Penunjuk dan strategi
Yit's Risk CalculatorIntroducing a risk a bulletproof risk calculator.
I'm tired of sitting on my brokerage, messing with my shares to buy while price action leaves me in the dust.
For my breakout strategy execution is everything i dont have time to stop and think.
within the Indicator settings you have free reign to change account size and risk%
*the stop loss is glued to the low of the day*
Fibonacci Degree System This Pine Script creates a sophisticated technical analysis tool that combines Fibonacci retracements with a degree-based cycle system. Here's a comprehensive breakdown:
Core Concept
The indicator maps price movements onto a 360-degree circular framework, treating market cycles like geometric angles. It creates a visual "mesh" where Fibonacci ratios intersect in both price (horizontal) and time (vertical) dimensions.
How It Works
1. Finding Reference Points
The script looks back over a specified period (default 100 bars) to identify:
Highest High: The peak price point
Lowest Low: The trough price point
Time Locations: Exactly which bars these extremes occurred on
These two points form the boundaries of your analysis window.
2. Creating the Fibonacci Grid
Horizontal Lines (Price Levels):
The script divides the price range between high and low into seven key Fibonacci ratios:
0% (Low) - Bottom boundary in red
23.6% - Minor retracement in orange
38.2% - Shallow retracement in yellow
50% - Midpoint in lime green
61.8% - Golden ratio in aqua (most significant)
78.6% - Deep retracement in blue
100% (High) - Top boundary in purple
Each line represents a potential support/resistance level where price might react.
Vertical Lines (Time Cycles):
The same Fibonacci ratios are applied to the time dimension between the high and low bars. If your high and low are 50 bars apart, vertical lines appear at:
Bar 0 (0%)
Bar 12 (23.6%)
Bar 19 (38.2%)
Bar 25 (50%)
Bar 31 (61.8%)
Bar 39 (78.6%)
Bar 50 (100%)
These suggest when price might make significant moves.
3. The Degree Mapping System
The innovative feature maps the time progression to degrees:
0° = Start point (0% time)
85° = 23.6% through the cycle
138° = 38.2% through the cycle
180° = Midpoint (50%)
222° = 61.8% through the cycle (golden angle)
283° = 78.6% through the cycle
360° = Complete cycle (100%)
This treats market movements as circular patterns, similar to how planets orbit or pendulums swing.
Visual Output
When you apply this indicator, you'll see:
A rectangular mesh extending beyond your high-low range (by 150% default)
Color-coded horizontal lines showing price Fibonacci levels
Matching vertical lines showing time Fibonacci intervals
Price labels on the right showing percentage levels
Degree labels at the bottom showing the angular position in the cycle
Intersection points creating a grid of potentially significant price-time coordinates
Trading Application
Traders use this to identify:
Support/Resistance Zones: Where horizontal and vertical lines intersect
Time Targets: When price might reverse (at vertical Fibonacci times)
Cycle Completion: When approaching 360°, a new cycle may begin
Harmonic Patterns: Geometric relationships between price and time
Customization Features
The script offers extensive control:
Lookback period: Adjust cycle length (10-500 bars)
Mesh extension: How far to project the grid forward
Visual toggles: Show/hide horizontal lines, vertical lines, labels
Styling: Line thickness, style (solid/dashed/dotted), colors
Label positioning: Fine-tune text placement for readability
The intersection at 61.8% time and 61.8% price at 222° becomes a key target zone.
This tool essentially converts the abstract concept of market cycles into a concrete, visual geometric framework that traders can analyze and act upon.
DISCLAIMER: This information is provided for educational purposes only and should not be considered financial, investment, or trading advice.
No guarantee of profits: Past performance and theoretical models do not guarantee future results. Trading and investing involve substantial risk of loss.
Not a recommendation: This script illustration does not constitute a recommendation to buy, sell, or hold any financial instrument.
Do your own research: Always conduct thorough independent research and consider consulting with a qualified financial advisor before making any trading decisions.
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.
AnAn FastKnife MNQ • V7 PRO (AI Signals + R/R + Dashboard)ai script developed to test the market and the speed and the volatility an the important signals
Triple Moving Averages Daily on Timeframe (10/20/50 with LabelsUnlike other MA's this give me on daily time frame irrespective of chart time
Multi-Timeframe EMA & SMA Scanner - Price Level LabelsOverview
A powerful multi-timeframe moving average scanner that displays EMA and SMA levels from up to 8 different timeframes simultaneously on your chart. Perfect for identifying key support/resistance levels, confluence zones, and multi-timeframe trend analysis.
Key Features
📊 Multi-Timeframe Analysis
Monitor up to 8 different timeframes simultaneously (5m, 10m, 15m, 30m, 1H, 4H, 1D, 1W)
Each timeframe can be independently enabled/disabled
Fully customizable timeframe selection
📈 Comprehensive Moving Averages
5 configurable EMA periods (default: 8, 21, 50, 100, 200)
2 configurable SMA periods (default: 200, 400)
All periods are fully customizable to match your trading strategy
🎯 Smart Price Level Labels
Labels positioned at actual price levels (not in a list)
Color-coded labels for easy identification
Dynamic text color: Green when price is above, Red when below
Compact notation: E8-5m means EMA 8 on 5-minute timeframe
Adjustable label offset from current price
📉 Optional Horizontal Lines
Dotted reference lines at each MA level
Color-matched to corresponding MA type
Can be toggled on/off independently
📋 Comprehensive Data Table
Shows all MA values organized by timeframe
Displays percentage distance from current price
Trend indicator (Strong Up/Up/Neutral/Down/Strong Down)
EMA alignment status (Bullish/Bearish/Mixed)
Color-coded cells for quick visual analysis
🎨 Full Customization
Individual color settings for each MA type
Adjustable table size (Tiny/Small/Normal/Large)
Choose table position (Left/Right)
Toggle any MA or timeframe on/off
🔔 Built-in Alerts
Golden Cross detection (EMA 50 crosses above EMA 200)
Death Cross detection (EMA 50 crosses below EMA 200)
Price crossing major EMAs
Available for multiple timeframes
How to Use
For Day Traders:
Enable lower timeframes (5m, 10m, 15m, 30m)
Focus on faster EMAs (8, 21, 50)
Watch for confluence zones where multiple timeframe MAs cluster
For Swing Traders:
Enable higher timeframes (1H, 4H, 1D)
Use all EMAs plus SMAs for broader perspective
Look for alignment across timeframes for high-probability setups
For Position Traders:
Focus on daily and weekly timeframes
Emphasize 100, 200 EMAs and 200, 400 SMAs
Use for long-term trend confirmation
Understanding the Labels
Label Format: E8-5m 45250.50
E8 = EMA with period 8
5m = 5-minute timeframe
45250.50 = Current price level
Green text = Price is currently above this level (potential support)
Red text = Price is currently below this level (potential resistance)
For SMAs: S200-1D 44500.00
S200 = SMA with period 200
1D = Daily timeframe
Trading Applications
Support/Resistance Identification
MAs act as dynamic support and resistance levels
Multiple timeframe MAs create stronger zones
Confluence Trading
When multiple MAs from different timeframes cluster together, it creates high-probability zones
These areas often result in strong reactions
Trend Analysis
Check the Alignment column: Bullish alignment = all EMAs in ascending order
Trend column shows overall price position relative to all MAs
Entry/Exit Timing
Use lower timeframe MAs for precise entries
Use higher timeframe MAs for trend direction and exits
Settings Guide
Timeframes Section:
Select and enable/disable up to 8 timeframes
Default: 5m, 10m, 15m, 30m, 1H, 4H, 1D, 1W
MA Periods Section:
Customize all EMA and SMA periods
Default EMAs: 8, 21, 50, 100, 200
Default SMAs: 200, 400
Display Section:
Toggle price labels and horizontal lines
Adjust label offset (distance from right edge)
Show/hide data table
Choose table position and size
Colors Section:
Customize colors for each MA type
Each MA has independent color control
Pro Tips
✅ Start with default settings and adjust based on your trading style
✅ Disable timeframes/MAs you don't use to reduce chart clutter
✅ Use the data table for quick overview, labels for precise levels
✅ Look for "confluence clusters" where multiple MAs from different timeframes align
✅ Green labels = potential support, Red labels = potential resistance
✅ Set alerts on key crossovers for automated notifications
Technical Specifications
Pine Script v6
Overlay indicator (displays on main chart)
Maximum 500 labels supported
Real-time updates on each bar close
Compatible with all instruments and timeframes
Perfect For:
Day traders seeking multi-timeframe confirmation
Swing traders looking for high-probability setups
Position traders monitoring long-term trends
Anyone using moving averages as part of their strategy
Note: This indicator does not provide buy/sell signals. It's a tool for analysis and should be used in conjunction with your trading strategy and risk management rules.
Hyper Squeeze Sniper (Dual Side: Long + Short)Hyper Squeeze Sniper (Dual Side Strategy)
This script is a comprehensive Volatility Breakout System designed to identify and trade explosive price moves following periods of consolidation. It combines the classical "Squeeze" theory with Linear Regression Momentum, Volume Analysis, and an ATR-based Trailing Stop to filter false signals and manage risk effectively.
The script operates on a logic of "Compression -> Explosion -> Trend Following" suitable for both Long and Short positions.
🛠 Detailed Methodology (How it works)
1. The Squeeze Detection (Consolidation) The core concept relies on the relationship between Bollinger Bands (BB) and Keltner Channels (KC).
Condition: When the Bollinger Bands (Standard Deviation) contract and fall inside the Keltner Channels (ATR based), it indicates a period of extremely low volatility (The Squeeze).
Visual: The background turns Gray to indicate "Do Not Trade / Wait Mode".
2. Momentum Confirmation (Linear Regression) Instead of using standard lagging indicators, this script utilizes Linear Regression of the price deviation to determine the direction of the breakout.
If the Linear Regression Slope > 0, the bias is Bullish.
If the Linear Regression Slope < 0, the bias is Bearish.
3. Volume Validation To avoid fake breakouts, a Volume Spike filter is applied. A signal is only valid if the current volume exceeds its moving average by a defined multiplier (Default x1.2).
4. Risk Management: ATR Trailing Stop Once a trade is entered, the script calculates a dynamic Trailing Stop based on the Average True Range (ATR).
- Long: The stop line trails below the price and never moves down.
- Short: The stop line trails above the price and never moves up.
- Exit: The position is closed immediately when the price breaches this volatility-based safety line.
How to Use
1. Wait: Look for the Gray Background. This is the accumulation phase.
2. Entry:
LONG: Wait for a Green Triangle ▲ (Price breaks Upper BB + Vol Spike + Bullish Momentum).
SHORT: Wait for a Red Triangle ▼ (Price breaks Lower BB + Vol Spike + Bearish Momentum).
3. Exit: Close the position when the "X" mark appears or when candles cross the trailing safety line.
Settings
- BB Length/Mult: Adjust the sensitivity of the squeeze detection.
- Vol Spike Factor: Increase this to filter out low-volume breakouts.
- ATR Period/Mult: Adjust the trailing stop distance (Higher = Wider stop for swing trading).
Key Levels by Romulus V2This is the updated key levels script I added dynamic levels that change throughout the day opening range high and low and customizable settings to adjust.
PRO Triple+ Confirmation Overlay SignalsThis script uses the 200 SMA + RSI + MACD confirmations as buy and sell signals. It only give a signal if all three line up. works well for general market direction signals. It also has a higher time frame filter that will filter out 70%-90% of traps and counter trend signals. MACD momentum trigger times entries with momentum shifts. RSI confirmation as well as volume confirmation to remove entries in low volume dead markets.
Low Volatility Breakout + TP/SL Levels█ OVERVIEW
"Low Volatility Breakout + TP/SL Levels" is a breakout indicator designed to detect and trade breakouts from periods of low volatility (consolidation). Unlike classic strategies based on fixed support/resistance levels, this indicator dynamically identifies consolidations characterized by small candle bodies and only generates a signal when the breakout occurs with a large, decisive candle. It also automatically plots 3 Take Profit levels and a Stop Loss (with two calculation modes), making it a complete breakout trading tool.
█ CONCEPTS
The strongest market moves most often start after a prolonged period of very low volatility — when candles become small and the market "falls asleep". The indicator first detects such consolidations (small bodies for at least X bars), draws a box around them, and then waits for a breakout with a candle significantly larger than the average. Additional filters (e.g., the box height cannot exceed the average candle body by too much) eliminate false consolidations and volatility traps. Immediately after the breakout, TP1, TP2, TP3, and SL levels are plotted.
█ FEATURES
Dynamic detection of low-volatility consolidations
- candles with small bodies (< average body × consolidationMultiplier)
- minimum number of bars in consolidation: confirmBars (default 5)
Automatic drawing of consolidation boxes
- green (bullish) or red (bearish) with transparent background (85)
- adjustable border thickness (border_width 1–5)
- box height filter (boxHeightMultiplier, default 6.0 × average body) – removes overly stretched/false consolidations
Breakout conditions
- current candle must be larger than average body × threshold (default 1.5)
- must be the largest candle in the entire consolidation
- must close above the highest high (long) or below the lowest low (short)
Breakout signals
- small green triangles below the bar (long)
- small red triangles above the bar (short)
Automatic Take Profit and Stop Loss levels (drawn 5 bars forward)
- two calculation modes:
• Candle Multiplier – based on average true range (high-low) over tp_sl_length period
• Percentage – fixed percentage from breakout close price (percentages must be manually adjusted to the asset and timeframe)
- 3 TP levels (default 2×, 3×, 4× or 2%, 3%, 4%)
- 1 SL level (default 2× or 1.5%)
Live TP/SL price table (top-right corner)
- displays exact current values of SL, TP1, TP2, TP3 immediately after each new signal
- colors identical to drawn lines (red background for SL, green for TP levels)
- updates automatically with every new breakout
Built-in alerts
- “Bullish Breakout Alert” and “Bearish Breakout Alert”
█ HOW TO USE
Add the indicator to your TradingView chart → Indicators → search “Low Volatility Breakout + TP/SL Levels”.
After each valid breakout you will immediately see:
- the colored box
- signal triangle
- horizontal TP/SL lines
- updated table in the top-right corner showing precise price levels for the current trade
Key settings to adjust:
Consolidation Settings
- Volatility Window (length) – period for average body calculation (default 20)
- Consolidation Multiplier – how small bodies must be to count as consolidation (default 2.0)
- Breakout Multiplier – minimum size of breakout candle (default 1.5)
- Box Height Multiplier – maximum allowed box height (default 6.0)
- Min Consolidation Bars – minimum bars required (default 5)
Risk Management Settings
- Choose TP/SL mode: Candle Multiplier or Percentage
- Adjust TP1–3 and SL multipliers/percentages to match your risk management style
Signal interpretation:
- Green triangle below bar + green box + green TP levels in table = long signal
- Red triangle above bar + red box + red SL level in table = short signal
- Boxes remain on chart until broken — they highlight accumulation/distribution zones
█ APPLICATIONS
- Trading breakouts from consolidation on all markets and timeframes
- Recommended to trade in the direction of the higher-timeframe trend or with additional confirmations (e.g., key level breaks). Aggressive mode (trading both directions) is also possible — provided box and TP/SL settings are properly optimized
- Experiment with different TP/SL ratios — higher reward-to-risk setups (e.g., SL 1×, TP3 6–8×) with lower win rate are often more profitable in the long run
- Strongly encourage testing various box parameters (consolidationMultiplier, boxHeightMultiplier, confirmBars) — small changes can dramatically affect signal frequency and quality
█ NOTES
Always test and optimize parameters for the specific instrument and timeframe.
Fair Value Gaps (FVG)This indicator automatically detects Fair Value Gaps (FVGs) using the classic 3-candle structure (ICT-style).
It is designed for traders who want clean charts and relevant FVGs only, without the usual clutter from past sessions or tiny, meaningless gaps.
Key Features
• Bullish & Bearish FVG detection
Identifies imbalances where price fails to trade efficiently between candles.
• Automatic FVG removal when filled
As soon as price trades back into the gap, the box is deleted in real time – no more outdated zones on the chart.
• Only shows FVGs from the current session
At the start of each new session, all previous FVGs are cleared.
Perfect for intraday traders who only care about today’s liquidity map.
• Flexible minimum gap size filter
Avoid noise by filtering FVGs using one of three modes:
Ticks (based on market tick size)
Percent (relative to current price)
Points (absolute price distance)
• Right-extension option
Keep gaps extended forward in time or limit them to the candles that created them.
Why This Indicator?
Many FVG indicators overwhelm the chart with zones from previous days or tiny imbalances that don’t matter.
This version keeps things clean, meaningful, and real-time accurate, ideal for day traders who rely on market structure and liquidity.
Keltner Channels - signal providerThis enhanced channel for pro traders visually indicates enhanced entry or exit signal based on the position of the underlying within the channel. Remember: EVERY TREND HAS ITS RETRACEMENTS - with this indicator you will avoid entering in full uptrend (bearing more downside risk than upside) or exiting (shorting) at max downtrend.
To be used together with the trend on higher timeframes (especially for the interpretation of the baseline)
Upper part = potential sell signal (especially in overall downtrends)
Lower part = potential buy signal (especially in overall uptrends)
Basis = potential buy signal (especially in strong uptrends)
= potential sell signal (especially in overall downtrends)
Auto Position CalculatorA position sizing tool that automatically detects the instrument you're trading and calculates the correct position size based on your risk parameters.
What It Does
This indicator calculates how many contracts, lots, or shares to trade based on your account size, risk percentage, and stop loss distance. It auto-detects the instrument type and adjusts the point/pip value accordingly.
Supported Instruments
Futures: NQ, MNQ, ES, MES, YM, MYM, RTY, M2K, CL, MCL, GC, MGC
Forex: All major pairs (USD, EUR, GBP, JPY, etc.)
Index CFDs: NAS100, US500, US30, GER40, UK100
Metals: XAU, XAG
Crypto and Stocks: Automatic detection
How to Use
Set your account size and risk % in settings
Click the settings icon and place Entry, Stop Loss, and Take Profit on the chart
The position size and risk calculations appear automatically
Levels auto-reset at your chosen session (Asia, London, or New York open)
Limitations
CFD and forex pip values assume standard lot sizing - your broker may differ
Auto-detection relies on ticker naming conventions, which vary by broker/data feed
Session reset times are based on ET (Eastern Time)
Futures Momentum Scanner – jyoti//@version=5
indicator("Futures Momentum Scanner – Avvu Edition", overlay=false, max_lines_count=500)
//------------------------------
// USER INPUTS
//------------------------------
rsiLen = input.int(14, "RSI Length")
macdFast = input.int(12, "MACD Fast")
macdSlow = input.int(26, "MACD Slow")
macdSignal = input.int(9, "MACD Signal")
stLength = input.int(10, "Supertrend Length")
stMult = input.float(3.0, "Supertrend Multiplier")
//------------------------------
// SUPER TREND
//------------------------------
= ta.supertrend(stMult, stLength)
trendUp = stDirection == 1
//------------------------------
// RSI
//------------------------------
rsi = ta.rsi(close, rsiLen)
rsiBull = rsi > 50 and rsi < 65
//------------------------------
// MACD
//------------------------------
= ta.macd(close, macdFast, macdSlow, macdSignal)
macdBull = macd > signal and macd > 0
//------------------------------
// MOVING AVERAGE TREND
//------------------------------
ema20 = ta.ema(close, 20)
ema50 = ta.ema(close, 50)
ema200 = ta.ema(close, 200)
trendStack = ema20 > ema50 and ema50 > ema200
//------------------------------
// BREAKOUT LOGIC
//------------------------------
prevHigh = ta.highest(high, 20)
breakout = close > prevHigh
//------------------------------
// FINAL SCANNER LOGIC
//------------------------------
bullishCandidate = trendUp and rsiBull and macdBull and trendStack and breakout
//------------------------------
// TABLE OUTPUT FOR SCANNER FEEL
//------------------------------
var table t = table.new(position.top_right, 1, 1)
if barstate.islast
msg = bullishCandidate ? "✔ BUY Candidate" : "– Not a Setup"
table.cell(t, 0, 0, msg, bgcolor=bullishCandidate ? color.new(color.green, 0) : color.new(color.red, 70))
//------------------------------
// ALERT
//------------------------------
alertcondition(bullishCandidate, title="Scanner Trigger", message="This stock meets Avvu's futures scanner criteria!")
Get_rich_aggressively_v5# 🚀 GET RICH AGGRESSIVELY v5 - TIER SYSTEM
### Precision Futures Scalping | NQ • ES • YM • GC • BTC
### *Leave Every Trade With Money*
---
## 📋 QUICK CHEATSHEET
```
┌─────────────────────────────────────────────────────────────────────────────┐
│ GRA v5 SIGNAL REQUIREMENTS │
├─────────────────────────────────────────────────────────────────────────────┤
│ ✓ TIER MET Points ≥ 10 (B), ≥ 50 (A), ≥ 100 (S) │
│ ✓ VOLUME ≥ 1.3x average │
│ ✓ DELTA ≥ 55% dominance (buyers OR sellers) │
│ ✓ DIRECTION Candle color = Delta direction │
│ ✓ SESSION In London (3-5AM) or NY (9:30-11:30AM) if filter ON │
├─────────────────────────────────────────────────────────────────────────────┤
│ TIER ACTIONS │
├─────────────────────────────────────────────────────────────────────────────┤
│ 🥇 S-TIER (100+ pts) │ HOLD LONGER │ Big institutional move │
│ 🥈 A-TIER (50-99 pts) │ HOLD A BIT │ Medium move, trail to BE │
│ 🥉 B-TIER (10-49 pts) │ CLOSE QUICK │ Scalp 5-10 pts, exit fast │
│ ❌ NO TIER (< 10 pts) │ NO TRADE │ Not enough conviction │
├─────────────────────────────────────────────────────────────────────────────┤
│ SESSION PRIORITY │
├─────────────────────────────────────────────────────────────────────────────┤
│ 🔵 LONDON OPEN 03:00-05:00 ET │ IB forms 03:00-04:00 │
│ 🟢 NY OPEN 09:30-11:30 ET │ IB forms 09:30-10:30 │
│ 📊 IB BREAKOUT Close beyond IB + Impulse + 1.3x Vol = HIGH CONVICTION│
├─────────────────────────────────────────────────────────────────────────────┤
│ VOLUME PROFILE ZONES │
├─────────────────────────────────────────────────────────────────────────────┤
│ 🔵 HVN (Blue BG) High volume = Support/Resistance, expect consolidation │
│ 🟡 LVN (Yellow BG) Low volume = Breakout acceleration, fast moves │
│ 🟣 POC Point of Control = Institutional fair value │
│ 🟣 VAH/VAL Value Area edges = S/R zones │
├─────────────────────────────────────────────────────────────────────────────┤
│ MARKET STATE DECODER │
├─────────────────────────────────────────────────────────────────────────────┤
│ TREND UP │ Price > EMA20 + CVD rising │ Trade WITH the trend │
│ TREND DN │ Price < EMA20 + CVD falling │ Trade WITH the trend │
│ RETRACE │ Price/CVD diverging │ Pullback, prepare for entry │
│ RANGE │ No clear direction │ Reduce size or skip │
├─────────────────────────────────────────────────────────────────────────────┤
│ 💎 HIGH CONVICTION UPGRADE │
├─────────────────────────────────────────────────────────────────────────────┤
│ Purple diamond (◆) appears when: │
│ • Strong delta (≥65%) + Strong volume (≥2x) + Market in imbalance │
│ → Consider upgrading tier (B→A, A→S) for position sizing │
└─────────────────────────────────────────────────────────────────────────────┘
```
---
## 🎯 THE TIER SYSTEM
The tier system classifies candles by **point movement** to determine trade management:
| Tier | Points | Action | Expected R:R |
|:----:|:------:|:------:|:------------:|
| 🥇 **S-TIER** | 100+ | HOLD LONGER | 2:1+ |
| 🥈 **A-TIER** | 50-99 | HOLD A BIT | 1.5:1 |
| 🥉 **B-TIER** | 10-49 | CLOSE QUICK | 1:1 |
| ❌ **NO TIER** | < 10 | NO TRADE | — |
---
## ✅ SIGNAL REQUIREMENTS
**ALL conditions must be TRUE for a signal:**
```
SIGNAL = TIER + VOLUME + DELTA + DIRECTION + SESSION
☐ Points ≥ 10 (minimum B-tier)
☐ Volume ≥ 1.3x average
☐ Delta dominance ≥ 55%
☐ Candle direction = Delta direction
☐ In session (if filter ON)
ANY FALSE = NO SIGNAL = NO TRADE
```
---
## 📊 VOLUME DOMINANCE ANALYSIS
This is the **core edge** of GRA v5. We use intrabar analysis to determine who is in control:
```
VOLUME ANALYSIS BREAKDOWN
Total Volume = Buy Volume + Sell Volume
Buy Volume: Who pushed price UP within the bar
Sell Volume: Who pushed price DOWN within the bar
Delta = Buy Volume - Sell Volume
Buy Dominance = Buy Volume / Total Volume
Sell Dominance = Sell Volume / Total Volume
≥ 55% = ONE SIDE IN CONTROL
≥ 65% = STRONG DOMINANCE (high conviction)
```
**Direction Confirmation Matrix:**
| Candle | Delta | Signal |
|:-------|:------|:-------|
| 🟢 Bullish | 55%+ Buyers | ✅ LONG |
| 🟢 Bullish | 55%+ Sellers | ❌ Trap |
| 🔴 Bearish | 55%+ Sellers | ✅ SHORT |
| 🔴 Bearish | 55%+ Buyers | ❌ Trap |
---
## 🕐 SESSION CONTEXT
### Initial Balance (IB) Framework
The **first hour** of each session establishes the IB range. Institutions use this for the day's framework.
```
SESSION WINDOWS (Eastern Time):
LONDON:
├── IB Period: 03:00 - 04:00 ← Range established
├── Trade Window: 03:00 - 05:00 ← Best signals
└── Extension Targets: 1.5x, 2.0x
NY:
├── IB Period: 09:30 - 10:30 ← Range established
├── Trade Window: 09:30 - 11:30 ← Best signals
└── Extension Targets: 1.5x, 2.0x
```
### IB Breakout Signals
```
L▲ / L▼ = London IB Breakout (Blue)
N▲ / N▼ = NY IB Breakout (Orange)
Confirmation Required:
☐ Close beyond IB level (not just wick)
☐ Impulse candle (body > 60% of range)
☐ Volume > 1.3x average
```
**IB Statistics:**
- 97% of days break either IB high or low
- 1.5x extension = first profit target
- 2.0x extension = full range target
- ~66% of London sessions sweep Asian high/low first
---
## 📈 VIRTUAL VOLUME PROFILE ZONES
GRA v5 calculates volume profile zones **without drawing the profile**, giving you the key levels:
### Zone Types
| Zone | Background | Meaning | Action |
|:-----|:-----------|:--------|:-------|
| **HVN** | 🔵 Blue | High Volume Node | S/R zone, expect consolidation |
| **LVN** | 🟡 Yellow | Low Volume Node | Breakout zone, fast acceleration |
| **POC** | 🟣 Purple dots | Point of Control | Institutional fair value |
| **VAH/VAL** | 🟣 Purple lines | Value Area edges | S/R boundaries |
### How to Use
```
ENTERING A TRADE:
At HVN:
├── Expect price to consolidate
├── Look for rejection/absorption
└── Better for reversals
At LVN:
├── Expect fast price movement
├── Don't fight the direction
└── Better for breakouts
Near POC:
├── Institutional fair value
├── Strong magnet effect
└── Watch for volume at POC
```
---
## 🔄 MARKET STATE DETECTION
GRA v5 classifies the market into four states using **CVD + Price Action**:
```
CVD Direction
↑ Rising ↓ Falling
┌─────────────┬─────────────┐
Price > EMA20 │ TREND UP │ RETRACE │
│ (Go Long) │ (Pullback) │
├─────────────┼─────────────┤
Price < EMA20 │ RETRACE │ TREND DN │
│ (Pullback) │ (Go Short) │
└─────────────┴─────────────┘
```
| State | Meaning | Action |
|:------|:--------|:-------|
| **TREND UP** | Buyers in control | Trade long, follow signals |
| **TREND DN** | Sellers in control | Trade short, follow signals |
| **RETRACE** | Pullback against trend | Prepare for continuation entry |
| **RANGE** | No clear direction | Reduce size or wait |
---
## 💎 HIGH CONVICTION UPGRADES
When extra conditions align, GRA v5 marks the signal with a **purple diamond**:
```
HIGH CONVICTION = Base Signal + Strong Delta (65%+) + Strong Volume (2x+) + Imbalance State
```
**Action:** Consider upgrading tier for position sizing:
- B-Tier → A-Tier management
- A-Tier → S-Tier management
---
## 📋 TRADING BY TIER
### 🥇 S-TIER (100+ points)
| | |
|:--|:--|
| **Entry** | Candle close |
| **Target** | IB extension / Next S/R |
| **Management** | HOLD LONGER |
**Rules:**
- Watch next candle - continues? HOLD
- Same tier same direction? ADD
- Opposite tier signal? EXIT on close
- Never close early unless reversal signal
### 🥈 A-TIER (50-99 points)
| | |
|:--|:--|
| **Entry** | Candle close |
| **Target** | 1.5x initial risk minimum |
| **Management** | HOLD A BIT |
**Rules:**
- Target 1.5:1 R:R minimum
- Trail to breakeven after 1:1
- If stalls, take profit
- Upgrade to S-tier management if high conviction
### 🥉 B-TIER (10-49 points)
| | |
|:--|:--|
| **Entry** | Candle close |
| **Target** | 5-10 points MAX |
| **Management** | CLOSE QUICK |
**Rules:**
- Exit in 1-3 candles
- DO NOT hold for more
- Any doubt = EXIT
- Quick scalp mentality
---
## ⚙️ SETTINGS BY INSTRUMENT
| Setting | NQ/ES | YM | GC | BTC |
|:--------|:-----:|:--:|:--:|:---:|
| **Timeframe** | 1-5 min | 1-5 min | 5-15 min | 1-15 min |
| **S-Tier** | 100 pts | 100 pts | 15 pts | 500 pts |
| **A-Tier** | 50 pts | 50 pts | 8 pts | 250 pts |
| **B-Tier** | 10 pts | 15 pts | 3 pts | 50 pts |
| **Min Volume** | 1.3x | 1.3x | 1.5x | 1.3x |
| **Delta %** | 55% | 55% | 58% | 55% |
| **Best Time** | 9:30-11:30 ET | 9:30-11:30 ET | 3-5AM & 8:30-10:30 ET | 24/7 |
---
## 📊 TABLE LEGEND
The info panel displays real-time market data:
| Row | Shows | Colors |
|:----|:------|:-------|
| **Pts** | Candle points | Gold/Green/Yellow by tier |
| **Tier** | S/A/B/X | Gold/Green/Yellow/White |
| **Vol** | Volume ratio | Yellow (2x+) / Green (1.3x+) / Red |
| **Delta** | Buy/Sell % | Green (buy) / Red (sell) / White |
| **CVD** | Direction | Green ▲ / Red ▼ |
| **State** | Market state | Green/Red/Orange/Gray |
| **Sess** | Session | Yellow if active |
| **Zone** | VP zone | Blue/Yellow/Purple |
| **Sig** | Signal | Green/Red if active |
---
## 🔔 ALERTS
| Alert | When | Action |
|:------|:-----|:-------|
| **S-TIER LONG/SHORT** | S-tier signal | Hold longer |
| **A-TIER LONG/SHORT** | A-tier signal | Hold a bit |
| **B-TIER LONG/SHORT** | B-tier signal | Close quick |
| **LON IB BREAK UP/DN** | London IB breakout | Major session move |
| **NY IB BREAK UP/DN** | NY IB breakout | Major session move |
| **HIGH CONVICTION** | Upgraded signal | Consider larger size |
| **LONDON/NY OPEN** | Session start | Get ready |
---
## 💰 THE GOLDEN RULE
> ### **LEAVE EVERY TRADE WITH MONEY**
>
> | Situation | Rule |
> |:----------|:-----|
> | B-Tier | Small win > Small loss |
> | A-Tier | Trail to BE, lock profit |
> | S-Tier | Let it run to target |
> | No Signal | NO TRADE |
> | Wrong Side | EXIT immediately |
>
> **Capital preserved = Trade tomorrow**
---
## ⚠️ DISCLAIMER
> Risk management is **YOUR** responsibility.
> Never risk more than 1-2% per trade.
> Paper trade until you understand the signals.
> Past performance ≠ future results.
---
### Get Rich. Stay Rich. Trade Aggressively. 🚀
**Get Rich Aggressively v5**
*Precision Futures Scalping*
EMA 7/21 + SuperTrend DEFINITIVOhe Ultimate 7/21 Signal: Trend-Filtered by Supertrend 🚀Tired of signals that trade against the main trend? This powerful indicator features the 7/21 EMA Crossover as its core signal, but with a massive upgrade in confirmation:Trend Alignment: Only signals that move in the direction of the Supertrend are confirmed, drastically reducing false entries.Momentum Filter: The ADX DI ensures the move has directional strength.Conviction Check: A Volume Filter validates the signal with market participation.This multi-stage filter provides clean, high-conviction signals for the $7/21$ strategy. The intuitive Informative Panel clearly shows when all conditions are met for a BUY or SELL.Trade with the trend. Trade with conviction.
US100 M5 - ESTRATEGIA GANADORA (Usuario) martinec130103jucale
"Use indicators, closed time window, no more than two trades per day, 45-minute cooldown between trades, strict stop loss."
paigep.llc - SuperMASuperMA is a multi-layered moving-average and candle-coloring system that combines SMA, EMA, and optional HMA logic to help traders visualize trend shifts, pullbacks, and momentum changes in a clean, structured way.
The script includes multiple modules: trend-based moving averages, pullback signals, exit logic, and an optional HMA cross engine.
📌 Core Features
1. Full SMA + EMA Framework
The indicator plots multiple moving averages (8, 9, 13, 20, 50, 200) using both SMA and EMA calculations. Each line automatically colors bullish or bearish based on its relationship to the 200-period baseline.Users can toggle SMAs and EMAs independently for clearer chart control.
2. Main Trend Entry & Exit Logic (8×200 and 8×20)
Built-in crossover logic detects:
Main Entry: SMA 8 crossing above/below EMA 200
Main Exit: SMA 8 and SMA 20 cross (with an option to choose which SMA is treated as the “fast” leg)
A “first exit only” option allows the script to ignore additional exit signals until a new trend regime begins.
3. Pullback Module (20 SMA Interaction)
Pullback entries and exits occur when price crosses the 20 SMA during existing trend conditions.
This includes:
Pullback entries through the 20 SMA
Pullback exits back across the 20 SMA
Labels and candle colors are available for all pullback events.
4. Optional HMA Cross Module
A separate module allows traders to use two Hull Moving Averages (HMA) with customizable:
Lengths
Independent timeframes
Line colors
Cross-based entries and exits
This module has its own events, labels, and optional candle coloring.
5. Advanced Candle Coloring System
Candle coloring is layered in priority order, based on:
Main trend entries
Main exits
HMA entries
HMA exits
Pullback entries
Pullback exits
Trend-only candles (based on SMA 8 relative to EMA 200)
Users may also independently color wicks and borders.
6. Configurable Alerts (Fully Decoupled from Visuals)
Alerts are available for all major events, including:
Main Entries (8×200)
Main Exits (8×20)
Pullback Entries and Exits
HMA Entries and Exits
Bull or Bear Trend candles
Any colored candle event
Alerts can fire on bar close only or intrabar, depending on user preference.
📌 Use Cases
SuperMA helps traders visualize:
Trend direction using SMA/EMA structure
Momentum shifts through HMA crosses
Pullback zones around the 20 SMA
Early regime transitions based on the 8×200 relationship
Candle-level context through color-coded bars
The indicator works across all markets and timeframes.
⚠️ Note
This tool is for visual and analytical assistance only. It does not guarantee future performance and should be combined with additional analysis and risk management.
[ICT] [SMC] True Market Structure [TDT]Introduction
The True Market Structure indicator is designed to help Smart Money Concepts (SMC) and ICT traders visualize the "True" mechanical structure of the market. Unlike standard ZigZag indicators that often repaint or react to minor noise, this script utilizes a strict Fractal Swing algorithm to identify valid Highs and Lows.
It automatically maps out the market trend by distinguishing between BOS (Break of Structure) for trend continuation and CHoCH (Change of Character) for trend reversals, while highlighting the "Protected" or "Strong" structural points.
How It Works
The indicator relies on a generic fractal calculation (Swing High/Low) determined by the user-defined length.
Trend Identification: The script tracks a state machine (Bullish/Bearish).
Weak Structure (Target): In a bullish trend, the recent High is the "Weak High" (the target to break).
Strong Structure (Protected): The Low responsible for breaking the High becomes the "Strong Low."
BOS vs. CHoCH:
BOS: When price breaks a Weak High (in an uptrend), it confirms continuation.
CHoCH: When price breaks a Strong Low (in an uptrend), it signals a potential reversal.
Key Features
True Fractal Detection: Uses a centered lookback period (Input: Swing Fractal Length) to find significant pivot points.
Confirmation Modes: Choose between candle Close (more conservative, filters wicks) or High/Low (more aggressive) for structure breaks.
Structure Mapping:
Solid Lines: Represent BOS (Trend Continuation).
Dashed Lines: Represent CHoCH (Trend Reversal).
Origin Dots (Protected Levels):
These dots mark the exact swing point that caused the break.
Usage: In an uptrend, the dot marks the Strong Low. If price closes below this dot, the trend flips.
Settings Guide
Swing Fractal Length: The lookback period to define a Swing High/Low.
Default: 3 (Standard ICT Intermediate Term High/Low).
Increase this number to see higher timeframe structure (e.g., set to 10-20 for major swings).
Break Confirmation:
Close: Price body must close beyond the structure level to confirm a break.
High/Low: A wick breaking the level is sufficient.
Visuals: Toggle lines and dots on/off and customize colors to fit your chart theme.
How to Use (Trading Strategy)
Trend Following: Wait for a BOS (Solid Line). Identify the Origin Dot created by that move. This is your "Protected Low/High." Look for entries (FVG/Order Blocks) between the current price and that Dot.
Reversal Trading: Watch for a CHoCH (Dashed Line). This indicates the "Strong Structure" has failed, and the bias has shifted.
Stop Placement: The Origin Dots serve as excellent invalidation points for Stop Losses.
Disclaimer
This tool is for educational purposes and market analysis only. It does not provide financial advice or guarantee future results. Always manage your risk.
EMA Stack Background HighlighterThis is a simple script that highlights my backround when my criteria for my context timeframe is met, specifically, price is above the 10 EMA, the 10 is above the 20, and the 20 is above the 50 for green and vice versa for red. I use this in a multi timeframe approach similar to mentfx's EVC criteria
