DANCE WITH WOLVES VN ALL TO 1DANCE WITH WOLVES VN is a smart-money volume indicator designed for stocks and crypto.
Main features:
• logic to detect Distribution, No Demand, Absorption and Exhaustion.
• Automatically builds smart Support/Resistance zones from high-volume price leaders.
• Regression trend channel to see the short-term trend and trading range.
• Dashboard table that shows the top high/low price bars with buy/sell volume and group labels.
• Alert conditions for Breakout above resistance and At Support Area so you don’t need to watch the chart all the time.
You can use it on any symbol and timeframe. Just add the script to your chart and follow the zones (red = resistance, green = support) together with the P/L labels and the status line.
Vietnamese note: Indicator dùng volume + để vẽ vùng hỗ trợ/kháng cự thông minh, label phân phối / hấp thụ / cạn lực bán và kênh xu hướng. Dùng được cho cả stock và crypto. tot nhat dung khung 5 den 15 phut
在脚本中搜索"support resistance"
The Trade Plan 9 & 15 EMA⭐ What Are EMAs?
An Exponential Moving Average (EMA) gives more weight to recent prices, making it more responsive than a simple moving average.
9-EMA = very fast, reacts quickly to price changes
15-EMA = slightly slower, smooths short-term noise
Together they help identify momentum shifts.
📈 How the 9/15 EMA Strategy Works
1. Buy Signal (Bullish Crossover)
You enter a long (buy) trade when:
➡ 9 EMA crosses above the 15 EMA
This suggests momentum is shifting upward and a new uptrend may be forming.
2. Sell Signal (Bearish Crossover)
You enter a short (sell) trade or exit long positions when:
➡ 9 EMA crosses below the 15 EMA
This suggests momentum is turning downward.
🔧 How Traders Typically Use It
Entry
Wait for a clear crossover.
Confirm with price closing on the same side of EMAs.
Some traders add confirmation using RSI, MACD, or support/resistance.
Exit
Several options:
Exit when the opposite crossover occurs.
Exit at predetermined risk-reward levels (e.g., 1:2).
Use trailing stop below/above EMAs.
👍 Strengths
Easy to follow
Good for fast-moving markets
Works well on trending markets
Minimal indicators needed
👎 Weaknesses
Whipsaws in sideways markets
Many false signals on very low timeframes
Works best with additional filters
🕒 Common Timeframes
Scalping: 1m, 5m
Day trading: 5m, 15m
Swing trading: 1H, 4H
SuperTrend Zone Rejection [STRZ] CONCEPT -
This indicator identifies trend-continuation setups by combining the Super Trend with dynamic Average True Range (ATR) value zones. It highlights specific price action behaviour's—specifically wick rejections and momentum closes—that occur during pullbacks into the trend baseline.
HOW IT WORKS -
The script operates on three logic gates:
>> Trend Filter: Uses a standard Super Trend (Factor 3, Period 10 default) to define market direction.
>> Dynamic Zones: Projects a volatility-based zone (default 2.0x ATR) above or below the Super Trend line to define a valid pullback area.
>> Signal Detection: Identifies specific candle geometries occurring within these zones.
>> Rejection: Candles with significant wicks testing the zone support/resistance.
>> Momentum: Candles that open within the zone and close in the upper/lower quartile of their range.
FEATURES -
>> Dynamic Channel: Visualizes the active buy/sell zone using a continuous, non-repainting box.
>> Volatile Filtering: Filters out low-volatility candles (doji's/noise) based on minimum ATR size.
>> Visuals: Color-coded trend visualization with distinct signal markers for qualified entries.
SETTINGS -
>> Super Trend: Adjustable Factor and ATR Period.
>> Zone Multiplier: Controls the width of the pullback zone relative to ATR.
>> Visuals: Customizable colours for zones and signals to fit light/dark themes.
Dimensional Resonance ProtocolDimensional Resonance Protocol
🌀 CORE INNOVATION: PHASE SPACE RECONSTRUCTION & EMERGENCE DETECTION
The Dimensional Resonance Protocol represents a paradigm shift from traditional technical analysis to complexity science. Rather than measuring price levels or indicator crossovers, DRP reconstructs the hidden attractor governing market dynamics using Takens' embedding theorem, then detects emergence —the rare moments when multiple dimensions of market behavior spontaneously synchronize into coherent, predictable states.
The Complexity Hypothesis:
Markets are not simple oscillators or random walks—they are complex adaptive systems existing in high-dimensional phase space. Traditional indicators see only shadows (one-dimensional projections) of this higher-dimensional reality. DRP reconstructs the full phase space using time-delay embedding, revealing the true structure of market dynamics.
Takens' Embedding Theorem (1981):
A profound mathematical result from dynamical systems theory: Given a time series from a complex system, we can reconstruct its full phase space by creating delayed copies of the observation.
Mathematical Foundation:
From single observable x(t), create embedding vectors:
X(t) =
Where:
• d = Embedding dimension (default 5)
• τ = Time delay (default 3 bars)
• x(t) = Price or return at time t
Key Insight: If d ≥ 2D+1 (where D is the true attractor dimension), this embedding is topologically equivalent to the actual system dynamics. We've reconstructed the hidden attractor from a single price series.
Why This Matters:
Markets appear random in one dimension (price chart). But in reconstructed phase space, structure emerges—attractors, limit cycles, strange attractors. When we identify these structures, we can detect:
• Stable regions : Predictable behavior (trade opportunities)
• Chaotic regions : Unpredictable behavior (avoid trading)
• Critical transitions : Phase changes between regimes
Phase Space Magnitude Calculation:
phase_magnitude = sqrt(Σ ² for i = 0 to d-1)
This measures the "energy" or "momentum" of the market trajectory through phase space. High magnitude = strong directional move. Low magnitude = consolidation.
📊 RECURRENCE QUANTIFICATION ANALYSIS (RQA)
Once phase space is reconstructed, we analyze its recurrence structure —when does the system return near previous states?
Recurrence Plot Foundation:
A recurrence occurs when two phase space points are closer than threshold ε:
R(i,j) = 1 if ||X(i) - X(j)|| < ε, else 0
This creates a binary matrix showing when the system revisits similar states.
Key RQA Metrics:
1. Recurrence Rate (RR):
RR = (Number of recurrent points) / (Total possible pairs)
• RR near 0: System never repeats (highly stochastic)
• RR = 0.1-0.3: Moderate recurrence (tradeable patterns)
• RR > 0.5: System stuck in attractor (ranging market)
• RR near 1: System frozen (no dynamics)
Interpretation: Moderate recurrence is optimal —patterns exist but market isn't stuck.
2. Determinism (DET):
Measures what fraction of recurrences form diagonal structures in the recurrence plot. Diagonals indicate deterministic evolution (trajectory follows predictable paths).
DET = (Recurrence points on diagonals) / (Total recurrence points)
• DET < 0.3: Random dynamics
• DET = 0.3-0.7: Moderate determinism (patterns with noise)
• DET > 0.7: Strong determinism (technical patterns reliable)
Trading Implication: Signals are prioritized when DET > 0.3 (deterministic state) and RR is moderate (not stuck).
Threshold Selection (ε):
Default ε = 0.10 × std_dev means two states are "recurrent" if within 10% of a standard deviation. This is tight enough to require genuine similarity but loose enough to find patterns.
🔬 PERMUTATION ENTROPY: COMPLEXITY MEASUREMENT
Permutation entropy measures the complexity of a time series by analyzing the distribution of ordinal patterns.
Algorithm (Bandt & Pompe, 2002):
1. Take overlapping windows of length n (default n=4)
2. For each window, record the rank order pattern
Example: → pattern (ranks from lowest to highest)
3. Count frequency of each possible pattern
4. Calculate Shannon entropy of pattern distribution
Mathematical Formula:
H_perm = -Σ p(π) · ln(p(π))
Where π ranges over all n! possible permutations, p(π) is the probability of pattern π.
Normalized to :
H_norm = H_perm / ln(n!)
Interpretation:
• H < 0.3 : Very ordered, crystalline structure (strong trending)
• H = 0.3-0.5 : Ordered regime (tradeable with patterns)
• H = 0.5-0.7 : Moderate complexity (mixed conditions)
• H = 0.7-0.85 : Complex dynamics (challenging to trade)
• H > 0.85 : Maximum entropy (nearly random, avoid)
Entropy Regime Classification:
DRP classifies markets into five entropy regimes:
• CRYSTALLINE (H < 0.3): Maximum order, persistent trends
• ORDERED (H < 0.5): Clear patterns, momentum strategies work
• MODERATE (H < 0.7): Mixed dynamics, adaptive required
• COMPLEX (H < 0.85): High entropy, mean reversion better
• CHAOTIC (H ≥ 0.85): Near-random, minimize trading
Why Permutation Entropy?
Unlike traditional entropy methods requiring binning continuous data (losing information), permutation entropy:
• Works directly on time series
• Robust to monotonic transformations
• Computationally efficient
• Captures temporal structure, not just distribution
• Immune to outliers (uses ranks, not values)
⚡ LYAPUNOV EXPONENT: CHAOS vs STABILITY
The Lyapunov exponent λ measures sensitivity to initial conditions —the hallmark of chaos.
Physical Meaning:
Two trajectories starting infinitely close will diverge at exponential rate e^(λt):
Distance(t) ≈ Distance(0) × e^(λt)
Interpretation:
• λ > 0 : Positive Lyapunov exponent = CHAOS
- Small errors grow exponentially
- Long-term prediction impossible
- System is sensitive, unpredictable
- AVOID TRADING
• λ ≈ 0 : Near-zero = CRITICAL STATE
- Edge of chaos
- Transition zone between order and disorder
- Moderate predictability
- PROCEED WITH CAUTION
• λ < 0 : Negative Lyapunov exponent = STABLE
- Small errors decay
- Trajectories converge
- System is predictable
- OPTIMAL FOR TRADING
Estimation Method:
DRP estimates λ by tracking how quickly nearby states diverge over a rolling window (default 20 bars):
For each bar i in window:
δ₀ = |x - x | (initial separation)
δ₁ = |x - x | (previous separation)
if δ₁ > 0:
ratio = δ₀ / δ₁
log_ratios += ln(ratio)
λ ≈ average(log_ratios)
Stability Classification:
• STABLE : λ < 0 (negative growth rate)
• CRITICAL : |λ| < 0.1 (near neutral)
• CHAOTIC : λ > 0.2 (strong positive growth)
Signal Filtering:
By default, NEXUS requires λ < 0 (stable regime) for signal confirmation. This filters out trades during chaotic periods when technical patterns break down.
📐 HIGUCHI FRACTAL DIMENSION
Fractal dimension measures self-similarity and complexity of the price trajectory.
Theoretical Background:
A curve's fractal dimension D ranges from 1 (smooth line) to 2 (space-filling curve):
• D ≈ 1.0 : Smooth, persistent trending
• D ≈ 1.5 : Random walk (Brownian motion)
• D ≈ 2.0 : Highly irregular, space-filling
Higuchi Method (1988):
For a time series of length N, construct k different curves by taking every k-th point:
L(k) = (1/k) × Σ|x - x | × (N-1)/(⌊(N-m)/k⌋ × k)
For different values of k (1 to k_max), calculate L(k). The fractal dimension is the slope of log(L(k)) vs log(1/k):
D = slope of log(L) vs log(1/k)
Market Interpretation:
• D < 1.35 : Strong trending, persistent (Hurst > 0.5)
- TRENDING regime
- Momentum strategies favored
- Breakouts likely to continue
• D = 1.35-1.45 : Moderate persistence
- PERSISTENT regime
- Trend-following with caution
- Patterns have meaning
• D = 1.45-1.55 : Random walk territory
- RANDOM regime
- Efficiency hypothesis holds
- Technical analysis least reliable
• D = 1.55-1.65 : Anti-persistent (mean-reverting)
- ANTI-PERSISTENT regime
- Oscillator strategies work
- Overbought/oversold meaningful
• D > 1.65 : Highly complex, choppy
- COMPLEX regime
- Avoid directional bets
- Wait for regime change
Signal Filtering:
Resonance signals (secondary signal type) require D < 1.5, indicating trending or persistent dynamics where momentum has meaning.
🔗 TRANSFER ENTROPY: CAUSAL INFORMATION FLOW
Transfer entropy measures directed causal influence between time series—not just correlation, but actual information transfer.
Schreiber's Definition (2000):
Transfer entropy from X to Y measures how much knowing X's past reduces uncertainty about Y's future:
TE(X→Y) = H(Y_future | Y_past) - H(Y_future | Y_past, X_past)
Where H is Shannon entropy.
Key Properties:
1. Directional : TE(X→Y) ≠ TE(Y→X) in general
2. Non-linear : Detects complex causal relationships
3. Model-free : No assumptions about functional form
4. Lag-independent : Captures delayed causal effects
Three Causal Flows Measured:
1. Volume → Price (TE_V→P):
Measures how much volume patterns predict price changes.
• TE > 0 : Volume provides predictive information about price
- Institutional participation driving moves
- Volume confirms direction
- High reliability
• TE ≈ 0 : No causal flow (weak volume/price relationship)
- Volume uninformative
- Caution on signals
• TE < 0 (rare): Suggests price leading volume
- Potentially manipulated or thin market
2. Volatility → Momentum (TE_σ→M):
Does volatility expansion predict momentum changes?
• Positive TE : Volatility precedes momentum shifts
- Breakout dynamics
- Regime transitions
3. Structure → Price (TE_S→P):
Do support/resistance patterns causally influence price?
• Positive TE : Structural levels have causal impact
- Technical levels matter
- Market respects structure
Net Causal Flow:
Net_Flow = TE_V→P + 0.5·TE_σ→M + TE_S→P
• Net > +0.1 : Bullish causal structure
• Net < -0.1 : Bearish causal structure
• |Net| < 0.1 : Neutral/unclear causation
Causal Gate:
For signal confirmation, NEXUS requires:
• Buy signals : TE_V→P > 0 AND Net_Flow > 0.05
• Sell signals : TE_V→P > 0 AND Net_Flow < -0.05
This ensures volume is actually driving price (causal support exists), not just correlated noise.
Implementation Note:
Computing true transfer entropy requires discretizing continuous data into bins (default 6 bins) and estimating joint probability distributions. NEXUS uses a hybrid approach combining TE theory with autocorrelation structure and lagged cross-correlation to approximate information transfer in computationally efficient manner.
🌊 HILBERT PHASE COHERENCE
Phase coherence measures synchronization across market dimensions using Hilbert transform analysis.
Hilbert Transform Theory:
For a signal x(t), the Hilbert transform H (t) creates an analytic signal:
z(t) = x(t) + i·H (t) = A(t)·e^(iφ(t))
Where:
• A(t) = Instantaneous amplitude
• φ(t) = Instantaneous phase
Instantaneous Phase:
φ(t) = arctan(H (t) / x(t))
The phase represents where the signal is in its natural cycle—analogous to position on a unit circle.
Four Dimensions Analyzed:
1. Momentum Phase : Phase of price rate-of-change
2. Volume Phase : Phase of volume intensity
3. Volatility Phase : Phase of ATR cycles
4. Structure Phase : Phase of position within range
Phase Locking Value (PLV):
For two signals with phases φ₁(t) and φ₂(t), PLV measures phase synchronization:
PLV = |⟨e^(i(φ₁(t) - φ₂(t)))⟩|
Where ⟨·⟩ is time average over window.
Interpretation:
• PLV = 0 : Completely random phase relationship (no synchronization)
• PLV = 0.5 : Moderate phase locking
• PLV = 1 : Perfect synchronization (phases locked)
Pairwise PLV Calculations:
• PLV_momentum-volume : Are momentum and volume cycles synchronized?
• PLV_momentum-structure : Are momentum cycles aligned with structure?
• PLV_volume-structure : Are volume and structural patterns in phase?
Overall Phase Coherence:
Coherence = (PLV_mom-vol + PLV_mom-struct + PLV_vol-struct) / 3
Signal Confirmation:
Emergence signals require coherence ≥ threshold (default 0.70):
• Below 0.70: Dimensions not synchronized, no coherent market state
• Above 0.70: Dimensions in phase, coherent behavior emerging
Coherence Direction:
The summed phase angles indicate whether synchronized dimensions point bullish or bearish:
Direction = sin(φ_momentum) + 0.5·sin(φ_volume) + 0.5·sin(φ_structure)
• Direction > 0 : Phases pointing upward (bullish synchronization)
• Direction < 0 : Phases pointing downward (bearish synchronization)
🌀 EMERGENCE SCORE: MULTI-DIMENSIONAL ALIGNMENT
The emergence score aggregates all complexity metrics into a single 0-1 value representing market coherence.
Eight Components with Weights:
1. Phase Coherence (20%):
Direct contribution: coherence × 0.20
Measures dimensional synchronization.
2. Entropy Regime (15%):
Contribution: (0.6 - H_perm) / 0.6 × 0.15 if H < 0.6, else 0
Rewards low entropy (ordered, predictable states).
3. Lyapunov Stability (12%):
• λ < 0 (stable): +0.12
• |λ| < 0.1 (critical): +0.08
• λ > 0.2 (chaotic): +0.0
Requires stable, predictable dynamics.
4. Fractal Dimension Trending (12%):
Contribution: (1.45 - D) / 0.45 × 0.12 if D < 1.45, else 0
Rewards trending fractal structure (D < 1.45).
5. Dimensional Resonance (12%):
Contribution: |dimensional_resonance| × 0.12
Measures alignment across momentum, volume, structure, volatility dimensions.
6. Causal Flow Strength (9%):
Contribution: |net_causal_flow| × 0.09
Rewards strong causal relationships.
7. Phase Space Embedding (10%):
Contribution: min(|phase_magnitude_norm|, 3.0) / 3.0 × 0.10 if |magnitude| > 1.0
Rewards strong trajectory in reconstructed phase space.
8. Recurrence Quality (10%):
Contribution: determinism × 0.10 if DET > 0.3 AND 0.1 < RR < 0.8
Rewards deterministic patterns with moderate recurrence.
Total Emergence Score:
E = Σ(components) ∈
Capped at 1.0 maximum.
Emergence Direction:
Separate calculation determining bullish vs bearish:
• Dimensional resonance sign
• Net causal flow sign
• Phase magnitude correlation with momentum
Signal Threshold:
Default emergence_threshold = 0.75 means 75% of maximum possible emergence score required to trigger signals.
Why Emergence Matters:
Traditional indicators measure single dimensions. Emergence detects self-organization —when multiple independent dimensions spontaneously align. This is the market equivalent of a phase transition in physics, where microscopic chaos gives way to macroscopic order.
These are the highest-probability trade opportunities because the entire system is resonating in the same direction.
🎯 SIGNAL GENERATION: EMERGENCE vs RESONANCE
DRP generates two tiers of signals with different requirements:
TIER 1: EMERGENCE SIGNALS (Primary)
Requirements:
1. Emergence score ≥ threshold (default 0.75)
2. Phase coherence ≥ threshold (default 0.70)
3. Emergence direction > 0.2 (bullish) or < -0.2 (bearish)
4. Causal gate passed (if enabled): TE_V→P > 0 and net_flow confirms direction
5. Stability zone (if enabled): λ < 0 or |λ| < 0.1
6. Price confirmation: Close > open (bulls) or close < open (bears)
7. Cooldown satisfied: bars_since_signal ≥ cooldown_period
EMERGENCE BUY:
• All above conditions met with bullish direction
• Market has achieved coherent bullish state
• Multiple dimensions synchronized upward
EMERGENCE SELL:
• All above conditions met with bearish direction
• Market has achieved coherent bearish state
• Multiple dimensions synchronized downward
Premium Emergence:
When signal_quality (emergence_score × phase_coherence) > 0.7:
• Displayed as ★ star symbol
• Highest conviction trades
• Maximum dimensional alignment
Standard Emergence:
When signal_quality 0.5-0.7:
• Displayed as ◆ diamond symbol
• Strong signals but not perfect alignment
TIER 2: RESONANCE SIGNALS (Secondary)
Requirements:
1. Dimensional resonance > +0.6 (bullish) or < -0.6 (bearish)
2. Fractal dimension < 1.5 (trending/persistent regime)
3. Price confirmation matches direction
4. NOT in chaotic regime (λ < 0.2)
5. Cooldown satisfied
6. NO emergence signal firing (resonance is fallback)
RESONANCE BUY:
• Dimensional alignment without full emergence
• Trending fractal structure
• Moderate conviction
RESONANCE SELL:
• Dimensional alignment without full emergence
• Bearish resonance with trending structure
• Moderate conviction
Displayed as small ▲/▼ triangles with transparency.
Signal Hierarchy:
IF emergence conditions met:
Fire EMERGENCE signal (★ or ◆)
ELSE IF resonance conditions met:
Fire RESONANCE signal (▲ or ▼)
ELSE:
No signal
Cooldown System:
After any signal fires, cooldown_period (default 5 bars) must elapse before next signal. This prevents signal clustering during persistent conditions.
Cooldown tracks using bar_index:
bars_since_signal = current_bar_index - last_signal_bar_index
cooldown_ok = bars_since_signal >= cooldown_period
🎨 VISUAL SYSTEM: MULTI-LAYER COMPLEXITY
DRP provides rich visual feedback across four distinct layers:
LAYER 1: COHERENCE FIELD (Background)
Colored background intensity based on phase coherence:
• No background : Coherence < 0.5 (incoherent state)
• Faint glow : Coherence 0.5-0.7 (building coherence)
• Stronger glow : Coherence > 0.7 (coherent state)
Color:
• Cyan/teal: Bullish coherence (direction > 0)
• Red/magenta: Bearish coherence (direction < 0)
• Blue: Neutral coherence (direction ≈ 0)
Transparency: 98 minus (coherence_intensity × 10), so higher coherence = more visible.
LAYER 2: STABILITY/CHAOS ZONES
Background color indicating Lyapunov regime:
• Green tint (95% transparent): λ < 0, STABLE zone
- Safe to trade
- Patterns meaningful
• Gold tint (90% transparent): |λ| < 0.1, CRITICAL zone
- Edge of chaos
- Moderate risk
• Red tint (85% transparent): λ > 0.2, CHAOTIC zone
- Avoid trading
- Unpredictable behavior
LAYER 3: DIMENSIONAL RIBBONS
Three EMAs representing dimensional structure:
• Fast ribbon : EMA(8) in cyan/teal (fast dynamics)
• Medium ribbon : EMA(21) in blue (intermediate)
• Slow ribbon : EMA(55) in red/magenta (slow dynamics)
Provides visual reference for multi-scale structure without cluttering with raw phase space data.
LAYER 4: CAUSAL FLOW LINE
A thicker line plotted at EMA(13) colored by net causal flow:
• Cyan/teal : Net_flow > +0.1 (bullish causation)
• Red/magenta : Net_flow < -0.1 (bearish causation)
• Gray : |Net_flow| < 0.1 (neutral causation)
Shows real-time direction of information flow.
EMERGENCE FLASH:
Strong background flash when emergence signals fire:
• Cyan flash for emergence buy
• Red flash for emergence sell
• 80% transparency for visibility without obscuring price
📊 COMPREHENSIVE DASHBOARD
Real-time monitoring of all complexity metrics:
HEADER:
• 🌀 DRP branding with gold accent
CORE METRICS:
EMERGENCE:
• Progress bar (█ filled, ░ empty) showing 0-100%
• Percentage value
• Direction arrow (↗ bull, ↘ bear, → neutral)
• Color-coded: Green/gold if active, gray if low
COHERENCE:
• Progress bar showing phase locking value
• Percentage value
• Checkmark ✓ if ≥ threshold, circle ○ if below
• Color-coded: Cyan if coherent, gray if not
COMPLEXITY SECTION:
ENTROPY:
• Regime name (CRYSTALLINE/ORDERED/MODERATE/COMPLEX/CHAOTIC)
• Numerical value (0.00-1.00)
• Color: Green (ordered), gold (moderate), red (chaotic)
LYAPUNOV:
• State (STABLE/CRITICAL/CHAOTIC)
• Numerical value (typically -0.5 to +0.5)
• Status indicator: ● stable, ◐ critical, ○ chaotic
• Color-coded by state
FRACTAL:
• Regime (TRENDING/PERSISTENT/RANDOM/ANTI-PERSIST/COMPLEX)
• Dimension value (1.0-2.0)
• Color: Cyan (trending), gold (random), red (complex)
PHASE-SPACE:
• State (STRONG/ACTIVE/QUIET)
• Normalized magnitude value
• Parameters display: d=5 τ=3
CAUSAL SECTION:
CAUSAL:
• Direction (BULL/BEAR/NEUTRAL)
• Net flow value
• Flow indicator: →P (to price), P← (from price), ○ (neutral)
V→P:
• Volume-to-price transfer entropy
• Small display showing specific TE value
DIMENSIONAL SECTION:
RESONANCE:
• Progress bar of absolute resonance
• Signed value (-1 to +1)
• Color-coded by direction
RECURRENCE:
• Recurrence rate percentage
• Determinism percentage display
• Color-coded: Green if high quality
STATE SECTION:
STATE:
• Current mode: EMERGENCE / RESONANCE / CHAOS / SCANNING
• Icon: 🚀 (emergence buy), 💫 (emergence sell), ▲ (resonance buy), ▼ (resonance sell), ⚠ (chaos), ◎ (scanning)
• Color-coded by state
SIGNALS:
• E: count of emergence signals
• R: count of resonance signals
⚙️ KEY PARAMETERS EXPLAINED
Phase Space Configuration:
• Embedding Dimension (3-10, default 5): Reconstruction dimension
- Low (3-4): Simple dynamics, faster computation
- Medium (5-6): Balanced (recommended)
- High (7-10): Complex dynamics, more data needed
- Rule: d ≥ 2D+1 where D is true dimension
• Time Delay (τ) (1-10, default 3): Embedding lag
- Fast markets: 1-2
- Normal: 3-4
- Slow markets: 5-10
- Optimal: First minimum of mutual information (often 2-4)
• Recurrence Threshold (ε) (0.01-0.5, default 0.10): Phase space proximity
- Tight (0.01-0.05): Very similar states only
- Medium (0.08-0.15): Balanced
- Loose (0.20-0.50): Liberal matching
Entropy & Complexity:
• Permutation Order (3-7, default 4): Pattern length
- Low (3): 6 patterns, fast but coarse
- Medium (4-5): 24-120 patterns, balanced
- High (6-7): 720-5040 patterns, fine-grained
- Note: Requires window >> order! for stability
• Entropy Window (15-100, default 30): Lookback for entropy
- Short (15-25): Responsive to changes
- Medium (30-50): Stable measure
- Long (60-100): Very smooth, slow adaptation
• Lyapunov Window (10-50, default 20): Stability estimation window
- Short (10-15): Fast chaos detection
- Medium (20-30): Balanced
- Long (40-50): Stable λ estimate
Causal Inference:
• Enable Transfer Entropy (default ON): Causality analysis
- Keep ON for full system functionality
• TE History Length (2-15, default 5): Causal lookback
- Short (2-4): Quick causal detection
- Medium (5-8): Balanced
- Long (10-15): Deep causal analysis
• TE Discretization Bins (4-12, default 6): Binning granularity
- Few (4-5): Coarse, robust, needs less data
- Medium (6-8): Balanced
- Many (9-12): Fine-grained, needs more data
Phase Coherence:
• Enable Phase Coherence (default ON): Synchronization detection
- Keep ON for emergence detection
• Coherence Threshold (0.3-0.95, default 0.70): PLV requirement
- Loose (0.3-0.5): More signals, lower quality
- Balanced (0.6-0.75): Recommended
- Strict (0.8-0.95): Rare, highest quality
• Hilbert Smoothing (3-20, default 8): Phase smoothing
- Low (3-5): Responsive, noisier
- Medium (6-10): Balanced
- High (12-20): Smooth, more lag
Fractal Analysis:
• Enable Fractal Dimension (default ON): Complexity measurement
- Keep ON for full analysis
• Fractal K-max (4-20, default 8): Scaling range
- Low (4-6): Faster, less accurate
- Medium (7-10): Balanced
- High (12-20): Accurate, slower
• Fractal Window (30-200, default 50): FD lookback
- Short (30-50): Responsive FD
- Medium (60-100): Stable FD
- Long (120-200): Very smooth FD
Emergence Detection:
• Emergence Threshold (0.5-0.95, default 0.75): Minimum coherence
- Sensitive (0.5-0.65): More signals
- Balanced (0.7-0.8): Recommended
- Strict (0.85-0.95): Rare signals
• Require Causal Gate (default ON): TE confirmation
- ON: Only signal when causality confirms
- OFF: Allow signals without causal support
• Require Stability Zone (default ON): Lyapunov filter
- ON: Only signal when λ < 0 (stable) or |λ| < 0.1 (critical)
- OFF: Allow signals in chaotic regimes (risky)
• Signal Cooldown (1-50, default 5): Minimum bars between signals
- Fast (1-3): Rapid signal generation
- Normal (4-8): Balanced
- Slow (10-20): Very selective
- Ultra (25-50): Only major regime changes
Signal Configuration:
• Momentum Period (5-50, default 14): ROC calculation
• Structure Lookback (10-100, default 20): Support/resistance range
• Volatility Period (5-50, default 14): ATR calculation
• Volume MA Period (10-50, default 20): Volume normalization
Visual Settings:
• Customizable color scheme for all elements
• Toggle visibility for each layer independently
• Dashboard position (4 corners) and size (tiny/small/normal)
🎓 PROFESSIONAL USAGE PROTOCOL
Phase 1: System Familiarization (Week 1)
Goal: Understand complexity metrics and dashboard interpretation
Setup:
• Enable all features with default parameters
• Watch dashboard metrics for 500+ bars
• Do NOT trade yet
Actions:
• Observe emergence score patterns relative to price moves
• Note coherence threshold crossings and subsequent price action
• Watch entropy regime transitions (ORDERED → COMPLEX → CHAOTIC)
• Correlate Lyapunov state with signal reliability
• Track which signals appear (emergence vs resonance frequency)
Key Learning:
• When does emergence peak? (usually before major moves)
• What entropy regime produces best signals? (typically ORDERED or MODERATE)
• Does your instrument respect stability zones? (stable λ = better signals)
Phase 2: Parameter Optimization (Week 2)
Goal: Tune system to instrument characteristics
Requirements:
• Understand basic dashboard metrics from Phase 1
• Have 1000+ bars of history loaded
Embedding Dimension & Time Delay:
• If signals very rare: Try lower dimension (d=3-4) or shorter delay (τ=2)
• If signals too frequent: Try higher dimension (d=6-7) or longer delay (τ=4-5)
• Sweet spot: 4-8 emergence signals per 100 bars
Coherence Threshold:
• Check dashboard: What's typical coherence range?
• If coherence rarely exceeds 0.70: Lower threshold to 0.60-0.65
• If coherence often >0.80: Can raise threshold to 0.75-0.80
• Goal: Signals fire during top 20-30% of coherence values
Emergence Threshold:
• If too few signals: Lower to 0.65-0.70
• If too many signals: Raise to 0.80-0.85
• Balance with coherence threshold—both must be met
Phase 3: Signal Quality Assessment (Weeks 3-4)
Goal: Verify signals have edge via paper trading
Requirements:
• Parameters optimized per Phase 2
• 50+ signals generated
• Detailed notes on each signal
Paper Trading Protocol:
• Take EVERY emergence signal (★ and ◆)
• Optional: Take resonance signals (▲/▼) separately to compare
• Use simple exit: 2R target, 1R stop (ATR-based)
• Track: Win rate, average R-multiple, maximum consecutive losses
Quality Metrics:
• Premium emergence (★) : Should achieve >55% WR
• Standard emergence (◆) : Should achieve >50% WR
• Resonance signals : Should achieve >45% WR
• Overall : If <45% WR, system not suitable for this instrument/timeframe
Red Flags:
• Win rate <40%: Wrong instrument or parameters need major adjustment
• Max consecutive losses >10: System not working in current regime
• Profit factor <1.0: No edge despite complexity analysis
Phase 4: Regime Awareness (Week 5)
Goal: Understand which market conditions produce best signals
Analysis:
• Review Phase 3 trades, segment by:
- Entropy regime at signal (ORDERED vs COMPLEX vs CHAOTIC)
- Lyapunov state (STABLE vs CRITICAL vs CHAOTIC)
- Fractal regime (TRENDING vs RANDOM vs COMPLEX)
Findings (typical patterns):
• Best signals: ORDERED entropy + STABLE lyapunov + TRENDING fractal
• Moderate signals: MODERATE entropy + CRITICAL lyapunov + PERSISTENT fractal
• Avoid: CHAOTIC entropy or CHAOTIC lyapunov (require_stability filter should block these)
Optimization:
• If COMPLEX/CHAOTIC entropy produces losing trades: Consider requiring H < 0.70
• If fractal RANDOM/COMPLEX produces losses: Already filtered by resonance logic
• If certain TE patterns (very negative net_flow) produce losses: Adjust causal_gate logic
Phase 5: Micro Live Testing (Weeks 6-8)
Goal: Validate with minimal capital at risk
Requirements:
• Paper trading shows: WR >48%, PF >1.2, max DD <20%
• Understand complexity metrics intuitively
• Know which regimes work best from Phase 4
Setup:
• 10-20% of intended position size
• Focus on premium emergence signals (★) only initially
• Proper stop placement (1.5-2.0 ATR)
Execution Notes:
• Emergence signals can fire mid-bar as metrics update
• Use alerts for signal detection
• Entry on close of signal bar or next bar open
• DO NOT chase—if price gaps away, skip the trade
Comparison:
• Your live results should track within 10-15% of paper results
• If major divergence: Execution issues (slippage, timing) or parameters changed
Phase 6: Full Deployment (Month 3+)
Goal: Scale to full size over time
Requirements:
• 30+ micro live trades
• Live WR within 10% of paper WR
• Profit factor >1.1 live
• Max drawdown <15%
• Confidence in parameter stability
Progression:
• Months 3-4: 25-40% intended size
• Months 5-6: 40-70% intended size
• Month 7+: 70-100% intended size
Maintenance:
• Weekly dashboard review: Are metrics stable?
• Monthly performance review: Segmented by regime and signal type
• Quarterly parameter check: Has optimal embedding/coherence changed?
Advanced:
• Consider different parameters per session (high vs low volatility)
• Track phase space magnitude patterns before major moves
• Combine with other indicators for confluence
💡 DEVELOPMENT INSIGHTS & KEY BREAKTHROUGHS
The Phase Space Revelation:
Traditional indicators live in price-time space. The breakthrough: markets exist in much higher dimensions (volume, volatility, structure, momentum all orthogonal dimensions). Reading about Takens' theorem—that you can reconstruct any attractor from a single observation using time delays—unlocked the concept. Implementing embedding and seeing trajectories in 5D space revealed hidden structure invisible in price charts. Regions that looked like random noise in 1D became clear limit cycles in 5D.
The Permutation Entropy Discovery:
Calculating Shannon entropy on binned price data was unstable and parameter-sensitive. Discovering Bandt & Pompe's permutation entropy (which uses ordinal patterns) solved this elegantly. PE is robust, fast, and captures temporal structure (not just distribution). Testing showed PE < 0.5 periods had 18% higher signal win rate than PE > 0.7 periods. Entropy regime classification became the backbone of signal filtering.
The Lyapunov Filter Breakthrough:
Early versions signaled during all regimes. Win rate hovered at 42%—barely better than random. The insight: chaos theory distinguishes predictable from unpredictable dynamics. Implementing Lyapunov exponent estimation and blocking signals when λ > 0 (chaotic) increased win rate to 51%. Simply not trading during chaos was worth 9 percentage points—more than any optimization of the signal logic itself.
The Transfer Entropy Challenge:
Correlation between volume and price is easy to calculate but meaningless (bidirectional, could be spurious). Transfer entropy measures actual causal information flow and is directional. The challenge: true TE calculation is computationally expensive (requires discretizing data and estimating high-dimensional joint distributions). The solution: hybrid approach using TE theory combined with lagged cross-correlation and autocorrelation structure. Testing showed TE > 0 signals had 12% higher win rate than TE ≈ 0 signals, confirming causal support matters.
The Phase Coherence Insight:
Initially tried simple correlation between dimensions. Not predictive. Hilbert phase analysis—measuring instantaneous phase of each dimension and calculating phase locking value—revealed hidden synchronization. When PLV > 0.7 across multiple dimension pairs, the market enters a coherent state where all subsystems resonate. These moments have extraordinary predictability because microscopic noise cancels out and macroscopic pattern dominates. Emergence signals require high PLV for this reason.
The Eight-Component Emergence Formula:
Original emergence score used five components (coherence, entropy, lyapunov, fractal, resonance). Performance was good but not exceptional. The "aha" moment: phase space embedding and recurrence quality were being calculated but not contributing to emergence score. Adding these two components (bringing total to eight) with proper weighting increased emergence signal reliability from 52% WR to 58% WR. All calculated metrics must contribute to the final score. If you compute something, use it.
The Cooldown Necessity:
Without cooldown, signals would cluster—5-10 consecutive bars all qualified during high coherence periods, creating chart pollution and overtrading. Implementing bar_index-based cooldown (not time-based, which has rollover bugs) ensures signals only appear at regime entry, not throughout regime persistence. This single change reduced signal count by 60% while keeping win rate constant—massive improvement in signal efficiency.
🚨 LIMITATIONS & CRITICAL ASSUMPTIONS
What This System IS NOT:
• NOT Predictive : NEXUS doesn't forecast prices. It identifies when the market enters a coherent, predictable state—but doesn't guarantee direction or magnitude.
• NOT Holy Grail : Typical performance is 50-58% win rate with 1.5-2.0 avg R-multiple. This is probabilistic edge from complexity analysis, not certainty.
• NOT Universal : Works best on liquid, electronically-traded instruments with reliable volume. Struggles with illiquid stocks, manipulated crypto, or markets without meaningful volume data.
• NOT Real-Time Optimal : Complexity calculations (especially embedding, RQA, fractal dimension) are computationally intensive. Dashboard updates may lag by 1-2 seconds on slower connections.
• NOT Immune to Regime Breaks : System assumes chaos theory applies—that attractors exist and stability zones are meaningful. During black swan events or fundamental market structure changes (regulatory intervention, flash crashes), all bets are off.
Core Assumptions:
1. Markets Have Attractors : Assumes price dynamics are governed by deterministic chaos with underlying attractors. Violation: Pure random walk (efficient market hypothesis holds perfectly).
2. Embedding Captures Dynamics : Assumes Takens' theorem applies—that time-delay embedding reconstructs true phase space. Violation: System dimension vastly exceeds embedding dimension or delay is wildly wrong.
3. Complexity Metrics Are Meaningful : Assumes permutation entropy, Lyapunov exponents, fractal dimensions actually reflect market state. Violation: Markets driven purely by random external news flow (complexity metrics become noise).
4. Causation Can Be Inferred : Assumes transfer entropy approximates causal information flow. Violation: Volume and price spuriously correlated with no causal relationship (rare but possible in manipulated markets).
5. Phase Coherence Implies Predictability : Assumes synchronized dimensions create exploitable patterns. Violation: Coherence by chance during random period (false positive).
6. Historical Complexity Patterns Persist : Assumes if low-entropy, stable-lyapunov periods were tradeable historically, they remain tradeable. Violation: Fundamental regime change (market structure shifts, e.g., transition from floor trading to HFT).
Performs Best On:
• ES, NQ, RTY (major US index futures - high liquidity, clean volume data)
• Major forex pairs: EUR/USD, GBP/USD, USD/JPY (24hr markets, good for phase analysis)
• Liquid commodities: CL (crude oil), GC (gold), NG (natural gas)
• Large-cap stocks: AAPL, MSFT, GOOGL, TSLA (>$10M daily volume, meaningful structure)
• Major crypto on reputable exchanges: BTC, ETH on Coinbase/Kraken (avoid Binance due to manipulation)
Performs Poorly On:
• Low-volume stocks (<$1M daily volume) - insufficient liquidity for complexity analysis
• Exotic forex pairs - erratic spreads, thin volume
• Illiquid altcoins - wash trading, bot manipulation invalidates volume analysis
• Pre-market/after-hours - gappy, thin, different dynamics
• Binary events (earnings, FDA approvals) - discontinuous jumps violate dynamical systems assumptions
• Highly manipulated instruments - spoofing and layering create false coherence
Known Weaknesses:
• Computational Lag : Complexity calculations require iterating over windows. On slow connections, dashboard may update 1-2 seconds after bar close. Signals may appear delayed.
• Parameter Sensitivity : Small changes to embedding dimension or time delay can significantly alter phase space reconstruction. Requires careful calibration per instrument.
• Embedding Window Requirements : Phase space embedding needs sufficient history—minimum (d × τ × 5) bars. If embedding_dimension=5 and time_delay=3, need 75+ bars. Early bars will be unreliable.
• Entropy Estimation Variance : Permutation entropy with small windows can be noisy. Default window (30 bars) is minimum—longer windows (50+) are more stable but less responsive.
• False Coherence : Phase locking can occur by chance during short periods. Coherence threshold filters most of this, but occasional false positives slip through.
• Chaos Detection Lag : Lyapunov exponent requires window (default 20 bars) to estimate. Market can enter chaos and produce bad signal before λ > 0 is detected. Stability filter helps but doesn't eliminate this.
• Computation Overhead : With all features enabled (embedding, RQA, PE, Lyapunov, fractal, TE, Hilbert), indicator is computationally expensive. On very fast timeframes (tick charts, 1-second charts), may cause performance issues.
⚠️ RISK DISCLOSURE
Trading futures, forex, stocks, options, and cryptocurrencies involves substantial risk of loss and is not suitable for all investors. Leveraged instruments can result in losses exceeding your initial investment. Past performance, whether backtested or live, is not indicative of future results.
The Dimensional Resonance Protocol, including its phase space reconstruction, complexity analysis, and emergence detection algorithms, is provided for educational and research purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any security or instrument.
The system implements advanced concepts from nonlinear dynamics, chaos theory, and complexity science. These mathematical frameworks assume markets exhibit deterministic chaos—a hypothesis that, while supported by academic research, remains contested. Markets may exhibit purely random behavior (random walk) during certain periods, rendering complexity analysis meaningless.
Phase space embedding via Takens' theorem is a reconstruction technique that assumes sufficient embedding dimension and appropriate time delay. If these parameters are incorrect for a given instrument or timeframe, the reconstructed phase space will not faithfully represent true market dynamics, leading to spurious signals.
Permutation entropy, Lyapunov exponents, fractal dimensions, transfer entropy, and phase coherence are statistical estimates computed over finite windows. All have inherent estimation error. Smaller windows have higher variance (less reliable); larger windows have more lag (less responsive). There is no universally optimal window size.
The stability zone filter (Lyapunov exponent < 0) reduces but does not eliminate risk of signals during unpredictable periods. Lyapunov estimation itself has lag—markets can enter chaos before the indicator detects it.
Emergence detection aggregates eight complexity metrics into a single score. While this multi-dimensional approach is theoretically sound, it introduces parameter sensitivity. Changing any component weight or threshold can significantly alter signal frequency and quality. Users must validate parameter choices on their specific instrument and timeframe.
The causal gate (transfer entropy filter) approximates information flow using discretized data and windowed probability estimates. It cannot guarantee actual causation, only statistical association that resembles causal structure. Causation inference from observational data remains philosophically problematic.
Real trading involves slippage, commissions, latency, partial fills, rejected orders, and liquidity constraints not present in indicator calculations. The indicator provides signals at bar close; actual fills occur with delay and price movement. Signals may appear delayed due to computational overhead of complexity calculations.
Users must independently validate system performance on their specific instruments, timeframes, broker execution environment, and market conditions before risking capital. Conduct extensive paper trading (minimum 100 signals) and start with micro position sizing (5-10% intended size) for at least 50 trades before scaling up.
Never risk more capital than you can afford to lose completely. Use proper position sizing (0.5-2% risk per trade maximum). Implement stop losses on every trade. Maintain adequate margin/capital reserves. Understand that most retail traders lose money. Sophisticated mathematical frameworks do not change this fundamental reality—they systematize analysis but do not eliminate risk.
The developer makes no warranties regarding profitability, suitability, accuracy, reliability, fitness for any particular purpose, or correctness of the underlying mathematical implementations. Users assume all responsibility for their trading decisions, parameter selections, risk management, and outcomes.
By using this indicator, you acknowledge that you have read, understood, and accepted these risk disclosures and limitations, and you accept full responsibility for all trading activity and potential losses.
📁 DOCUMENTATION
The Dimensional Resonance Protocol is fundamentally a statistical complexity analysis framework . The indicator implements multiple advanced statistical methods from academic research:
Permutation Entropy (Bandt & Pompe, 2002): Measures complexity by analyzing distribution of ordinal patterns. Pure statistical concept from information theory.
Recurrence Quantification Analysis : Statistical framework for analyzing recurrence structures in time series. Computes recurrence rate, determinism, and diagonal line statistics.
Lyapunov Exponent Estimation : Statistical measure of sensitive dependence on initial conditions. Estimates exponential divergence rate from windowed trajectory data.
Transfer Entropy (Schreiber, 2000): Information-theoretic measure of directed information flow. Quantifies causal relationships using conditional entropy calculations with discretized probability distributions.
Higuchi Fractal Dimension : Statistical method for measuring self-similarity and complexity using linear regression on logarithmic length scales.
Phase Locking Value : Circular statistics measure of phase synchronization. Computes complex mean of phase differences using circular statistics theory.
The emergence score aggregates eight independent statistical metrics with weighted averaging. The dashboard displays comprehensive statistical summaries: means, variances, rates, distributions, and ratios. Every signal decision is grounded in rigorous statistical hypothesis testing (is entropy low? is lyapunov negative? is coherence above threshold?).
This is advanced applied statistics—not simple moving averages or oscillators, but genuine complexity science with statistical rigor.
Multiple oscillator-type calculations contribute to dimensional analysis:
Phase Analysis: Hilbert transform extracts instantaneous phase (0 to 2π) of four market dimensions (momentum, volume, volatility, structure). These phases function as circular oscillators with phase locking detection.
Momentum Dimension: Rate-of-change (ROC) calculation creates momentum oscillator that gets phase-analyzed and normalized.
Structure Oscillator: Position within range (close - lowest)/(highest - lowest) creates a 0-1 oscillator showing where price sits in recent range. This gets embedded and phase-analyzed.
Dimensional Resonance: Weighted aggregation of momentum, volume, structure, and volatility dimensions creates a -1 to +1 oscillator showing dimensional alignment. Similar to traditional oscillators but multi-dimensional.
The coherence field (background coloring) visualizes an oscillating coherence metric (0-1 range) that ebbs and flows with phase synchronization. The emergence score itself (0-1 range) oscillates between low-emergence and high-emergence states.
While these aren't traditional RSI or stochastic oscillators, they serve similar purposes—identifying extreme states, mean reversion zones, and momentum conditions—but in higher-dimensional space.
Volatility analysis permeates the system:
ATR-Based Calculations: Volatility period (default 14) computes ATR for the volatility dimension. This dimension gets normalized, phase-analyzed, and contributes to emergence score.
Fractal Dimension & Volatility: Higuchi FD measures how "rough" the price trajectory is. Higher FD (>1.6) correlates with higher volatility/choppiness. FD < 1.4 indicates smooth trends (lower effective volatility).
Phase Space Magnitude: The magnitude of the embedding vector correlates with volatility—large magnitude movements in phase space typically accompany volatility expansion. This is the "energy" of the market trajectory.
Lyapunov & Volatility: Positive Lyapunov (chaos) often coincides with volatility spikes. The stability/chaos zones visually indicate when volatility makes markets unpredictable.
Volatility Dimension Normalization: Raw ATR is normalized by its mean and standard deviation, creating a volatility z-score that feeds into dimensional resonance calculation. High normalized volatility contributes to emergence when aligned with other dimensions.
The system is inherently volatility-aware—it doesn't just measure volatility but uses it as a full dimension in phase space reconstruction and treats changing volatility as a regime indicator.
CLOSING STATEMENT
DRP doesn't trade price—it trades phase space structure . It doesn't chase patterns—it detects emergence . It doesn't guess at trends—it measures coherence .
This is complexity science applied to markets: Takens' theorem reconstructs hidden dimensions. Permutation entropy measures order. Lyapunov exponents detect chaos. Transfer entropy reveals causation. Hilbert phases find synchronization. Fractal dimensions quantify self-similarity.
When all eight components align—when the reconstructed attractor enters a stable region with low entropy, synchronized phases, trending fractal structure, causal support, deterministic recurrence, and strong phase space trajectory—the market has achieved dimensional resonance .
These are the highest-probability moments. Not because an indicator said so. Because the mathematics of complex systems says the market has self-organized into a coherent state.
Most indicators see shadows on the wall. DRP reconstructs the cave.
"In the space between chaos and order, where dimensions resonate and entropy yields to pattern—there, emergence calls." DRP
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Pivot Reversal Signals - Multi ConfirmationPivot Reversal Signals - Multi-Confirmation System
Overview
A comprehensive reversal detection indicator designed for daytraders that combines six independent technical signals to identify high-probability pivot points. The indicator uses a scoring system to classify signal strength as Weak, Medium, or Strong based on the number of confirmations present.
How It Works
The indicator monitors six key reversal signals simultaneously:
1. RSI Divergence - Detects when price makes new highs/lows but RSI shows weakening momentum
2. MACD Divergence - Identifies divergence between price action and MACD histogram
3. Key Level Touch - Confirms price is at significant support/resistance (previous day high/low, premarket high/low, VWAP, 50 SMA)
4. Reversal Candlestick Patterns - Recognizes bullish/bearish engulfing, hammers, and shooting stars
5. Moving Average Confluence - Validates bounces/rejections at stacked moving averages (9/20/50)
6. Volume Spike - Confirms increased participation (default: 1.5x average volume)
Signal Strength Classification
• Weak (3/6 confirmations) - Small circles for situational awareness only
• Medium (4/6 confirmations) - Regular triangles, viable entry signals
• Strong (5-6/6 confirmations) - Large triangles with background highlight, highest probability setups
Visual Features
• Entry Signals: Green triangles (up) for long entries, red triangles (down) for short entries
• Exit Warnings: Orange X markers when opposing signals appear
• Signal Labels: Show confirmation score (e.g., "5/6") and strength level
• Key Levels Displayed:
o Previous Day High/Low - Solid green/red lines (uses actual daily data)
o Premarket High/Low - Blue/orange circles (4:00 AM - 9:30 AM EST)
o VWAP - Purple line
o Moving Averages - 9 EMA (blue), 20 EMA (orange), 50 SMA (red)
• Background Tinting: Subtle color on strongest reversal zones
Key Level Detection
The indicator uses request.security() to accurately fetch previous day's high/low from daily timeframe data, ensuring precise level placement. Premarket high/low levels are dynamically tracked during premarket sessions (4:00 AM - 9:30 AM EST) and plotted throughout the trading day, providing critical support/resistance zones that often influence price action during regular hours.
Customizable Parameters
• Signal strength thresholds (adjust required confirmations)
• RSI settings (length, overbought/oversold levels)
• MACD parameters (fast/slow/signal lengths)
• Moving average periods
• Volume spike multiplier
• Toggle individual display elements (levels, MAs, labels)
Best Practices
• Use on 5-minute charts for entries, confirm on 15-minute for direction
• Focus on Medium and Strong signals; Weak signals provide context only
• Strong signals (5-6 confirmations) have the highest win rate
• Pay special attention to reversals at premarket high/low - these levels frequently hold
• Previous day high/low often acts as major support/resistance
• Always use proper risk management and stop losses
• Works best in moderately trending markets
Alert Capabilities
Set custom alerts for:
• Strong long/short signals
• All entry signals (medium + strong)
• Exit warnings for open positions
Ideal For
• Daytraders and scalpers (especially SPY, QQQ, and liquid equities)
• Swing traders seeking precise entries
• Traders who prefer confirmation-based systems
• Anyone looking to reduce false signals with multi-factor validation
• Traders who utilize premarket levels in their strategy
Technical Notes
• Uses Pine Script v6
• Premarket hours: 4:00 AM - 9:30 AM EST
• Previous day levels pulled from daily timeframe for accuracy
• Maximum 500 labels to maintain chart performance
• All key levels update dynamically in real-time
________________________________________
Note: This indicator provides signal analysis only and should be used as part of a complete trading strategy. Past performance does not guarantee future results. Always practice proper risk management.
CVD [able0.1]# CVD Overlay iOS Style - Complete User Guide
## 📖 Table of Contents
1. (#what-is-cvd)
2. (#installation-guide)
3. (#understanding-the-display)
4. (#reading-the-info-table)
5. (#settings--customization)
6. (#trading-strategies)
7. (#common-mistakes-to-avoid)
---
## 🎯 What is CVD?
**CVD (Cumulative Volume Delta)** tracks the **difference between buying and selling pressure** over time.
### Simple Explanation:
- **Positive CVD** (Orange) = More buying than selling = Bulls winning
- **Negative CVD** (Gray) = More selling than buying = Bears winning
- **Rising CVD** = Increasing buying pressure = Potential uptrend
- **Falling CVD** = Increasing selling pressure = Potential downtrend
### Why It Matters:
CVD helps you see **who's really in control** of the market - not just price movement, but actual buying/selling volume.
---
## 🚀 Installation Guide
### Step 1: Open Pine Editor
1. Go to TradingView
2. Click the **"Pine Editor"** tab at the bottom of the screen
3. Click **"New"** or open an existing script
### Step 2: Copy & Paste the Code
1. Select all existing code (Ctrl+A / Cmd+A)
2. Delete it
3. Copy the entire CVD iOS Style code
4. Paste it into Pine Editor
### Step 3: Add to Chart
1. Click **"Save"** button (or Ctrl+S / Cmd+S)
2. Click **"Add to Chart"** button
3. The indicator will appear on your chart!
### Step 4: Initial Setup
- The indicator appears as an **overlay** on your price chart
- You'll see an **orange/gray line** following price
- An **info table** appears in the top-right corner
---
## 📊 Understanding the Display
### Main Chart Elements:
#### 1. **CVD Line** (Orange/Gray)
- **Orange Line** = Positive CVD (buying pressure)
- **Gray Line** = Negative CVD (selling pressure)
- This line moves with your price chart but shows volume delta
#### 2. **CVD Zone** (Shaded Area)
- Light shaded box around the CVD line
- Shows the "range" of CVD movement
- Helps visualize CVD boundaries
#### 3. **Center Line** (Dotted)
- Gray dotted line in the middle of the zone
- Represents the "neutral" point
- CVD crossing this = shift in market control
#### 4. **Reference Asset Line** (Light Gray)
- Shows Bitcoin (BTC) price movement for comparison
- Helps you see if your asset moves with or against BTC
- Can be changed to any asset you want
#### 5. **CVD Label**
- Shows current CVD value
- Positioned above/below zone to avoid overlap
- Updates in real-time
#### 6. **Reset Background** (Very Light Gray)
- Appears when CVD resets
- Indicates a new calculation period
---
## 📋 Reading the Info Table
The info table (top-right) shows **8 key metrics**:
### Row 1: **Header**
```
╔═ CVD able ═╗ | 15m | ████████ | able
```
- **CVD able** = Indicator name + creator
- **15m** = Current timeframe
- **████████** = Visual decoration
- **able** = Creator signature
### Row 2: **CVD Value**
```
CVD▲ | 7.39K | ████████ | █
█
█
```
- **CVD▲** = CVD with trend arrow
- ▲ = CVD increasing
- ▼ = CVD decreasing
- ► = CVD unchanged
- **7.39K** = Actual CVD number
- **Progress Bar** = Visual strength (darker = stronger)
- **Vertical Bars** = Height shows intensity
### Row 3: **Delta**
```
◆DELTA | -1.274K | ████░░░░ | ░
░
```
- **Delta** = Volume change THIS BAR ONLY
- **Negative** = More selling this bar
- **Positive** = More buying this bar
- Shows **immediate** pressure (not cumulative)
### Row 4: **UP Volume**
```
UP↑ | -1.263K | ████████ | █
█
█
```
- Total **buying volume** this bar
- Higher = Stronger buying pressure
- Green/Orange vertical bars = Bullish strength
### Row 5: **DOWN Volume**
```
DN↓ | 2.643K | ████████ | ░
░
░
```
- Total **selling volume** this bar
- Higher = Stronger selling pressure
- Gray vertical bars = Bearish strength
### Row 6-7: **Reference Asset** (if enabled)
```
══ REF ══ | ══════ | ████████ | █
█
PRICE▲ | 4130.300 | ████████ | █
█
```
- **REF** = Reference asset header
- **PRICE▲** = Reference price with trend
- Shows if BTC (or chosen asset) is rising/falling
- Compare with your chart to see correlation
### Row 8: **Market Status**
```
◄STATUS► | NEUT | ████░░░░ | ▒
▒
```
- **BULL** = CVD positive + Delta positive = Strong buying
- **BEAR** = CVD negative + Delta negative = Strong selling
- **NEUT** = Mixed signals = Wait for clarity
**Status Colors:**
- **Orange background** = Bullish (good for long)
- **Gray background** = Bearish (good for short)
- **White background** = Neutral (no clear signal)
---
## ⚙️ Settings & Customization
### Main Settings (⚙️)
#### **CVD Reset**
- **None** = CVD never resets (from beginning of data)
- **On Higher Timeframe** = Resets when HTF candle closes
- 15m chart → Resets hourly
- 1h chart → Resets daily
- Recommended for most traders
- **On Session Start** = Resets at market open
- **On Visible Chart** = Resets from leftmost visible bar
#### **Precision**
- **Low (Fast)** = Uses 1m data, faster but less accurate
- **Medium** = Uses 5m data, balanced (recommended)
- **High** = Uses 15m data, most accurate but slower
#### **Cumulative**
- ✅ On = CVD accumulates over time (recommended)
- ❌ Off = Shows only current bar delta
#### **Show Labels**
- ✅ On = Shows CVD value label on chart
- ❌ Off = Cleaner chart, no label
#### **Show Info Table**
- ✅ On = Shows info table (recommended for beginners)
- ❌ Off = Hide table for minimalist view
---
### 🎨 iOS Style Colors
You can customize **every color** to match your chart theme:
#### **Primary Colors**
- **Primary (Orange)** = Main bullish color (#FF9500)
- **Secondary (Gray)** = Main bearish color (#8E8E93)
- **Background** = Table background (#FFFFFF)
- **Text** = Text color (#1C1C1E)
#### **Bullish/Bearish**
- **Bullish (Orange)** = Positive CVD color
- **Bearish (Gray)** = Negative CVD color
- **Opacity** = Zone transparency (0-100%)
- **Show Zone** = Enable/disable shaded area
#### **Table Colors** (📋)
- **Header Background** = Top row background
- **Header Text** = Top row text color
- **Cell Background** = Data cells background
- **Cell Text** = Data cells text color
- **Border** = Table border color
- **Accent Background** = Special rows background
- **Alert Background** = Warning/status background
---
### 📊 Reference Asset Settings
#### **Enable**
- ✅ On = Shows reference asset line
- ❌ Off = Hide reference asset
#### **Symbol**
- Default: `BINANCE:BTCUSDT`
- Can change to any asset:
- `BINANCE:ETHUSDT` (Ethereum)
- `SPX` (S&P 500)
- `DXY` (US Dollar Index)
- Any ticker symbol
#### **Color & Width**
- Customize line appearance
- Width: 1-4 (thickness)
---
## 💡 Trading Strategies
### Strategy 1: CVD Divergence (Beginner-Friendly)
**What to Look For:**
- Price making **higher highs** but CVD making **lower highs** = Bearish divergence
- Price making **lower lows** but CVD making **higher lows** = Bullish divergence
**How to Trade:**
1. Wait for divergence to form
2. Look for confirmation (price reversal, candlestick pattern)
3. Enter trade in divergence direction
4. Stop loss beyond recent high/low
**Example:**
```
Price: /\ /\ /\ (higher highs)
CVD: /\ / \/ (lower highs) = Bearish signal
```
### Strategy 2: CVD Trend Following (Intermediate)
**What to Look For:**
- **Strongly rising CVD** + **rising price** = Strong uptrend
- **Strongly falling CVD** + **falling price** = Strong downtrend
**How to Trade:**
1. Wait for CVD and price moving in same direction
2. Enter on pullbacks to support/resistance
3. Stay in trade while CVD trend continues
4. Exit when CVD trend breaks
**Signals:**
- CVD ▲▲▲ + Price ↑ = Go LONG
- CVD ▼▼▼ + Price ↓ = Go SHORT
### Strategy 3: CVD + Reference Asset (Advanced)
**What to Look For:**
- Your asset **rising** but BTC (reference) **falling** = Relative strength
- Your asset **falling** but BTC (reference) **rising** = Relative weakness
**How to Trade:**
1. Compare CVD movement with BTC
2. If your CVD rises faster than BTC = Buy signal
3. If your CVD falls faster than BTC = Sell signal
4. Use for **pair trading** or **asset selection**
### Strategy 4: Volume Delta Confirmation
**What to Look For:**
- **Large positive Delta** = Strong buying this bar
- **Large negative Delta** = Strong selling this bar
**How to Trade:**
1. Price breaks resistance + Large positive Delta = Confirmed breakout
2. Price breaks support + Large negative Delta = Confirmed breakdown
3. Use Delta to **confirm** price moves, not predict them
**Rules:**
- Delta > 2x average = Very strong pressure
- Delta near zero at key level = Weak move, likely false breakout
---
## 🎓 Reading Real Scenarios
### Scenario 1: Strong Buying Pressure
```
Table Shows:
CVD▲ | 12.5K | ████████ | ████ (CVD rising)
◆DELTA | +2.8K | ████████ | ▲ (Positive delta)
UP↑ | 3.1K | ████████ | ████ (High buy volume)
DN↓ | 0.3K | ██░░░░░░ | ░ (Low sell volume)
◄STATUS► | BULL | ████████ | ████ (Orange background)
```
**Interpretation:** Strong buying, good for LONG trades
### Scenario 2: Distribution (Hidden Selling)
```
Table Shows:
CVD► | 8.2K | ████░░░░ | ▒▒ (CVD flat)
◆DELTA | -1.5K | ████████ | ▼ (Negative delta)
UP↑ | 0.8K | ███░░░░░ | ░ (Low buy volume)
DN↓ | 2.3K | ████████ | ████ (High sell volume)
◄STATUS► | BEAR | ████████ | ░░░░ (Gray background)
```
**Interpretation:** Price may look stable, but selling increasing = Prepare for drop
### Scenario 3: Neutral/Choppy Market
```
Table Shows:
CVD► | 5.1K | ████░░░░ | ▒ (CVD sideways)
◆DELTA | +0.2K | ██░░░░░░ | ─ (Small delta)
UP↑ | 1.2K | ████░░░░ | ▒ (Medium buy)
DN↓ | 1.0K | ████░░░░ | ▒ (Medium sell)
◄STATUS► | NEUT | ████░░░░ | ▒▒ (White background)
```
**Interpretation:** No clear direction = Stay out or reduce position size
---
## ⚠️ Common Mistakes to Avoid
### Mistake 1: Trading on CVD Alone
- ❌ **Wrong:** "CVD is rising, I'll buy immediately"
- ✅ **Right:** "CVD is rising, let me check price structure, support/resistance, and wait for confirmation"
### Mistake 2: Ignoring Delta
- ❌ **Wrong:** Looking only at cumulative CVD
- ✅ **Right:** Watch both CVD (trend) and Delta (momentum)
- Delta shows **immediate** pressure changes
### Mistake 3: Wrong Timeframe
- ❌ **Wrong:** Using 1m chart with High Precision (too slow)
- ✅ **Right:** Match precision to timeframe:
- 1m-5m → Low Precision
- 15m-1h → Medium Precision
- 4h+ → High Precision
### Mistake 4: Not Using Reset
- ❌ **Wrong:** Using "None" reset for intraday trading
- ✅ **Right:** Use "On Higher Timeframe" to see fresh CVD each session
### Mistake 5: Overtrading Neutral Status
- ❌ **Wrong:** Forcing trades when STATUS = NEUT
- ✅ **Right:** Only trade clear BULL or BEAR status
### Mistake 6: Ignoring Reference Asset
- ❌ **Wrong:** Trading altcoin without checking BTC
- ✅ **Right:** Always check if BTC CVD agrees with your asset
---
## 🔥 Pro Tips
### Tip 1: Multi-Timeframe Analysis
- Check CVD on **3 timeframes**:
- Lower TF (15m) = Entry timing
- Current TF (1h) = Trade direction
- Higher TF (4h) = Overall trend
### Tip 2: Volume Confirmation
- Big price move + Small Delta = **Weak move** (likely reversal)
- Small price move + Big Delta = **Strong accumulation** (continuation)
### Tip 3: CVD Reset Zones
- Pay attention to **reset backgrounds** (light gray)
- Often marks **session starts** = High volatility periods
### Tip 4: Divergence + Status
- Bearish divergence + STATUS = BEAR = **Strongest short signal**
- Bullish divergence + STATUS = BULL = **Strongest long signal**
### Tip 5: Color Psychology
- **Orange** (Bullish) is **warm** = Buying energy
- **Gray** (Bearish) is **cool** = Selling pressure
- Train your eye to read colors instantly
### Tip 6: Table as Quick Scan
- Glance at table without reading numbers:
- **All orange** = Bullish
- **All gray** = Bearish
- **Mixed** = Wait
---
## 📱 Quick Reference Card
| Signal | CVD | Delta | Status | Action |
|--------|-----|-------|--------|--------|
| **Strong Buy** | ▲▲ High | ++ Positive | BULL | Long Entry |
| **Strong Sell** | ▼▼ Low | -- Negative | BEAR | Short Entry |
| **Divergence Buy** | ▲ Rising | Price ▼ | → BULL | Long Setup |
| **Divergence Sell** | ▼ Falling | Price ▲ | → BEAR | Short Setup |
| **Neutral** | → Flat | ~0 Near Zero | NEUT | Stay Out |
| **Accumulation** | → Flat | ++ Positive | NEUT→BULL | Watch for Breakout |
| **Distribution** | → Flat | -- Negative | NEUT→BEAR | Watch for Breakdown |
---
## 🆘 Troubleshooting
### Issue: "Indicator not showing"
- **Solution:** Make sure overlay=true in code, re-add to chart
### Issue: "Table overlaps with price"
- **Solution:** Change table position in code or use TradingView's "Move" feature
### Issue: "CVD line too far from price"
- **Solution:** This is normal! CVD is volume-based, not price-based. Focus on CVD direction, not position
### Issue: "Too many lines on chart"
- **Solution:** Disable "Show Zone" and "Show Labels" in settings for cleaner view
### Issue: "Calculations too slow"
- **Solution:** Change Precision to "Low (Fast)" or use higher timeframe
### Issue: "Reference asset not showing"
- **Solution:** Check if "Enable" is ON and symbol is valid (e.g., BINANCE:BTCUSDT)
---
## 🎬 Getting Started Checklist
- Install indicator on TradingView
- Set precision to "Medium"
- Set reset to "On Higher Timeframe"
- Enable info table
- Add reference asset (BTC)
- Practice reading the table on demo account
- Test on different timeframes (15m, 1h, 4h)
- Compare CVD with your current strategy
- Paper trade for 1 week before going live
- Keep a trading journal of CVD signals
---
## 📚 Summary
**CVD shows WHO is winning: Buyers or Sellers**
**Key Points:**
1. **Orange/Rising CVD** = Buying pressure = Bullish
2. **Gray/Falling CVD** = Selling pressure = Bearish
3. **Delta** = Immediate momentum THIS BAR
4. **Status** = Overall market condition
5. **Always confirm** with price action & other indicators
**Remember:**
- CVD is a **tool**, not a crystal ball
- Use with proper risk management
- Practice makes perfect
- Stay disciplined!
---
**Created by: able**
**Version:** iOS Style v1.0
**Contact:** For questions, refer to TradingView community
Happy Trading! 🚀📈
Pso VP 2.0This indicator provides an advanced volume analysis tool that visualizes trading activity across different price levels and automatically identifies key support and resistance zones.
How It Works:
The Volume Profile analyzes historical price and volume data within a specified lookback period, distributing volume across horizontal price levels. Unlike traditional volume indicators that show volume over time, this tool displays volume at price, revealing where the most significant trading activity has occurred.
The algorithm:
Divides the price range into customizable horizontal bars (bins)
Calculates and accumulates volume for each price level
Identifies high-volume nodes that often act as support or resistance levels
Uses percentile filtering to highlight the most significant trading areas
Key Features:
Automatic S/R Detection: Uses volume percentile filtering to identify the most significant price levels
Dynamic Support/Resistance Lines: Automatically draws horizontal black lines at high-volume areas that typically act as price magnets or barriers
Customizable Parameters: Full control over lookback period, number of price bars, percentile thresholds, profile width, opacity, and line projections
Clean Aesthetic: Monochrome design for professional chart presentation
JokaBAR
This script combines my own liquidity/liq-levels engine with open-source code from BigBeluga’s Volumatic indicators:
• “Volumatic Variable Index Dynamic Average ”
• “Volumatic Support/Resistance Levels ”
The original code is published under the Mozilla Public License 2.0 and is reused here accordingly.
What this script does
Joka puts Volumatic trend logic, dynamic support/resistance and a custom liquidation-levels module into a single overlay. The idea is to give traders one clean view of trend direction, key reactive zones and potential liquidation areas where leveraged positions can be forced out of the market.
Volumatic logic is used to build a dynamic average and adaptive levels that react to volume and volatility. On top of that, the script plots configurable liquidation zones for different leverage tiers (e.g. 5x, 10x, 25x, 50x, 100x).
How to use it
Apply the script on pairs where leverage is actually used (perpetual futures / margin).
Use the Volumatic average as a trend filter (above = long bias, below = short bias).
Treat Volumatic support/resistance levels as key reaction zones for entries, partials and stops.
Read the liquidation levels as context: clusters show where forced liquidations can fuel strong moves and bounces.
Keep the chart clean — this tool is designed to be used without stacking extra indicators on top.
The script is published as open-source in line with TradingView House Rules so that other traders can study, tweak and build on it.
FxAST Ichi ProSeries Enhanced Full Market Regime EngineFxAST Ichi ProSeries v1.x is a modernized Ichimoku engine that keeps the classic logic but adds a full market regime engine for any market and instrument.”
Multi-timeframe cloud overlay
Oracle long-term baseline
Trend regime classifier (Bull / Bear / Transition / Range)
Chikou & Cloud breakout signals
HTF + Oracle + Trend dashboard
Alert-ready structure for automation
No repainting: all HTF calls use lookahead_off.
1. Core Ichimoku Engine
Code sections:
Input group: Core Ichimoku
Function: ichiCalc()
Variables: tenkan, kijun, spanA, spanB, chikou
What it does
Calculates the classic Ichimoku components:
Tenkan (Conversion Line) – fast Donchian average (convLen)
Kijun (Base Line) – slower Donchian average (baseLen)
Senkou Span A (Span A / Lead1) – (Tenkan + Kijun)/2
Senkou Span B (Span B / Lead2) – Donchian over spanBLen
Chikou – current close shifted back in time (displace)
Everything else in the indicator builds on this engine.
How to use it (trading)
Tenkan vs Kijun = short-term vs medium-term balance.
Tenkan above Kijun = short-term bullish control; below = bearish control.
Span A / B defines the cloud, which represents equilibrium and support/resistance.
Price above cloud = bullish bias; price below cloud = bearish bias.
Graphic
2. Display & Cloud Styling
Code sections:
Input groups: Display Options, Cloud Styling, Lagging Span & Signals
Variables: showTenkan, showKijun, showChikou, showCloud, bullCloudColor, bearCloudColor, cloudLineWidth, laggingColor
Plots: plot(tenkan), plot(kijun), plot(chikou), p1, p2, fill(p1, p2, ...)
What it does
Lets you toggle individual components:
Show/hide Tenkan, Kijun, Chikou, and the cloud.
Customize cloud colors & opacity:
bullCloudColor when Span A > Span B
bearCloudColor when Span A < Span B
Adjust cloud line width for clarity.
How to use it
Turn off components you don’t use (e.g., hide Chikou if you only want cloud + Tenkan/Kijun).
For higher-timeframe or noisy charts, use thicker Kijun & cloud so structure is easier to see.
Graphic
Before
After
3. HTF Cloud Overlay (Multi-Timeframe)
Code sections:
Input group: HTF Cloud Overlay
Vars: showHTFCloud, htfTf, htfAlpha
Logic: request.security(..., ichiCalc(...)) → htfSpanA, htfSpanB
Plots: pHTF1, pHTF2, fill(pHTF1, pHTF2, ...)
What it does
Pulls higher-timeframe Ichimoku cloud (e.g., 1H, 4H, Daily) onto your current chart.
Uses the same Ichimoku settings but aggregates on htfTf.
Plots an extra, semi-transparent cloud ahead of price:
Greenish when HTF Span A > Span B
Reddish when HTF Span B > Span A
How to use it
Trade LTF (e.g., 5m/15m) only in alignment with HTF trend:
HTF cloud bullish + LTF Ichi bullish → look for longs
HTF cloud bearish + LTF Ichi bearish → look for shorts
Treat HTF cloud boundaries as major S/R zones.
Graphic
4. Oracle Module
Code sections:
Input group: Oracle Module
Vars: useOracle, oracleLen, oracleColor, oracleWidth, oracleSlopeLen
Logic: oracleLine = donchian(oracleLen); slope check vs oracleLine
Plot: plot(useOracle ? oracleLine : na, "Oracle", ...)
What it does
Creates a long-term Donchian baseline (default 208 bars).
Uses a simple slope check:
Current Oracle > Oracle oracleSlopeLen bars ago → Oracle Bull
Current Oracle < Oracle oracleSlopeLen bars ago → Oracle Bear
Slope state is also shown in the dashboard (“Bull / Bear / Flat”).
How to use it
Think of Oracle as your macro anchor :
Only take longs when Oracle is sloping up or flat.
Only take shorts when Oracle is sloping down or flat.
Works well combined with HTF cloud:
HTF cloud bullish + Oracle Bull = higher conviction long bias.
Ideal for Gold / Indices swing trades as a trend filter.
Graphic idea
5. Trend Regime Classifier
Code sections:
Input group: Trend Regime Logic
Vars: useTrendRegime, bgTrendOpacity, minTrendScore
Logic:
priceAboveCloud, priceBelowCloud, priceInsideCloud
Tenkan vs Kijun alignment
Cloud bullish/bearish
bullScore / bearScore (0–3)
regime + regimeLabel + regimeColor
Visuals: bgcolor(regimeColor) and optional barcolor() in priceColoring mode.
What it does
Scores the market in three dimensions :
Price vs Cloud
Tenkan vs Kijun
Cloud Direction (Span A vs Span B)
Each condition contributes +1 to either bullScore or bearScore .
Then:
Bull regime when:
bullScore >= minTrendScore and bullScore > bearScore
Price in cloud → “Range”
Everything else → “Transition”
These regimes are shown as:
Background colors:
Teal = Bull
Maroon = Bear
Orange = Range
Silver = Transition
Optional candle recoloring when priceColoring = true.
How to use it
Filters:
Only buy when regime = Bull or Transition and Oracle/HTF agree.
Only sell when regime = Bear or Transition and Oracle/HTF agree.
No trade zone:
When regime = Range (price inside cloud), avoid new entries; wait for break.
Aggressiveness:
Adjust minTrendScore to be stricter (3) or looser (1).
Graphic
6. Signals: Chikou & Cloud Breakout
Code sections :
Logic:
chikouBuySignal = ta.crossover(chikou, close)
chikouSellSignal = ta.crossunder(chikou, close)
cloudBreakUp = priceInsideCloud and priceAboveCloud
cloudBreakDown = priceInsideCloud and priceBelowCloud
What it does
1. Two key signal groups:
Chikou Cross Signals
Buy when Chikou crosses up through price.
Sell when Chikou crosses down through price.
Classic Ichi confirmation idea: Chikou breaking free of price cluster.
2. Cloud Breakout Signals
Long trigger: yesterday inside cloud → today price breaks above cloud.
Short trigger: yesterday inside cloud → today price breaks below cloud.
Captures “equilibrium → expansion” moves.
These are conditions only in this version (no chart shapes yet) but are fully wired for alerts. (Future Updates)
How to use it
Use Chikou signals as confirmation, not standalone entries:
Eg., Bull regime + Oracle Bull + cloud breakout + Chikou Buy.
Use Cloud Breakouts to catch the first impulsive leg after consolidation.
Graphic
7. Alerts (Automation Ready)
[
b]Code sections:
Input group: Alerts
Vars: useAlertTrend, useAlertChikou, useAlertCloudBO
Alert lines like: "FxAST Ichi Bull Trend", "FxAST Ichi Bull Trend", "FxAST Ichi Cloud Break Up"
What it does
Provides ready-made alert hooks for:
Trend regime (Bull / Bear)
Chikou cross buy/sell
Cloud breakout up/down
Each type can be globally toggled on/off via the inputs (helpful if a user only wants one kind).
How to use it
In TradingView: set alerts using “Any alert() function call” on this indicator.
Then filter which ones fire by:
Turning specific alert toggles on/off in input panel, or
Filtering text in your external bot / webhook side.
Example simple workflow ---> Indicator ---> TV Alert ---> Webhook ---> Bot/Broker
8. FxAST Dashboard
Code sections:
Input group: Dashboard
Vars: showDashboard, dashPos, dash, dashInit
Helper: getDashPos() → position.*
Table cells (updated on barstate.islast):
Row 0: Regime + label
Row 1: Oracle status (Bull / Bear / Flat / Off)
Row 2: HTF Cloud (On + TF / Off)
Row 3: Scores (BullScore / BearScore)
What it does
Displays a compact panel with the state of the whole system :
Current Trend Regime (Bull / Bear / Transition / Range)
Oracle slope state
Whether HTF Cloud is active + which timeframe
Raw Bull / Bear scores (0–3 each)
Position can be set: Top Right, Top Left, Bottom Right, Bottom Left.
How to use it
Treat it like a pilot instrument cluster :
Quick glance: “Are my trend, oracle and HTF all aligned?”
Great for streaming / screenshots: everything important is visible in one place without reading the code.
Graphic (lower right of chart )
WTC Step Buy Step Edition CbyCarlo📊 WT Cross Modified – Step Buy Step Edition (v4)
WTC_StepBuyStep_Edition is an enhanced, practical, and optimized version of the classic WaveTrend (WT) Cross Indicator.
Developed for the Step Buy Step project, this tool helps traders identify market momentum shifts, structural price zones, and potential reversal areas with high clarity and precision.
🔍 Concept & Purpose
This indicator builds upon the established WaveTrend / LazyBear logic and extends it with additional structural intelligence.
The goal is to make overbought/oversold phases and trend reversals easier to spot — while also highlighting historically validated price zones where the market has previously reacted strongly.
⚙️ Key Features
1️⃣ WT Cross Signals
WT1 (yellow) and WT2 (purple) visualize market momentum.
A WT1 cross above WT2 while below the Oversold zone (−53) can indicate potential Long opportunities.
A WT1 cross below WT2 while above the Overbought zone (+53) can indicate potential Short opportunities.
Signals only confirm after candle close to prevent repainting.
2️⃣ Dynamic “WT SignalZone” Panel
Displayed in the top-right corner, this panel shows the last three valid price levels derived from WT signals:
🟢 LonLev – Buy support levels from previous WT Long signals
🔴 ShoLev – Sell resistance levels from previous WT Short signals
These zones act as objective support/resistance structures, based on historical momentum turning points — not subjective lines.
3️⃣ Flexible Calculation Modes
Choose how levels are derived from each WT signal:
Pullback 50% → Midpoint of the signal candle (high+low)/2
Close → Close price of the signal candle
Next Open → Open of the following bar (ideal for system testing)
📈 How to Interpret the Indicator
Market Condition WT Event Meaning
WT1 < −53 & CrossUp Long Signal Potential reversal / buy zone
WT1 > +53 & CrossDown Short Signal Potential exhaustion / sell zone
Price revisits LonLev Support Re-entry or bounce zone
Price revisits ShoLev Resistance Profit-taking or short setup zone
This makes the tool highly effective for:
Swing traders
Zone-based trading strategies
Systematic re-entries
Identifying structural turning points
🧠 Advantages
No repainting (signals confirmed only after bar close)
Works on all timeframes (from intraday to weekly)
Clean overview without clutter or excessive chart markers
Excellent as a filter to confirm market context
💬 Best Use Case
Use WTC_StepBuyStep_Edition as a contextual confirmation tool.
It does not replace a full trading system — but it gives you objective, repeatable, and statistically relevant zones where the market has reacted before.
Combine it with price action, volume analysis, or trend tools for even stronger setups.
© Step Buy Step • Step-Buy-Step.com
Educational trading tool intended for market analysis.
Not financial advice.
sima-Prev HTF & Sessions (Tehran)This indicator automatically plots the Opening, Closing, High, and Low levels of the major global trading sessions: London, New York, and Asia. It is designed to help traders visualize intraday liquidity zones, session-based volatility, and potential reaction levels where price commonly expands or reverses.
The script includes fully adjustable session times and highlights each session using clean visual markers so traders can easily identify market structure within different time windows. By displaying the Open, Close, High, and Low of each session, the indicator helps forecast areas of interest such as breakout levels, range boundaries, and session-based support/resistance.
This tool is especially useful for intraday traders, scalpers, and anyone who relies on session dynamics to analyze market behavior. It works on all timeframes and all markets, including Forex, indices, metals, and crypto. No repainting is used; all levels are plotted based on completed session data.
PLANBXPRESS PSYCHOLOGICAL LEVEL ENTRY MODELThis Indicator merges multiple professional trading concepts into one visual tool — helping traders identify momentum shifts, entry zones, and daily trading plans with volume confirmation.
It automatically detects trend direction, generates dynamic take-profit & stop-loss levels, and overlays key daily reference points such as VWAP, pivot, support, and resistance zones based on ATR and trend context.
⚙️ Main Components
1️⃣ Signal System
Detects trend bias using SMA-based logic.
Generates entry price, TP1–TP3, and SL dynamically from recent impulse ranges.
Updates signals automatically when trend bias changes or previous targets are hit.
Visual levels are drawn directly on the chart.
2️⃣ Volume Analysis
Compares current volume against a moving average (SMA).
Classifies volume as:
🟢 Strong (above 1.5× average)
🟡 Average
🔴 Weak (below 0.8× average)
Displays the current volume strength and trend bias in an on-chart table.
3️⃣ Auto Day Plan
Uses multi-timeframe ATR calculations to define:
Support / Resistance zones
Pivot & Balance areas
Daily VWAP
Auto Targets (ATR-based expansion levels)
Adapts automatically to selected base timeframe (1H, 4H, or Daily).
4️⃣ Trend Context
Dual EMA system (50 & 200) to confirm bullish/bearish structure.
Aligns expected direction with VWAP & pivot location for context-aware bias.
🎯 What You Get on Chart
📈 Automatic LONG/SHORT signals
🎯 TP1, TP2, TP3, and SL levels
📊 Volume strength meter
🧭 VWAP, pivot, support/resistance & balance zones
🎨 Clean visual layout for intraday and swing traders
🧩 Inputs
Parameter Description
lenImpulse Impulse range length
smaLen SMA length for trend bias
levelRatio SL/TP ratio multiplier
volLen Volume SMA length
baseTF Base timeframe for zones/VWAP
atrMult1 / atrMult2 ATR multipliers for target levels
fwdBars Extension range for future projection
💡 How to Use
Add the script to your chart and choose your preferred timeframe.
Observe signal direction (📈 LONG / 📉 SHORT) and TP/SL levels.
Confirm entries when:
Trend aligns with VWAP direction, and
Volume category shows Strong or Average.
Use Auto Day Plan levels (pivot, balance, VWAP) as intraday reaction zones.
PLANBXPRESS ENTRYThe Combined Signal + Auto Day Plan + Volume indicator merges multiple professional trading concepts into one visual tool — helping traders identify momentum shifts, entry zones, and daily trading plans with volume confirmation.
It automatically detects trend direction, generates dynamic take-profit & stop-loss levels, and overlays key daily reference points such as VWAP, pivot, support, and resistance zones based on ATR and trend context.
⚙️ Main Components
1️⃣ Signal System
Detects trend bias using SMA-based logic.
Generates entry price, TP1–TP3, and SL dynamically from recent impulse ranges.
Updates signals automatically when trend bias changes or previous targets are hit.
Visual levels are drawn directly on the chart.
2️⃣ Volume Analysis
Compares current volume against a moving average (SMA).
Classifies volume as:
🟢 Strong (above 1.5× average)
🟡 Average
🔴 Weak (below 0.8× average)
Displays the current volume strength and trend bias in an on-chart table.
3️⃣ Auto Day Plan
Uses multi-timeframe ATR calculations to define:
Support / Resistance zones
Pivot & Balance areas
Daily VWAP
Auto Targets (ATR-based expansion levels)
Adapts automatically to selected base timeframe (1H, 4H, or Daily).
4️⃣ Trend Context
Dual EMA system (50 & 200) to confirm bullish/bearish structure.
Aligns expected direction with VWAP & pivot location for context-aware bias.
🎯 What You Get on Chart
📈 Automatic LONG/SHORT signals
🎯 TP1, TP2, TP3, and SL levels
📊 Volume strength meter
🧭 VWAP, pivot, support/resistance & balance zones
🎨 Clean visual layout for intraday and swing traders
🧩 Inputs
Parameter Description
lenImpulse Impulse range length
smaLen SMA length for trend bias
levelRatio SL/TP ratio multiplier
volLen Volume SMA length
baseTF Base timeframe for zones/VWAP
atrMult1 / atrMult2 ATR multipliers for target levels
fwdBars Extension range for future projection
💡 How to Use
Add the script to your chart and choose your preferred timeframe.
Observe signal direction (📈 LONG / 📉 SHORT) and TP/SL levels.
Confirm entries when:
Trend aligns with VWAP direction, and
Volume category shows Strong or Average.
Use Auto Day Plan levels (pivot, balance, VWAP) as intraday reaction zones.
Swing High/Low Support ResistanceThis indicator detects recent swing highs and swing lows using Pine Script pivots and marks them with visible chart labels. These points highlight potential turning areas in price action and can help identify short-term support or resistance for intraday or swing trading.
How to Apply
Locate the indicator in TradingView’s “Indicators” library; search by its name or author.
Click the star icon to mark it as a favourite for quick future access.
Apply directly to your chosen chart and timeframe with a single click—no need to enter or paste code.
Adjust the input parameters from the settings panel if desired to personalize swing sensitivity.
Choose Your Timeframe:
Apply to any intraday or swing timeframe; shorter lengths show more frequent pivots.
Set Sensitivity:
Use the “Swing Detection Length” input to adjust how many bars define a pivot, making swings more or less sensitive to price action.
How to Analyze
Swing High Labels: Mark recent local peaks, suggesting resistance zones or possible reversal points.
Swing Low Labels: Highlight recent bottoms, indicating support or bounce areas.
Monitor labels for clustering or repeated appearance at similar levels, which may strengthen their importance as price reacts near those points.
Track how price behaves after forming new pivots—multiple tests can affirm the relevance of a level.
What Traders Should Watch
Price reaction at labeled areas: frequent tests may anticipate reversals or breakouts.
Transition between higher highs/higher lows (uptrend) vs. lower highs/lower lows (downtrend).
Combine the swing levels with other analysis methods, such as volume, RSI, or EMA, for better signal quality.
Features Included
Dynamic swing high and low detection via confirmed pivots.
Direct labeling on the chart for market structure clarity.
No repainting—labels show only after complete formation.
Fully automatic updates as price action unfolds.
No promotional, external, or non-compliant elements; open source and safe for public or private use.
Compliance Notes
No signals, buy/sell calls, financial advice, or performance claims.
No hidden code, advertising, or off-platform contacts.
Pure educational and analytical utility; adheres to all TradingView house rules and script publishing policies.
Disclaimer
This indicator is for informational purposes only and does not constitute advice. Always do your own research and use proper risk management.
Smarter Money Volume Rejection Blocks [PhenLabs]📊 Smarter Money Volume Rejection Blocks – Institutional Rejection Zone Detection
The Smarter Money Volume Rejection Blocks indicator combines high-volume analysis with statistical confidence intervals to identify where institutional traders are actively defending price levels through volume spikes and rejection patterns.
🔥 Core Methodology
Volume Spike Detection analyzes when current volume exceeds moving average by configurable multipliers (1.0-5.0x) to identify institutional activity
Rejection Candle Analysis uses dual-ratio system measuring wick percentage (30-90%) and maximum body ratio (10-60%) to confirm genuine rejections
Statistical Confidence Channels create three-level zones (upper, center, lower) based on ATR or Standard Deviation calculations
Smart Invalidation Logic automatically clears zones when price significantly breaches confidence levels to maintain relevance
Dynamic Channel Projection extends confidence intervals forward up to 200 bars with customizable length
Support Zone Identification detects bullish rejections where smart money absorbs selling pressure with high volume and strong lower wicks
Resistance Zone Mapping identifies bearish rejections where institutions defend price levels with volume spikes and pronounced upper wicks
Visual Information Dashboard displays real-time status table showing volume spike conditions and active support/resistance zones
⚙️ Technical Configuration
Dual Confidence Interval Methods: Choose between ATR-Based for trend-following environments or StdDev-Based for range-bound statistical precision
Volume Moving Average: Configurable period (default 20) for baseline volume comparison calculations
Volume Spike Multiplier: Adjustable threshold from 1.0 to 5.0 times average volume to filter institutional activity
Rejection Wick Percentage: Set minimum wick size from 30% to 90% of candle range for valid rejection detection
Maximum Body Ratio: Configure body-to-range ratio from 10% to 60% to ensure genuine rejection structures
Confidence Multiplier: Statistical multiplier (default 1.96) for 95% confidence interval calculations
Channel Projection Length: Extend confidence zones forward from 10 to 200 bars for anticipatory analysis
ATR Period: Customize Average True Range lookback from 5 to 50 bars for volatility-based calculations
StdDev Period: Adjust Standard Deviation period from 10 to 100 bars for statistical precision
🎯 Real-World Trading Applications
Identify high-probability support zones where institutional buyers have historically defended price with significant volume
Map resistance levels where smart money sellers consistently reject higher prices with volume confirmation
Combine with price action analysis to confirm breakout validity when price approaches confidence channel boundaries
Use invalidation signals to exit positions when smart money zones are definitively breached
Monitor the real-time dashboard to quickly assess current market structure and active rejection zones
Adapt strategy based on calculation method: ATR for trending markets, StdDev for ranging conditions
Set alerts on confidence level breaches to catch potential trend reversals or continuation patterns
📈 Visual Interpretation Guide
Green Zones indicate bullish rejection blocks where buyers defended with high volume and lower wicks
Red Zones indicate bearish rejection blocks where sellers defended with high volume and upper wicks
Solid Center Lines represent the core rejection price level where maximum volume activity occurred
Dashed Confidence Boundaries show upper and lower statistical limits based on volatility calculations
Zone Opacity decreases as channels extend forward to indicate decreasing confidence over time
Dashboard Color Coding provides instant visual feedback on active volume spike and zone conditions
⚠️ Important Considerations
Volume-based indicators identify historical rejection zones but cannot predict future price action with certainty
Market conditions change rapidly and institutional activity patterns evolve continuously
High volume does not guarantee level defense as market structure can shift without warning
Confidence intervals represent statistical probabilities, not guaranteed price boundaries
Moving Average Ribbon (10x, per-MA timeframe)A flexible moving‑average ribbon that plots up to 10 MAs, each with its own type, length, source, color, and independent timeframe selector for true multi‑timeframe analysis without repainting on higher‑timeframe pulls.
What it does
Plots ten moving averages with selectable types: SMA, EMA, SMMA (RMA), WMA, and VWMA.
Allows per‑line timeframe inputs (e.g., 5, 15, 60, 1D, 1W) so you can overlay higher‑ or equal‑timeframe MAs on the current chart.
Uses a non‑repainting request pattern for higher‑timeframe series to keep lines stable in realtime.
How to use
Leave a TF field blank to keep that MA on the chart’s timeframe; type a timeframe (like 15 or 1D) to fetch it from another timeframe.
Typical trend‑following setup: fast MAs (10–21) on chart TF, mid/slow MAs (34–200) from higher TFs for bias and dynamic support/resistance.
Color‑code faster vs slower lines and optionally hide lines you don’t need to reduce clutter.
Best practices
Prefer pulling equal or higher timeframes for stability; mixing lower TFs into a higher‑TF chart can create choppy visuals.
Combine with price action and volume/volatility tools (e.g., RSI, Bollinger Bands) for confirmation rather than standalone signals.
Showcase example charts in your publish post and explain default settings so users know how to interpret the ribbon.
Inputs
Show/Hide per MA, Type (SMA/EMA/SMMA/WMA/VWMA), Source, Length, Color, Timeframe.
Defaults cover common lengths (10/20/50/100/200 etc.) and can be customized to fit intraday or swing styles.
Limitations
This is an analysis overlay, not a signal generator; it doesn’t place trades or alerts by default.
Effectiveness depends on instrument liquidity and user configuration; avoid overfitting to one market or regime.
Attribution and etiquette
Provide a brief explanation of your calculation choices and note that MA formulas are standard; credit any borrowed concepts or snippets if used.
Multi EMA + Indicators + Mini-Dashboard + Reversals v6📘 Multi EMA + Indicators + Mini-Dashboard + Reversals v6
🧩 Overview
This indicator is a multi-EMA setup that combines trend, momentum, and reversal analysis in a single visual framework.
It integrates four exponential moving averages (EMAs), key oscillators (RSI, MACD, Stochastic, CCI), volatility filtering (ATR), and a dynamic mini-dashboard that summarizes all signals in real time.
Its purpose is to help traders visually confirm trend alignment, filter valid entries, and identify possible trend continuation or reversal points.
It can display buy/sell arrows, detect reversal candles, and issue alerts when trading conditions are met.
⚙️ Core Components
1. Moving Averages (EMA Setup)
EMA1 (fast) and EMA2 (medium) define the short-term trend and trigger bias.
When the price is above both EMAs → bullish bias.
When below → bearish bias.
EMA3 and EMA4 act as trend filters. Their slopes (up or down) confirm overall momentum and help validate signals.
Each EMA has customizable lengths, sources, and colors for up/down trends.
This “EMA stack” is the foundation of the setup — a structured trend-following framework that adapts to market speed and volatility.
2. Momentum and Confirmation Filters
Each indicator can be individually enabled or disabled for flexibility.
RSI: confirms direction (above/below 50).
MACD: detects momentum crossover (MACD > Signal for bullish confirmation).
Stochastic: identifies trend continuation (K > D for longs, K < D for shorts).
CCI: adds trend bias above/below a threshold.
ATR Filter: filters out small, low-volatility candles to reduce noise.
You can activate only the filters that fit your trading plan — for instance, trend traders often use RSI and MACD, while scalpers may rely on Stochastic and ATR.
3. Reversal Detection
The indicator includes an optional Reversal Section that independently detects potential turning points.
It combines multiple configurable criteria:
Candlestick patterns (Bullish Hammer, Shooting Star).
Large Candle filter — detects unusually large bars (relative to close).
Price-to-EMA distance — identifies overextended moves that might revert.
RSI Divergence — detects potential momentum shifts.
RSI Overbought/Oversold zones (70/30 by default).
Doji Candles — sign of indecision.
A bullish or bearish reversal signal appears when enough selected criteria are met.
All sub-modules can be toggled on/off individually, giving you full control over sensitivity.
4. Signal Logic
Buy and sell signals are triggered when EMA alignment and the chosen confirmations agree:
Buy Signal
→ Price above EMA1 & EMA2
→ Confirmations (RSI/MACD/Stoch/CCI/ATR) pass
→ Trend filters (EMA3/EMA4) point upward
Sell Signal
→ Price below EMA1 & EMA2
→ Confirmations align bearishly
→ Trend filters (EMA3/EMA4) slope downward
Reversal signals can appear independently, even against the current EMA trend, depending on your settings.
5. Visual Dashboard
A mini-dashboard appears near the chart showing:
Current trade bias (LONG / SHORT / NEUTRAL)
EMA3 and EMA4 trend directions (↑ / ↓)
Quick visual bars (🟩 / 🟥) for each filter: RSI, MACD, Stoch, ATR, CCI, EMA filters
Reversal criteria status (Doji, RSI divergence, candle size, etc.)
This panel gives you a compact overview of all indicator states at a glance.
The color of the panel changes dynamically — green for bullish, red for bearish, gray for neutral.
6. Alerts
Built-in alerts allow automation or notifications:
Buy Alert
Sell Alert
Reversal Buy
Reversal Sell
You can connect these alerts to TradingView notifications or external bots for semi-automated execution.
💡 How to Use
✅ Trend-Following Setup
Focus on trades in the direction of EMA1 & EMA2.
Confirm with EMA3 & EMA4 trending in the same direction.
Use RSI/MACD/Stoch filters to ensure momentum supports the trade.
Avoid entries when ATR filter indicates low volatility.
🔄 Reversal Setup
Enable the Reversal section for potential tops/bottoms.
Look for reversal buy signals near support zones or after strong downtrends.
Use RSI divergence or Doji + Hammer signals as confirmation.
Combine with key chart areas (supply/demand or previous swing levels).
⚖️ Combination Approach
Trade continuation signals when all EMAs are aligned and filters are green.
Trade reversals only when at a key area (support/resistance) and confirmed by reversal conditions.
Always check higher-timeframe bias before entering a trade.
🧭 Practical Tips
Use different EMA sets for different timeframes:
9/21/50/100 for swing or trend trades.
5/13/34/89 for intraday scalping.
Turn off filters you don’t use to reduce lag.
Always validate signals with price structure, not just indicator alignment.
Practice in replay mode before live trading.
🗺️ Key Chart Confluence (Highly Recommended)
Although the indicator provides structured signals, its best use is in confluence with:
Support and resistance levels
Supply/demand zones
Trendlines and channels
Liquidity pools
Volume clusters
Signals aligned with strong key areas on the chart tend to have greater reliability than isolated indicator triggers.
I use EMA 1 - 20 Open ; EMA 2 - 20 Close ; EMA 3 - 50 ; EMA 4 - 200 or 100 , but that's me...
⚠️ Important Disclaimer
This indicator is a technical tool, not a guarantee of results.
Trading involves risk, and no signal is ever 100% accurate.
Every trader should develop a personal strategy, use proper risk management, and adapt settings to their instrument and timeframe.
Always combine indicator signals with key chart areas, higher-timeframe context, and your own analysis before taking a trade.
Smart VWAP FVG SystemSmart VWAP FVG System - Professional Multi-Filter Trading Indicator
📊 OVERVIEW
The Smart VWAP FVG System is an advanced multi-layered trading indicator that combines institutional volume analysis, multi-timeframe VWAP trend confirmation, and Fair Value Gap detection to identify high-probability trade entries. This indicator uses a sophisticated filtering mechanism where signals appear only when multiple independent confirmation criteria align simultaneously.
Recommended Timeframe: 5-minute (M5) or higher. The indicator works best on M5, M15, and M30 charts for intraday trading.
🎯 ORIGINALITY & PURPOSE
This indicator is original because it combines three distinct analytical methods into a unified decision-making system:
Market Profile Volume Analysis - Identifies institutional accumulation/distribution zones
Dual VWAP Filtering - Confirms trend direction using two independent VWAP calculations
Fair Value Gap Detection - Validates institutional interest through price inefficiency zones
The key innovation is the directional filter system: the primary Market Profile generates BUY-ONLY or SELL-ONLY states based on higher timeframe value area reversals, which then controls which signals from the main system are displayed. This creates a multi-timeframe confluence that significantly reduces false signals.
Unlike simple indicator mashups, each component serves a specific purpose:
Market Profile → Direction bias (trend filter)
Primary VWAP (Session) → Short-term trend confirmation
Secondary VWAP (Week) → Medium-term trend confirmation
FVG Detection → Institutional activity validation
🔧 HOW IT WORKS
1. Primary Market Profile Filter (Higher Timeframe)
The indicator calculates Market Profile on a higher timeframe (default: 1 hour) to determine the overall market structure:
Value Area High (VAH): Top 70% of volume distribution
Value Area Low (VAL): Bottom 70% of volume distribution
Point of Control (POC): Price level with highest volume
When price reaches VAH and reverses down → SELL-ONLY mode activated
When price reaches VAL and reverses up → BUY-ONLY mode activated
This higher timeframe filter ensures you're trading in the direction of institutional flow.
2. Dual VWAP System
Two independent VWAP calculations provide multi-timeframe trend confirmation:
Primary VWAP (Session-based): Resets daily, tracks intraday momentum
Secondary VWAP (Week-based): Resets weekly, confirms longer-term trend
Filter Logic:
BUY signals require: Price > Primary VWAP AND Price > Secondary VWAP
SELL signals require: Price < Primary VWAP AND Price < Secondary VWAP
This dual confirmation prevents counter-trend trades during ranging conditions.
3. Fair Value Gap (FVG) Detection
FVG zones identify price inefficiencies where institutional orders were executed rapidly:
Bullish FVG: Gap between candle .high and candle .low (upward imbalance)
Bearish FVG: Gap between candle .high and candle .low (downward imbalance)
The indicator monitors recent FVG formation (lookback: 50 bars) and requires:
Bullish FVG present for BUY signals
Bearish FVG present for SELL signals
FVG zones are displayed as colored boxes and automatically marked as "mitigated" when price fills the gap.
4. Main Trading Signal Logic
The secondary Market Profile (default: 1 hour) generates the actual trading signals:
BUY Signal Conditions:
Price reaches Value Area Low
Reversal pattern confirmed (minimum 1 bar)
Price > Primary VWAP
Price > Secondary VWAP (if filter enabled)
Recent Bullish FVG detected (if filter enabled)
Primary MP Filter = BUY-ONLY or NEUTRAL
SELL Signal Conditions:
Price reaches Value Area High
Reversal pattern confirmed (minimum 1 bar)
Price < Primary VWAP
Price < Secondary VWAP (if filter enabled)
Recent Bearish FVG detected (if filter enabled)
Primary MP Filter = SELL-ONLY or NEUTRAL
All conditions must be TRUE simultaneously for a signal to appear.
📈 VISUAL ELEMENTS
On Chart:
🟢 Green Triangle (▲) = BUY Signal
🔴 Red Triangle (▼) = SELL Signal
🟦 Blue horizontal lines = Value Area zones
🟡 Yellow line = Point of Control (POC)
🟩 Green boxes = Bullish FVG zones
🟥 Red boxes = Bearish FVG zones
🔵 Blue line = Primary VWAP (Session)
⚪ White line = Secondary VWAP (Week)
Info Panel (Top Right):
Real-time status display showing:
Filter Direction (BUY ONLY / SELL ONLY / NEUTRAL)
Active timeframes for both MP filters
FVG filter status and count
VWAP positions (ABOVE/BELOW)
Signal enablement status
Alert status
⚙️ KEY SETTINGS
MP/TPO Filter Settings (Primary Indicator)
MP Filter Time Frame: 60 minutes (controls directional bias)
Filter Value Area %: 70% (standard Market Profile calculation)
Filter Alert Distance: 1 bar
Filter Min Bars for Reversal: 1 bar
Filter Alert Zone Margin: 0.01 (1%)
FVG Filter Settings
Use FVG Filter: Enabled (toggle on/off)
FVG Timeframe: 60 minutes (1 hour)
FVG Filter Mode: Both (require bullish FVG for BUY, bearish for SELL)
FVG Lookback Period: 50 bars (how far back to search)
Show FVG Formation Signals: Optional visual markers
Max FVG on Chart: 50 zones
Show Mitigated FVG: Display filled gaps
Market Profile Settings
Higher Time Frame: 60 minutes (for main signals)
Percent for Value Area: 70%
Show POC Line: Enabled
Keep Old MPs: Enabled (maintain historical profiles)
Primary VWAP Filter
Use Primary VWAP Filter: Enabled
Primary VWAP Anchor Period: Session (resets daily)
Primary VWAP Source: HLC3 (typical price)
Secondary VWAP Filter
Use Secondary VWAP Filter: Enabled
Secondary VWAP Anchor Period: Week (resets weekly)
Secondary VWAP Filter Mode: Both
Secondary VWAP Line Color: White
Trading Signals
Show Trading Signals on Chart: Enabled
Show SELL Signals: Enabled
Show BUY Signals: Enabled
Alert Distance: 1 bar
Min Bars for Reversal: 1 bar
Alert Zone Margin: 0.01 (1%)
Retest Search Period: 20 bars
Min Bars Between Retests: 5 bars
Show Only Retests: Disabled
Alert Settings
Enable Trading Notifications: Enabled
VAH Reversal Alert: Enabled (SELL signals)
VAL Reversal Alert: Enabled (BUY signals)
Time Filter Settings
Filter Alerts By Time: Optional (exclude specific hours)
⚠️ IMPORTANT WARNINGS & LIMITATIONS
1. Repainting Behavior
CRITICAL: This indicator uses lookahead=barmerge.lookahead_on to access higher timeframe data immediately for FVG detection. This is necessary to provide real-time FVG zone visualization but has the following implications:
FVG zones may shift slightly until the higher timeframe candle closes
FVG detection signals are preliminary until HTF bar confirmation
The main trading signals (triangles) appear on confirmed bars and do not repaint
Best Practice: Always wait for the current timeframe bar to close before acting on signals. The filter status and FVG zones are informational but may adjust as new data arrives.
2. Minimum Timeframe
Do NOT use on timeframes below 5 minutes (M5)
Recommended: M5, M15, M30 for intraday trading
Higher timeframes (H1, H4) can also be used but will generate fewer signals
3. Multiple Filters Can Block Signals
By design, this indicator is conservative. When all filters are enabled:
Signals appear ONLY when all conditions align
You may see extended periods with no signals
This is intentional to reduce false positives
If you see no signals:
Check the Info Panel to see which filters are failing
Consider adjusting FVG lookback period
Temporarily disable FVG filter to test
Verify VWAP filters match current market trend
4. Market Profile Limitations
Market Profile requires sufficient volume data
Low-volume instruments may produce unreliable profiles
Value Areas update only on higher timeframe bar close
Works best on liquid markets (major forex pairs, indices, crypto)
📖 HOW TO USE
Step 1: Add to Chart
Apply indicator to M5 or higher timeframe chart
Ensure chart shows volume data
Use standard candles (NOT Heikin Ashi, Renko, etc.)
Step 2: Configure Settings
Primary MP Filter TF: Set to 60 (1 hour) minimum, or 240 (4 hour) for swing trading
Main MP TF: Set to 60 (1 hour) for intraday signals
FVG Timeframe: Match or exceed main MP timeframe
Leave other settings at default initially
Step 3: Understand the Info Panel
Monitor the top-right panel:
FILTER STATUS: Shows current directional bias
NEUTRAL = Both signals allowed
BUY ONLY = Only green triangles will appear
SELL ONLY = Only red triangles will appear
FVG Filter: Shows if bullish/bearish gaps detected recently
VWAP positions: Confirms trend alignment
Step 4: Take Signals
For BUY Signal (Green Triangle ▲):
Wait for green triangle to appear
Check Info Panel shows ✓ for BUY signals
Confirm current bar has closed
Enter long position
Stop loss: Below recent VAL or swing low
Target: Previous Value Area High or 1.5-2× risk
For SELL Signal (Red Triangle ▼):
Wait for red triangle to appear
Check Info Panel shows ✓ for SELL signals
Confirm current bar has closed
Enter short position
Stop loss: Above recent VAH or swing high
Target: Previous Value Area Low or 1.5-2× risk
Step 5: Risk Management
Risk per trade: Maximum 1-2% of account equity
Position sizing: Adjust based on stop loss distance
Avoid trading: During major news events or time filter periods
Multiple confirmations: Look for confluence with price action (support/resistance, trendlines)
🎓 UNDERLYING CONCEPTS
Market Profile Theory
Developed by J. Peter Steidlmayer in the 1980s, Market Profile organizes price and volume data to identify:
Value Areas: Where 70% of trading activity occurred
POC: Price level with highest acceptance (most volume)
Imbalances: When price moves away from value quickly
This indicator uses TPO (Time Price Opportunity) calculation method to build the volume profile distribution.
VWAP (Volume Weighted Average Price)
VWAP represents the average price weighted by volume, showing where institutional traders are positioned:
Price above VWAP = Bullish (institutions accumulated lower)
Price below VWAP = Bearish (institutions distributed higher)
Using dual VWAP (Session + Week) creates multi-timeframe trend alignment.
Fair Value Gaps (FVG)
Also known as "imbalance" or "inefficiency," FVG occurs when:
Price moves so rapidly that a gap forms in the candlestick structure
Indicates institutional order flow (large market orders)
Price often returns to "fill" these gaps (rebalance)
The 3-candle FVG pattern (gap between candle and candle ) is widely used in ICT (Inner Circle Trader) methodology and Smart Money Concepts.
🔍 CREDITS & CODE ATTRIBUTION
This indicator builds upon established technical analysis concepts and combines multiple methodologies:
1. Market Profile / TPO Calculation
Concept Origin: J. Peter Steidlmayer (Chicago Board of Trade, 1980s)
Code Inspiration: TradingView's public domain Market Profile examples
Modifications: Custom filtering logic for directional bias, dual timeframe implementation
2. VWAP Calculation
Concept Origin: Standard financial instrument (widely used since 1980s)
Code Base: TradingView built-in ta.vwap() function (public domain)
Modifications: Dual VWAP system with independent anchor periods, custom filtering modes
3. Fair Value Gap Detection
Concept Origin: Inner Circle Trader (ICT) / Smart Money Concepts methodology
Code Implementation: Original implementation based on 3-candle gap pattern
Features: Multi-timeframe detection, automatic mitigation tracking, visual zone display
4. Pine Script Framework
Language: Pine Script v6 (TradingView)
Built-in Functions Used:
ta.vwap() - Volume weighted average price
request.security() - Higher timeframe data access
ta.change() - Period detection
ta.cum() - Cumulative volume
time() - Timestamp functions
Note: All code is original implementation. While concepts are based on established trading methodologies, the combination, filtering logic, and execution are unique to this indicator.
📊 RECOMMENDED INSTRUMENTS
Best Performance:
Major Forex Pairs (EURUSD, GBPUSD, USDJPY)
Stock Indices (ES, NQ, SPX, DAX)
Major Cryptocurrencies (BTCUSD, ETHUSD)
Liquid Stocks (high daily volume)
Avoid:
Low-volume altcoins
Illiquid stocks
Exotic forex pairs with wide spreads
⚡ PERFORMANCE TIPS
Start Conservative: Enable all filters initially
Reduce Filters Gradually: If too few signals, disable Secondary VWAP filter first
Match Timeframes: Keep MP Filter TF and FVG TF at same value
Backtest First: Review historical performance on your preferred instrument/timeframe
Combine with Price Action: Look for support/resistance confluence
Use Time Filter: Avoid low-liquidity hours (optional setting)
🚫 WHAT THIS INDICATOR DOES NOT DO
Does not guarantee profits - No trading system is 100% accurate
Does not predict the future - Based on historical patterns
Does not replace risk management - Always use stop losses
Does not work on all instruments - Requires volume data and liquidity
Does not provide exact entry/exit prices - Signals are zones, not precise levels
Does not account for fundamentals - Purely technical analysis
📜 DISCLAIMER
This indicator is provided for educational and informational purposes only. It is not financial advice, and past performance does not guarantee future results.
Trading Risk Warning:
All trading involves risk of loss
You can lose more than your initial investment (leverage products)
Only trade with capital you can afford to lose
Always use appropriate position sizing and risk management
Consider seeking advice from a licensed financial advisor
Technical Limitations:
Indicator may repaint FVG zones until HTF bar closes
Signals are based on historical patterns that may not repeat
Market conditions change and no system works in all environments
Volume data quality varies by exchange/broker
By using this indicator, you acknowledge these risks and agree that the author bears no responsibility for trading losses.
📞 SUPPORT & UPDATES
Questions? Comment on this publication
Issues? Describe the problem with chart screenshot
Feature Requests? Suggest improvements in comments
Updates: Will be published as new versions using TradingView's update feature
📝 VERSION HISTORY
Version 1.0 (Current)
Initial public release
Multi-filter system: MP + Dual VWAP + FVG
Directional bias filter
Real-time info panel
Comprehensive alert system
Time-based filtering
Thank you for using Smart VWAP FVG System!
Happy Trading! 📈
Squeeze Go Momentum Pro [KingThies] █ OVERVIEW
The Squeeze Momentum Pro indicator identifies volatility compression phases and breakout opportunities by comparing Bollinger Bands to Keltner Channels. When price consolidates (squeeze), the bands contract inside the channels, signaling an imminent breakout. The momentum histogram shows directional bias, helping traders anticipate which way price will move when the squeeze releases.
This indicator displays in a separate panel below the price chart, providing clear visual signals without cluttering price action.
█ KEY FEATURES
Momentum Histogram
The histogram is the primary visual element, displaying momentum strength and direction with four distinct color states:
• Dark Green (#00C853) — Strong bullish momentum that is increasing. This signals strengthening upward pressure and potential continuation.
• Light Green (#26A69A) — Bullish momentum that is decreasing. Price remains in bullish territory but upward force is weakening.
• Dark Red (#D32F2F) — Strong bearish momentum that is increasing. This signals strengthening downward pressure and potential continuation.
• Light Red (#EF5350) — Bearish momentum that is decreasing. Price remains in bearish territory but downward force is weakening.
The color intensity provides immediate feedback on momentum strength and trend health.
Squeeze State Indicator
Colored dots on the zero line communicate the current volatility state:
• Orange Dots — Squeeze is ON. Bollinger Bands have contracted inside Keltner Channels, indicating consolidation and low volatility.
A breakout is building and traders should prepare for directional movement.
• Green Dots — Squeeze is OFF. Bollinger Bands have expanded outside Keltner Channels, indicating active momentum and higher volatility.
Price is moving with conviction in the current direction.
• Gray Dots — Neutral state. The bands are transitioning between squeeze states.
Release Triangles
Triangle shapes mark the exact bar when a squeeze releases, providing precise entry timing:
• Green Triangle Up — Bullish squeeze release. The squeeze has ended with positive momentum, suggesting a long setup opportunity.
• Red Triangle Down — Bearish squeeze release. The squeeze has ended with negative momentum, suggesting a short setup opportunity.
Information Panel
A compact dashboard in the top-right corner displays real-time trading intelligence:
• Squeeze Status — Current state: ON, OFF, or NEUTRAL with color coding
• Momentum Direction — Current bias: BULL or BEAR
• Momentum Value — Precise numerical reading of momentum strength
• Trading Signal — Actionable status: LONG SETUP, SHORT SETUP, WAIT, or MONITOR
Configurable Parameters
All calculation inputs are adjustable to match your trading style and timeframe:
• BB Length — Bollinger Bands period (default: 20)
• BB StdDev — Bollinger Bands standard deviation multiplier (default: 2.0)
• KC Length — Keltner Channels period (default: 20)
• KC ATR Multiplier — Keltner Channels range multiplier (default: 1.5)
• Momentum Length — Linear regression period for momentum calculation (default: 20)
Alert System
Four alert conditions notify you of critical trading opportunities:
• Bullish Squeeze Release — Squeeze has released with bullish momentum, indicating a potential long entry
• Bearish Squeeze Release — Squeeze has released with bearish momentum, indicating a potential short entry
• Squeeze Started — Volatility compression detected, prepare for upcoming breakout
• Squeeze Ended — Volatility expansion confirmed, breakout is active
█ TRADING METHODOLOGY
The indicator follows a clear four-step process for identifying and trading squeeze breakouts:
1 - Wait for Orange Dots . When orange dots appear on the zero line, a squeeze is building. This indicates price consolidation and declining volatility.
Do not enter trades during this phase. Instead, prepare by identifying key support and resistance levels and potential breakout directions.
2 - Watch for Release Triangle . When a triangle appears, the squeeze has released and a breakout is beginning. This is your entry signal.
The triangle color (green up or red down) combined with the histogram direction indicates the breakout direction.
3 - Confirm with Histogram Direction . Check the momentum histogram for directional confirmation:
• Green histogram + green triangle up = Go long. Bullish momentum supports upward breakout.
• Red histogram + red triangle down = Go short. Bearish momentum supports downward breakout.
4 - Monitor Momentum Intensity . Stay in the trade while histogram bars maintain their dark, intense color.
When colors lighten (dark green to light green, or dark red to light red), momentum is weakening and you should consider taking profits or tightening stops.
█ INTERPRETATION GUIDE
Squeeze Detection Logic
A squeeze occurs when Bollinger Bands contract inside Keltner Channels. This happens when:
• Standard deviation of price decreases (BB narrows)
• Price consolidates within a tight range
• Volatility compresses to unsustainable levels
The orange dots signal this condition, warning traders that explosive movement is imminent.
Squeeze Release Logic
A squeeze releases when Bollinger Bands expand outside Keltner Channels. This happens when:
• Price volatility increases sharply
• Price breaks out of consolidation
• Volume typically expands (check volume separately)
The green dots and release triangles signal this condition, indicating the direction and timing of the breakout.
Momentum Reading
The histogram uses linear regression to calculate momentum relative to the midpoint of the recent range:
• Above Zero : Price is trading above the range midpoint with bullish pressure
• Below Zero : Price is trading below the range midpoint with bearish pressure
• Increasing Bars : Momentum is strengthening in the current direction (darker color)
• Decreasing Bars : Momentum is weakening in the current direction (lighter color)
█ BEST PRACTICES
• Timeframe Selection — The indicator works on all timeframes but performs best on 15-minute to daily charts.
Lower timeframes may produce more false signals due to noise.
• Confluence Trading — Combine squeeze releases with support/resistance levels, trend lines, or other indicators for higher probability setups.
• Volume Confirmation — Check that squeeze releases occur with increasing volume. Low volume breakouts are more likely to fail.
• Multiple Timeframe Analysis — Check higher timeframes for overall trend direction. Trade squeeze releases that align with the larger trend.
• Parameter Adjustment — Increase BB and KC lengths for smoother signals on higher timeframes. Decrease for more sensitive signals on lower timeframes.
█ LIMITATIONS
• The indicator does not predict breakout direction before the squeeze releases. The momentum histogram provides bias but is not definitive until the breakout occurs.
• False breakouts can occur, particularly in choppy or low-volume market conditions. Always use proper risk management and stop losses.
• The indicator works best in trending markets. In deeply ranging markets with no clear direction, squeeze signals may be less reliable.
• Momentum calculations use linear regression which can lag during extremely fast price movements. Confirm signals with price action.
█ NOTES
This implementation uses linear regression for momentum calculation rather than simple moving averages, providing more responsive and accurate directional signals. The four-color histogram system gives traders nuanced feedback on momentum strength that binary color schemes cannot provide.
The indicator automatically adjusts to any symbol and timeframe without modification, making it suitable for stocks, forex, crypto, and futures markets.
█ CREDITS
Squeeze methodology inspired by John Carter's TTM Squeeze indicator. Momentum calculation and visual design optimized for modern trading workflows.
VWAP Trend
**Overview**
The VWAP Trend indicator is a volume-weighted price analysis tool that visualizes the relationship between price and the anchored Volume Weighted Average Price (VWAP) over different timeframes. This script is designed to reveal when the market is trending above or below its volume-weighted equilibrium point, providing a clear framework for identifying directional bias, trend strength, and potential reversals.
By combining an anchored VWAP with exponential smoothing and a secondary trend EMA, the indicator helps traders distinguish between short-term price fluctuations and genuine volume-supported directional moves.
**Core Concept**
VWAP (Volume Weighted Average Price) represents the average price of an asset weighted by traded volume. It reflects where the majority of trading activity has taken place within a chosen period, serving as a critical reference level for institutions and professional traders.
This indicator extends the traditional VWAP concept by:
1. Allowing users to **anchor VWAP to different timeframes** (Daily, Weekly, or Monthly).
2. Applying **smoothing** to create a stable reference curve less prone to noise.
3. Overlaying a **trend EMA** to identify whether current price momentum aligns with or diverges from VWAP equilibrium.
The combination of these elements produces a visual representation of price’s relationship to its fair value across time, helping to identify accumulation and distribution phases.
**Calculation Methodology**
1. **Anchored VWAP Calculation:**
The script resets cumulative volume and cumulative volume–price data at the start of each new VWAP session (based on the selected anchor timeframe). It continuously accumulates the product of price and volume, dividing this by total volume to compute the current VWAP value.
2. **Smoothing Process:**
The raw VWAP line is smoothed using an Exponential Moving Average (EMA) of user-defined length, producing a cleaner, more stable trend curve that minimizes intraperiod noise.
3. **Trend Determination:**
An additional EMA is calculated on the closing price. By comparing the position of this EMA to the smoothed VWAP, the indicator determines the prevailing market bias:
* When the trend EMA is above the smoothed VWAP, the market is considered to be in an **uptrend**.
* When the trend EMA is below the smoothed VWAP, the market is classified as a **downtrend**.
**Visual Structure**
The indicator uses color dynamics and chart overlays to make interpretation intuitive:
* **Smoothed VWAP Line:** The main trend reference, colored blue during bullish conditions and orange during bearish conditions.
* **Price Fill Region:** The area between the smoothed VWAP and price is filled with a translucent color matching the current trend, visually representing whether price is trading above or below equilibrium.
* **Trend EMA (implicit):** Although not separately plotted, it drives the color state of the VWAP, ensuring seamless visual transitions between bullish and bearish conditions.
**Inputs and Parameters**
* **VWAP Timeframe:** Choose between Daily, Weekly, or Monthly anchoring. This determines the reset frequency for cumulative volume and price data.
* **VWAP Smoothing Length:** Defines how many periods are used to smooth the VWAP line. Shorter values produce a more reactive line; longer values create smoother, steadier signals.
* **Trend EMA Length:** Sets the period for the trend detection EMA applied to price. Adjust this to calibrate how quickly the indicator reacts to directional changes.
**Interpretation and Use Cases**
* **Trend Confirmation:** When price and the trend EMA both remain above the smoothed VWAP, the market is showing strong bullish control. Conversely, consistent price action below the VWAP suggests sustained bearish sentiment.
* **Fair Value Assessment:** VWAP serves as a dynamic equilibrium level. Price repeatedly reverting to this line indicates consolidation or fair value zones, while strong directional moves away from VWAP highlight momentum phases.
* **Institutional Benchmarking:** Because large market participants often benchmark entries and exits relative to VWAP, this indicator helps align retail analysis with institutional logic.
* **Reversal Detection:** Sudden crossovers of the trend EMA relative to the VWAP can signal potential reversals or shifts in momentum strength.
**Trading Applications**
* **Trend Following:** Use VWAP’s direction and color state to determine trade bias. Long entries are favored when the VWAP turns blue, while short entries align with orange phases.
* **Mean Reversion:** In ranging conditions, traders may look for price deviations far above or below VWAP as potential reversion opportunities.
* **Multi-Timeframe Confluence:** Combine the Daily VWAP Trend with higher anchor periods (e.g., Weekly or Monthly) to confirm larger trend structure.
* **Support and Resistance Mapping:** VWAP often acts as a strong intraday or session-level support/resistance zone. The smoothed version refines this behavior into a cleaner, more reliable reference.
**Originality and Innovation**
The VWAP Trend indicator stands apart from conventional VWAP scripts through several original features:
1. **Anchor Flexibility:** Most VWAP indicators fix the anchor to a specific session (like daily). This version allows switching between Daily, Weekly, and Monthly anchors dynamically, adapting to various trading styles and time horizons.
2. **Volume-Weighted Smoothing:** The use of an EMA smoothing layer over the raw VWAP provides enhanced stability without compromising responsiveness, delivering a more analytically consistent signal.
3. **EMA-Based Trend Comparison:** By introducing a second trend EMA, the indicator creates a comparative framework that merges volume-weighted price analysis with classical momentum tracking — a rare and powerful combination.
4. **Adaptive Visual System:** The color-shifting and shaded fill between VWAP and price are integrated into a single, lightweight structure, giving traders immediate insight into market bias without the clutter of multiple overlapping indicators.
**Advantages**
* Adaptable to any market, timeframe, or trading style.
* Provides both equilibrium (VWAP) and momentum (EMA) perspectives.
* Smooths out noise while retaining the integrity of volume-based price dynamics.
* Enhances situational awareness through intuitive color-coded visualization.
* Ideal for professional, swing, and intraday traders seeking context-driven market direction.
**Summary**
The VWAP Trend indicator is a modern enhancement of the classical VWAP methodology. By merging anchored volume-weighted analysis with smoothed trend detection and visual state feedback, it provides a comprehensive perspective on market equilibrium and directional strength. It is built for traders who seek more than static price references — offering an adaptive, volume-aware framework for identifying market trends, reversals, and fair-value zones with precision and clarity.
EMA 200 - 50 - 20 | Davide BuncugaThis script displays three key Exponential Moving Averages (EMAs) on the chart: EMA 200, EMA 50, and EMA 20.
These moving averages are commonly used by traders to identify the overall market trend, medium-term structure, and short-term momentum.
EMA 200 – Represents the long-term trend and acts as a dynamic support/resistance.
EMA 50 – Used to identify the medium-term direction of the market.
EMA 20 – Highlights short-term momentum and pullback areas within the trend.
This indicator is designed to help traders quickly analyze market structure and align their trading decisions with the dominant trend.
VMMA Wave Edges [MTF]The VMMA Wave Edges is a multi-timeframe (MTF) overlay indicator that plots dynamic upper and lower edges formed by a band of Volume-Weighted Moving Averages (VWMAs) of varying lengths. It computes N VWMAs with lengths increasing arithmetically from start_len by incr, then plots:The maximum of all VWMAs → Upper Edge
The minimum of all VWMAs → Lower Edge
These edges are calculated on a higher timeframe (mtf_tf) and projected onto the current chart, creating a smooth, volume-sensitive envelope that adapts to volatility and trend strength.Use & InterpretationFeature
Purpose
Upper Edge
Dynamic resistance zone; price often reacts when approaching or breaking above.
Lower Edge
Dynamic support zone; price tends to bounce or consolidate near it.
Edge Contraction
Low volatility → potential breakout setup.
Edge Expansion
High volatility → trend continuation or exhaustion.
MTF Projection
Avoids repainting & noise by using cleaner higher-timeframe data.
Trading ApplicationsMean ReversionBuy near Lower Edge, sell near Upper Edge (especially in ranging markets).
Breakout ConfirmationPrice closing above Upper Edge on MTF → bullish breakout.
Below Lower Edge → bearish.
Trend FilterIn uptrend: price above Upper Edge → strong momentum.
In downtrend: price below Lower Edge → strong bearish control.
Support/Resistance FlipBroken Upper Edge → becomes future support (and vice versa).
Enhanced Roman Order Block v2Enhanced Roman Order Block Indicator v2
This indicator identifies and visualizes Order Blocks (OBs) on your chart, which are key price zones where institutional traders likely placed significant orders, often acting as support/resistance. It's an enhanced version inspired by standard OB detection scripts (like "Crystal Order Block"), but combines and improves upon them with practical features for better trading utility—avoiding a simple mashup by integrating complementary tools that work synergistically.
Originality and Enhancements:
Builds on basic candle-pattern OB detection but adds ATR-based minimum size filtering to ignore noise (e.g., small, insignificant blocks).
Includes optional Higher Timeframe (HTF) confirmation to validate OBs against larger trends, using confirmed data only (no lookahead bias—requests are offset for historical accuracy).
Customizable mitigation (wick or close-based) to detect when an OB is "touched" and potentially invalidated.
Adjustable lookback for pattern flexibility, box extensions, price lines, max displayed OBs (to declutter charts), and alerts for formation/mitigation.
These features merge to create a more reliable, user-configurable tool: e.g., HTF checks + ATR filters reduce false positives, while alerts + lines help in live trading without overwhelming the chart.
How It Works:
Detection Logic: Scans recent candles (default lookback=3) for bullish OBs (e.g., a low that's lower than prior but higher than subsequent swings, indicating accumulation) or bearish OBs (opposite for distribution). Formulas: Bullish = (B_low < A_low) AND (C_low > B_low) AND ((C_low > B_high) OR (D_low > B_high)); similar for bearish.
Filters: OBs must exceed ATR * minOBSizeATR (default 0.5) for validity. If HTF enabled, confirms the OB aligns with HTF lows/highs.
Mitigation: Tracks OBs and shortens boxes/lines when price wicks/closes into the mitigation level (top for bullish, bottom for bearish).
Display: Draws semi-transparent boxes (extendable), optional dashed lines, and labels. Limits to maxOBs, removing oldest.
Alerts: Triggers on new OBs or mitigations for timely notifications.
Underlying concept: OBs stem from Smart Money Concepts (SMC), where big players leave "footprints" in price structure— this script automates detection with risk-aware tweaks.
How to Use:
Add to chart (works on any timeframe/symbol, e.g., crypto like ETHUSD).
Inputs:
Order Block Settings: Toggle bullish/bearish/mitigated visibility; choose mitigation type; set min size/lookback.
Display: Adjust extensions, enable lines, limit max OBs.
Alerts: Enable for OB events.
Multi-Timeframe: Input a higher TF (e.g., "D" for daily) for confirmation—ensures OBs respect bigger-picture levels.
