green Fill/Bar Color: Indicates positive money flow, suggesting potential accumulation.
Red Fill/Bar Color: Indicates negative money flow, signaling potential distribution.
Overbought and oversold thresholds are dynamically emphasized with transparency, making it easier to identify high-confidence zones.
Use Case:
Ideal for traders focusing on volume-driven sentiment to identify turning points or confirm existing trends.
Suitable for assessing broader market conditions when used alongside other indicators like oscillators or correlation analysis.
Provides additional clarity in spotting areas of accumulation or distribution, making it a valuable complement to price action and momentum studies.
---
#### Option 4: Correlation Meter
- What It Does:
- Colors the bars based on the indicator’s Correlation Meter output. The script checks multiple chosen tickers and sums up how many are trending positively or negatively.
- If the meter indicates an overall bullish bias (e.g., more than three assets in uptrend), bars turn green; if it’s bearish, bars turn red.
- Trend Readings:
- The correlation meter typically plots a histogram of bullish/neutral/bearish states. The bar color option links your chart’s candlestick coloring to that higher-level market sentiment.
- Use Case:
- Useful for traders wanting a quick visual prompt of whether the broader market (or a selection of related assets) is bullish or bearish at any given time.
- Helps avoid signals that conflict with the market majority.
#### Option 5: Smoothed HMA
- What It Does:
- Bar colors are driven by the slope or state of the Hull Moving Average (HMA) of the oscillator, rather than individual buy/sell triggers or correlation data.
- If the HMA indicates a strong upward slope (possibly darkening), bars may turn green; if the slope is downward (purple in the HMA line), bars turn red.
- Use Case:
- Ideal for those who focus on momentum continuity rather than discrete signals like overbought/oversold or divergence.
- May help identify smoother, more sustained moves, as the HMA filters out minor oscillations.
---
### 3. Using the Hull Moving Average (HMA) of the Oscillator
- HMA Calculation: You can enable a dedicated Hull Moving Average (HMA) for the oscillator. This creates a smoother line of the same underlying momentum reading, typically responding more quickly than classic moving averages.
- Color Intensity: As the HMA sustains an uptrend or downtrend, the script can adjust the line’s color. When slope momentum persists in one direction, the color appears more opaque. This intensification can hint that the existing direction may be well-established.
- Reversal Potential: If you observe the HMA color shifting or darkening after multiple bars of slope in the same direction, it may indicate increasing momentum. Conversely, a sudden flattening or change in color can be a clue that momentum is waning.
---
### 4. Moving Average Overlays & Gradient Cloud
- Oscillator MA: The script allows you to apply moving average types (SMA, EMA, SMMA, WMA, or VWMA) to the core oscillator, rather than to price. This can smooth out noise in the oscillator, potentially highlighting more consistent momentum shifts.
- Gradient Cloud: You can also enable a cloud in overlay true between two moving averages (for instance, a Hull MA and a Double EMA) on the price chart. The cloud fills with different colors, depending on which MA is above the other. This can provide a quick visual reference to bullish or bearish areas.
---
### 5. Divergence Detection
- Bullish & Bearish Divergence: By toggling “Calculate Divergence,” the script looks for oscillator pivots that contrast with price pivots (e.g., price making a lower low while the oscillator makes a higher low).
- A divergence is when the price makes an opposite pivot to the indicator value. E.g. Price makes lower low but indicator does higher low - This suggests a bullish divergence. THe opposite is for a bearish divergence.
- Visual Labels: When a divergence is found, labels (such as “Bull” or “Bear”) appear on the oscillator. This helps you see if the oscillator’s momentum patterns differ from the price movement.
- Filtering Signals: You can combine divergence signals with other features like overbought/oversold or the HMA slope to refine potential entries or exits.
---
### 6. Correlation & Multi-Ticker Analysis
- Correlation Meter: You can select up to five tickers in the settings. The script calculates a slope-based metric for each, then combines those metrics to show an overall bullish or bearish tendency (displayed as a histogram).
- Bar Coloring & Overlay: If you activate correlation-based bar coloring, it will reflect the broader trend alignment among the selected assets, potentially indicating when most are trending in the same direction.
- Use Case: If you trade multiple markets, the correlation histogram can help you quickly see if several major assets support the same market bias or are diverging from one another.
—
### 7. Money Flow Tracker
Money Flow Calculation: The Money Flow Tracker calculates the Money Flow Index (MFI) based on price and volume data, factoring in buying pressure and selling pressure. The output is smoothed using a low-lag EMA to reduce noise and enhance usability.
Visual Features:
Dynamic Gradient Fill:
The space between the smoothed MFI line and the midline (set at 50) is filled with a gradient.
Above 50: Green gradient, with intensity increasing as the MFI moves further above the midline.
Below 50: Red gradient, with intensity increasing as the MFI moves further below the midline.
This gradient provides a clear visual representation of money flow strength and direction, making it easier to assess sentiment shifts at a glance.
Overbought/Oversold Levels: Default thresholds are set at 70 (overbought) and 30 (oversold). When the MFI crosses these levels, it signals potential reversals or trend continuations.
Bar Coloring:
Bars turn green for positive money flow and red for negative money flow.
Color intensity fades over time, ensuring recent signals stand out while older ones remain visible without dominating the chart.
Alerts:
Alerts are triggered when the Money Flow Tracker crosses into overbought or oversold zones, keeping traders informed of critical conditions without constant monitoring.
Practical Applications:
Trend Confirmation: Use the Money Flow Tracker alongside the oscillator or HMA to confirm trends or identify potential reversals.
Volume-Based Reversal Signals: Spot turning points where price action aligns with shifts in money flow direction.
Sentiment Analysis: Gauge whether market participants are accumulating (positive flow) or distributing (negative flow) assets, offering an additional layer of insight into price movement.
(Space for an example chart: “Money Flow Tracker with gradient fills and overbought/oversold levels”)
### 8. Putting It All Together
- Combining Signals: A practical approach might be to watch for a bullish divergence in the oscillator, confirm it with a shift in the HMA slope color, and then wait for the price to be near or below oversold conditions. The correlation histogram may further confirm if the broader market is also leaning bullish at that time.
- Visual Cues: Bar coloring adds another layer, making your chart easier to interpret at a glance. You can also set alerts to ensure you don’t miss key events like divergences, crossovers, or moving average flips.
- Flexibility: Not every feature needs to be used simultaneously. You might opt to focus on divergences and overbought/oversold signals, or you could emphasize the correlation histogram and bar colors. The settings let you enable or disable each module to suit your style.
---
### 9. Tips for Customization
- Adjust Periods: Shorter periods can yield more signals but also more noise. Longer periods may provide steadier, but fewer, signals.
- Set Appropriate Alert Conditions: Only alert on events most relevant to your strategy to avoid overload.
- Explore Different MAs: Depending on the instrument, some moving average types may give a smoother or more responsive indication.
- Monitor Risk Management: As with any tool, these signals do not guarantee performance, so consider position sizing and stop-loss strategies.
---
By toggling and experimenting with the features described above—buy/sell signals, divergences, moving averages, dynamic gradient clouds, and correlation analysis—you can tailor Uptrick: Oscillator Spectrum to your specific trading approach. Each module is designed to give you a clearer, structured view of potential momentum shifts, overbought or oversold states, and the alignment or divergence of multiple assets.
## Features Explanation
Below is a detailed overview of key features in Uptrick: Oscillator Spectrum. Each component is designed to provide different angles of market analysis, allowing you to customize the tool to your preferences.
---
### 1. Main Oscillator
- Purpose: The primary oscillator in this script merges short-, medium-, and long-term views of buying pressure and true range into a single line.
- Calculation: It weights each period’s contribution (e.g., a heavier focus on the short period if desired) and normalizes the result on a 0–100 scale, where higher readings may suggest more robust momentum. (like from the classic Ultimate Oscillator)
- Practical Use:
- Traders can watch for overbought/oversold conditions at user-defined thresholds (e.g., 70/30).
- It can also provide a straightforward momentum reading for those who prefer to see if momentum is rising, falling, or leveling off.
---
### 2. HMA of the Smoothed Oscillator
- What It Is: A Hull Moving Average (HMA) applied to the main oscillator values. The HMA is often more responsive than standard MAs, offering smoother lines while preserving relatively quick reaction to changes.
- How It Works:
- The script takes the oscillator’s output and processes it through a Hull MA calculation.
- The HMA’s slope and color can change more dynamically, highlighting sharper momentum shifts.
- Why It’s Useful:
- By smoothing out minor fluctuations, the HMA can highlight trends in the oscillator’s trajectory.
- If you see an extended run in the HMA slope, it may indicate a more persistent trend in momentum.
- Color Intensity:
- As the HMA continues in one direction for several bars, the script can intensify the color, signaling stronger or more sustained momentum in that direction.
- Sudden changes in color or slope can signal the start of a new momentum swing.
---
### 3. Gradient Fill
This script uses two gradient-based visual elements:
1. Shining/Layered Gradient on the Main Oscillator
- Purpose: Adds multiple layers around the oscillator line (above and below) to emphasize slope changes and highlight how quickly the oscillator is moving up or down.
- Color Changes:
- When the oscillator rises, it uses a color scheme (e.g., aqua/blue) that intensifies as the slope grows.
- When the oscillator declines, it uses a distinct color (e.g., red/pink).
- User Benefit: Makes it easier to see at a glance if momentum is accelerating or decelerating, beyond just the numerical reading.
2. Dynamic Cloud Fill (Between MAs)
- Purpose: Allows you to plot two moving averages (for example, a short-term Hull MA and a longer-term DEMA) and fill the area between them with a color gradient.
- Bullish vs. Bearish:
- When the short MA is above the long MA, the cloud might appear in a greenish hue.
- When the short MA is below the long MA, the cloud can switch to red or another color.
- Transparency/Intensity:
- The fill can get more opaque if the difference between the two MAs is large, indicating a stronger trend but a higher probability of a reversal.
- User Benefit: Helps visualize changes in trend or momentum across multiple time horizons, all within a single chart overlay.
---
### 4. Correlation Meter & Symbol Inputs
- What It Is: This feature looks at multiple user-selected symbols (e.g., BTC, ETH, BNB, etc.) and computes each symbol’s short-term slope. It then aggregates these slopes into an overall “trend” score.
- Inputs Configuration:
1. Ticker Inputs: You can specify up to five different tickers.
2. Timeframe: Decide whether to pull data from different chart timeframes for each symbol.
3. Slope Calculation: The script may compute, for instance, a 5-period SMA minus a 20-period SMA to gauge if each symbol is trending up or down.
- Market Trend Histogram:
- Displays a column that goes above/below zero depending on how many symbols are bullish or bearish.
- If more than three (out of five) symbols are bullish, the histogram can show a green bar at +1; if fewer than three are bullish, it can show red at –1.
- How to Use:
- Quick Glance: Lets you know if most correlated assets are aligning or diverging.
- Bar Coloring (Optional): If enabled, your main chart’s bars can reflect the aggregated correlation, turning green or red depending on the meter’s reading.
---
### 5. Advanced Metrics Table
- What It Is: An optional table displaying additional metrics for several cryptocurrencies (or any symbols you define).
- Metrics Included:
1. ROI (30D): Calculates return relative to the lowest price in a 30-day period.
2. Collateral Risk: Uses standard deviation to assess volatility (higher risk if standard deviation is large).
3. Liquidity Recovery: A rolling average of volume, aiming to show how liquidity flows might recover over time.
4. Weakening (Rate of Change): Reflects how quickly price is changing compared to previous bars.
5. Monetary Bias (SMA): A simple average of recent prices. If price is below this SMA, it might be seen as undervalued relative to the short term.
6. Risk Phase: Categorizes risk as low, medium, or high based on the standard deviation figure.
7. DCA Signal: Suggests “Accumulate” or “Do Not Accumulate” by checking if the current price is below or above the SMA.
- Why It’s Useful:
- Offers a concise view of multiple assets in one place—helpful for portfolio-level insight.
- DCA (Dollar-Cost Averaging) suggestions can guide longer-term strategies, while volatility (collateral risk) helps gauge how aggressive the price swings might be.
---
### 6. Other Vital Aspects
- Alerts & Notifications:
- The script can trigger alerts for various conditions—crossovers, divergence detections, overbought/oversold transitions, or correlation-based signals.
- Useful for automating watchlists or ensuring you don’t miss a key setup while away from the screen.
- Customization:
- Each module (oscillator settings, divergence detection, correlation meter, advanced metrics table, etc.) can be enabled or disabled based on your preferences.
- You can fine-tune parameters (e.g., periods, smoothing lengths, alert triggers) to align the indicator with different trading styles—scalping, swing, or position trading.
- Combining Features:
- One might watch the main oscillator for momentum extremes, confirm via the HMA slope, check if correlation supports the same bias, and look at the table for risk-phase validation.
- This multi-layer approach can help develop a more structured and informed trading view.
(Space for an example chart: “A fully configured layout showing oscillator, HMA, gradient cloud, correlation meter, and table all in use.”)
7. Money Flow Tracker
Purpose: The Money Flow Tracker adds a volume-based perspective to the indicator suite by incorporating the Money Flow Index (MFI), which assesses buying and selling pressure over a defined period. By smoothing the MFI using an exponential moving average (EMA), the feature highlights the directional flow of capital into and out of the market with greater clarity and reduced noise.
Dynamic Gradient Visualization:
The Money Flow Tracker enhances visual analysis with gradient fills that reflect the MFI’s relationship to the midline (50).
Above 50: A green gradient emerges, intensifying as the MFI moves higher, indicating stronger positive money flow.
Below 50: A red gradient appears, with deeper shades signifying increasing selling pressure.
Transparency dynamically adjusts based on the MFI’s proximity to the midline, making high-confidence zones (closer to 0 or 100) visually distinct.
Directional Sensitivity:
The Tracker emphasizes the importance of overbought (above 70) and oversold (below 30) zones. These thresholds help traders identify when an asset might be overextended, signaling potential reversals or trend continuations.
The inclusion of a midline (50) as a neutral zone helps gauge shifts between accumulation (money flowing in) and distribution (money flowing out).
Bar Integration:
By enabling bar coloring linked to the Money Flow Tracker, traders can visualize its impact directly on price bars.
Green bars reflect positive money flow (above 50), signaling bullish conditions.
Red bars indicate negative money flow (below 50), highlighting bearish sentiment.
Intensity adjustments ensure that recent signals are more visually prominent, while older signals gradually fade for a clean, non-cluttered chart.
Key Advantages:
Volume-Informed Context: Traditional oscillators often focus solely on price; the Money Flow Tracker incorporates volume, adding a crucial dimension for analyzing market behavior.
Adaptive Filtering: The EMA-smoothing feature ensures that sudden, insignificant spikes in volume don’t trigger false signals, providing a clearer and more actionable representation of money flow trends.
Early Warning System: Divergences between price movement and the Money Flow Tracker’s trends can signal potential turning points, helping traders anticipate reversals before they occur.
Practical Use Cases:
Trend Confirmation: Pair the Money Flow Tracker with the oscillator or HMA to confirm bullish or bearish trends. For example, a rising oscillator with positive money flow indicates strong buying interest.
Identifying Entry/Exit Zones: Use overbought/oversold conditions as entry/exit points, particularly when combined with other features like divergence detection.
Market Sentiment Analysis: The Tracker’s ability to dynamically assess buying and selling pressure provides a clear picture of market sentiment, helping traders adjust their strategies to align with broader trends.
By understanding these features—main oscillator readings, the HMA’s smoothing capabilities, gradient-based visual highlights, correlation insights, advanced metrics, and the money flow tracker—you can tailor Uptrick: Oscillator Spectrum to your specific needs, whether you’re focusing on quick trades, longer-term market moves, or broad portfolio health.
Originality of the “Uptrick: Oscillator Spectrum” Indicator
While it includes elements of standard momentum analysis, Uptrick: Oscillator Spectrum sets itself apart by adding an array of features that broaden the typical oscillator’s scope:
1. Slope Coloring & Layered Gradient Effects
- Beyond just plotting a single line, the indicator visually highlights momentum shifts using color changes and gradient fills.
- As the oscillator’s slope becomes steeper or flatter, these gradients intensify or fade, helping users see at a glance when momentum is accelerating, slowing, or reversing.
2. Mean Reversion & Divergence Detection
- The script offers optional logic for marking potential mean reversion points (e.g., overbought/oversold crossovers) and flagging divergences between price and the oscillator line.
- These divergence signals come with adjustable lookback parameters, giving traders control over how recent or extended the pivots should be for detection.
- This functionality can reveal subtle momentum discrepancies that a basic oscillator might overlook.
3. Integrated Multi-Asset Correlation Meter
- In addition to monitoring a single symbol, the indicator can fetch data for multiple tickers. It aggregates each symbol’s slope into a histogram showing whether the broader market (or a group of assets) leans bullish or bearish.
- This cross-market insight moves beyond standard “one-symbol, one-oscillator” usage, adding a bigger-picture perspective in one tool.
4. Advanced Metrics Table
- Users can enable a table that covers ROI calculations, volatility-based risk (“Collateral Risk”), liquidity checks, DCA signals, and more.
- Rather than just seeing an oscillator value, traders can view additional metrics for selected assets in one place, helping them judge overall market conditions or assess multiple instruments simultaneously.
5. Flexible Overlay & Bar Coloring
- Signals can be displayed directly on the price chart (Overlay True) or in a sub-window (Overlay False).
- Bars themselves may change color (e.g., green for bullish or red for bearish) according to different rules—signals, dynamic cloud fill, correlation meter states, etc.
- This adaptability allows traders to keep the chart as simple or as info-rich as they prefer.
6. Custom Smoothing Options & HMA Extensions
- The oscillator can be processed further with a Hull Moving Average (HMA) to reduce noise while still reacting quickly to market changes.
- Slope-based coloring on the HMA provides an additional layer of visual feedback, which is not common in a standard oscillator.
By blending traditional momentum checks with slope-based color feedback, mean reversion triggers, divergence signals, correlation analysis, and an optional metrics table, Uptrick: Oscillator Spectrum offers a more rounded approach than a typical oscillator. It integrates multiple market insights—both visual and analytical—into one script, giving users a broader toolkit for studying potential reversals, gauging momentum strength, and assessing multi-asset trends.
## Conclusion
Uptrick: Oscillator Spectrum brings together multiple layers of analysis—oscillator momentum, divergence detection, correlation insights, HMA smoothing, and more—into one adaptable toolkit. It aims to streamline your charting process by offering meaningful visual cues (such as gradient fills and bar color shifts), advanced tables for broader market data, and flexible alerts to keep you informed of potential setups.
Traders can choose the specific features that suit their style, whether they prefer to focus on raw oscillator signals, multi-ticker correlation, or smooth trend cues from the HMA. By centralizing these different methods in one place, Uptrick: Oscillator Spectrum can help users build more structured approaches to spotting trend shifts and extended conditions, while also remaining compatible with additional analysis techniques.
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### Disclaimer
This script is provided for informational purposes only and does not constitute financial or investment advice. Past performance is not indicative of future results, and all trading involves risk. You should carefully consider your objectives, risk tolerance, and financial situation before making any trading decisions.
AI Momentum [YinYang]Overview:
AI Momentum is a kernel function based momentum Indicator. It uses Rational Quadratics to help smooth out the Moving Averages, this may give them a more accurate result. This Indicator has 2 main uses, first it displays ‘Zones’ that help you visualize the potential movement areas and when the price is out of bounds (Overvalued or Undervalued). Secondly it creates signals that display the momentum of the current trend.
The Zones are composed of the Highest Highs and Lowest lows turned into a Rational Quadratic over varying lengths. These create our Rational High and Low zones. There is however a second zone. The second zone is composed of the avg of the Inner High and Inner Low zones (yellow line) and the Rational Quadratic of the current Close. This helps to create a second zone that is within the High and Low bounds that may represent momentum changes within these zones. When the Rationalized Close crosses above the High and Low Zone Average it may signify a bullish momentum change and vice versa when it crosses below.
There are 3 different signals created to display momentum:
Bullish and Bearish Momentum. These signals display when there is current bullish or bearish momentum happening within the trend. When the momentum changes there will likely be a lull where there are neither Bullish or Bearish momentum signals. These signals may be useful to help visualize when the momentum has started and stopped for both the bulls and the bears. Bullish Momentum is calculated by checking if the Rational Quadratic Close > Rational Quadratic of the Highest OHLC4 smoothed over a VWMA. The Bearish Momentum is calculated by checking the opposite.
Overly Bullish and Bearish Momentum. These signals occur when the bar has Bullish or Bearish Momentum and also has an Rationalized RSI greater or less than a certain level. Bullish is >= 57 and Bearish is <= 43. There is also the option to ‘Factor Volume’ into these signals. This means, the Overly Bullish and Bearish Signals will only occur when the Rationalized Volume > VWMA Rationalized Volume as well as the previously mentioned factors above. This can be useful for removing ‘clutter’ as volume may dictate when these momentum changes will occur, but it can also remove some of the useful signals and you may miss the swing too if the volume just was low. Overly Bullish and Bearish Momentum may dictate when a momentum change will occur. Remember, they are OVERLY Bullish and Bearish, meaning there is a chance a correction may occur around these signals.
Bull and Bear Crosses. These signals occur when the Rationalized Close crosses the Gaussian Close that is 2 bars back. These signals may show when there is a strong change in momentum, but be careful as more often than not they’re predicting that the momentum may change in the opposite direction.
Tutorial:
As we can see in the example above, generally what happens is we get the regular Bullish or Bearish momentum, followed by the Rationalized Close crossing the Zone average and finally the Overly Bullish or Bearish signals. This is normally the order of operations but isn’t always how it happens as sometimes momentum changes don’t make it that far; also the Rationalized Close and Zone Average don’t follow any of the same math as the Signals which can result in differing appearances. The Bull and Bear Crosses are also quite sporadic in appearance and don’t generally follow any sort of order of operations. However, they may occur as a Predictor between Bullish and Bearish momentum, signifying the beginning of the momentum change.
The Bull and Bear crosses may be a Predictor of momentum change. They generally happen when there is no Bullish or Bearish momentum happening; and this helps to add strength to their prediction. When they occur during momentum (orange circle) there is a less likely chance that it will happen, and may instead signify the exact opposite; it may help predict a large spike in momentum in the direction of the Bullish or Bearish momentum. In the case of the orange circle, there is currently Bearish Momentum and therefore the Bull Cross may help predict a large momentum movement is about to occur in favor of the Bears.
We have disabled signals here to properly display and talk about the zones. As you can see, Rationalizing the Highest Highs and Lowest Lows over 2 different lengths creates inner and outer bounds that help to predict where parabolic movement and momentum may move to. Our Inner and Outer zones are great for seeing potential Support and Resistance locations.
The secondary zone, which can cross over and change from Green to Red is also a very important zone. Let's zoom in and talk about it specifically.
The Middle Zone Crosses may help deduce where parabolic movement and strong momentum changes may occur. Generally what may happen is when the cross occurs, you will see parabolic movement to the High / Low zones. This may be the Inner zone but can sometimes be the outer zone too. The hard part is sometimes it can be a Fakeout, like displayed with the Blue Circle. The Cross doesn’t mean it may move to the opposing side, sometimes it may just be predicting Parabolic movement in a general sense.
When we turn the Momentum Signals back on, we can see where the Fakeout occurred that it not only almost hit the Inner Low Zone but it also exhibited 2 Overly Bearish Signals. Remember, Overly bearish signals mean a momentum change in favor of the Bulls may occur soon and overly Bullish signals mean a momentum change in favor of the Bears may occur soon.
You may be wondering, well what does “may occur soon” mean and how do we tell?
The purpose of the momentum signals is not only to let you know when Momentum has occurred and when it is still prevalent. It also matters A LOT when it has STOPPED!
In this example above, we look at when the Overly Bullish and Bearish Momentum has STOPPED. As you can see, when the Overly Bullish or Bearish Momentum stopped may be a strong predictor of potential momentum change in the opposing direction.
We will conclude our Tutorial here, hopefully this Indicator has been helpful for showing you where momentum is occurring and help predict how far it may move. We have been dabbling with and are planning on releasing a Strategy based on this Indicator shortly.
Settings:
1. Momentum:
Show Signals: Sometimes it can be difficult to visualize the zones with signals enabled.
Factor Volume: Factor Volume only applies to Overly Bullish and Bearish Signals. It's when the Volume is > VWMA Volume over the Smoothing Length.
Zone Inside Length: The Zone Inside is the Inner zone of the High and Low. This is the length used to create it.
Zone Outside Length: The Zone Outside is the Outer zone of the High and Low. This is the length used to create it.
Smoothing length: Smoothing length is the length used to smooth out our Bullish and Bearish signals, along with our Overly Bullish and Overly Bearish Signals.
2. Kernel Settings:
Lookback Window: The number of bars used for the estimation. This is a sliding value that represents the most recent historical bars. Recommended range: 3-50.
Relative Weighting: Relative weighting of time frames. As this value approaches zero, the longer time frames will exert more influence on the estimation. As this value approaches infinity, the behavior of the Rational Quadratic Kernel will become identical to the Gaussian kernel. Recommended range: 0.25-25.
Start Regression at Bar: Bar index on which to start regression. The first bars of a chart are often highly volatile, and omission of these initial bars often leads to a better overall fit. Recommended range: 5-25.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
Dee_MeterHere's how you can effectively use the Dee Meter indicator:
1. **Understanding the Basics**:
- Dee Meter evaluates the market sentiment across various sectors.
- It calculates the overall market trend and presents it in percentage form through a line graph.
2. **Indicator Results**:
- When you add the Dee Meter indicator to your chart, you'll notice two key results: Bull and Bear percentages, along with a line graph.
- The Bull percentage reflects the strength of bullish (positive) sentiment, while the Bear percentage indicates bearish (negative) sentiment.
- For example, if the Bull percentage is 55% and the Bear percentage is 45%, it signifies that the bulls currently have a stronger influence in the market.
3. **Interpreting Percentages**:
- Utilize the Bull and Bear percentages to craft your analysis strategy.
- A high Bull percentage in a bullish market suggests strong bullish momentum.
- In the case of a bullish trend showing signs of weakening (e.g., a double top pattern), monitor the Bull and Bear percentages for early reversal indications.
- A decrease in the Bull percentage and an increase in the Bear percentage could hint at a potential market reversal.
4. **Line Graph Analysis**:
- The line graph visually depicts the strength of bulls (green line) and bears (red line) over time.
- During a bullish trend, the green line rises while the red line remains lower, indicating bullish strength.
- Conversely, during a bearish trend, the red line climbs higher, indicating bearish dominance.
5. **Cross Over and Cross Under**:
- Cross-over and cross-under scenarios occur when the market abruptly reverses direction.
- For instance, in a bullish market that suddenly turns bearish, the red line could cross above the green line, indicating increased bearish power.
- In a bearish market that experiences a sudden influx of buying activity, the green line might cross above the red line, signifying strong buying interest.
6. **Applying the Indicator**:
- Use the Dee Meter to build your own trading strategies and make informed decisions.
- Keep an eye on changes in Bull and Bear percentages to identify shifts in market sentiment.
- Monitor line graph movements to assess the relative strength of bulls and bears.
In summary, the Dee Meter indicator is a valuable tool for assessing market sentiment and confirming trends in the Indian market. By understanding and utilizing the Bull and Bear percentages, line graph analysis, and cross-over/cross-under scenarios, you can develop effective trading strategies and trade with greater confidence.
RedK EVEREX - Effort Versus Results ExplorerRedK EVEREX is an experimental indicator that explores "Volume Price Analysis" basic concepts and Wyckoff law "Effort versus Result" - by inspecting the relative volume (effort) and the associated (relative) price action (result) for each bar - showing the analysis as an easy to read "stacked bands" visual. From that analysis, we calculate a "Relative Rate of Flow" - an easy to use +100/-100 oscilator that can be used to trigger a signal when a bullish or bearish mode is detected for a certain user-selected length of bars.
Basic Concepts of VPA
-------------------------------
(The topics of VPA & Wyckoff Effort vs Results law are too comprehensive to cover here - So here's just a very basic summary - please review these topics in detail in various sources available here in TradingView or on the web)
* Volume Price Analysis (VPA) is the examination of the number of shares or contracts of a security that have been traded in a given period, and the associated price movement. By analyzing trends in volume in conjunction with price movements, traders can determine the significance of changes in price and what may unfold in the near future.
* Oftentimes, high volumes of trading can infer a lot about investors’ outlook on a market or security. A significant price increase along with a significant volume increase, for example, could be a credible sign of a continued bullish trend or a bullish reversal. Adversely, a significant price decrease with a significant volume increase can point to a continued bearish trend or a bearish trend reversal.
* Incorporating volume into a trading decision can help an investor to have a more balanced view of all the broad market factors that could be influencing a security’s price, which helps an investor to make a more informed decision.
* Wyckoff's law "Effort versus results" dictates that large effort is expected to be accompanied with big results - which means that we should expect to see a big price move (result) associated with a large relative volume (effort) for a certain trading period (bar).
* The way traders use this concept in chart analysis is to mainly look for imbalances or invalidation. for example, when we observe a large relative volume that is associated with very limited price change - that should trigger an early flag/warning sign that the current price trend is facing challenges and may be an early sign of "reversal" - this applies in both bearish and bullish conditions. on the other hand, when price starts to trend in a certain direction and that's associated with increasing volume, that can act as kind of validation, or a confirmation that the market supports that move.
How does EVEREX work
---------------------------------
* EVEREX inspects each bar and calculates a relative value for volume (effort) and "strength of price movement" (result) compared to a specified lookback period. The results are then visualized as stacked bands - the lower band represents the relative volume, the upper band represents the relative price strength - with clear color coding for easier analysis.
* The scale of the band is initially set to 100 (each band can occupy up to 50) - and that can be changed in the settings to 200 or 400 - mainly to allow a "zoom in" on the bands.
* Reading the resulting stacked bands makes it easier to see "balanced" volume/price action (where both bands are either equally strong, or equally weak), or when there's imbalance between volume and price (for example, a compression bar will show with high volume band and very small/tiny price action band) - another favorite pattern in VPA is the "Ease of Move", which will show as a relatively small volume band associated with a large "price action band" (either bullish or bearish) .. and so on.
* a bit of a techie piece: why the use of a custom "Normalize()" function to calculate "relative" values in EVEREX?
When we evaluate a certain value against an average (for example, volume) we need a mechanism to deal with "super high" values that largely exceed that average - I also needed a mechanism that mimics how a trader looks at a volume bar and decides that this volume value is super low, low, average, above average, high or super high -- the issue with using a stoch() function, which is the usual technique for comparing a data point against a lookback average, is that this function will produce a "zero" for low values, and cause a large distortion of the next few "ratios" when super large values occur in the data series - i researched multiple techniques here and decided to use the custom Normalize() function - and what i found is, as long as we're applying the same formula consistently to the data series, since it's all relative to itself, we can confidently use the result. Please feel free to play around with this part further if you like - the code is commented for those who would like to research this further.
* Overall, the hope is to make the bar-by-bar analysis easier and faster for traders who apply VPA concepts in their trading
What is RROF?
--------------------------
* Once we have the values of relative volume and relative price strength, it's easy from there to combine these values into a moving index that can be used to track overall strength and detect reversals in market direction - if you think about it this a very similar concept to a volume-weighted RSI. I call that index the "Relative Rate of Flow" - or RROF (cause we're not using the direct volume and price values in the calculation, but rather relative values that we calculated with the proprietary "Normalize" function in the script.
* You can show RROF as a single or double-period - and you can customize it in terms of smoothing, and signal line - and also utilize the basic alerts to get notified when a change in strength from one side to the other (bullish vs bearish) is detected
* In the chart above, you can see how the RROF was able to detect change in market condition from Bearsh to Bullish - then from Bullish to Bearish for TSLA with good accuracy.
Other Usage Options in EVEREX
------------------------------------
* I wrote EVEREX with a lot of flexibility and utilization in mind, while focusing on a clean and easy to use visual - EVEREX should work with any time frame and any instrument - in instruments with no volume data, only price data will be used.
* You can completely hide the "EVEREX bands" and use EVEREX as a single or dual period strength indicator (by exposing the Bias/Sentiment plot which is hidden by default) -
here's how this setup would look like - in this mode, you will basically be using EVEREX the same way you're using a volume-weighted RSI
* or you can hide the bias/sentiment, and expose the Bulls & Bears plots (using the indicator's "Style" tab), and trade it like a Bull/Bear Pressure Index like this
* you can choose Moving Average type for most plot elements in EVEREX, including how to deal with the Lookback averaging
* you can set EVEREX to a different time frame than the chart
* did i mention basic alerts in this v1.0 ?? There's room to add more VPA-specific alerts in future version (for example, when Ease-of-Move or Compression bars are detected...etc) - let me know if the comments what you want to see
Final Thoughts
--------------------
* EVEREX can be used for bar-by-bar VPA analysis - There are so much literature out there about VPA and it's highly recommended that traders read more about what VPA is and how it works - as it adds an interesting (and critical) dimension to technical analysis and will improve decision making
* RROF is a "strength indicator" - it does not track price values (levels) or momentum - as you will see when you use it, the price can be moving up, while the RROF signal line starts moving down, reflecting decreasing strength (or otherwise, increasing bear strength) - So if you incorporate EVEREX in your trading you will need to use it alongside other momentum and price value indicators (like MACD, MA's, Trend Channels, Support & Resistance Lines, Fib / Donchian..etc) - to use for trade confirmation
Bar metrics / Flowly Indicators— Overview
Rather than eyeball evaluating bullishness/bearishness in any given bar, bar metrics allow a quantified approach using three basic fundamental data points: relative close, relative volatility and relative volume. These data points are visualized in a discreet data dashboard form, next to all real-time bars. Each value also has a dot in front, representing color coded extremes in the values.
Relative close represents position of bar's close relative to high and low, high of bar being 100% and low of bar being 0%. Relative close indicates strength of bulls/bears in a given bar, the higher the better for bulls, the lower the better for bears. Relative volatility (bar range, high - low) and relative volume are presented in a form of a multiplier, relative to their respective moving averages (SMA 20). A value of 1x indicates volume/volatility being on par with moving average, 2x indicates volume/volatility being twice as much as moving average and so on. Relative volume and volatility can be used for measuring general market participant interest, the "weight of the bar" as it were.
— Features
Users can gauge past bar metrics using lookback via input menu. Past bars, especially recent ones, are helpful for giving context for current bar metrics. Lookback bars are highlighted on the chart using a yellow box and metrics presented on the data dashboard with lookback symbols:
To inspect bar metric data and its implications, users can highlight bars with specified bracket values for each metric:
When bar highlighter is toggled on and desired bar metric values set, alert for the specified combination can be toggled on via alert menu. Note that bar highlighter must be enabled in order for alerts to function.
— Visuals
Bar metric dots are gradient colored the following way:
Relative volatility & volume
0x -> 1x / Neutral (white) -> Light (yellow)
1x -> 1.7x / Light (yellow) -> Medium (orange)
1.7x -> 2.4x / Medium (orange) -> Heavy (red)
Relative close
0% -> 25% / Heavy bearish (red) -> Light bearish (dark red)
25% -> 45% / Light bearish (dark red) -> Neutral (white)
45% - 55% / Neutral (white)
55% -> 75% / Neutral (white) -> Light bullish (dark green)
75% -> 100% / Light bullish (dark green) -> Heavy bullish (green)
All colors can be adjusted via input menu. Label size, label distance from bar (offset) and text format (regular/stealth) can be adjusted via input menu as well:
— Practical guide
As interpretation of bar metrics is highly contextual, it is especially important to use other means in conjunction with the metrics. Levels, oscillators, moving averages, whatever you have found useful for your process. In short, relative close indicates directional bias and relative volume/volatility indicates "weight" of directional bias.
General interpretation
High relative close, low relative volume/volatility = mildly bullish, bias up/consolidation
High relative close, medium relative volume/volatility = bullish, bias up
High relative close, high relative volume/volatility = exuberantly bullish, bias up/down depending on context
Medium relative close, low relative volume/volatility = noise, no bias
Medium relative close, medium to high relative volume/volatility = indecision, further evidence needed to evaluate bias
Low relative close, low relative volume/volatility = mildly bearish, bias down/consolidation
Low relative close, medium relative volume/volatility = bearish, bias down
Low relative close, high relative volume/volatility = exuberantly bearish, bias down/up depending on context
Nuances & considerations
As to relative close, it's important to note that each bar is a trading range when viewed on a lower timeframe, ES 1W vs. ES 4H:
When relative close is high, bulls were able to push price to range high by the time of close. When relative close is low, bears were able to push price to range low by the time of close. In other words, bulls/bears were able to gain the upper hand over a given trading range, hinting strength for the side that made the final push. When relative close is around middle range (40-60%), it can be said neither side is clearly dominating the range, hinting neutral/indecision bias from a relative close perspective.
As to relative volume/volatility, low values (less than ~0.7x) imply bar has low market participant interest and therefore is likely insignificant, as it is "lacking weight". Values close to or above 1x imply meaningful market participant interest, whereas values well above 1x (greater than ~1.3x) imply exuberance. This exuberance can manifest as initiation (beginning of a trend) or as exhaustion (end of a trend):
XAUMO ECON DS OSCXAUMO — ECON DS OSC (XAUUSD)
DeltaProxy • Sweep/Reclaim • Sessions • MTF BlendNet • Dynamic Colors • BG Regimes • Alerts
Execution TF: 15m | Bias TF: 1H | Script Session TZ: Europe/London
EDUCATIONAL ONLY — Not financial advice — Not trade signals.
───────────────────────────────────────────
OVERVIEW
───────────────────────────────────────────
XAUMO — ECON DS OSC is a Demand/Supply pressure oscillator built for intraday
execution on gold. It converts candle structure + relative volume behavior into
three actionable lines (Demand, Supply, and a blended decision net), then adds
“proof layers” (session normalization, sweep/reclaim validation, imbalance
dominance filters, and MTF confluence) so you can separate real pressure from
noise.
This is NOT a “buy/sell arrow” script. It is a decision framework:
PRESSURE → PROOF → TRIGGER → ENTRY → RISK (SL1/SL2) → TARGETS (TP1/TP2)
───────────────────────────────────────────
WHAT YOU SEE ON THE CHART (3 LINES)
───────────────────────────────────────────
1) Demand (LTF) = buying pressure estimate
2) Supply (LTF) = selling pressure estimate
3) Net Blend (LTF+HTF) = decision line (institutional filter)
Definitions:
- LTF Net = Demand - Supply
- HTF Net = (HTF Demand - HTF Supply) on your chosen bias timeframe
- BlendNet = (1 - weight)*LTF Net + weight*HTF Net
Trader meaning:
- Demand above Supply = bullish pressure
- Supply above Demand = bearish pressure
- BlendNet = execution is 15m, bias is 1H (filter + confluence)
───────────────────────────────────────────
SCREENSHOT WALKTHROUGH (THE PROVIDED 15m/1H CHART)
───────────────────────────────────────────
On the attached chart:
- HTF Demand is above HTF Supply → the 1H bias is bullish
- LTF Demand stays above LTF Supply → local pressure supports the bias
- Net Blend stays positive → LTF pressure is aligned with HTF context
- “SW” markers show Sweep/Reclaim events → liquidity taken then reclaimed
- Background regimes highlight cross / net shift / sweep / dominance states
Use this to avoid one common mistake:
Do not chase tops. Wait for proof (SW/IMB) and enter on structure, not emotion.
───────────────────────────────────────────
PROOF LAYERS (WHY THIS IS NOT “JUST AN OSCILLATOR”)
───────────────────────────────────────────
1) Session Normalization (Europe/London)
Raw volume differs by session (Asia vs London vs NY). When enabled, the script
normalizes volume by session baselines so “high volume” means “high relative to
this session,” not an absolute number.
2) DeltaProxy Pressure Model (wick-aware)
For XAUUSD, wicks matter (stop-runs, liquidity grabs). DeltaProxy infers intent
from body direction + wick bias, then adjusts by ATR/spread (clamped) to avoid
fake extremes. Output is bounded for stability.
3) Sweep → Reclaim Validation (liquidity proof)
A sweep is only meaningful if price reclaims (closes back inside). You can use:
- Swing sweeps (structure)
- VWAP/VA sweeps (mean/value behavior)
- Gate sweeps (manual XAUMO levels)
- Any (broad coverage)
4) Imbalance Dominance Filter (validated triggers)
Imbalance logic confirms DOMINANCE using thresholds such as:
- ratio (Demand/Supply)
- dominance share
- z-score of net pressure vs baseline
Optional: require a sweep/reclaim proof before validating imbalance.
5) MTF BlendNet Confluence (15m execution filtered by 1H context)
The HTF net is blended into the LTF net via a weight:
Higher weight = safer/slower entries
Lower weight = faster/more aggressive entries
───────────────────────────────────────────
BACKGROUND REGIMES + MARKERS (FAST VISUAL READ)
───────────────────────────────────────────
Each background layer can be toggled ON/OFF:
BG #1 Cross (Demand/Supply) = early flips (fast, can whipsaw in chop)
BG #2 Net Cross (BlendNet) = stronger shift with HTF influence
BG #3 Sweep/Reclaim = liquidity-proof timing layer
BG #4 Imbalance Regime = dominance regime (avoid fading while active)
Markers:
- SW = sweep/reclaim event (proof)
- IMB D = bullish validated imbalance (dominance trigger)
- IMB S = bearish validated imbalance (dominance trigger)
───────────────────────────────────────────
ALERTS (SCANNING + EXECUTION)
───────────────────────────────────────────
A) Individual alerts (alertcondition)
Typical conditions:
- Bull/Bear Demand–Supply cross
- Bull/Bear Net Blend cross
- Bull/Bear Sweep/Reclaim
- Bull/Bear Validated Imbalance
B) Master alert() (dynamic message, recommended)
If you use dynamic values in the message, create alert using:
Create Alert → Condition → “Any alert() function call”
This is best for webhooks and execution bots.
───────────────────────────────────────────
PRACTICAL PLAYBOOK (HOW TRADERS USE IT)
───────────────────────────────────────────
Setup A — Continuation (intraday bread-and-butter)
1) 1H Bias clear:
Bull: HTF Demand > HTF Supply
Bear: HTF Supply > HTF Demand
2) BlendNet aligned and sloping (not flat)
3) Trigger:
Best: IMB validated in bias direction
Next: Net Cross in bias direction
4) Entry:
Trigger candle close OR first pullback after trigger (preferred)
5) Risk:
SL1 (mitigated) = beyond last 15m micro swing / reclaim reference
SL2 (tailgate) = beyond deeper structure OR ~1.2–1.5 ATR(15m)
6) Targets:
TP1 = first friction/reaction
TP2 = only while BlendNet remains aligned (no fading/flattening)
Setup B — Sweep → Reclaim Reversal (sniper)
1) SW prints (bull or bear)
2) Confirmation within 1–3 candles:
Best: IMB validated in sweep direction
OK: Cross after SW
3) Entry:
Reclaim close OR clean retest of reclaim reference
4) Risk:
SL1 = beyond swept level (reclaim ref)
SL2 = beyond next major structure swing
5) Targets:
TP1 = mean return / first friction
TP2 = only if BlendNet flips and holds
───────────────────────────────────────────
RISK MODEL (SL1 + SL2)
───────────────────────────────────────────
SL1 (mitigated) = “trade idea is wrong quickly” (tight structural stop)
SL2 (tailgate) = “survive spikes” (deeper structure / ATR emergency stop)
TP1 = reduce risk and pay yourself
TP2 = only if BlendNet stays aligned and not fading
If you did not define SL1 and SL2 before entry, do not enter.
───────────────────────────────────────────
NOTES / LIMITATIONS
───────────────────────────────────────────
- This is an indicator, not a guarantee of performance.
- Volume/wick inference depends on feed quality.
- Session normalization may require tuning per broker/feed.
- Close-confirmed logic reduces false triggers, but chop can still whipsaw.
───────────────────────────────────────────
DISCLAIMER
───────────────────────────────────────────
EDUCATIONAL ONLY — Not financial advice — Not trade signals.
Trading involves substantial risk, including the risk of loss.
You are responsible for your own decisions, risk management, and execution.
───────────────────────────────────
───────────────────────────────────
───────────────────────────────────
XAUMO — ECON DS OSC (XAUUSD)
DeltaProxy • Sweep/Reclaim • Sessions • MTF BlendNet • Dynamic Colors • BG Regimes • Alerts
إطار التنفيذ: 15 دقيقة | إطار الانحياز: 1 ساعة | توقيت الجلسات داخل السكربت: Europe/London
للتعليم فقط — ليس نصيحة مالية — ليس إشارات تداول.
───────────────────────────────────────────
نظرة عامة
───────────────────────────────────────────
XAUMO — ECON DS OSC هو أوسيليتور ضغط طلب/عرض مصمم لتنفيذ تداولات الذهب داخل
اليوم. يقوم بتحويل بنية الشمعة + سلوك الحجم النسبي إلى 3 خطوط عملية (الطلب،
العرض، وصافي قرار ممزوج)، ثم يضيف “طبقات إثبات” (تطبيع الجلسات، تحقق
Sweep/Reclaim، فلاتر سيادة عدم التوازن، وتوافق متعدد الأطر) حتى تميّز الضغط
الحقيقي من الضوضاء.
هذا ليس سكربت “أسهم شراء/بيع”. هذا إطار قرار واضح:
ضغط → إثبات → زناد → دخول → مخاطرة (SL1/SL2) → أهداف (TP1/TP2)
───────────────────────────────────────────
ماذا ترى على الشارت (3 خطوط)
───────────────────────────────────────────
1) الطلب (LTF) = تقدير ضغط الشراء
2) العرض (LTF) = تقدير ضغط البيع
3) صافي Blend (LTF+HTF) = خط القرار (فلتر “مؤسسي”)
التعريفات:
- صافي LTF = الطلب - العرض
- صافي HTF = (طلب HTF - عرض HTF) على إطار الانحياز المختار
- BlendNet = (1 - الوزن)*صافي LTF + الوزن*صافي HTF
المعنى للمتداول:
- الطلب فوق العرض = ضغط صاعد
- العرض فوق الطلب = ضغط هابط
- BlendNet = التنفيذ 15د، والانحياز 1س (فلتر + توافق)
───────────────────────────────────────────
شرح اللقطة (الشارت المرفق 15م/1س)
───────────────────────────────────────────
على الشارت المرفق:
- طلب HTF أعلى من عرض HTF → الانحياز على 1س صاعد
- طلب LTF يظل أعلى من عرض LTF → الضغط المحلي يدعم الانحياز
- صافي Blend يظل موجب → ضغط 15د متوافق مع سياق 1س
- علامات “SW” تُظهر أحداث Sweep/Reclaim → سيولة تُسحب ثم تُستعاد بالإغلاق
- أنظمة الخلفية تُبرز حالات: تقاطع / تحوّل صافي / سويب / سيادة
قاعدة عملية لتجنب خطأ شائع:
لا تطارد القمم. استنَ الإثبات (SW/IMB) وادخل على بنية مؤكدة، لا على انفعال.
───────────────────────────────────────────
طبقات الإثبات (لماذا هذا ليس “أوسيليتور عادي”)
───────────────────────────────────────────
1) تطبيع الجلسات (Europe/London)
الحجم الخام يختلف بين الجلسات (آسيا/لندن/نيويورك). عند تفعيل التطبيع يقوم
السكربت بتطبيع الحجم بخطوط أساس لكل جلسة، فيصبح “حجم مرتفع” = مرتفع مقارنة
بهذه الجلسة، وليس رقمًا مطلقًا.
2) نموذج الضغط DeltaProxy (ذكي مع الذيول)
في الذهب، الذيول مهمة (Stop-runs وسحب سيولة). DeltaProxy يستنتج النية من
اتجاه الجسم + انحياز الذيول، ثم يضبط بعامل ATR/Spread (ضمن حدود) لتجنب
التطرفات الوهمية. الناتج محدود لاستقرار أفضل.
3) تحقق Sweep → Reclaim (إثبات السيولة)
السويب لا يهم إلا إذا حدث Reclaim (إغلاق داخل النطاق مرة أخرى). يمكنك اختيار:
- Swing sweeps (بنية/سوينجات)
- VWAP/VA sweeps (قيمة/متوسط)
- Gate sweeps (مستويات XAUMO اليدوية)
- Any (تغطية واسعة)
4) فلتر سيادة عدم التوازن (Triggers مُتحققة)
منطق عدم التوازن يؤكد “السيادة” باستخدام عتبات مثل:
- Ratio (الطلب/العرض)
- Dominance Share (حصة السيطرة)
- Z-Score لصافي الضغط مقابل خط الأساس
اختياري: اشتراط وجود Sweep/Reclaim قبل اعتماد عدم التوازن.
5) توافق متعدد الأطر عبر BlendNet (تنفيذ 15د مفلتر بسياق 1س)
يتم مزج صافي HTF داخل صافي LTF عبر وزن:
وزن أعلى = دخول أأمن/أبطأ
وزن أقل = دخول أسرع/أكثر عدوانية
───────────────────────────────────────────
أنظمة الخلفية + العلامات (قراءة بصرية سريعة)
───────────────────────────────────────────
يمكن تفعيل/تعطيل كل طبقة خلفية:
BG #1 تقاطع الطلب/العرض = قلب مبكر (سريع وقد يضرب في التذبذب)
BG #2 تقاطع الصافي BlendNet = تحوّل أقوى بتأثير HTF
BG #3 Sweep/Reclaim = طبقة توقيت بإثبات سيولة
BG #4 نظام عدم التوازن = سيادة (تجنب معاكسة الطرف المسيطر)
العلامات:
- SW = حدث Sweep/Reclaim (إثبات)
- IMB D = عدم توازن صاعد مُتحقق (زناد سيادة)
- IMB S = عدم توازن هابط مُتحقق (زناد سيادة)
───────────────────────────────────────────
التنبيهات (Scanning + Execution)
───────────────────────────────────────────
A) تنبيهات فردية (alertcondition)
أمثلة شائعة:
- تقاطع صاعد/هابط بين الطلب والعرض
- تقاطع صاعد/هابط لصافي BlendNet
- Sweep/Reclaim صاعد/هابط
- عدم توازن مُتحقق صاعد/هابط
B) تنبيه رئيسي عبر alert() (رسالة ديناميكية — مُفضل)
إذا كانت رسالتك تحتوي قيَم ديناميكية، أنشئ التنبيه باستخدام:
Create Alert → Condition → “Any alert() function call”
وهذا أفضل للـwebhooks وبوتات التنفيذ.
───────────────────────────────────────────
دليل عملي (كيف يستخدمه المتداولون)
───────────────────────────────────────────
Setup A — استمرار مع الانحياز (شغل اليوم)
1) انحياز 1س واضح:
صاعد: طلب HTF > عرض HTF
هابط: عرض HTF > طلب HTF
2) BlendNet متوافق ومائل (غير مسطح)
3) الزناد:
الأفضل: IMB مُتحقق في اتجاه الانحياز
التالي: تقاطع صافي في اتجاه الانحياز
4) الدخول:
إغلاق شمعة الزناد أو أول Pullback بعدها (مُفضل)
5) المخاطرة:
SL1 (مخفف) = وراء آخر Micro Swing على 15د / مرجع الـReclaim
SL2 (Tailgate) = وراء بنية أعمق أو ~1.2–1.5 ATR(15m)
6) الأهداف:
TP1 = أول احتكاك/رد فعل
TP2 = فقط طالما BlendNet متوافق (لا بهتان/لا تسطح)
Setup B — سويب ثم استرجاع (قنّاص انعكاس)
1) ظهور SW (صاعد أو هابط)
2) تأكيد خلال 1–3 شمعات:
الأفضل: IMB مُتحقق في اتجاه السويب
مقبول: تقاطع بعد SW
3) الدخول:
إغلاق الـReclaim أو إعادة اختبار نظيفة لمرجع الـReclaim
4) المخاطرة:
SL1 = وراء المستوى المسحوب (مرجع الـReclaim)
SL2 = وراء سوينج بنيوي أكبر
5) الأهداف:
TP1 = رجوع للمتوسط / أول احتكاك
TP2 = فقط إذا BlendNet انقلب وثبت
───────────────────────────────────────────
نموذج المخاطرة (SL1 + SL2)
───────────────────────────────────────────
SL1 (مخفف) = “فكرة الصفقة غلط بسرعة” (ستوب بنيوي قريب)
SL2 (Tailgate) = “تحمّل السبايكس” (بنية أعمق / ستوب طوارئ ATR)
TP1 = خفف المخاطرة وادفع نفسك
TP2 = فقط إذا BlendNet يظل متوافقًا ولا يبهت
لو لم تحدد SL1 وSL2 قبل الدخول، لا تدخل.
───────────────────────────────────────────
ملاحظات / حدود الاستخدام
───────────────────────────────────────────
- هذا مؤشر، وليس ضمانًا لأي نتائج.
- استنتاج الحجم/الذيول يعتمد على جودة الـFeed.
- تطبيع الجلسات قد يحتاج ضبط حسب الوسيط/البيانات.
- منطق الإغلاق المؤكد يقلل الإشارات الكاذبة، لكن التذبذب قد يسبب Whipsaws.
───────────────────────────────────────────
إخلاء مسؤولية
───────────────────────────────────────────
للتعليم فقط — ليس نصيحة مالية — ليس إشارات تداول.
التداول ينطوي على مخاطر كبيرة بما فيها خسارة رأس المال.
أنت مسؤول عن قراراتك وإدارة المخاطر والتنفيذ.
Super Scalper[XAUUSD]// © SuperScalper
//@version=5
indicator('Super Scalper ', overlay=true, max_labels_count=500)
show_tp_sl = input.bool(true, 'Display TP & SL', group='Techical', tooltip='Display the exact TP & SL price levels for BUY & SELL signals.')
rrr = input.string('1:2', 'Risk to Reward Ratio', group='Techical', options= , tooltip='Set a risk to reward ratio (RRR).')
tp_sl_multi = input.float(1, 'TP & SL Multiplier', 1, group='Techical', tooltip='Multiplies both TP and SL by a chosen index. Higher - higher risk.')
tp_sl_prec = input.int(2, 'TP & SL Precision', 0, group='Techical')
candle_stability_index_param = 0.7
rsi_index_param = 80
candle_delta_length_param = 10
disable_repeating_signals_param = input.bool(true, 'Disable Repeating Signals', group='Techical', tooltip='Removes repeating signals. Useful for removing clusters of signals and general clarity.')
GREEN = color.rgb(29, 255, 40)
RED = color.rgb(255, 0, 0)
TRANSPARENT = color.rgb(0, 0, 0, 100)
//indicator("Author Info Display"
// Create table
var table infoTable = table.new(position.top_right, 2, 6, bgcolor=color.new(#000000, 1), border_width=1)
if barstate.islast
table.cell(infoTable, 0, 0, "Author:", text_color=color.white, text_size=size.small)
table.cell(infoTable, 1, 0, "Klasscco", text_color=color.rgb(255, 251, 0), text_size=size.large)
table.cell(infoTable, 0, 1, "Etsy:", text_color=color.white, text_size=size.small)
table.cell(infoTable, 1, 1, "https://www.etsy.com/shop/KlasscCo", text_color=color.rgb(255, 251, 0), text_size=size.small)
table.cell(infoTable, 0, 3, "Website:", text_color=color.white, text_size=size.small)
table.cell(infoTable, 1, 3, "etsy.com/shop/KlasscCo", text_color=color.rgb(255, 251, 0), text_size=size.small)
label_size = input.string('normal', 'Label Size', options= , group='Cosmetic')
label_style = input.string('text bubble', 'Label Style', , group='Cosmetic')
buy_label_color = input(GREEN, 'BUY Label Color', inline='Highlight', group='Cosmetic')
sell_label_color = input(RED, 'SELL Label Color', inline='Highlight', group='Cosmetic')
label_text_color = input(color.white, 'Label Text Color', inline='Highlight', group='Cosmetic')
stable_candle = math.abs(close - open) / ta.tr > candle_stability_index_param
rsi = ta.rsi(close, 14)
atr = ta.atr(14)
bullish_engulfing = close < open and close > open and close > open
rsi_below = rsi < rsi_index_param
decrease_over = close < close
var last_signal = ''
var tp = 0.
var sl = 0.
bull_state = bullish_engulfing and stable_candle and rsi_below and decrease_over and barstate.isconfirmed
bull = bull_state and (disable_repeating_signals_param ? (last_signal != 'buy' ? true : na) : true)
bearish_engulfing = close > open and close < open and close < open
rsi_above = rsi > 100 - rsi_index_param
increase_over = close > close
bear_state = bearish_engulfing and stable_candle and rsi_above and increase_over and barstate.isconfirmed
bear = bear_state and (disable_repeating_signals_param ? (last_signal != 'sell' ? true : na) : true)
round_up(number, decimals) =>
factor = math.pow(10, decimals)
math.ceil(number * factor) / factor
if bull
last_signal := 'buy'
dist = atr * tp_sl_multi
tp_dist = rrr == '2:3' ? dist / 2 * 3 : rrr == '1:2' ? dist * 2 : rrr == '1:4' ? dist * 4 : dist
tp := round_up(close + tp_dist, tp_sl_prec)
sl := round_up(close - dist, tp_sl_prec)
if label_style == 'text bubble'
label.new(bar_index, low, 'BUY', color=buy_label_color, style=label.style_label_up, textcolor=label_text_color, size=label_size)
else if label_style == 'triangle'
label.new(bar_index, low, 'BUY', yloc=yloc.belowbar, color=buy_label_color, style=label.style_triangleup, textcolor=TRANSPARENT, size=label_size)
else if label_style == 'arrow'
label.new(bar_index, low, 'BUY', yloc=yloc.belowbar, color=buy_label_color, style=label.style_arrowup, textcolor=TRANSPARENT, size=label_size)
label.new(show_tp_sl ? bar_index : na, low, 'TP: ' + str.tostring(tp) + '\nSL: ' + str.tostring(sl), yloc=yloc.price, color=color.gray, style=label.style_label_down, textcolor=label_text_color)
if bear
last_signal := 'sell'
dist = atr * tp_sl_multi
tp_dist = rrr == '2:3' ? dist / 2 * 3 : rrr == '1:2' ? dist * 2 : rrr == '1:4' ? dist * 4 : dist
tp := round_up(close - tp_dist, tp_sl_prec)
sl := round_up(close + dist, tp_sl_prec)
if label_style == 'text bubble'
label.new(bear ? bar_index : na, high, 'SELL', color=sell_label_color, style=label.style_label_down, textcolor=label_text_color, size=label_size)
else if label_style == 'triangle'
label.new(bear ? bar_index : na, high, 'SELL', yloc=yloc.abovebar, color=sell_label_color, style=label.style_triangledown, textcolor=TRANSPARENT, size=label_size)
else if label_style == 'arrow'
label.new(bear ? bar_index : na, high, 'SELL', yloc=yloc.abovebar, color=sell_label_color, style=label.style_arrowdown, textcolor=TRANSPARENT, size=label_size)
label.new(show_tp_sl ? bar_index : na, low, 'TP: ' + str.tostring(tp) + '\nSL: ' + str.tostring(sl), yloc=yloc.price, color=color.gray, style=label.style_label_up, textcolor=label_text_color)
alertcondition(bull or bear, 'BUY & SELL Signals', 'New signal!')
alertcondition(bull, 'BUY Signals (Only)', 'New signal: BUY')
alertcondition(bear, 'SELL Signals (Only)', 'New signal: SELL')
Order Blocks Volume Delta 3D | Flux ChartsGENERAL OVERVIEW:
Order Blocks Volume Delta 3D by Flux Charts is a rule-based order block and volume delta visualization tool. It detects bullish and bearish order blocks using a profile-of-price approach: the indicator finds the most actively traded price area (Point of Control, or POC) between a swing high/low and the Break of Structure (BOS), then anchors the order block to the earliest still-valid candle that traded through that POC band. From there, it tracks all candles that continue to interact with that zone and overlays both 2D and 3D volume delta views directly inside the order block.
Unlike traditional order block tools that simply use candle bodies or wicks, this indicator is volume-aware. It lets you optionally pull volume from a lower timeframe feed (for example, using 1-minute data while watching a 5-minute chart) to build a much more accurate picture of how buyers and sellers actually traded inside the zone. This makes every block not just a price box, but a volume story: which side dominated, where, and by how much.
All order blocks printed by this indicator are confirmed: BOS and retests are evaluated strictly on closed candles. Nothing is drawn or alerted on partially formed bars, which helps avoid repaint-style flicker and keeps the signals clean and stable.
What is the theory behind the indicator?:
The core idea behind Order Blocks Volume Delta 3D is that not all price levels inside an order block are equal. Some prices are barely touched, while others act like magnets where candles repeatedly trade and heavy volume passes through.
The indicator first finds a swing high or swing low, waits for a clear Break of Structure (BOS), then scans the candles between the swing point and the BOS to find the price level that was touched the most. That level is treated as the POC.
From all candles in the swing-to-BOS range that interact with this POC band, the indicator looks for the earliest candle that is not already mitigated and uses that as the anchor candle for the order block:
The top of the block equals the anchor candle’s high (for a bearish OB) or the top of its wick zone.
The bottom equals the anchor candle’s low (for a bullish OB) or the bottom of its wick zone.
This “earliest valid POC-touching candle” rule makes it easier to visualize how price and volume developed from the very start of a meaningful zone, while ignoring POC touches that are already fully mitigated by the time the structure is confirmed. On top of that, each candle is split into bullish and bearish volume. If you choose a lower timeframe volume input, the tool aggregates lower timeframe candles into your chart timeframe, giving a more granular bull-versus-bear breakdown for each bar. The result is
an order block that not only shows where price moved but also which side pushed it, how aggressively, and how that balance shifted over time.
ORDER BLOCKS VOLUME DELTA 3D FEATURES:
The Order Blocks Volume Delta 3D indicator includes 4 main features:
1. Order Blocks
2. Volume Delta
3. 3D Visualization
4. Alerts
ORDER BLOCKS:
🔹What is an Order Block
An order block is a price zone where a clear displacement move began after liquidity was taken. It usually forms around the last consolidation or cluster of candles before price breaks structure with a strong move.
In this indicator, order blocks are defined as structured zones that:
Begin at the earliest unmitigated candle that interacted with the most-touched price level (POC) between swing and BOS.
Extend through the full wick range of that anchor candle.
Stretch forward in time, tracking how price continues to trade through, respect, retest, or invalidate the zone.
Are only printed once the BOS is fully confirmed on closed candles (confirmed order blocks only).
Example of bullish and bearish order blocks anchored at the earliest unmitigated candle in the POC zone:
🔹How are Order Blocks detected
The indicator uses a step-by-step, rules-based process to detect bullish and bearish order blocks. The logic is designed to match discretionary Smart Money concepts but with strict, repeatable rules.
Step 1: Detect swing highs and swing lows
Swing High: a candle whose high is higher than the highs of surrounding candles.
Swing Low: a candle whose low is lower than the lows of surrounding candles.
The Swing Length input controls how many candles are checked to the left and right.
Example of swing high and swing low detection:
Step 2: Confirm Break of Structure (BOS)
Once a swing is confirmed, the indicator waits for price to break past that swing:
Bullish BOS: price closes above a previous swing high.
Bearish BOS: price closes below a previous swing low.
To avoid “live” flicker, BOS logic is evaluated based on the previous closed candle. The order block is only confirmed once the BOS candle has fully closed and the next bar has opened. This is one of the reasons the script only shows confirmed, non-repainting order blocks.
Example of bullish BOS and bearish BOS:
Step 3: Build the POC range between swing and BOS
Between the swing candle and the BOS candle, the indicator:
Scans all candles in that range.
Tracks every price level touched using binning (POC bins).
Counts how many times each price band was touched by candle wicks.
The bin with the highest touch count becomes the POC band. This is where price traded most often, not necessarily where volume was highest.
Example of the POC band between swing and BOS.
Step 4 – Anchor the order block to the earliest valid POC candle
From all candles in the swing-to-BOS range, the indicator finds the earliest candle whose high/low overlaps the POC band and whose zone is not already mitigated. That candle becomes the anchor candle for the order block:
For a bearish OB, the block spans the anchor candle’s full wick range, with its top at the high.
For a bullish OB, the block spans the anchor candle’s full wick range, with its bottom at the low.
By requiring the anchor to be the earliest unmitigated interaction with POC, the script avoids building blocks from price action that has already been fully traded through and is less relevant.
Step 5: Extend and manage the order block
Once created, the block:
Extends to the right by a configurable number of candles (Extend Zones).
Continues until it is invalidated by wick or close, depending on the chosen method.
Can show retest labels when price revisits the zone after creation.
Is included or excluded from display depending on the Show Nearest and Hide Invalidated Zones settings.
Example of active and invalidated OB.
🔹Order Block Settings
◇ Swing Length
Swing Length controls how sensitive swing highs and lows are.
Lower Swing Length: Swings form more frequently, which leads to more frequent BOS events and order block formations.
Higher Swing Length: Only larger, more meaningful swings are detected, which leads to less frequent BOS events and less order block formations.
◇ Invalidation
Invalidation determines how an order block is considered “mitigated” or no longer valid.
Wick: For bullish OBs, if price wicks completely through the bottom of the zone, the order block is invalidated. For bearish OBs, if price wicks completely through the top, the order block is invalidated.
Close: For bullish OBs, the block is invalidated only when a candle closes below the bottom. For bearish OBs, it is invalidated only when a candle closes above the top.
Example of wick invalidation:
Example of close invalidation:
◇ Show Nearest
Show Nearest limits how many active order blocks are displayed based on proximity to current price. For example, a value of 2 will display only the two nearest bullish order blocks and two nearest bearish order blocks.
Chart with Show Nearest set to 3:
◇ Extend Zones
Extend Zones define how many candles forward each order block should project beyond the right most candle on the chart.
Chart with Extend Zones set to 10:
◇ Retest Labels
When enabled, the indicator prints labels on every clean retest of an active order block, as long as that block remains valid. Key points:
A retest label is only printed once the retest candle has fully closed – you always see confirmed retests, not intrabar tests.
Retest labels are positioned on the actual retest candle so you can visually see which bar interacted with the zone.
In addition, if multiple retests occur in quick succession, the indicator applies a built-in three-candle buffer between retests. That means only the first valid retest within each three-bar window is labeled (and can trigger an alert), helping to reduce clutter while still highlighting meaningful interactions with the zone.
Example of retest labels on bullish and bearish order blocks.
◇ Hide Invalidated Zones
Hide Invalidated Zones controls whether mitigated/invalidated blocks stay drawn.
Enabled: Only currently valid, unmitigated order blocks are shown (subject to Show Nearest)
Disabled: Both active and invalidated order blocks are displayed.
VOLUME DELTA:
🔹What is Volume Delta
Volume delta measures the difference between buying and selling volume. Instead of only showing “how much volume traded”, it separates volume into bullish and bearish components.
In this indicator:
Bullish volume = volume from candles (or lower timeframe candles) that closed higher.
Bearish volume = volume from candles that closed lower.
Delta % shows how dominant one side was compared to the total.
Example of bullish and bearish order blocks with volume delta and total volume.
🔹How is Volume Delta calculated?
The indicator uses a flexible, timeframe-aware volume engine.
1. Choose a Volume Delta Timeframe.
If the selected timeframe is equal to or higher than the chart timeframe, the indicator simply uses chart-volume per candle.
If the selected timeframe is lower than the chart timeframe (for example, 1‑minute volume on a 5‑minute chart), the indicator pulls all lower timeframe candles for each chart bar and sums them.
2. Split each bar into bull and bear volume.
For each contributing candle:
If close > open → its volume is added to bullish volume.
If close < open → its volume is added to bearish volume.
If close == open → its volume is split evenly between bullish and bearish.
3. Aggregate for each order block.
For each order block:
The indicator loops once from the swing candle to the BOS candle.
It records every candle that touches the POC band.
For each touching candle, it adds its bull and bear volumes (either directly from chart candles or from aggregated lower timeframe candles).
Total volume = bullish volume + bearish volume
Delta % = (bullish volume or bearish volume / total volume ) * 100, depending on which side is dominant.
🔹Volume Delta Settings:
◇ Display Style
Display Style controls how the volume delta is drawn inside each order block:
Horizontal:
Bullish and bearish fills extend horizontally from left to right.
The filled strip sits along the base of the block, with a bull vs bear gradient.
Vertical:
Bullish and bearish fills stretch vertically inside the zone.
The bullish percentage controls how much of the block is filled with the “dominant” color.
Example of Horizontal display style.
Example of Vertical display style.
◇ Volume Delta Timeframe
Volume Delta Timeframe tells the indicator whether to use chart volume or lower timeframe volume. When set to a lower timeframe, the indicator aggregates all lower timeframe candles that fall inside each chart bar, splitting their volume into bullish and bearish components before summing.
Using a lower timeframe:
Increases precision for how volume truly behaved inside each bar.
Helps reveal hidden absorption and aggressive flows that a higher timeframe candle might hide.
Example of volume delta based on chart timeframe.
Example of volume delta based on lower timeframe than chart(same OB as above)
◇ Display Total Volume
When enabled, the indicator prints the total volume for each order block as a label positioned inside the zone, near the bottom-right corner. This total is the sum of bullish and bearish volume used in the delta calculation and gives you a quick sense of how “heavy” the trading was in that block compared to others.
Example of total volume label inside multiple order blocks.
◇ Show Delta %
Show Delta % draws a small text label on the strip of the block that displays the dominant side’s percentage. For example, a bullish block might show “72%” if 72% of all volume inside that POC band came from bullish volume.
Example of Delta %:
3D VISUALIZATION:
The 3D Visualization feature turns each order block into a 3D plot.
🔹What the 3D Visualization does:
Wraps the order block with side faces and a top face to create a 3D bar effect.
Uses delta percentages to tilt the top face toward the dominant side.
Projects blocks into the future using Extend Zones, making the 3D blocks visually stand out.
🔹How it works:
The front face of the OB shows the standard 2D zone.
The side face extends forward in time based on the 3D depth setting.
The top face is angled depending on the Display Style and bull vs bear delta, making strong bullish blocks “rise” and strong bearish blocks “sink”.
🔹How the 3D depth setting affects visuals
Lower 3D depth:
Shorter side faces.
Subtle 3D effect.
Higher 3D depth:
Longer side faces projecting further into the future.
Stronger 3D effect that visually highlights key zones.
Example of lower 3D depth:
Example of higher 3D depth:
ALERTS:
The indicator supports alert conditions through TradingView’s AnyAlert() engine, allowing you to set alerts for the following:
New Bullish Order Block formed
New Bearish Order Block formed
Bullish OB Retest
Bearish OB Retest
Important alert behavior:
Order block alerts only fire when a new block is confirmed (after BOS closes and the next bar opens).
Retest alerts only fire when a retest candle has completely finished, matching the behavior of the visual retest labels.
IMPORTANT NOTES:
3D faces for order blocks are built using polylines. In some situations, especially when an order block’s starting point (its left edge) is beyond the chart’s left-most visible bar, the top 3D face may appear slightly irregular, skewed, or incomplete. This is purely a drawing limitation related to how the chart engine handles off-screen polyline points. Once the starting point of that order block comes into view (by zooming out or scrolling back), the 3D top face corrects itself and the visual becomes fully consistent. This issue affects only the 3D top face drawing, not the actual order-block box itself. The underlying zone, prices, and volume calculations remain accurate at all times.
If all conditions are met to create a new order block but the resulting zone would overlap an existing active order block, the new block is intentionally not created. A built-in guard prevents overlapping active zones to keep the structure clean and easier to interpret.
3D face drawing is implemented using an adaptive polyline method, which can be relatively calculation-heavy on certain symbols, timeframes, or chart histories. In some cases this may lead to calculation timeout error from TradingView.
UNIQUENESS:
This indicator is unique because it:
Anchors each order block to the earliest unmitigated candle that traded through the most-touched POC band between swing and BOS, rather than a generic “last up/down candle” or a random volume spike.
Builds a dedicated volume engine that can pull either chart timeframe volume or aggregated lower timeframe volume, then splits it into bull and bear components.
Adds 3D visualization on top of standard zones, turning each OB into a visually weighted slab rather than a flat rectangle.
Provides clean toggles (Show Nearest, Hide Invalidated Zones, Extend Zones, Display Style, Delta %, and total volume labels) so you can dial the indicator from extremely minimal to fully detailed, depending on your trading workflow.
Combined, these features make the indicator not just an order block plotter, but a complete volume‑informed structure tool tailored for traders who want to see where price actually traded and whether bulls or bears truly controlled the move inside each order block.
FVG - MTF Confirmed Tracker [JP/EN]Indicator Description: FVG MTF Concluded Bar Tracker
This indicator is a highly functional tool that identifies FVG for the currently displayed bar or a higher-level bar (MTF) and determines its "resolution" when the candlestick is resolved.
Its most notable feature is that it only displays history (gray) on the chart and sends an alert when a "significant level that has been continuously observed for a certain period of time" is resolved.
1. Timeframe Settings
Base Timeframe: Select the timeframe on which to detect FVG. Select "Same as chart" to use the current bar, or select another bar (1-hour, 4-hour, etc.) to project the FVG of the higher-level bar onto the current chart.
2. Active FVG Settings
Sets the currently active support/resistance area that has not yet been filled by price.
Show Bull/Bear: Individually toggles whether to display bull (buy) and bear (sell) FVG.
Color: Specifies the color of the box for the unresolved state.
Extend Right (Active): When enabled, the box will continue to extend indefinitely toward the right edge of the chart until the FVG is resolved.
Max Active FVG: This sets the maximum number of unresolved boxes to display on the chart. When a new FVG is detected, the oldest unresolved box will be automatically deleted if it exceeds this limit, saving resources.
3. Filled FVG Settings (Resolved, Grayed Out, Determination Logic)
These are very important settings for displaying history when the price fills an FVG.
Show Filled: Select whether to leave resolved FVGs grayed out (default color) as "history."
Color: Specifies the color of boxes that have been resolved (Filled).
Extend Right (Filled): When this is turned off, the box extension will stop at the candlestick where the resolution is confirmed, making the resolution point clear.
Max Filled FVG: This sets the maximum number of grayed out boxes to display as history. When the limit is reached, the oldest history will be deleted.
Min Bars to Keep & Alert (Important): This is the threshold for the number of bars elapsed between the occurrence of an FVG and its resolution.
If the threshold is not met: The event is considered a temporary reaction, and no alert will be sounded. The event will also be deleted without being recorded in the history (gray).
If the threshold is met or exceeded: The event is considered a significant market event, and the box will turn gray and an alert will be sent.
4. Alert Settings (Alert Notification Logic)
Alerts are executed in perfect sync with the "resolution of significant levels (graying out)."
Alert when Bull / Bear turns Gray: A notification will be sent the moment a bullish or bearish FVG is resolved after meeting the threshold and turning gray.
Execution Timing: A notification will only be sent when the candlestick is confirmed. It will not be triggered if the candlestick is only momentarily touched by the wick midway through the candlestick. This allows you to know for sure that the event was resolved at the time of closing.
インジケーター解説：FVG MTF 確定足トラッカー
このインジケーターは、現在表示している足、または上位足（MTF）のFVGを特定し、その「解消」をローソク足の確定時に判定する高機能ツールです。
最大の特徴は、**「一定期間意識され続けた重要な水準」**が解消された時のみ、チャートに履歴（グレー）を残し、アラートを通知する設計にあります。
1. Timeframe Settings（時間足設定）
Base Timeframe / 基準にする時間足: FVGを検知する時間足を選択します。「Same as chart（チャートと同じ）」を選べば現在の足、それ以外（1時間足、4時間足など）を選べば上位足のFVGを現在のチャートに投影します。
2. Active FVG Settings（未解消時の設定ロジック）
まだ価格に埋められていない、現在有効なサポート・レジスタンス領域の設定です。
Show Bull / Bear: ブル（買い）およびベア（売り）のFVGを表示するかどうかを個別に切り替えます。
Color: 未解消状態のボックスの色を指定します。
Extend Right (Active): 有効にすると、FVGが解消されるまでボックスをチャートの右端に向かって無制限に延長し続けます。
Max Active FVG: チャート上に表示する未解消ボックスの最大数です。新しいFVGが検知された際、この上限を超えていると最も古い未解消ボックスが自動的に削除され、リソースを節約します。
3. Filled FVG Settings（解消済み・グレー化・判定本数ロジック）
価格がFVGを埋めた際の、履歴表示に関する非常に重要な設定項目です。
Show Filled: 解消されたFVGを「履歴」としてグレー表示（デフォルト色）で残すかどうかを選択します。
Color: 解消済み（Filled）状態になったボックスの色を指定します。
Extend Right (Filled): これをOFFにすると、解消が確定したローソク足の位置でボックスの延長が止まり、解消地点が明確になります。
Max Filled FVG: 履歴として残すグレーボックスの最大数です。上限に達すると、古い履歴から順に削除されます。
Min Bars to Keep & Alert (重要): FVGが発生してから解消されるまでの「経過本数」の閾値です。
判定本数に満たない場合: 一時的な反応とみなし、アラートを鳴らさず、履歴（グレー）にも残さず削除します。
判定本数以上の場合: 市場で十分に意識された「重要な水準」とみなし、ボックスをグレーに変更し、アラートを通知します。
4. Alert Settings（アラート通知ロジック）
アラートは「重要水準の解消（グレー化）」と完全に同期して実行されます。
Alert when Bull / Bear turns Grey: ブル/ベアそれぞれのFVGが、上記の「判定本数」を満たした状態で解消され、グレーに変化した瞬間に通知を送ります。
実行タイミング: ローソク足の確定時にのみ通知されます。足の途中のヒゲで一時的に触れただけでは鳴りません。これにより、クローズ時点で確実に解消されたことのみを把握できます。
Impulse Reactor RSI-SMA Trend Indicator [ApexLegion]Impulse Reactor RSI-SMA Trend Indicator
Introduction and Theoretical Background
Design Rationale
Standard indicators frequently generate binary 'BUY' or 'SELL' signals without accounting for the broader market context. This often results in erratic "Flip-Flop" behavior, where signals are triggered indiscriminately regardless of the prevailing volatility regime.
Impulse Reactor was engineered to address this limitation by unifying two critical requirements: Quantitative Rigor and Execution Flexibility.
The Solution
Composite Analytical Framework This script is not a simple visual overlay of existing indicators. It is an algorithmic synthesis designed to function as a unified decision-making engine. The primary objective was to implement rigorous quantitative analysis (Volatility Normalization, Structural Filtering) directly within an alert-enabled framework. This architecture is designed to process signals through strict, multi-factor validation protocols before generating real-time notifications, allowing users to focus on structurally validated setups without manual monitoring.
How It Works
This is not a simple visual mashup. It utilizes a cross-validation algorithm where the Trend Structure acts as a gatekeeper for Momentum signals:
Logic over Lag: Unlike simple moving average crossovers, this script uses a 15-layer Gradient Ribbon to detect "Laminar Flow." If the ribbon is knotted (Compression), the system mathematically suppresses all signals.
Volatility Normalization: The core calculation adapts to ATR (Average True Range). This means the indicator automatically expands in volatile markets and contracts in quiet ones, maintaining accuracy without constant manual tweaking.
Adaptive Signal Thresholding: It incorporates an 'Anti-Greed' algorithm (Dynamic Thresholding) that automatically adjusts entry criteria based on trend duration. This logic aims to mitigate the risk of entering positions during periods of statistical trend exhaustion.
Why Use It?
Market State Decoding: The gradient Ribbon visualizes the underlying trend phase in real-time.
◦ Cyan/Blue Flow: Strong Bullish Trend (Laminar Flow).
◦ Magenta/Pink Flow: Strong Bearish Trend.
◦ Compressed/Knotted: When the ribbon lines are tightly squeezed or overlapping, it signals Consolidation. The system filters signals here to avoid chop.
Noise Reduction: The goal is not to catch every pivot, but to isolate high-confidence setups. The logic explicitly filters out minor fluctuations to help maintain position alignment with the broader trend.
⚖️ Chapter 1: System Architecture
Introduction: Composite Analytical Framework
System Overview
Impulse Reactor serves as a comprehensive technical analysis engine designed to synthesize three distinct market dimensions—Momentum, Volatility, and Trend Structure—into a unified decision-making framework. Unlike traditional methods that analyze these metrics in isolation, this system functions as a central processing unit that integrates disparate data streams to construct a coherent model of market behavior.
Operational Objective
The primary objective is to transition from single-dimensional signal generation to a multi-factor assessment model. By fusing data from the Impulse Core (Volatility), Gradient Oscillator (Momentum), and Structural Baseline (Trend), the system aims to filter out stochastic noise and identify high-probability trade setups grounded in quantitative confluence.
Market Microstructure Analysis: Limitations of Conventional Models
Extensive backtesting and quantitative analysis have identified three critical inefficiencies in standard oscillator-based strategies:
• Bounded Oscillator Limitations (The "Oscillation Trap"): Traditional indicators such as RSI or Stochastics are mathematically constrained between fixed values (0 to 100). In strong trending environments, these metrics often saturate in "overbought" or "oversold" zones. Consequently, traders relying on static thresholds frequently exit structurally valid positions prematurely or initiate counter-trend trades against prevailing momentum, resulting in suboptimal performance.
• Quantitative Blindness to Quality: Standard moving averages and trend indicators often fail to distinguish the qualitative nature of price movement. They treat low-volume drift and high-velocity expansion identically. This inability to account for "Volatility Quality" leads to delayed responsiveness during critical market events.
• Fractal Dissonance (Timeframe Disconnect): Financial markets exhibit fractal characteristics where trends on lower timeframes may contradict higher timeframe structures. Manual integration of multi-timeframe analysis increases cognitive load and susceptibility to human error, often resulting in conflicting biases at the point of execution.
Core Design Principles
To mitigate the aforementioned systemic inefficiencies, Impulse Reactor employs a modular architecture governed by three foundational principles:
Principle A:
Volatility Precursor Analysis Market mechanics demonstrate that volatility expansion often functions as a leading indicator for directional price movement. The system is engineered to detect "Volatility Deviation" — specifically, the divergence between short-term and long-term volatility baselines—prior to its manifestation in price action. This allows for entry timing aligned with the expansion phase of market volatility.
Principle B:
Momentum Density Visualization The system replaces singular momentum lines with a "Momentum Density" model utilizing a 15-layer Simple Moving Average (SMA) Ribbon.
• Concept: This visualization represents the aggregate strength and consistency of the trend.
• Application: A fully aligned and expanded ribbon indicates a robust trend structure ("Laminar Flow") capable of withstanding minor counter-trend noise, whereas a compressed ribbon signals consolidation or structural weakness.
Principle C:
Adaptive Confluence Protocols Signal validity is strictly governed by a multi-dimensional confluence logic. The system suppresses signal generation unless there is synchronized confirmation across all three analytical vectors:
1. Volatility: Confirmed expansion via the Impulse Core.
2. Momentum: Directional alignment via the Hybrid Oscillator.
3. Structure: Trend validation via the Baseline. This strict filtering mechanism significantly reduces false positives in non-trending (choppy) environments while maintaining sensitivity to genuine breakouts.
🔍 Chapter 2: Core Modules & Algorithmic Logic
Module A: Impulse Core (Normalized Volatility Deviation)
Operational Logic The Impulse Core functions as a volatility-normalized momentum gauge rather than a standard oscillator. It is designed to identify "Volatility Contraction" (Squeeze) and "Volatility Expansion" phases by quantifying the divergence between short-term and long-term volatility states.
Volatility Z-Score Normalization
The formula implements a custom normalization algorithm. Unlike standard oscillators that rely on absolute price changes, this logic calculates the Z-Score of the Volatility Spread.
◦ Numerator: (atr_f - atr_s) captures the raw momentum of volatility expansion.
◦ Denominator: (std_f + 1e-6) standardizes this value against historical variance.
◦ Result: This allows the indicator scales consistently across assets (e.g., Bitcoin vs. Euro) without manual recalibration.
f_impulse() =>
atr_f = ta.atr(fastLen) // Fast Volatility Baseline
atr_s = ta.atr(slowLen) // Slow Volatility Baseline
std_f = ta.stdev(atr_f, devLen) // Volatility Standard Deviation
(atr_f - atr_s) / (std_f + 1e-6) // Normalized Differential Calculation
Algorithmic Framework
• Differential Calculation: The system computes the spread between a Fast Volatility Baseline (ATR-10) and a Slow Volatility Baseline (ATR-30).
• Normalization Protocol: To standardize consistency across diverse asset classes (e.g., Forex vs. Crypto), the raw differential is divided by the standard deviation of the volatility itself over a 30-period lookback.
• Signal Generation:
◦ Contraction (Squeeze): When the Fast ATR compresses below the Slow ATR, it registers a potential volatility buildup phase.
◦ Expansion (Release): A rapid divergence of the Fast ATR above the Slow ATR signals a confirmed volatility expansion, validating the strength of the move.
Module B: Gradient Oscillator (RSI-SMA Hybrid)
Design Rationale To mitigate the "noise" and "false reversal" signals common in single-line oscillators (like standard RSI), this module utilizes a 15-Layer Gradient Ribbon to visualize momentum density and persistence.
Technical Architecture
• Ribbon Array: The system generates 15 sequential Simple Moving Averages (SMA) applied to a volatility-adjusted RSI source. The length of each layer increases incrementally.
• State Analysis:
Momentum Alignment (Laminar Flow): When all 15 layers are expanded and parallel, it indicates a robust trend where buying/selling pressure is distributed evenly across multiple timeframes. This state helps filter out premature "overbought/oversold" signals.
• Consolidation (Compression): When the distance between the fastest layer (Layer 1) and the slowest layer (Layer 15) approaches zero or the layers intersect, the system identifies a "Non-Tradable Zone," preventing entries during choppy market conditions.
// Laminar Flow Validation
f_validate_trend() =>
// Calculate spread between Ribbon layers
ribbon_spread = ta.stdev(ribbon_array, 15)
// Only allow signals if Ribbon is expanded (Laminar Flow)
is_flowing = ribbon_spread > min_expansion_threshold
// If compressed (Knotted), force signal to false
is_flowing ? signal : na
Module C: Adaptive Signal Filtering (Behavioral Bias Mitigation)
This subsystem, operating as an algorithmic "Anti-Greed" Mechanism, addresses the statistical tendency for signal degradation following prolonged trends.
Dynamic Threshold Adjustment
• Win Streak Detection: The algorithm internally tracks the outcome of closed trade cycles.
• Sensitivity Multiplier: Upon detecting consecutive successful signals in the same direction, a Penalty_Factor is applied to the entry logic.
• Operational Impact: This effectively raises the Required_Slope threshold for subsequent signals. For example, after three consecutive bullish signals, the system requires a 30% steeper trend angle to validate a fourth entry. This enforces stricter discipline during extended trends to reduce the probability of entering at the point of trend exhaustion.
Anti-Greed Logic: Dynamic Threshold Calculation
f_adjust_threshold(base_slope, win_streak) =>
// Adds a 10% penalty to the difficulty for every consecutive win
penalty_factor = 0.10
risk_scaler = 1 + (win_streak * penalty_factor)
// Returns the new, harder-to-reach threshold
base_slope * risk_scaler
Module D: Trend Baseline (Triple-Smoothed Structure)
The Trend Baseline serves as the structural filter for all signals. It employs a Triple-Smoothed Hybrid Algorithm designed to balance lag reduction with noise filtration.
Smoothing Stages
1. Volatility Banding: Utilizes a SuperTrend-based calculation to establish the upper and lower boundaries of price action.
2. Weighted Filter: Applies a Weighted Moving Average (WMA) to prioritize recent price data.
3. Exponential Smoothing: A final Exponential Moving Average (EMA) pass is applied to create a seamless baseline curve.
Functionality
This "Heavy" baseline resists minor intraday volatility spikes while remaining responsive to sustained structural shifts. A signal is only considered valid if the price action maintains structural integrity relative to this baseline
🚦 Chapter 3: Risk Management & Exit Protocols
Quantitative Risk Management (TP/SL & Trailing)
Foundational Architecture: Volatility-Adjusted Geometry Unlike strategies relying on static nominal values, Impulse Reactor establishes dynamic risk boundaries derived from quantitative volatility metrics. This design aligns trade invalidation levels mathematically with the current market regime.
• ATR-Based Dynamic Bracketing:
The protocol calculates Stop-Loss and Take-Profit levels by applying Fibonacci coefficients (Default: 0.786 for SL / 1.618 for TP) to the Average True Range (ATR).
◦ High Volatility Environments: The risk bands automatically expand to accommodate wider variance, preventing premature exits caused by standard market noise.
◦ Low Volatility Environments: The bands contract to tighten risk parameters, thereby dynamically adjusting the Risk-to-Reward (R:R) geometry.
• Close-Validation Protocol ("Soft Stop"):
Institutional algorithms frequently execute liquidity sweeps—driving prices briefly below key support levels to accumulate inventory.
◦ Mechanism: When the "Soft Stop" feature is enabled, the system filters out intraday volatility spikes. The stop-loss is conditional; execution is triggered only if the candle closes beyond the invalidation threshold.
◦ Strategic Advantage: This logic distinguishes between momentary price wicks and genuine structural breakdowns, preserving positions during transient volatility.
• Step-Function Trailing Mechanism:
To protect unrealized PnL while allowing for normal price breathing, a two-phase trailing methodology is employed:
◦ Phase 1 (Activation): The trailing function remains dormant until the price advances by a pre-defined percentage threshold.
◦ Phase 2 (Dynamic Floor): Once armed, the stop level creates a moving floor, adjusting relative to price action while maintaining a volatility-based (ATR) buffer to systematically protect unrealized PnL.
• Algorithmic Exit Protocols (Dynamic Liquidity Analysis)
◦ Rationale: Inefficiencies of Static Targets Static "Take Profit" levels often result in suboptimal exits. They compel traders to close positions based on arbitrary figures rather than evolving market structure, potentially capping upside during significant trends or retaining positions while the underlying trend structure deteriorates.
◦ Solution: Structural Integrity Assessment The system utilizes a Dynamic Liquidity Engine to continuously audit the validity of the position. Instead of targeting a specific price point, the algorithm evaluates whether the trend remains statistically robust.
Multi-Factor Exit Logic (The Tri-Vector System)
The Smart Exit protocol executes only when specific algorithmic invalidation criteria are met:
• 1. Momentum Exhaustion (Confluence Decay): The system monitors a 168-hour rolling average of the Confluence Score. A significant deviation below this historical baseline indicates momentum exhaustion, signaling that the driving force behind the trend has dissipated prior to a price reversal. This enables preemptive exits before a potential drawdown.
• 2. Statistical Over-Extension (Mean Reversion): Utilizing the core volatility logic, the system identifies instances where price deviates beyond 2.0 standard deviations from the mean. While the trend may be technically bullish, this statistical anomaly suggests a high probability of mean reversion (elastic snap-back), triggering a defensive exit to capitalize on peak valuation.
• 3. Oscillator Rejection (Immediate Pivot): To manage sudden V-shaped volatility, the system monitors RSI pivots. If a sharp "Pivot High" or divergence is detected, the protocol triggers an immediate "Peak Exit," bypassing standard trend filters to secure liquidity during high-velocity reversals.
🎨 Chapter 4: Visualization Guide
Gradient Oscillator Ribbon
The 15-layer SMA ribbon visualized via plot(r1...r15) represents the "Momentum Density" of the market.
• Visuals:
◦ Cyan/Blue Ribbon: Indicates Bullish Momentum.
◦ Pink/Magenta Ribbon: Indicates Bearish Momentum.
• Interpretation:
◦ Laminar Flow: When the ribbon expands widely and flows in parallel, it signifies a robust trend where momentum is distributed evenly across timeframes. This is the ideal state for trend-following.
◦ Compression (Consolidation): If the ribbon becomes narrow, twisted, or knotted, it indicates a "Non-Tradable Zone" where the market lacks a unified direction. Traders are advised to wait for clarity.
◦ Over-Extension: If the top layer crosses the Overbought (85) or Oversold (15) lines, it visually warns of potential market overheating.
Trend Baseline
The thick, color-changing line plotted via plot(baseline) represents the Structural Backbone of the market.
• Visuals: Changes color based on the trend direction (Blue for Bullish, Pink for Bearish).
• Interpretation:
Structural Filter: Long positions are statistically favored only when price action sustains above this baseline, while short positions are favored below it.
Dynamic Support/Resistance: The baseline acts as a dynamic support level during uptrends and resistance during downtrends.
Entry Signals & Labels
Text labels ("Long Entry", "Short Entry") appear when the system detects high-probability setups grounded in quantitative confluence.
• Visuals: Labeled signals appear above/below specific candles.
• Interpretation:
These signals represent moments where Volatility (Expansion), Momentum (Alignment), and Structure (Trend) are synchronized.
Smart Exit: Labels such as "Smart Exit" or "Peak Exit" appear when the system detects momentum exhaustion or structural decay, prompting a defensive exit to preserve capital.
Dynamic TP/SL Boxes
The semi-transparent colored zones drawn via fill() represent the risk management geometry.
• Visuals: Colored boxes extending from the entry point to the Take Profit (TP) and Stop Loss (SL) levels.
• Function:
Volatility-Adjusted Geometry: Unlike static price targets, these boxes expand during high volatility (to prevent wicks from stopping you out) and contract during low volatility (to optimize Risk-to-Reward ratios).
SAR + MACD Glow
Small glowing shapes appearing above or below candles.
• Visuals: Triangle or circle glows near the price bars.
• Interpretation:
This visual indicates a secondary confirmation where Parabolic SAR and MACD align with the main trend direction. It serves as an additional confluence factor to increase confidence in the trade setup.
Support/Resistance Table
A small table located at the bottom-right of the chart.
• Function: Automatically identifies and displays recent Pivot Highs (Resistance) and Pivot Lows (Support).
• Interpretation: These levels can be used as potential targets for Take Profit or invalidation points for manual Stop Loss adjustments.
🖥️ Chapter 5: Dashboard & Operational Guide
Integrated Analytics Panel (Dashboard Overview)
To facilitate rapid decision-making without manual calculation, the system aggregates critical market dimensions into a unified "Heads-Up Display" (HUD). This panel monitors real-time metrics across multiple timeframes and analytical vectors.
A. Intermediate Structure (12H Trend)
• Function: Anchors the intraday analysis to the broader market structure using a 12-hour rolling window.
• Interpretation:
◦ Bullish (> +0.5%): Indicates a positive structural bias. Long setups align with the macro flow.
◦ Bearish (< -0.5%): Indicates structural weakness. Short setups are statistically favored.
◦ Neutral: Represents a ranging environment where the Confluence Score becomes the primary weighting factor.
B. Composite Confluence Score (Signal Confidence)
• Definition: A probability metric derived from the synchronization of Volatility (Impulse Core), Momentum (Ribbon), and Trend (Baseline).
• Grading Scale:
Strong Buy/Sell (> 7.0 / < 3.0): Indicates full alignment across all three vectors. Represents a "Prime Setup" eligible for standard position sizing.
Buy/Sell (5.0–7.0 / 3.0–5.0): Indicates a valid trend but with moderate volatility confirmation.
Neutral: Signals conflicting data (e.g., Bullish Momentum vs. Bearish Structure). Trading is not recommended ("No-Trade Zone").
C. Statistical Deviation Status (Mean Reversion)
• Logic: Utilizes Bollinger Band deviation principles to quantify how far price has stretched from the statistical mean (20 SMA).
• Alert States:
Over-Extended (> 2.0 SD): Warning that price is statistically likely to revert to the mean (Elastic Snap-back), even if the trend remains technically valid. New entries are discouraged in this zone.
Normal: Price is within standard distribution limits, suitable for trend-following entries.
D. Volatility Regime Classification
• Metric: Compares current ATR against a 100-period historical baseline to categorize the market state.
• Regimes:
Low Volatility (Lvl < 1.0): Market Compression. Often precedes volatility expansion events.
Mid Volatility (Lvl 1.0 - 1.5): Standard operating environment.
High Volatility (Lvl > 1.5): Elevated market stress. Risk parameters should be adjusted (e.g., reduced position size) to account for increased variance.
E. Performance Telemetry
• Function: Displays the historical reliability of the Trend Baseline for the current asset and timeframe.
• Operational Threshold: If the displayed Win Rate falls below 40%, it suggests the current market behavior is incoherent (choppy) and does not respect trend logic. In such cases, switching assets or timeframes is recommended.
Operational Protocols & Signal Decoding
Visual Interpretation Standards
• Laminar Flow (Trade Confirmation): A valid trend is visually confirmed when the 15-layer SMA Ribbon is fully expanded and parallel. This indicates distributed momentum across timeframes.
• Consolidation (No-Trade): If the ribbon appears twisted, knotted, or compressed, the market lacks a unified directional vector.
• Baseline Interaction: The Triple-Smoothed Baseline acts as a dynamic support/resistance filter. Long positions remain valid only while price sustains above this structure.
System Calibration (Settings)
• Adaptive Signal Filtering (Prev. Anti-Greed): Enabled by default. This logic automatically raises the required trend slope threshold following consecutive wins to mitigate behavioral bias.
• Impulse Sensitivity: Controls the reactivity of the Volatility Core. Higher settings capture faster moves but may introduce more noise.
⚙️ Chapter 6: System Configuration & Alert Guide
This section provides a complete breakdown of every adjustable setting within Impulse Reactor to assist you in tailoring the engine to your specific needs.
🌐 LANGUAGE SETTINGS (Localization)
◦ Select Language (Default: English):
Function: Instantly translates all chart labels, dashboard texts into your preferred language.
Supported: English, Korean, Chinese, Spanish
⚡ IMPULSE CORE SETTINGS (Volatility Engine)
◦ Deviation Lookback (Default: 30): The period used to calculate the standard deviation of volatility.
Role: Sets the baseline for normalizing momentum. Higher values make the core smoother but slower to react.
◦ Fast Pulse Length (Default: 10): The short-term ATR period.
Role: Detects rapid volatility expansion.
◦ Slow Pulse Length (Default: 30): The long-term ATR baseline.
Role: Establishes the background volatility level. The core signal is derived from the divergence between Fast and Slow pulses.
🎯 TP/SL SETTINGS (Risk Management)
◦ SL/TP Fibonacci (Default: 0.786 / 1.618): Selects the Fibonacci ratio used for risk calculation.
◦ SL/TP Multiplier (Default: 1.5 / 2): Applies a multiplier to the ATR-based bands.
Role: Expands or contracts the Take Profit and Stop Loss boxes. Increase these values for higher volatility assets (like Altcoins) to avoid premature stop-outs.
◦ ATR Length (Default: 14): The lookback period for calculating the Average True Range used in risk geometry.
◦ Use Soft Stop (Close Basis):
Role: If enabled, Stop Loss alerts only trigger if a candle closes beyond the invalidation level. This prevents being stopped out by wick manipulations.
🔊 RIBBON SETTINGS (Momentum Visualization)
◦ Show SMA Ribbon: Toggles the visibility of the 15-layer gradient ribbon.
◦ Ribbon Line Count (Default: 15): The number of SMA lines in the ribbon array.
◦ Ribbon Start Length (Default: 2) & Step (Default: 1): Defines the spread of the ribbon.
Role: Controls the "thickness" of the momentum density visualization. A wider step creates a broader ribbon, useful for higher timeframes.
📎 DISPLAY OPTIONS
◦ Show Entry Lines / TP/SL Box / Position Labels / S/R Levels / Dashboard: Toggles individual visual elements on the chart to reduce clutter.
◦ Show SAR+MACD Glow: Enables the secondary confirmation shapes (triangles/circles) above/below candles.
📈 TREND BASELINE (Structural Filter)
◦ Supertrend Factor (Default: 12) & ATR Period (Default: 90): Controls the sensitivity of the underlying Supertrend algorithm used for the baseline calculation.
◦ WMA Length (40) & EMA Length (14): The smoothing periods for the Triple-Smoothed Baseline.
◦ Min Trend Duration (Default: 10): The minimum number of bars the trend must be established before a signal is considered valid.
🧠 SMART EXIT (Dynamic Liquidity)
◦ Use Smart Exit: Enables the momentum exhaustion logic.
◦ Exit Threshold Score (Default: 3): The sensitivity level for triggering a Smart Exit. Lower values trigger earlier exits.
◦ Average Period (168) & Min Hold Bars (5): Defines the rolling window for momentum decay analysis and the minimum duration a trade must be held before Smart Exit logic activates.
🛡️ TRAILING STOP (Step)
◦ Use Trailing Stop: Activates the step-function trailing mechanism.
◦ Step 1 Activation % (0.5) & Offset % (0.5): The price must move 0.5% in your favor to arm the first trail level, which sets a stop 0.5% behind price.
◦ Step 2 Activation % (1) & Offset % (0.2): Once price moves 1%, the trail tightens to 0.2%, securing the position.
🌀 SAR & MACD SETTINGS (Secondary Confirmation)
◦ SAR Start/Increment/Max: Standard Parabolic SAR parameters.
◦ SAR Score Scaling (ATR): Adjusts how much weight the SAR signal has in the overall confluence score.
◦ MACD Fast/Slow/Signal: Standard MACD parameters used for the "Glow" signals.
🔄 ANTI-GREED LOGIC (Behavioral Bias)
◦ Strict Entry after Win: Enables the negative feedback loop.
◦ Strict Multiplier (Default: 1.1): Increases the entry difficulty by 10% after each win.
Role: Prevents overtrading and entering at the top of an extended trend.
🌍 HTF FILTER (Multi-Timeframe)
◦ Use Auto-Adaptive HTF Filter: Automatically selects a higher timeframe (e.g., 1H -> 4H) to filter signals.
◦ Bypass HTF on Steep Trigger: Allows an entry even against the HTF trend if the local momentum slope is exceptionally steep (catch powerful reversals).
📉 RSI PEAK & CHOPPINESS
◦ RSI Peak Exit (Instant): Triggers an immediate exit if a sharp RSI pivot (V-shape) is detected.
◦ Choppiness Filter: Suppresses signals if the Choppiness Index is above the threshold (Default: 60), indicating a flat market.
📐 SLOPE TRIGGER LOGIC
◦ Force Entry on Steep Slope: Overrides other filters if the price angle is extremely vertical (high velocity).
◦ Slope Sensitivity (1.5): The angle required to trigger this override.
⛔ FLAT MARKET FILTER (ADX & ATR)
◦ Use ADX Filter: Blocks signals if ADX is below the threshold (Default: 20), indicating no trend.
◦ Use ATR Flat Filter: Blocks signals if volatility drops below a critical level (dead market).
🔔 Alert Configuration Guide
Impulse Reactor is designed with a comprehensive suite of alert conditions, allowing you to automate your trading or receive real-time notifications for specific market events.
How to Set Up:
Click the "Alert" (Clock) icon in the TradingView toolbar.
Select "Impulse Reactor " from the Condition dropdown.
Choose one of the specific trigger conditions below:
🚀 Entry Signals (Trend Initiation)
Long Entry:
Trigger: Fires when a confirmed Bullish Setup is detected (Momentum + Volatility + Structure align).
Usage: Use this to enter new Long positions.
Short Entry:
Trigger: Fires when a confirmed Bearish Setup is detected.
Usage: Use this to enter new Short positions.
🎯 Profit Taking (Target Levels)
Long TP:
Trigger: Fires when price hits the calculated Take Profit level for a Long trade.
Usage: Automate partial or full profit taking.
Short TP:
Trigger: Fires when price hits the calculated Take Profit level for a Short trade.
Usage: Automate partial or full profit taking.
🛡️ Defensive Exits (Risk Management)
Smart Exit:
Trigger: Fires when the system detects momentum decay or statistical exhaustion (even if the trend hasn't fully reversed).
Usage: Recommended for tightening stops or closing positions early to preserve gains.
Overbought / Oversold:
Trigger: Fires when the ribbon extends into extreme zones.
Usage: Warning signal to prepare for a potential reversal or pullback.
💡 Secondary Confirmation (Confluence)
SAR+MACD Bullish:
Trigger: Fires when Parabolic SAR and MACD align bullishly with the main trend.
Usage: Ideal for Pyramiding (adding to an existing winning position).
SAR+MACD Bearish:
Trigger: Fires when Parabolic SAR and MACD align bearishly.
Usage: Ideal for adding to short positions.
⚠️ Chapter 7: Conclusion & Risk Disclosure
Methodological Synthesis
Impulse Reactor represents a shift from reactive price tracking to proactive energy analysis. By decomposing market activity into its atomic components — Volatility, Momentum, and Structure — and reconstructing them into a coherent decision model, the system aims to provide a quantitative framework for market engagement. It is designed not to predict the future, but to identify high-probability conditions where kinetic energy and trend structure align.
Disclaimer & Risk Warnings
◦ Educational Purpose Only
This indicator, including all associated code, documentation, and visual outputs, is provided strictly for educational and informational purposes. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments.
◦ No Guarantee of Performance
Past performance is not indicative of future results. All metrics displayed on the dashboard (including "Win Rate" and "P&L") are theoretical calculations based on historical data. These figures do not account for real-world trading factors such as slippage, liquidity gaps, spread costs, or broker commissions.
◦ High-Risk Warning
Trading cryptocurrencies, futures, and leveraged financial products involves a substantial risk of loss. The use of leverage can amplify both gains and losses. Users acknowledge that they are solely responsible for their trading decisions and should conduct independent due diligence before executing any trades.
◦ Software Limitations
The software is provided "as is" without warranty. Users should be aware that market data feeds on analysis platforms may experience latency or outages, which can affect signal generation accuracy.
Force Pulse█ OVERVIEW
Force Pulse is a fast-reacting oscillator that measures the internal strength of market sides by analyzing the aggregated dominance of bulls and bears based on candle size.
The indicator normalizes this difference into a 0–100 range, generates signals (OB/OS, midline cross, MA midline cross), and detects divergences between price and the oscillator.
It also offers advanced visualization, signal markers, and alerts, making it a versatile tool suitable for many trading styles.
█ CONCEPTS
Force Pulse was designed as a universal tool that can be applied to various trading strategies depending on its settings:
- increasing the period lengths and smoothing transforms it into a momentum/trend indicator, revealing a stable dominance of one market side.
- Lowering these parameters turns it into a peak/low detector, ideal for contrarian and mean-reversion strategies.
The oscillator analyzes the relationship between the sum of bullish and bearish candles over a selected period, based on:
- candle body size, or
- average candle body size (AVG Body).
Depending on the selected mode, OB/OS levels should be adjusted, as value dynamics differ between modes.
The output is normalized to 0–100, where:
> 50 – bullish dominance,
< 50 – bearish dominance.
The additional MA line is derived from smoothed oscillator values and serves as a signal line for midline crosses and as a trend filter.
The indicator also detects divergences (HL/LL) between price and the oscillator.
█ FEATURES
Bull & Bear Strength:
- Calculations are based on Body or AVG Body – mode selection requires adjusting OB/OS levels.
- Bullish and bearish candle values are summed separately.
- All results are normalized to the 0–100 scale.
Force Pulse Oscillator:
- The main line reflects the current dominance of either market side.
Dynamic colors:
- Green – above 50,
- Red – below 50.
Signal MA:
- SMA based on oscillator values functions as a signal line.
- Helps detect momentum shifts and generates signals via midline crosses.
- Can serve as a trend confirmation filter.
Overbought / Oversold:
- Configurable OB/OS levels, also for the MA line.
- Dynamic OB/OS line colors: when the MA line exceeds the defined threshold (e.g., MA > maOverbought or MA < maOversold), OB/OS lines change color (red/green).
- This often signals a potential reversal or correction and may act as additional confirmation for oscillator-generated signals.
Divergences:
- Detection based on swing pivots:
- Bullish: price LL, oscillator HL
- Bearish: price HH, oscillator LH
- Displayed as “Bull” / “Bear” labels.
Signals:
Supports multiple signal types:
- Overbought/Oversold Cross
- Midline Cross
- MA Midline Cross (based on the signal MA line)
- Signals appear as triangles above/below the oscillator.
Visualization:
- Gradient options for lines and levels.
- Full customization of colors, transparency, and line thickness.
Alerts available for:
- Divergences
- OB/OS crossings
- Midline crossings
- MA midline crossings
█ HOW TO USE
Add the indicator to your TradingView chart → Indicators → search “Force Pulse”
Parameter Configuration
Calculation Settings:
- Calculation Period (lookback) – defines the strength calculation window.
Force Mode (Body / AVG Body):
- Body – faster response, higher sensitivity.
- AVG Body – more stable output; adjust band levels and periods to your strategy.
- EMA Smoothing (smoothLen) – reduces oscillator noise.
- MA Length – length of the signal line (SMA).
Threshold Levels:
- Set Overbought/Oversold levels for both the oscillator and the MA line.
- Adjust levels depending on Body / AVG Body mode.
Divergence Detection:
- Enable/disable divergence detection.
- PivotLength affects both delay and signal quality.
- Signal Settings: Choose one or multiple signal types.
- Style & Colors: Full control over color schemes, gradients, and transparency.
Signal Interpretation
BUY:
- Oscillator leaves oversold (OS crossover).
- Midline cross upward.
- MA crosses the midline from below.
- Bullish divergence.
SELL:
- Oscillator leaves overbought (drops below OB).
- Midline cross downward.
- MA crosses the midline from above.
- Bearish divergence.
Trend / Momentum:
-Longer periods and stronger smoothing → stable directional signals.
-MA as a trend filter: e.g., signal line above the midline (50) and MA pointing upward indicates continuation of a bullish impulse.
Contrarian / Mean Reversion:
- Short periods → rapid detection of peaks and troughs; ideal for contrarian signals and pullback entries.
█ APPLICATIONS
- Trend Trading: Using midline and MA midline crosses to determine direction.
- Reversal Trading: OB/OS levels and divergences help identify reversals.
- Scalping & Intraday: Short settings + signal line above the midline with bullish MA → shows short-term impulse and continuation.
- Swing Trading: Longer MA and higher lookback provide a stable view of market-side dominance.
- Momentum Analysis: Force Pulse highlights the strength of the wave before price movement occurs.
█ NOTES
- In strong trends, the oscillator may stay in extreme zones for a long time — this reflects dominance, not necessarily a reversal signal.
- Divergences are more reliable on higher timeframes.
- OB/OS levels should be tailored to Body/AVG Body mode and the instrument.
- Best results come from combining the indicator with other tools (S/R, market structure, volume).
VMDM - Volume, Momentum & Divergence Master [BullByte]VMDM - Volume, Momentum and Divergence Master
Educational Multi-Layer Market Structure Analysis System
Multi-factor divergence engine that scores RSI momentum, volume pressure, and institutional footprints into one non-repainting confluence rating (0-100).
WHAT THIS INDICATOR IS
VMDM is an educational indicator designed to teach traders how to recognize high-probability reversal and continuation patterns by analyzing four independent market dimensions simultaneously. Instead of relying on a single indicator that may produce frequent false signals, VMDM creates a confluence-based scoring system that weights multiple confirmation factors, helping you understand which setups have stronger technical backing and which are lower quality.
This is NOT a trading system or signal generator. It is a learning tool that visualizes complex market structure concepts in an accessible format for both coders and non-coders.
THE PROBLEM IT SOLVES
Most traders face these common challenges:
Challenge 1 - Indicator Overload: Running RSI, volume analysis, and divergence detection separately creates chart clutter and conflicting signals. You waste time cross-referencing multiple windows trying to determine if all factors align.
Challenge 2 - False Divergences: Standard divergence indicators trigger on every minor pivot, creating noise. Many divergences fail because they lack supporting evidence from volume or market structure.
Challenge 3 - Missed Context: A bullish RSI divergence means nothing if it occurs during weak volume or in the middle of strong distribution. Context determines quality.
Challenge 4 - Repainting Confusion: Many divergence scripts repaint, showing perfect historical signals that never actually triggered in real-time, leading to false confidence.
Challenge 5 - Institutional Pattern Recognition: Absorption zones, stop hunts, and exhaustion patterns are taught in trading education but difficult to identify systematically without manual analysis.
VMDM addresses all five challenges by combining complementary analytical layers into one transparent, non-repainting, confluence-weighted system with visual clarity.
WHY THIS SPECIFIC COMBINATION - MASHUP JUSTIFICATION
This indicator is NOT a random mashup of popular indicators. Each of the four layers serves a specific analytical purpose and together they create a complete market structure assessment framework.
THE FOUR ANALYTICAL LAYERS
LAYER 1 - RSI MOMENTUM DIVERGENCE (Trend Exhaustion Detection)
Purpose: Identifies when price momentum is weakening before price itself reverses.
Why RSI: The Relative Strength Index measures momentum on a bounded 0-100 scale, making divergence detection mathematically consistent across all assets and timeframes. Unlike raw price oscillators, RSI normalizes momentum regardless of volatility regime.
How It Contributes: Divergence between price pivots and RSI pivots reveals early momentum exhaustion. A lower price low with a higher RSI low (bullish regular divergence) signals sellers are losing strength even as price makes new lows. This is the PRIMARY signal generator in VMDM.
Limitation If Used Alone: RSI divergence by itself produces many false signals because momentum can remain weak during continued trends. It needs confirmation from volume and structural evidence.
LAYER 2 - VOLUME PRESSURE ANALYSIS (Buying vs Selling Intensity)
Purpose: Quantifies whether the current bar's volume reflects buying pressure or selling pressure based on where price closed within the bar's range.
Methodology: Instead of just measuring volume size, VMDM calculates WHERE in the bar range the close occurred. A close near the high on high volume indicates strong buying absorption. A close near the low indicates selling pressure. The calculation accounts for wick size (wicks reduce pressure quality) and uses percentile ranking over a lookback period to normalize pressure strength on a 0-100 scale.
Formula Concept:
Buy Pressure = Volume × (Close - Low) / (High - Low) × Wick Quality Factor
Sell Pressure = Volume × (High - Close) / (High - Low) × Wick Quality Factor
Net Pressure = Buy Pressure - Sell Pressure
Pressure Strength = Percentile Rank of Net Pressure over lookback period
Why Percentile Ranking: Absolute volume varies by asset and session. Percentile ranking makes 85th percentile pressure on low-volume crypto comparable to 85th percentile pressure on high-volume forex.
How It Contributes: When a bullish divergence occurs at a pivot low AND pressure strength is above 60 (strong buying), this adds 25 confluence points. It confirms that the divergence is occurring during actual accumulation, not just weak selling.
Limitation If Used Alone: Pressure analysis shows current bar intensity but cannot identify trend exhaustion or reversal timing. High buying pressure can exist during a strong uptrend with no reversal imminent.
LAYER 3 - BEHAVIORAL FOOTPRINT PATTERNS (Volume Anomaly Detection)
CRITICAL DISCLAIMER: The terms "institutional footprint," "absorption," "stop hunt," and "exhaustion" used in this indicator are EDUCATIONAL LABELS for specific price and volume behavioral patterns. These patterns are detected through technical analysis of publicly available price, volume, and bar structure data. This indicator does NOT have access to actual institutional order flow, market maker data, broker stop-loss locations, or any non-public data source. These pattern names are used because they are common terminology in trading education to describe these technical behaviors. The analysis is interpretive and based on observable price action, not privileged information.
Purpose: Detect volume anomalies and price patterns that historically correlate with potential reversal zones or trend continuation failure.
Pattern Type 1 - Absorption (Labeled as "ACCUMULATION" or "DISTRIBUTION")
Detection Criteria: Volume is more than 2x the moving average AND bar range is less than 50 percent of the average bar range.
Interpretation: High volume compressed into a tight range suggests large participants are absorbing supply (accumulation) or distribution (distribution) without allowing price to move significantly. This often precedes directional moves once absorption completes.
Visual: Colored box zone highlighting the absorption area.
Pattern Type 2 - Stop Hunt (Labeled as "BULL HUNT" or "BEAR HUNT")
Detection Criteria: Price penetrates a recent 10-bar high or low by a small margin (0.2 percent), then closes back inside the range on above-average volume (1.5x+).
Interpretation: Price briefly spikes beyond recent structure (likely triggering stop losses placed just beyond obvious levels) then reverses. This is a classic false breakout pattern often seen before reversals.
Visual: Label at the wick extreme showing hunt direction.
Pattern Type 3 - Exhaustion (Labeled as "SELL EXHAUST" or "BUY EXHAUST")
Detection Criteria: Lower wick is more than 2.5x the body size with volume above 1.8x average and RSI below 35 (sell exhaustion), OR upper wick more than 2.5x body size with volume above 1.8x average and RSI above 65 (buy exhaustion).
Interpretation: Large wicks with high volume and extreme RSI suggest aggressive buying or selling was met with equally aggressive rejection. This exhaustion often marks short-term extremes.
Visual: Label showing exhaustion type.
How These Contribute: When a divergence forms at a pivot AND one of these behavioral patterns is active, the confluence score increases by 20 points. This confirms the divergence is occurring during structural anomaly activity, not just normal price flow.
Limitation If Used Alone: These patterns can occur mid-trend and do not indicate direction without momentum context. Absorption in a strong uptrend may just be continuation accumulation.
LAYER 4 - CONFLUENCE SCORING MATRIX (Quality Weighting System)
Purpose: Translate all detected conditions into a single 0-100 quality score so you can objectively compare setups.
Scoring Breakdown:
Divergence Present: +30 points (primary signal)
Pressure Confirmation: +25 points (volume supports direction)
Behavioral Footprint Active: +20 points (structural anomaly present)
RSI Extreme: +15 points (RSI below 30 or above 70 at pivot)
Volume Spike: +10 points (current volume above 1.5x average)
Maximum Possible Score: 100 points
Why These Weights: The weights reflect reliability hierarchy based on backtesting observation. Divergence is the core signal (30 points), but without volume confirmation (25 points) many fail. Behavioral patterns add meaningful context (20 points). RSI extremes and volume spikes are secondary confirmations (15 and 10 points).
Quality Tiers:
90-100: TEXTBOOK (all factors aligned)
75-89: HIGH QUALITY (strong confluence)
60-74: VALID (meets minimum threshold)
Below 60: DEVELOPING (not displayed unless threshold lowered)
How It Contributes: The confluence score allows you to filter noise. You can set your minimum quality threshold in settings. Higher thresholds (75+) show fewer but higher-quality patterns. Lower thresholds (50-60) show more patterns but include lower-confidence setups. This teaches you to distinguish strong setups from weak ones.
Limitation: Confluence scoring is historical observation-based, not predictive guarantee. A 95-point setup can still fail. The score represents technical alignment, not future certainty.
WHY THIS COMBINATION WORKS TOGETHER
Each layer addresses a limitation in the others:
RSI Divergence identifies WHEN momentum is exhausting (timing)
Volume Pressure confirms WHETHER the exhaustion is accompanied by opposite-side accumulation (confirmation)
Behavioral Footprint shows IF structural anomalies support the reversal hypothesis (context)
Confluence Scoring weights ALL factors into an objective quality metric (filtering)
Using only RSI divergence gives you timing without confirmation. Using only volume pressure gives you intensity without directional context. Using only pattern detection gives you anomalies without trend exhaustion context. Using all four together creates a complete analytical framework where each layer compensates for the others' weaknesses.
This is not a mashup for the sake of combining indicators. It is a structured analytical system where each component has a defined role in a multi-dimensional market assessment process.
HOW TO READ THE INDICATOR - VISUAL ELEMENTS GUIDE
VMDM displays up to five visual layer types. You can enable or disable each layer independently in settings under "Visual Layers."
VISUAL LAYER 1 - MARKET STRUCTURE (Pivot Points and Lines)
What You See:
Small labels at swing highs and lows marked "PH" (Pivot High) and "PL" (Pivot Low) with horizontal dashed lines extending right from each pivot.
What It Means:
These are CONFIRMED pivots, not real-time. A pivot low appears AFTER the required right-side confirmation bars pass (default 3 bars). This creates a delay but prevents repainting. The pivot only appears once it is mathematically confirmed.
The horizontal lines represent support (from pivot lows) and resistance (from pivot highs) levels where price previously found significant rejection.
Color Coding:
Green label and line: Pivot Low (potential support)
Red label and line: Pivot High (potential resistance)
How To Use:
These pivots are the foundation for divergence detection. Divergence is only calculated between confirmed pivots, ensuring all signals are non-repainting. The lines help you see historical structure levels.
VISUAL LAYER 2 - PRESSURE ZONES (Background Color)
What You See:
Subtle background color shading on bars - light green or light red tint.
What It Means:
This visualizes volume pressure strength in real-time.
Color Coding:
Light Green Background: Pressure Strength above 70 (strong buying pressure - price closing near highs on volume)
Light Red Background: Pressure Strength below 30 (strong selling pressure - price closing near lows on volume)
No Color: Neutral pressure (pressure between 30-70)
How To Use:
When a bullish divergence pattern appears during green pressure zones, it suggests the divergence is forming during accumulation. When a bearish divergence appears during red zones, distribution is occurring. Pressure zones help you filter divergences - those forming in supportive pressure environments have higher probability.
VISUAL LAYER 3 - DIVERGENCE LINES (Dotted Connectors)
What You See:
Dotted lines connecting two pivot points (either two pivot lows or two pivot highs).
What It Means:
A divergence has been detected between those two pivots. The line connects the price pivots where RSI showed opposite behavior.
Color Coding:
Bright Green Line: Bullish divergence (regular or hidden)
Bright Red Line: Bearish divergence (regular or hidden)
How To Use:
The divergence line appears ONLY after the second pivot is confirmed (delayed by right-side confirmation bars). This is intentional to prevent repainting. When you see the line appear, it means:
For Bullish Regular Divergence:
Price made a lower low (second pivot lower than first)
RSI made a higher low (RSI at second pivot higher than first)
Interpretation: Downtrend losing momentum
For Bullish Hidden Divergence:
Price made a higher low (second pivot higher than first)
RSI made a lower low (RSI at second pivot lower than first)
Interpretation: Uptrend continuation likely (pullback within uptrend)
For Bearish Regular Divergence:
Price made a higher high (second pivot higher than first)
RSI made a lower high (RSI at second pivot lower than first)
Interpretation: Uptrend losing momentum
For Bearish Hidden Divergence:
Price made a lower high (second pivot lower than first)
RSI made a higher high (RSI at second pivot higher than first)
Interpretation: Downtrend continuation likely (bounce within downtrend)
If "Show Consolidated Analysis Label" is disabled, a small label will appear on the divergence line showing the divergence type abbreviation.
VISUAL LAYER 4 - BEHAVIORAL FOOTPRINT MARKERS
What You See:
Boxes, labels, and markers at specific bars showing pattern detection.
ABSORPTION ZONES (Boxes):
Colored rectangular boxes spanning one or more bars.
Purple Box: Accumulation absorption zone (high volume, tight range, bullish close)
Red Box: Distribution absorption zone (high volume, tight range, bearish close)
If absorption continues for multiple consecutive bars, the box extends and a counter appears in the label showing how many bars the absorption lasted.
What It Means: Large volume is being absorbed without significant price movement. This often precedes directional breakouts once the absorption phase completes.
STOP HUNT MARKERS (Labels):
Small labels below or above wicks labeled "BULL HUNT" or "BEAR HUNT" (may show bar count if consecutive).
What It Means:
BULL HUNT : Price spiked below recent lows then reversed back up on volume - likely triggered sell stops before reversing
BEAR HUNT : Price spiked above recent highs then reversed back down on volume - likely triggered buy stops before reversing
EXHAUSTION MARKERS (Labels):
Labels showing "SELL EXHAUST" or "BUY EXHAUST."
What It Means:
SELL EXHAUST : Large lower wick with high volume and low RSI - aggressive selling met with strong rejection
BUY EXHAUST : Large upper wick with high volume and high RSI - aggressive buying met with strong rejection
How To Use:
These markers help you identify WHERE structural anomalies occurred. When a divergence signal appears AT THE SAME TIME as one of these patterns, the confluence score increases. You are looking for alignment - divergence + behavioral pattern + pressure confirmation = high-quality setup.
VISUAL LAYER 5 - CONSOLIDATED ANALYSIS LABEL (Main Pattern Signal)
What You See:
A large label appearing at pivot points (or in real-time mode, at current bar) containing full pattern analysis.
Label Appearance:
Depending on your "Use Compact Label Format" setting:
COMPACT MODE (Single Line):
Example: "BULLISH REGULAR | Q:HIGH QUALITY C:82"
Breakdown:
BULLISH REGULAR: Divergence type detected
Q:HIGH QUALITY: Pattern quality tier
C:82: Confluence score (82 out of 100)
FULL MODE (Multi-Line Detailed):
Example:
PATTERN DETECTED
-------------------
BULLISH REGULAR
Quality: HIGH QUALITY
Price: Lower Low
Momentum: Higher Low
Signal: Weakening Downtrend
CONFLUENCE: 82/100
-------------------
Divergence: 30
Pressure: 25
Institutional: 20
RSI Extreme: 0
Volume: 10
Breakdown:
Top section: Pattern type and quality
Middle section: Divergence explanation (what price did vs what RSI did)
Bottom section: Confluence score with itemized breakdown showing which factors contributed
Label Position:
In Confirmed modes: Label appears AT the pivot point (delayed by confirmation bars)
In Real-time mode: Label appears at current bar as conditions develop
Label Color:
Gold: Textbook quality (90+ confluence)
Green: High quality (75-89 confluence)
Blue: Valid quality (60-74 confluence)
How To Use:
This is your primary decision-making label. When it appears:
Check the divergence type (regular divergences are reversal signals, hidden divergences are continuation signals)
Review the quality tier (textbook and high quality have better historical win rates)
Examine the confluence breakdown to see which factors are present and which are missing
Look at the chart context (trend, support/resistance, timeframe)
Use this information to assess whether the setup aligns with your strategy
The label does NOT tell you to buy or sell. It tells you a technical pattern has formed and provides the quality assessment. Your trading decision must incorporate risk management, market context, and your strategy rules.
UNDERSTANDING THE THREE DETECTION MODES
VMDM offers three signal detection modes in settings to accommodate different trading styles and learning objectives.
MODE 1: "Confluence Only (Real-Time)"
How It Works: Displays signals AS THEY DEVELOP on the current bar without waiting for pivot confirmation. The system calculates confluence score from pressure, volume, RSI extremes, and behavioral patterns. Divergence signals are NOT required in this mode.
Delay: ZERO - signals appear immediately.
Use Case: Real-time scanning for high-confluence zones without divergence requirement. Useful for intraday traders who want immediate alerts when multiple factors align.
Tradeoff: More frequent signals but includes setups without confirmed divergence. Higher false signal rate. Signals can change as the bar develops (not repainting in historical bars, but current bar updates).
Visual Behavior: Labels appear at the current bar. No divergence lines unless divergence happens to be present.
MODE 2: "Divergence + Confluence (Confirmed)" - DEFAULT RECOMMENDED
How It Works: Full system engagement. Signals appear ONLY when:
A pivot is confirmed (requires right-side confirmation bars to pass)
Divergence is detected between current pivot and previous pivot
Total confluence score meets or exceeds your minimum threshold
Delay: Equal to your "Pivot Right Bars" setting (default 3 bars). This means signals appear 3 bars AFTER the actual pivot formed.
Use Case: Highest-quality, non-repainting signals for swing traders and learners who want to study confirmed pattern completion.
Tradeoff: Delayed signals. You will not receive the signal until confirmation occurs. In fast-moving markets, price may have already moved significantly by the time the signal appears.
Visual Behavior: Labels appear at the historical pivot location (in the past). Divergence lines connect the two pivots. This is the most educational mode because it shows completed, confirmed patterns.
Non-Repainting Guarantee: Yes. Once a signal appears, it never disappears or changes.
MODE 3: "Divergence + Confluence (Relaxed)"
How It Works: Same as Confirmed mode but with adaptive thresholds. If confluence is very high (10 points above threshold), the signal may appear even if some factors are weak. If divergence is present but confluence is slightly below threshold (within 10 points), it may still appear.
Delay: Same as Confirmed mode (right-side confirmation bars).
Use Case: Slightly more signals than Confirmed mode for traders willing to accept near-threshold setups.
Tradeoff: More signals but lower average quality than Confirmed mode.
Visual Behavior: Same as Confirmed mode.
DASHBOARD GUIDE - READING THE METRICS
The dashboard appears in the corner of your chart (position selectable in settings) and provides real-time market state analysis.
You can choose between four dashboard detail levels in settings: Off, Compact, Optimized (default), Full.
DASHBOARD ROW EXPLANATIONS
ROW 1 - Header Information
Left: Current symbol and timeframe
Center: "VMDM "
Right: Version number
ROW 2 - Mode and Delay
Shows which detection mode you are using and the signal delay.
Example: "CONFIRMED | Delay: 3 bars"
This reminds you that signals in confirmed mode appear 3 bars after the pivot forms.
ROW 3 - Market Regime
Format: "TREND UP HV" or "RANGING NV"
First Part - Trend State:
TREND UP: 20 EMA above 50 EMA with strong separation
TREND DOWN: 20 EMA below 50 EMA with strong separation
RANGING: EMAs close together, low trend strength
TRANSITION: Between trending and ranging states
Second Part - Volatility State:
HV: High Volatility (current ATR more than 1.3x the 50-bar average ATR)
NV: Normal Volatility (current ATR between 0.7x and 1.3x average)
LV: Low Volatility (current ATR less than 0.7x average)
Third Column: Volatility ratio (example: "1.45x" means current ATR is 1.45 times normal)
How To Use: Regime context helps you interpret signals. Reversal divergences are more reliable in ranging or transitional regimes. Continuation divergences (hidden) are more reliable in trending regimes. High volatility means wider stops may be needed.
ROW 4 - Pressure
Shows current volume pressure state.
Format: "BUYING | ██████████░░░░░░░░░"
States:
BUYING : Pressure strength above 60 (closes near highs)
SELLING : Pressure strength below 40 (closes near lows)
NEUTRAL : Pressure strength between 40-60
Bar Visualization: Each block represents 10 percentile points. A full bar (10 filled blocks) = 100th percentile pressure.
Color: Green for buying, red for selling, gray for neutral.
How To Use: When pressure aligns with divergence direction (bullish divergence during buying pressure), confluence is stronger.
ROW 5 - Volume and RSI
Format: "1.8x | RSI 68 | OB"
First Value: Current volume ratio (1.8x = volume is 1.8 times the moving average)
Second Value: Current RSI reading
Third Value: RSI state
OB: Overbought (RSI above 70)
OS: Oversold (RSI below 30)
Blank: Neutral RSI
How To Use: Volume spikes (above 1.5x) during divergence formation add confluence. RSI extremes at pivots add confluence.
ROW 6 - Behavioral Footprint
Format: "BULL HUNT | 2 bars"
Shows the most recent behavioral pattern detected and how long ago.
States:
ACCUMULATION / DISTRIBUTION: Absorption detected
BULL HUNT / BEAR HUNT: Stop hunt detected
SELL EXHAUST / BUY EXHAUST: Exhaustion detected
SCANNING: No recent pattern
NOW: Pattern is active on current bar
How To Use: When footprint activity is recent (within 50 bars) or active now, it adds context to divergence signals forming in that area.
ROW 7 - Current Pattern
Shows the divergence type currently detected (if any).
Examples: "BULLISH REGULAR", "BEARISH HIDDEN", "Scanning..."
Quality: Shows pattern quality (TEXTBOOK, HIGH QUALITY, VALID)
How To Use: This tells you what type of signal is active. Regular divergences are reversal setups. Hidden divergences are continuation setups.
ROW 8 - Session Summary
Format: "14 events | A3 H8 E3"
First Value: Total institutional events this session
Breakdown:
A: Absorption events
H: Stop hunt events
E: Exhaustion events
How To Use: High event counts suggest an active, volatile session with frequent structural anomalies. Low counts suggest quiet, orderly price action.
ROW 9 - Confluence Score (Optimized/Full mode only)
Format: "78/100 | ████████░░"
Shows current real-time confluence score even if no pattern is confirmed yet.
How To Use: Watch this in real-time to see how close you are to pattern formation. When it exceeds your threshold and divergence forms, a signal will appear (after confirmation delay).
ROW 10 - Patterns Studied (Optimized/Full mode only)
Format: "47 patterns | 12 bars ago"
First Value: Total confirmed patterns detected since chart loaded
Second Value: How many bars since the last confirmed pattern appeared
How To Use: Helps you understand pattern frequency on your selected symbol and timeframe. If many bars have passed since last pattern, market may be trending without reversal opportunities.
ROW 11 - Bull/Bear Ratio (Optimized/Full mode only)
Format: "28:19 | BULL"
Shows count of bullish vs bearish patterns detected.
Balance:
BULL: More bullish patterns detected (suggests market has had more bullish reversals/continuations)
BEAR: More bearish patterns detected
BAL: Equal counts
How To Use: Extreme imbalances can indicate directional bias in the studied period. A heavily bullish ratio in a downtrend might suggest frequent failed rallies (bearish continuation). Context matters.
ROW 12 - Volume Ratio Detail (Optimized/Full mode only)
Shows current volume vs average volume in absolute terms.
Example: "1.4x | 45230 / 32300"
How To Use: Confirms whether current activity is above or below normal.
ROW 13 - Last Institutional Event (Full mode only)
Shows the most recent institutional pattern type and how many bars ago it occurred.
Example: "DISTRIBUTION | 23 bars"
How To Use: Tracks recency of last anomaly for context.
SETTINGS GUIDE - EVERY PARAMETER EXPLAINED
PERFORMANCE SECTION
Enable All Visuals (Master Toggle)
Default: ON
What It Does: Master kill switch for ALL visual elements (labels, lines, boxes, background colors, dashboard). When OFF, only plot outputs remain (invisible unless you open data window).
When To Change: Turn OFF on mobile devices, 1-second charts, or slow computers to improve performance. You can still receive alerts even with visuals disabled.
Impact: Dramatic performance improvement when OFF, but you lose all visual feedback.
Maximum Object History
Default: 50 | Range: 10-100
What It Does: Limits how many of each object type (labels, lines, boxes) are kept in memory. Older objects beyond this limit are deleted.
When To Change: Lower to 20-30 on fast timeframes (1-minute charts) to prevent slowdown. Increase to 100 on daily charts if you want more historical pattern visibility.
Impact: Lower values = better performance but less historical visibility. Higher values = more history visible but potential slowdown on fast timeframes.
Alert Cooldown (Bars)
Default: 5 | Range: 1-50
What It Does: Minimum number of bars that must pass before another alert of the same type can fire. Prevents alert spam when multiple patterns form in quick succession.
When To Change: Increase to 20+ on 1-minute charts to reduce noise. Decrease to 1-2 on daily charts if you want every pattern alerted.
Impact: Higher cooldown = fewer alerts. Lower cooldown = more alerts.
USER EXPERIENCE SECTION
Show Enhanced Tooltips
Default: ON
What It Does: Enables detailed hover-over tooltips on labels and visual elements.
When To Change: Turn OFF if you encounter Pine Script compilation errors related to tooltip arguments (rare, platform-specific issue).
Impact: Minimal. Just adds helpful hover text.
MARKET STRUCTURE DETECTION SECTION
Pivot Left Bars
Default: 3 | Range: 2-10
What It Does: Number of bars to the LEFT of the center bar that must be higher (for pivot low) or lower (for pivot high) than the center bar for a pivot to be valid.
Example: With value 3, a pivot low requires the center bar's low to be lower than the 3 bars to its left.
When To Change:
Increase to 5-7 on noisy timeframes (1-minute charts) to filter insignificant pivots
Decrease to 2 on slow timeframes (daily charts) to catch more pivots
Impact: Higher values = fewer, more significant pivots = fewer signals. Lower values = more frequent pivots = more signals but more noise.
Pivot Right Bars
Default: 3 | Range: 2-10
What It Does: Number of bars to the RIGHT of the center bar that must pass for confirmation. This creates the non-repainting delay.
Example: With value 3, a pivot is confirmed 3 bars AFTER it forms.
When To Change:
Increase to 5-7 for slower, more confirmed signals (better for swing trading)
Decrease to 2 for faster signals (better for intraday, but still non-repainting)
Impact: Higher values = longer delay but more reliable confirmation. Lower values = faster signals but less confirmation. This setting directly controls your signal delay in Confirmed and Relaxed modes.
Minimum Confluence Score
Default: 60 | Range: 40-95
What It Does: The threshold score required for a pattern to be displayed. Patterns with confluence scores below this threshold are not shown.
When To Change:
Increase to 75+ if you only want high-quality textbook setups (fewer signals)
Decrease to 50-55 if you want to see more developing patterns (more signals, lower average quality)
Impact: This is your primary signal filter. Higher threshold = fewer, higher-quality signals. Lower threshold = more signals but includes weaker setups. Recommended starting point is 60-65.
TECHNICAL PERIODS SECTION
RSI Period
Default: 14 | Range: 5-50
What It Does: Lookback period for RSI calculation.
When To Change:
Decrease to 9-10 for faster, more sensitive RSI that detects shorter-term momentum changes
Increase to 21-28 for slower, smoother RSI that filters noise
Impact: Lower values make RSI more volatile (more frequent extremes and divergences). Higher values make RSI smoother (fewer but more significant divergences). 14 is industry standard.
Volume Moving Average Period
Default: 20 | Range: 10-200
What It Does: Lookback period for calculating average volume. Current volume is compared to this average to determine volume ratio.
When To Change:
Decrease to 10-14 for shorter-term volume comparison (more sensitive to recent volume changes)
Increase to 50-100 for longer-term volume comparison (smoother, less sensitive)
Impact: Lower values make volume ratio more volatile. Higher values make it more stable. 20 is standard.
ATR Period
Default: 14 | Range: 5-100
What It Does: Lookback period for Average True Range calculation used for volatility measurement and label positioning.
When To Change: Rarely needs adjustment. Use 7-10 for faster volatility response, 21-28 for slower.
Impact: Affects volatility ratio calculation and visual label spacing. Minimal impact on signals.
Pressure Percentile Lookback
Default: 50 | Range: 10-300
What It Does: Lookback period for calculating volume pressure percentile ranking. Your current pressure is ranked against the pressure of the last X bars.
When To Change:
Decrease to 20-30 for shorter-term pressure context (more responsive to recent changes)
Increase to 100-200 for longer-term pressure context (smoother rankings)
Impact: Lower values make pressure strength more sensitive to recent bars. Higher values provide more stable, long-term pressure assessment. Capped at 300 for performance reasons.
SIGNAL DETECTION SECTION
Signal Detection Mode
Default: "Divergence + Confluence (Confirmed)"
Options:
Confluence Only (Real-time)
Divergence + Confluence (Confirmed)
Divergence + Confluence (Relaxed)
What It Does: Selects which detection logic mode to use (see "Understanding The Three Detection Modes" section above).
When To Change: Use Confirmed for learning and non-repainting signals. Use Real-time for live scanning without divergence requirement. Use Relaxed for slightly more signals than Confirmed.
Impact: Fundamentally changes when and how signals appear.
VISUAL LAYERS SECTION
All toggles default to ON. Each controls visibility of one visual layer:
Show Market Structure: Pivot markers and support/resistance lines
Show Pressure Zones: Background color shading
Show Divergence Lines: Dotted lines connecting pivots
Show Institutional Footprint Markers: Absorption boxes, hunt labels, exhaustion labels
Show Consolidated Analysis Label: Main pattern detection label
Use Compact Label Format
Default: OFF
What It Does: Switches consolidated label between single-line compact format and multi-line detailed format.
When To Change: Turn ON if you find full labels too large or distracting.
Impact: Visual clarity vs. information density tradeoff.
DASHBOARD SECTION
Dashboard Mode
Default: "Optimized"
Options: Off, Compact, Optimized, Full
What It Does: Controls how much information the dashboard displays.
Off: No dashboard
Compact: 8 rows (essential metrics only)
Optimized: 12 rows (recommended balance)
Full: 13 rows (every available metric)
Dashboard Position
Default: "Top Right"
Options: Top Right, Top Left, Bottom Right, Bottom Left
What It Does: Screen corner where dashboard appears.
HOW TO USE VMDM - PRACTICAL WORKFLOW
STEP 1 - INITIAL SETUP
Add VMDM to your chart
Select your detection mode (Confirmed recommended for learning)
Set your minimum confluence score (start with 60-65)
Adjust pivot parameters if needed (default 3/3 is good for most timeframes)
Enable the visual layers you want to see
STEP 2 - CHART ANALYSIS
Let the indicator load and analyze historical data
Review the patterns that appear historically
Examine the confluence scores - notice which patterns had higher scores
Observe which patterns occurred during supportive pressure zones
Notice the divergence line connections - understand what price vs RSI did
STEP 3 - PATTERN RECOGNITION LEARNING
When a consolidated analysis label appears:
Read the divergence type (regular or hidden, bullish or bearish)
Check the quality tier (textbook, high quality, or valid)
Review the confluence breakdown - which factors contributed
Look at the chart context - where is price relative to structure, trend, etc.
Observe the behavioral footprint markers nearby - do they support the pattern
STEP 4 - REAL-TIME MONITORING
Watch the dashboard for real-time regime and pressure state
Monitor the current confluence score in the dashboard
When it approaches your threshold, be alert for potential pattern formation
When a new pattern appears (after confirmation delay), evaluate it using the workflow above
Use your trading strategy rules to decide if the setup aligns with your criteria
STEP 5 - POST-PATTERN OBSERVATION
After a pattern appears:
Mark the level on your chart
Observe what price does after the pattern completes
Did price respect the reversal/continuation signal
What was the confluence score of patterns that worked vs. those that failed
Learn which quality tiers and confluence levels produce better results on your specific symbol and timeframe
RECOMMENDED TIMEFRAMES AND ASSET CLASSES
VMDM is timeframe-agnostic and works on any asset with volume data. However, optimal performance varies:
BEST TIMEFRAMES
15-Minute to 1-Hour: Ideal balance of signal frequency and reliability. Pivot confirmation delay is acceptable. Sufficient volume data for pressure analysis.
4-Hour to Daily: Excellent for swing trading. Very high-quality signals. Lower frequency but higher significance. Recommended for learning because patterns are clearer.
1-Minute to 5-Minute: Works but requires adjustment. Increase pivot bars to 5-7 for filtering. Decrease max object history to 30 for performance. Expect more noise.
Weekly/Monthly: Works but very infrequent signals. Increase confluence threshold to 70+ to ensure only major patterns appear.
BEST ASSET CLASSES
Forex Majors: Excellent volume data and clear trends. Pressure analysis works well.
Crypto (Major Pairs): Good volume data. High volatility makes divergences more pronounced. Works very well.
Stock Indices (SPY, QQQ, etc.): Excellent. Clean price action and reliable volume.
Individual Stocks: Works well on high-volume stocks. Low-volume stocks may produce unreliable pressure readings.
Commodities (Gold, Oil, etc.): Works well. Clear trends and reactions.
WHAT THIS INDICATOR CANNOT DO - LIMITATIONS
LIMITATION 1 - It Does Not Predict The Future
VMDM identifies when technical conditions align historically associated with potential reversals or continuations. It does not predict what will happen next. A textbook 95-confluence pattern can still fail if fundamental events, news, or larger timeframe structure override the setup.
LIMITATION 2 - Confirmation Delay Means You Miss Early Entry
In Confirmed and Relaxed modes, the non-repainting design means you receive signals AFTER the pivot is confirmed. Price may have already moved significantly by the time you receive the signal. This is the tradeoff for non-repainting reliability. You can use Real-time mode for faster signals but sacrifice divergence confirmation.
LIMITATION 3 - It Does Not Tell You Position Sizing or Risk Management
VMDM provides technical pattern analysis. It does not calculate stop loss levels, take profit targets, or position sizing. You must apply your own risk management rules. Never risk more than you can afford to lose based on a technical signal.
LIMITATION 4 - Volume Pressure Analysis Requires Reliable Volume Data
On assets with thin volume or unreliable volume reporting, pressure analysis may be inaccurate. Stick to major liquid assets with consistent volume data.
LIMITATION 5 - It Cannot Detect Fundamental Events
VMDM is purely technical. It cannot predict earnings reports, central bank decisions, geopolitical events, or other fundamental catalysts that can override technical patterns.
LIMITATION 6 - Divergence Requires Two Pivots
The indicator cannot detect divergence until at least two pivots of the same type have formed. In strong trends without pullbacks, you may go long periods without signals.
LIMITATION 7 - Institutional Pattern Names Are Interpretive
The behavioral footprint patterns are named using common trading education terminology, but they are detected through technical analysis, not actual institutional data access. The patterns are interpretations based on price and volume behavior.
CONCEPT FOUNDATION - WHY THIS APPROACH WORKS
MARKET PRINCIPLE 1 - Momentum Divergence Precedes Price Reversal
Price is the final output of market forces, but momentum (the rate of change in those forces) shifts first. When price makes a new low but the momentum behind that move is weaker (higher RSI low), it signals that sellers are losing strength even though they temporarily pushed price lower. This precedes reversal. This is a fundamental principle in technical analysis taught by Charles Dow, widely observed in market behavior.
MARKET PRINCIPLE 2 - Volume Reveals Conviction
Price can move on low volume (low conviction) or high volume (high conviction). When price makes a new low on declining volume while RSI shows improving momentum, it suggests the new low is not confirmed by participant conviction. Adding volume pressure analysis to momentum divergence adds a confirmation layer that filters false divergences.
MARKET PRINCIPLE 3 - Anomalies Mark Structural Extremes
When volume spikes significantly but range contracts (absorption), or when price spikes beyond structure then reverses (stop hunt), or when aggressive moves are met with large-wick rejection (exhaustion), these anomalies often mark short-term extremes. Combining these structural observations with momentum analysis creates context.
MARKET PRINCIPLE 4 - Confluence Improves Probability
No single technical factor is reliable in isolation. RSI divergence alone fails frequently. Volume analysis alone cannot time entries. Combining multiple independent factors into a weighted system increases the probability that observed patterns have structural significance rather than random noise.
THE EDUCATIONAL VALUE
By visualizing all four layers simultaneously and breaking down the confluence scoring transparently, VMDM teaches you to think in terms of multi-dimensional analysis rather than single-indicator reliance. Over time, you will learn to recognize these patterns manually and understand which combinations produce better results on your traded assets.
INSTITUTIONAL TERMINOLOGY - IMPORTANT CLARIFICATION
This indicator uses the following terms that are common in trading education:
Institutional Footprint
Absorption (Accumulation / Distribution)
Stop Hunt
Exhaustion
CRITICAL DISCLAIMER:
These terms are EDUCATIONAL LABELS for specific price action and volume behavior patterns detected through technical analysis of publicly available chart data (open, high, low, close, volume). This indicator does NOT have access to:
Actual institutional order flow or order book data
Market maker positions or intentions
Broker stop-loss databases
Non-public trading data
Proprietary institutional information
The patterns labeled as "institutional footprint" are interpretations based on observable price and volume behavior that educational trading literature often associates with potential large-participant activity. The detection is algorithmic pattern recognition, not privileged data access.
When this indicator identifies "absorption," it means it detected high volume within a small range - a condition that MAY indicate large orders being filled but is not confirmation of actual institutional participation.
When it identifies a "stop hunt," it means price briefly penetrated a structural level then reversed - a pattern that MAY have triggered stop losses but is not confirmation that stops were specifically targeted.
When it identifies "exhaustion," it means high volume with large rejection wicks - a pattern that MAY indicate aggressive participation meeting strong opposition but is not confirmation of institutional involvement.
These are technical analysis interpretations, not factual statements about market participant identity or intent.
DISCLAIMER AND RISK WARNING
EDUCATIONAL PURPOSE ONLY
This indicator is designed as an educational tool to help traders learn to recognize technical patterns, understand multi-factor analysis, and practice systematic market observation. It is NOT a trading system, signal service, or financial advice.
NO PERFORMANCE GUARANTEE
Past pattern behavior does not guarantee future results. A pattern that historically preceded price movement in one direction may fail in the future due to changing market conditions, fundamental events, or random variance. Confluence scores reflect historical technical alignment, not future certainty.
TRADING INVOLVES SUBSTANTIAL RISK
Trading financial instruments involves substantial risk of loss. You can lose more than your initial investment. Never trade with money you cannot afford to lose. Always use proper risk management including stop losses, position sizing, and portfolio diversification.
NO PREDICTIVE CLAIMS
This indicator does NOT predict future price movement. It identifies when technical conditions align in patterns that historically have been associated with potential reversals or continuations. Market behavior is probabilistic, not deterministic.
BACKTESTING LIMITATIONS
If you backtest trading strategies using this indicator, ensure you account for:
Realistic commission costs
Realistic slippage (difference between signal price and actual fill price)
Sufficient sample size (minimum 100 trades for statistical relevance)
Reasonable position sizing (risking no more than 1-2 percent of account per trade)
The confirmation delay inherent in the indicator (you cannot enter at the exact pivot in Confirmed mode)
Backtests that do not account for these factors will produce unrealistic results.
AUTHOR LIABILITY
The author (BullByte) is not responsible for any trading losses incurred using this indicator. By using this indicator, you acknowledge that all trading decisions are your sole responsibility and that you understand the risks involved.
NOT FINANCIAL ADVICE
Nothing in this indicator, its code, its description, or its visual outputs constitutes financial, investment, or trading advice. Consult a licensed financial advisor before making investment decisions.
FREQUENTLY ASKED QUESTIONS
Q: Why do signals appear in the past, not at the current bar
A: In Confirmed and Relaxed modes, signals appear at confirmed pivots, which requires waiting for right-side confirmation bars (default 3). This creates a delay but prevents repainting. Use Real-time mode if you want current-bar signals without pivot confirmation.
Q: Can I use this for automated trading
A: You can create alert-based automation, but understand that Confirmed mode signals appear AFTER the pivot with delay, so your entry will not be at the pivot price. Real-time mode signals can change as the current bar develops. Automation requires careful consideration of these factors.
Q: How do I know which confluence score to use
A: Start with 60. Observe which patterns work on your symbol/timeframe. If too many false signals, increase to 70-75. If too few signals, decrease to 55. Quality vs. quantity tradeoff.
Q: Do regular divergences mean I should enter a reversal trade immediately
A: No. Regular divergences indicate momentum exhaustion, which is a WARNING sign that trend may reverse, not a confirmation that it will. Use confluence score, market context, support/resistance, and your strategy rules to make entry decisions. Many divergences fail.
Q: What's the difference between regular and hidden divergence
A: Regular divergence = price and momentum move in opposite directions at extremes = potential reversal signal. Hidden divergence = price and momentum move in opposite directions during pullbacks = potential continuation signal. Hidden divergence suggests the pullback is just a correction within the larger trend.
Q: Why does the pressure zone color sometimes conflict with the divergence direction
A: Pressure is real-time current bar analysis. Divergence is confirmed pivot analysis from the past. They measure different things at different times. A bullish divergence confirmed 3 bars ago might appear during current selling pressure. This is normal.
Q: Can I use this on stocks without volume data
A: No. Volume is required for pressure analysis and behavioral pattern detection. Use only on assets with reliable volume reporting.
Q: How often should I expect signals
A: Depends on timeframe and settings. Daily charts might produce 5-10 signals per month. 1-hour charts might produce 20-30. 15-minute charts might produce 50-100. Adjust confluence threshold to control frequency.
Q: Can I modify the code
A: Yes, this is open source. You can modify for personal use. If you publish a modified version, please credit the original and ensure your publication meets TradingView guidelines.
Q: What if I disagree with a pattern's confluence score
A: The scoring weights are based on general observations and may not suit your specific strategy or asset. You can modify the code to adjust weights if you have data-driven reasons to do so.
Final Notes
VMDM - Volume, Momentum and Divergence Master is an educational multi-layer market analysis system designed to teach systematic pattern recognition through transparent, confluence-weighted signal detection. By combining RSI momentum divergence, volume pressure quantification, behavioral footprint pattern recognition, and quality scoring into a unified framework, it provides a comprehensive learning environment for understanding market structure.
Use this tool to develop your analytical skills, understand how multiple technical factors interact, and learn to distinguish high-quality setups from noise. Remember that technical analysis is probabilistic, not predictive. No indicator replaces proper education, risk management, and trading discipline.
Trade responsibly. Learn continuously. Risk only what you can afford to lose.
-BullByte
RSI HTF Hardcoded (A/B Presets) + Regimes [CHE]RSI HTF Hardcoded (A/B Presets) + Regimes — Higher-timeframe RSI emulation with acceptance-based regime filter and on-chart diagnostics
Summary
This indicator emulates a higher-timeframe RSI on the current chart by resolving hardcoded “HTF-like” lengths from a time-bucket mapping, avoiding cross-timeframe requests. It computes RSI on a resolved length, smooths it with a resolved moving average, and derives a histogram-style difference (RSI minus its smoother). A four-state regime classifier is gated by a dead-band and an acceptance filter requiring consecutive bars before a regime is considered valid. An on-chart table reports the active preset, resolved mapping tag, resolved lengths, and the current filtered regime.
Pine version: v6
Overlay: false
Primary outputs: RSI line, SMA(RSI) line, RSI–SMA histogram columns, reference levels (30/50/70), regime-change alert, info table
Motivation
Cross-timeframe RSI implementations often rely on `request.security`, which can introduce repaint pathways and additional update latency. This design uses deterministic, on-series computation: it infers a coarse target bucket (or uses a forced bucket) and resolves lengths accordingly. The dead-band reduces noise at the decision boundaries (around RSI 50 and around the RSI–SMA difference), while the acceptance filter suppresses rapid flip-flops by requiring sustained agreement across bars.
Differences
Baseline: Standard RSI with a user-selected length on the same timeframe, or HTF RSI via cross-timeframe requests.
Key differences:
Hardcoded preset families and a bucket-based mapping to resolve “HTF-like” lengths on the current chart.
No `request.security`; all calculations run on the chart’s own series.
Regime classification uses two independent signals (RSI relative to 50 and RSI–SMA difference), gated by a configurable dead-band and an acceptance counter.
Always-on diagnostics via a persistent table (optional), showing preset, mapping tag, resolved lengths, and filtered regime.
Practical effect: The oscillator behaves like a slower, higher-timeframe variant with more stable regime transitions, at the cost of delayed recognition around sharp turns (by design).
How it works
1. Bucket selection: The script derives a coarse “target bucket” from the chart timeframe (Auto) or uses a user-forced bucket.
2. Length resolution: A chosen preset defines base lengths (RSI length and smoothing length). A bucket/timeframe mapping resolves a multiplier, producing final lengths used for RSI and smoothing.
3. Oscillator construction: RSI is computed on the resolved RSI length. A moving average of RSI is computed on the resolved smoothing length. The difference (RSI minus its smoother) is used as the histogram series.
4. Regime classification: Four regimes are defined from:
RSI relative to 50 (bullish above, bearish below), with a dead-band around 50
Difference relative to 0 (positive/negative), with a dead-band around 0
These two axes produce strong/weak bull and bear states, plus a neutral state when inside the dead-band(s).
5. Acceptance filter: The raw regime must persist for `n` consecutive bars before it becomes the filtered regime. The alert triggers when the filtered regime changes.
6. Diagnostics and visualization: Histogram columns change shade based on sign and whether the difference is rising/falling. The table displays preset, mapping tag, resolved lengths, and the filtered regime description.
Parameter Guide
Source — Input series for RSI — Default: Close — Smoother sources reduce noise but add lag.
Preset — Base lengths family — Default: A(14/14) — Switch presets to change RSI and smoothing responsiveness.
Target Bucket — Auto or forced bucket — Default: Auto — Force a bucket to lock behavior across chart timeframe changes.
Table X / Table Y — Table anchor — Default: right / top — Move to avoid covering content.
Table Size — Table text size — Default: normal — Increase for presentations, decrease for dense layouts.
Dark Mode — Table theme — Default: enabled — Match chart background for readability.
Show Table — Toggle diagnostics table — Default: enabled — Disable for a cleaner pane.
Epsilon (dead-band) — Noise gate for decisions — Default: 1.0 — Raise to reduce flips near boundaries; lower to react faster.
Acceptance bars (n) — Bars required to confirm a regime — Default: 3 — Higher reduces whipsaw; lower increases reactivity.
Reading
Histogram (RSI–SMA):
Above zero indicates RSI is above its smoother (positive momentum bias).
Below zero indicates RSI is below its smoother (negative momentum bias).
Darker/lighter shading indicates whether the difference is increasing or decreasing versus the previous bar.
RSI vs SMA(RSI):
RSI’s position relative to 50 provides broad directional bias.
RSI’s position relative to its smoother provides momentum confirmation/contra-signal.
Regimes:
Strong bull: RSI meaningfully above 50 and difference meaningfully above 0.
Weak bull: RSI above 50 but difference below 0 (pullback/transition).
Strong bear: RSI meaningfully below 50 and difference meaningfully below 0.
Weak bear: RSI below 50 but difference above 0 (pullback/transition).
Neutral: inside the dead-band(s).
Table:
Use it to validate the active preset, the mapping tag, the resolved lengths, and the filtered regime output.
Workflows
Trend confirmation:
Favor long bias when strong bull is active; favor short bias when strong bear is active.
Treat weak regimes as pullback/transition context rather than immediate reversals, especially with higher acceptance.
Structure + oscillator:
Combine regimes with swing structure, breakouts, or a baseline trend filter to avoid trading against dominant structure.
Use regime change alerts as a “state change” notification, not as a standalone entry.
Multi-asset consistency:
The bucket mapping helps keep a consistent “feel” across different chart timeframes without relying on external timeframe series.
Behavior/Constraints
Intrabar behavior:
No cross-timeframe requests are used; values can still evolve on the live bar and settle at close depending on your chart/update timing.
Warm-up requirements:
Large resolved lengths require sufficient history to seed RSI and smoothing. Expect a warm-up period after loading or switching symbols/timeframes.
Latency by design:
Dead-band and acceptance filtering reduce noise but can delay regime changes during sharp reversals.
Chart types:
Intended for standard time-based charts. Non-time-based or synthetic chart types (e.g., Heikin-Ashi, Renko, Kagi, Point-and-Figure, Range) can distort oscillator behavior and regime stability.
Tuning
Too many flips near decision boundaries:
Increase Epsilon and/or increase Acceptance bars.
Too sluggish in clean trends:
Reduce Acceptance bars by one, or choose a faster preset (shorter base lengths).
Too sensitive on lower timeframes:
Choose a slower preset (longer base lengths) or force a higher Target Bucket.
Want less clutter:
Disable the table and keep only the alert + plots you need.
What it is/isn’t
This indicator is a regime and visualization layer for RSI using higher-timeframe emulation and stability gates. It is not a complete trading system and does not provide position sizing, risk management, or execution rules. Use it alongside structure, liquidity/volatility context, and protective risk controls.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Best regards and happy trading
Chervolino.
VuManChu Filtered OverlayVuManChu Filtered Overlay is a price-overlay signal tool inspired by VuManChu Cipher B.
Instead of plotting the full oscillator in a separate pane, this script focuses on generating clean long/short signals directly on the chart, combining WaveTrend, Money Flow–style momentum, and an adjustable overbought/oversold threshold.
Under the hood, the script builds a smoothed “Inertia Wave” using a normalized (close–open)/(high–low) money-flow proxy and a long SMA. This is used together with a classic WaveTrend (wt1 / wt2) calculation. Signals are only triggered when:
WaveTrend lines cross (wt1 vs wt2),
The cross direction matches the expected bias
Bull: cross up from below, WaveTrend below zero
Bear: cross down from above, WaveTrend above zero
The custom money-flow curve (rsiMFI) confirms direction
Bull: rsiMFI > 0
Bear: rsiMFI < 0
The WaveTrend line is beyond a user-defined OS/OB magnitude (Wavetrendtrigger), so only meaningful extremes are considered.
The “VuManChu WaveTrend OS/OB threshold (+/-)” input lets you control how aggressive the signals are:
Lower values (e.g. 5–10) → more frequent, more sensitive signals
Higher values (e.g. 40–60) → fewer signa
ls, focused on strong exhaustion moves
Bullish and bearish opportunities are plotted as green and red dots on the candles, and corresponding alerts are fired:
🟢 Optimized VuManChu LONG signal detected on timeframe: X
🔴 Optimized VuManChu SHORT signal detected on timeframe: X
This script is meant as a filter / confirmation layer, not a standalone system. For best results, combine it with your own trend, volume, or higher-timeframe context. This is not financial advice and should be used for educational and experimental purposes only.
