Williams VIX For Bottoms [DCD]Williams VIX Original - Authentic Volatility Fear Gauge
What This Indicator Does
The Williams VIX Fix measures market fear by calculating how far current lows deviate from recent highs, identifying potential market bottoms during high volatility periods. This implementation provides Larry Williams' original formula in its purest form.
How It Works
Core Formula:
VIX Fix = ((Highest High over 22 periods - Current Low) / Highest High over 22 periods) × 100
The calculation process:
Measures Relative Distance: Compares current low to highest high over lookback period
Converts to Percentage: Normalizes values for cross-market comparison
Applies Statistical Analysis: Uses Bollinger Bands (2 std dev) around VIX Fix values
Filters with Percentiles: 85th percentile threshold removes noise
Signal Generation
Green Flash Signals trigger when either condition is met:
VIX Fix exceeds upper Bollinger Band (2 standard deviations above 20-period MA)
VIX Fix exceeds Range High (85th percentile of recent values)
This dual-condition approach reduces false signals while capturing genuine volatility spikes.
What Makes This Original
Pure Formula Implementation: Uses Williams' exact original calculation without modifications
Dual Confirmation System: Combines Bollinger Bands with percentile analysis
Professional Visualization: Histogram display, background highlighting, and live value table
Comprehensive Alerts: Signal start/end notifications plus Green Flash alerts
How to Use
Primary Purpose: Spot high-probability reversal zones during market fear climaxes
Signal Interpretation:
Green triangle + background highlight = High volatility reversal zone
Higher VIX Fix values = Stronger fear/better reversal potential
Use with price action confirmation for best results
Optimal Settings:
Timeframes: 4H, Daily, Weekly
Markets: All (stocks, crypto, forex, commodities)
Combine with support levels and candlestick patterns
Key Parameters:
VIX Fix Length (22): Lookback period for highest high
Std Dev Multiplier (2.0): Bollinger Band sensitivity
Percentile High (0.85): Only top 15% of readings trigger signals
The VIX Fix excels at identifying market fear climaxes that coincide with significant price bottoms, making it valuable for swing traders seeking high-probability entries during market stress.
Cerca negli script per "weekly"
ATR Rangeshows the high and low of the given range of the asset base on the daily atr fixed by the weekly trend.
Mongoose EMA Ribbon — Pro EditionMongoose EMA Ribbon — Pro Edition
The Mongoose EMA Ribbon is a precision tool designed to support directional bias, trend integrity, and momentum alignment through a structured multi-EMA system. It is built for traders seeking clarity across high-timeframe trend conditions without sacrificing speed or simplicity.
Key Features:
Five customizable EMAs optimized for layered ribbon analysis
Configurable color logic for clean visual separation
Built-in ribbon compression and expansion visibility
Support for ribbon-based trend continuation zones
Optional label and visual tag for real-time trend state
Applications:
Identify trend strength and reversals with ribbon alignment
Detect compression zones that precede directional moves
Support discretionary or system-based trading strategies
Integrates well with price structure and macro overlays
This script is part of the Mongoose Capital toolkit and was developed to meet internal standards for clarity, execution readiness, and cross-asset compatibility.
Version: Pro Edition
Timeframes: Optimized for 1H, 4H, Daily, Weekly
Tensor Market Analysis Engine (TMAE)# Tensor Market Analysis Engine (TMAE)
## Advanced Multi-Dimensional Mathematical Analysis System
*Where Quantum Mathematics Meets Market Structure*
---
## 🎓 THEORETICAL FOUNDATION
The Tensor Market Analysis Engine represents a revolutionary synthesis of three cutting-edge mathematical frameworks that have never before been combined for comprehensive market analysis. This indicator transcends traditional technical analysis by implementing advanced mathematical concepts from quantum mechanics, information theory, and fractal geometry.
### 🌊 Multi-Dimensional Volatility with Jump Detection
**Hawkes Process Implementation:**
The TMAE employs a sophisticated Hawkes process approximation for detecting self-exciting market jumps. Unlike traditional volatility measures that treat price movements as independent events, the Hawkes process recognizes that market shocks cluster and exhibit memory effects.
**Mathematical Foundation:**
```
Intensity λ(t) = μ + Σ α(t - Tᵢ)
```
Where market jumps at times Tᵢ increase the probability of future jumps through the decay function α, controlled by the Hawkes Decay parameter (0.5-0.99).
**Mahalanobis Distance Calculation:**
The engine calculates volatility jumps using multi-dimensional Mahalanobis distance across up to 5 volatility dimensions:
- **Dimension 1:** Price volatility (standard deviation of returns)
- **Dimension 2:** Volume volatility (normalized volume fluctuations)
- **Dimension 3:** Range volatility (high-low spread variations)
- **Dimension 4:** Correlation volatility (price-volume relationship changes)
- **Dimension 5:** Microstructure volatility (intrabar positioning analysis)
This creates a volatility state vector that captures market behavior impossible to detect with traditional single-dimensional approaches.
### 📐 Hurst Exponent Regime Detection
**Fractal Market Hypothesis Integration:**
The TMAE implements advanced Rescaled Range (R/S) analysis to calculate the Hurst exponent in real-time, providing dynamic regime classification:
- **H > 0.6:** Trending (persistent) markets - momentum strategies optimal
- **H < 0.4:** Mean-reverting (anti-persistent) markets - contrarian strategies optimal
- **H ≈ 0.5:** Random walk markets - breakout strategies preferred
**Adaptive R/S Analysis:**
Unlike static implementations, the TMAE uses adaptive windowing that adjusts to market conditions:
```
H = log(R/S) / log(n)
```
Where R is the range of cumulative deviations and S is the standard deviation over period n.
**Dynamic Regime Classification:**
The system employs hysteresis to prevent regime flipping, requiring sustained Hurst values before regime changes are confirmed. This prevents false signals during transitional periods.
### 🔄 Transfer Entropy Analysis
**Information Flow Quantification:**
Transfer entropy measures the directional flow of information between price and volume, revealing lead-lag relationships that indicate future price movements:
```
TE(X→Y) = Σ p(yₜ₊₁, yₜ, xₜ) log
```
**Causality Detection:**
- **Volume → Price:** Indicates accumulation/distribution phases
- **Price → Volume:** Suggests retail participation or momentum chasing
- **Balanced Flow:** Market equilibrium or transition periods
The system analyzes multiple lag periods (2-20 bars) to capture both immediate and structural information flows.
---
## 🔧 COMPREHENSIVE INPUT SYSTEM
### Core Parameters Group
**Primary Analysis Window (10-100, Default: 50)**
The fundamental lookback period affecting all calculations. Optimization by timeframe:
- **1-5 minute charts:** 20-30 (rapid adaptation to micro-movements)
- **15 minute-1 hour:** 30-50 (balanced responsiveness and stability)
- **4 hour-daily:** 50-100 (smooth signals, reduced noise)
- **Asset-specific:** Cryptocurrency 20-35, Stocks 35-50, Forex 40-60
**Signal Sensitivity (0.1-2.0, Default: 0.7)**
Master control affecting all threshold calculations:
- **Conservative (0.3-0.6):** High-quality signals only, fewer false positives
- **Balanced (0.7-1.0):** Optimal risk-reward ratio for most trading styles
- **Aggressive (1.1-2.0):** Maximum signal frequency, requires careful filtering
**Signal Generation Mode:**
- **Aggressive:** Any component signals (highest frequency)
- **Confluence:** 2+ components agree (balanced approach)
- **Conservative:** All 3 components align (highest quality)
### Volatility Jump Detection Group
**Volatility Dimensions (2-5, Default: 3)**
Determines the mathematical space complexity:
- **2D:** Price + Volume volatility (suitable for clean markets)
- **3D:** + Range volatility (optimal for most conditions)
- **4D:** + Correlation volatility (advanced multi-asset analysis)
- **5D:** + Microstructure volatility (maximum sensitivity)
**Jump Detection Threshold (1.5-4.0σ, Default: 3.0σ)**
Standard deviations required for volatility jump classification:
- **Cryptocurrency:** 2.0-2.5σ (naturally volatile)
- **Stock Indices:** 2.5-3.0σ (moderate volatility)
- **Forex Major Pairs:** 3.0-3.5σ (typically stable)
- **Commodities:** 2.0-3.0σ (varies by commodity)
**Jump Clustering Decay (0.5-0.99, Default: 0.85)**
Hawkes process memory parameter:
- **0.5-0.7:** Fast decay (jumps treated as independent)
- **0.8-0.9:** Moderate clustering (realistic market behavior)
- **0.95-0.99:** Strong clustering (crisis/event-driven markets)
### Hurst Exponent Analysis Group
**Calculation Method Options:**
- **Classic R/S:** Original Rescaled Range (fast, simple)
- **Adaptive R/S:** Dynamic windowing (recommended for trading)
- **DFA:** Detrended Fluctuation Analysis (best for noisy data)
**Trending Threshold (0.55-0.8, Default: 0.60)**
Hurst value defining persistent market behavior:
- **0.55-0.60:** Weak trend persistence
- **0.65-0.70:** Clear trending behavior
- **0.75-0.80:** Strong momentum regimes
**Mean Reversion Threshold (0.2-0.45, Default: 0.40)**
Hurst value defining anti-persistent behavior:
- **0.35-0.45:** Weak mean reversion
- **0.25-0.35:** Clear ranging behavior
- **0.15-0.25:** Strong reversion tendency
### Transfer Entropy Parameters Group
**Information Flow Analysis:**
- **Price-Volume:** Classic flow analysis for accumulation/distribution
- **Price-Volatility:** Risk flow analysis for sentiment shifts
- **Multi-Timeframe:** Cross-timeframe causality detection
**Maximum Lag (2-20, Default: 5)**
Causality detection window:
- **2-5 bars:** Immediate causality (scalping)
- **5-10 bars:** Short-term flow (day trading)
- **10-20 bars:** Structural flow (swing trading)
**Significance Threshold (0.05-0.3, Default: 0.15)**
Minimum entropy for signal generation:
- **0.05-0.10:** Detect subtle information flows
- **0.10-0.20:** Clear causality only
- **0.20-0.30:** Very strong flows only
---
## 🎨 ADVANCED VISUAL SYSTEM
### Tensor Volatility Field Visualization
**Five-Layer Resonance Bands:**
The tensor field creates dynamic support/resistance zones that expand and contract based on mathematical field strength:
- **Core Layer (Purple):** Primary tensor field with highest intensity
- **Layer 2 (Neutral):** Secondary mathematical resonance
- **Layer 3 (Info Blue):** Tertiary harmonic frequencies
- **Layer 4 (Warning Gold):** Outer field boundaries
- **Layer 5 (Success Green):** Maximum field extension
**Field Strength Calculation:**
```
Field Strength = min(3.0, Mahalanobis Distance × Tensor Intensity)
```
The field amplitude adjusts to ATR and mathematical distance, creating dynamic zones that respond to market volatility.
**Radiation Line Network:**
During active tensor states, the system projects directional radiation lines showing field energy distribution:
- **8 Directional Rays:** Complete angular coverage
- **Tapering Segments:** Progressive transparency for natural visual flow
- **Pulse Effects:** Enhanced visualization during volatility jumps
### Dimensional Portal System
**Portal Mathematics:**
Dimensional portals visualize regime transitions using category theory principles:
- **Green Portals (◉):** Trending regime detection (appear below price for support)
- **Red Portals (◎):** Mean-reverting regime (appear above price for resistance)
- **Yellow Portals (○):** Random walk regime (neutral positioning)
**Tensor Trail Effects:**
Each portal generates 8 trailing particles showing mathematical momentum:
- **Large Particles (●):** Strong mathematical signal
- **Medium Particles (◦):** Moderate signal strength
- **Small Particles (·):** Weak signal continuation
- **Micro Particles (˙):** Signal dissipation
### Information Flow Streams
**Particle Stream Visualization:**
Transfer entropy creates flowing particle streams indicating information direction:
- **Upward Streams:** Volume leading price (accumulation phases)
- **Downward Streams:** Price leading volume (distribution phases)
- **Stream Density:** Proportional to information flow strength
**15-Particle Evolution:**
Each stream contains 15 particles with progressive sizing and transparency, creating natural flow visualization that makes information transfer immediately apparent.
### Fractal Matrix Grid System
**Multi-Timeframe Fractal Levels:**
The system calculates and displays fractal highs/lows across five Fibonacci periods:
- **8-Period:** Short-term fractal structure
- **13-Period:** Intermediate-term patterns
- **21-Period:** Primary swing levels
- **34-Period:** Major structural levels
- **55-Period:** Long-term fractal boundaries
**Triple-Layer Visualization:**
Each fractal level uses three-layer rendering:
- **Shadow Layer:** Widest, darkest foundation (width 5)
- **Glow Layer:** Medium white core line (width 3)
- **Tensor Layer:** Dotted mathematical overlay (width 1)
**Intelligent Labeling System:**
Smart spacing prevents label overlap using ATR-based minimum distances. Labels include:
- **Fractal Period:** Time-based identification
- **Topological Class:** Mathematical complexity rating (0, I, II, III)
- **Price Level:** Exact fractal price
- **Mahalanobis Distance:** Current mathematical field strength
- **Hurst Exponent:** Current regime classification
- **Anomaly Indicators:** Visual strength representations (○ ◐ ● ⚡)
### Wick Pressure Analysis
**Rejection Level Mathematics:**
The system analyzes candle wick patterns to project future pressure zones:
- **Upper Wick Analysis:** Identifies selling pressure and resistance zones
- **Lower Wick Analysis:** Identifies buying pressure and support zones
- **Pressure Projection:** Extends lines forward based on mathematical probability
**Multi-Layer Glow Effects:**
Wick pressure lines use progressive transparency (1-8 layers) creating natural glow effects that make pressure zones immediately visible without cluttering the chart.
### Enhanced Regime Background
**Dynamic Intensity Mapping:**
Background colors reflect mathematical regime strength:
- **Deep Transparency (98% alpha):** Subtle regime indication
- **Pulse Intensity:** Based on regime strength calculation
- **Color Coding:** Green (trending), Red (mean-reverting), Neutral (random)
**Smoothing Integration:**
Regime changes incorporate 10-bar smoothing to prevent background flicker while maintaining responsiveness to genuine regime shifts.
### Color Scheme System
**Six Professional Themes:**
- **Dark (Default):** Professional trading environment optimization
- **Light:** High ambient light conditions
- **Classic:** Traditional technical analysis appearance
- **Neon:** High-contrast visibility for active trading
- **Neutral:** Minimal distraction focus
- **Bright:** Maximum visibility for complex setups
Each theme maintains mathematical accuracy while optimizing visual clarity for different trading environments and personal preferences.
---
## 📊 INSTITUTIONAL-GRADE DASHBOARD
### Tensor Field Status Section
**Field Strength Display:**
Real-time Mahalanobis distance calculation with dynamic emoji indicators:
- **⚡ (Lightning):** Extreme field strength (>1.5× threshold)
- **● (Solid Circle):** Strong field activity (>1.0× threshold)
- **○ (Open Circle):** Normal field state
**Signal Quality Rating:**
Democratic algorithm assessment:
- **ELITE:** All 3 components aligned (highest probability)
- **STRONG:** 2 components aligned (good probability)
- **GOOD:** 1 component active (moderate probability)
- **WEAK:** No clear component signals
**Threshold and Anomaly Monitoring:**
- **Threshold Display:** Current mathematical threshold setting
- **Anomaly Level (0-100%):** Combined volatility and volume spike measurement
- **>70%:** High anomaly (red warning)
- **30-70%:** Moderate anomaly (orange caution)
- **<30%:** Normal conditions (green confirmation)
### Tensor State Analysis Section
**Mathematical State Classification:**
- **↑ BULL (Tensor State +1):** Trending regime with bullish bias
- **↓ BEAR (Tensor State -1):** Mean-reverting regime with bearish bias
- **◈ SUPER (Tensor State 0):** Random walk regime (neutral)
**Visual State Gauge:**
Five-circle progression showing tensor field polarity:
- **🟢🟢🟢⚪⚪:** Strong bullish mathematical alignment
- **⚪⚪🟡⚪⚪:** Neutral/transitional state
- **⚪⚪🔴🔴🔴:** Strong bearish mathematical alignment
**Trend Direction and Phase Analysis:**
- **📈 BULL / 📉 BEAR / ➡️ NEUTRAL:** Primary trend classification
- **🌪️ CHAOS:** Extreme information flow (>2.0 flow strength)
- **⚡ ACTIVE:** Strong information flow (1.0-2.0 flow strength)
- **😴 CALM:** Low information flow (<1.0 flow strength)
### Trading Signals Section
**Real-Time Signal Status:**
- **🟢 ACTIVE / ⚪ INACTIVE:** Long signal availability
- **🔴 ACTIVE / ⚪ INACTIVE:** Short signal availability
- **Components (X/3):** Active algorithmic components
- **Mode Display:** Current signal generation mode
**Signal Strength Visualization:**
Color-coded component count:
- **Green:** 3/3 components (maximum confidence)
- **Aqua:** 2/3 components (good confidence)
- **Orange:** 1/3 components (moderate confidence)
- **Gray:** 0/3 components (no signals)
### Performance Metrics Section
**Win Rate Monitoring:**
Estimated win rates based on signal quality with emoji indicators:
- **🔥 (Fire):** ≥60% estimated win rate
- **👍 (Thumbs Up):** 45-59% estimated win rate
- **⚠️ (Warning):** <45% estimated win rate
**Mathematical Metrics:**
- **Hurst Exponent:** Real-time fractal dimension (0.000-1.000)
- **Information Flow:** Volume/price leading indicators
- **📊 VOL:** Volume leading price (accumulation/distribution)
- **💰 PRICE:** Price leading volume (momentum/speculation)
- **➖ NONE:** Balanced information flow
- **Volatility Classification:**
- **🔥 HIGH:** Above 1.5× jump threshold
- **📊 NORM:** Normal volatility range
- **😴 LOW:** Below 0.5× jump threshold
### Market Structure Section (Large Dashboard)
**Regime Classification:**
- **📈 TREND:** Hurst >0.6, momentum strategies optimal
- **🔄 REVERT:** Hurst <0.4, contrarian strategies optimal
- **🎲 RANDOM:** Hurst ≈0.5, breakout strategies preferred
**Mathematical Field Analysis:**
- **Dimensions:** Current volatility space complexity (2D-5D)
- **Hawkes λ (Lambda):** Self-exciting jump intensity (0.00-1.00)
- **Jump Status:** 🚨 JUMP (active) / ✅ NORM (normal)
### Settings Summary Section (Large Dashboard)
**Active Configuration Display:**
- **Sensitivity:** Current master sensitivity setting
- **Lookback:** Primary analysis window
- **Theme:** Active color scheme
- **Method:** Hurst calculation method (Classic R/S, Adaptive R/S, DFA)
**Dashboard Sizing Options:**
- **Small:** Essential metrics only (mobile/small screens)
- **Normal:** Balanced information density (standard desktop)
- **Large:** Maximum detail (multi-monitor setups)
**Position Options:**
- **Top Right:** Standard placement (avoids price action)
- **Top Left:** Wide chart optimization
- **Bottom Right:** Recent price focus (scalping)
- **Bottom Left:** Maximum price visibility (swing trading)
---
## 🎯 SIGNAL GENERATION LOGIC
### Multi-Component Convergence System
**Component Signal Architecture:**
The TMAE generates signals through sophisticated component analysis rather than simple threshold crossing:
**Volatility Component:**
- **Jump Detection:** Mahalanobis distance threshold breach
- **Hawkes Intensity:** Self-exciting process activation (>0.2)
- **Multi-dimensional:** Considers all volatility dimensions simultaneously
**Hurst Regime Component:**
- **Trending Markets:** Price above SMA-20 with positive momentum
- **Mean-Reverting Markets:** Price at Bollinger Band extremes
- **Random Markets:** Bollinger squeeze breakouts with directional confirmation
**Transfer Entropy Component:**
- **Volume Leadership:** Information flow from volume to price
- **Volume Spike:** Volume 110%+ above 20-period average
- **Flow Significance:** Above entropy threshold with directional bias
### Democratic Signal Weighting
**Signal Mode Implementation:**
- **Aggressive Mode:** Any single component triggers signal
- **Confluence Mode:** Minimum 2 components must agree
- **Conservative Mode:** All 3 components must align
**Momentum Confirmation:**
All signals require momentum confirmation:
- **Long Signals:** RSI >50 AND price >EMA-9
- **Short Signals:** RSI <50 AND price 0.6):**
- **Increase Sensitivity:** Catch momentum continuation
- **Lower Mean Reversion Threshold:** Avoid counter-trend signals
- **Emphasize Volume Leadership:** Institutional accumulation/distribution
- **Tensor Field Focus:** Use expansion for trend continuation
- **Signal Mode:** Aggressive or Confluence for trend following
**Range-Bound Markets (Hurst <0.4):**
- **Decrease Sensitivity:** Avoid false breakouts
- **Lower Trending Threshold:** Quick regime recognition
- **Focus on Price Leadership:** Retail sentiment extremes
- **Fractal Grid Emphasis:** Support/resistance trading
- **Signal Mode:** Conservative for high-probability reversals
**Volatile Markets (High Jump Frequency):**
- **Increase Hawkes Decay:** Recognize event clustering
- **Higher Jump Threshold:** Avoid noise signals
- **Maximum Dimensions:** Capture full volatility complexity
- **Reduce Position Sizing:** Risk management adaptation
- **Enhanced Visuals:** Maximum information for rapid decisions
**Low Volatility Markets (Low Jump Frequency):**
- **Decrease Jump Threshold:** Capture subtle movements
- **Lower Hawkes Decay:** Treat moves as independent
- **Reduce Dimensions:** Simplify analysis
- **Increase Position Sizing:** Capitalize on compressed volatility
- **Minimal Visuals:** Reduce distraction in quiet markets
---
## 🚀 ADVANCED TRADING STRATEGIES
### The Mathematical Convergence Method
**Entry Protocol:**
1. **Fractal Grid Approach:** Monitor price approaching significant fractal levels
2. **Tensor Field Confirmation:** Verify field expansion supporting direction
3. **Portal Signal:** Wait for dimensional portal appearance
4. **ELITE/STRONG Quality:** Only trade highest quality mathematical signals
5. **Component Consensus:** Confirm 2+ components agree in Confluence mode
**Example Implementation:**
- Price approaching 21-period fractal high
- Tensor field expanding upward (bullish mathematical alignment)
- Green portal appears below price (trending regime confirmation)
- ELITE quality signal with 3/3 components active
- Enter long position with stop below fractal level
**Risk Management:**
- **Stop Placement:** Below/above fractal level that generated signal
- **Position Sizing:** Based on Mahalanobis distance (higher distance = smaller size)
- **Profit Targets:** Next fractal level or tensor field resistance
### The Regime Transition Strategy
**Regime Change Detection:**
1. **Monitor Hurst Exponent:** Watch for persistent moves above/below thresholds
2. **Portal Color Change:** Regime transitions show different portal colors
3. **Background Intensity:** Increasing regime background intensity
4. **Mathematical Confirmation:** Wait for regime confirmation (hysteresis)
**Trading Implementation:**
- **Trending Transitions:** Trade momentum breakouts, follow trend
- **Mean Reversion Transitions:** Trade range boundaries, fade extremes
- **Random Transitions:** Trade breakouts with tight stops
**Advanced Techniques:**
- **Multi-Timeframe:** Confirm regime on higher timeframe
- **Early Entry:** Enter on regime transition rather than confirmation
- **Regime Strength:** Larger positions during strong regime signals
### The Information Flow Momentum Strategy
**Flow Detection Protocol:**
1. **Monitor Transfer Entropy:** Watch for significant information flow shifts
2. **Volume Leadership:** Strong edge when volume leads price
3. **Flow Acceleration:** Increasing flow strength indicates momentum
4. **Directional Confirmation:** Ensure flow aligns with intended trade direction
**Entry Signals:**
- **Volume → Price Flow:** Enter during accumulation/distribution phases
- **Price → Volume Flow:** Enter on momentum confirmation breaks
- **Flow Reversal:** Counter-trend entries when flow reverses
**Optimization:**
- **Scalping:** Use immediate flow detection (2-5 bar lag)
- **Swing Trading:** Use structural flow (10-20 bar lag)
- **Multi-Asset:** Compare flow between correlated assets
### The Tensor Field Expansion Strategy
**Field Mathematics:**
The tensor field expansion indicates mathematical pressure building in market structure:
**Expansion Phases:**
1. **Compression:** Field contracts, volatility decreases
2. **Tension Building:** Mathematical pressure accumulates
3. **Expansion:** Field expands rapidly with directional movement
4. **Resolution:** Field stabilizes at new equilibrium
**Trading Applications:**
- **Compression Trading:** Prepare for breakout during field contraction
- **Expansion Following:** Trade direction of field expansion
- **Reversion Trading:** Fade extreme field expansion
- **Multi-Dimensional:** Consider all field layers for confirmation
### The Hawkes Process Event Strategy
**Self-Exciting Jump Trading:**
Understanding that market shocks cluster and create follow-on opportunities:
**Jump Sequence Analysis:**
1. **Initial Jump:** First volatility jump detected
2. **Clustering Phase:** Hawkes intensity remains elevated
3. **Follow-On Opportunities:** Additional jumps more likely
4. **Decay Period:** Intensity gradually decreases
**Implementation:**
- **Jump Confirmation:** Wait for mathematical jump confirmation
- **Direction Assessment:** Use other components for direction
- **Clustering Trades:** Trade subsequent moves during high intensity
- **Decay Exit:** Exit positions as Hawkes intensity decays
### The Fractal Confluence System
**Multi-Timeframe Fractal Analysis:**
Combining fractal levels across different periods for high-probability zones:
**Confluence Zones:**
- **Double Confluence:** 2 fractal levels align
- **Triple Confluence:** 3+ fractal levels cluster
- **Mathematical Confirmation:** Tensor field supports the level
- **Information Flow:** Transfer entropy confirms direction
**Trading Protocol:**
1. **Identify Confluence:** Find 2+ fractal levels within 1 ATR
2. **Mathematical Support:** Verify tensor field alignment
3. **Signal Quality:** Wait for STRONG or ELITE signal
4. **Risk Definition:** Use fractal level for stop placement
5. **Profit Targeting:** Next major fractal confluence zone
---
## ⚠️ COMPREHENSIVE RISK MANAGEMENT
### Mathematical Position Sizing
**Mahalanobis Distance Integration:**
Position size should inversely correlate with mathematical field strength:
```
Position Size = Base Size × (Threshold / Mahalanobis Distance)
```
**Risk Scaling Matrix:**
- **Low Field Strength (<2.0):** Standard position sizing
- **Moderate Field Strength (2.0-3.0):** 75% position sizing
- **High Field Strength (3.0-4.0):** 50% position sizing
- **Extreme Field Strength (>4.0):** 25% position sizing or no trade
### Signal Quality Risk Adjustment
**Quality-Based Position Sizing:**
- **ELITE Signals:** 100% of planned position size
- **STRONG Signals:** 75% of planned position size
- **GOOD Signals:** 50% of planned position size
- **WEAK Signals:** No position or paper trading only
**Component Agreement Scaling:**
- **3/3 Components:** Full position size
- **2/3 Components:** 75% position size
- **1/3 Components:** 50% position size or skip trade
### Regime-Adaptive Risk Management
**Trending Market Risk:**
- **Wider Stops:** Allow for trend continuation
- **Trend Following:** Trade with regime direction
- **Higher Position Size:** Trend probability advantage
- **Momentum Stops:** Trail stops based on momentum indicators
**Mean-Reverting Market Risk:**
- **Tighter Stops:** Quick exits on trend continuation
- **Contrarian Positioning:** Trade against extremes
- **Smaller Position Size:** Higher reversal failure rate
- **Level-Based Stops:** Use fractal levels for stops
**Random Market Risk:**
- **Breakout Focus:** Trade only clear breakouts
- **Tight Initial Stops:** Quick exit if breakout fails
- **Reduced Frequency:** Skip marginal setups
- **Range-Based Targets:** Profit targets at range boundaries
### Volatility-Adaptive Risk Controls
**High Volatility Periods:**
- **Reduced Position Size:** Account for wider price swings
- **Wider Stops:** Avoid noise-based exits
- **Lower Frequency:** Skip marginal setups
- **Faster Exits:** Take profits more quickly
**Low Volatility Periods:**
- **Standard Position Size:** Normal risk parameters
- **Tighter Stops:** Take advantage of compressed ranges
- **Higher Frequency:** Trade more setups
- **Extended Targets:** Allow for compressed volatility expansion
### Multi-Timeframe Risk Alignment
**Higher Timeframe Trend:**
- **With Trend:** Standard or increased position size
- **Against Trend:** Reduced position size or skip
- **Neutral Trend:** Standard position size with tight management
**Risk Hierarchy:**
1. **Primary:** Current timeframe signal quality
2. **Secondary:** Higher timeframe trend alignment
3. **Tertiary:** Mathematical field strength
4. **Quaternary:** Market regime classification
---
## 📚 EDUCATIONAL VALUE AND MATHEMATICAL CONCEPTS
### Advanced Mathematical Concepts
**Tensor Analysis in Markets:**
The TMAE introduces traders to tensor analysis, a branch of mathematics typically reserved for physics and advanced engineering. Tensors provide a framework for understanding multi-dimensional market relationships that scalar and vector analysis cannot capture.
**Information Theory Applications:**
Transfer entropy implementation teaches traders about information flow in markets, a concept from information theory that quantifies directional causality between variables. This provides intuition about market microstructure and participant behavior.
**Fractal Geometry in Trading:**
The Hurst exponent calculation exposes traders to fractal geometry concepts, helping understand that markets exhibit self-similar patterns across multiple timeframes. This mathematical insight transforms how traders view market structure.
**Stochastic Process Theory:**
The Hawkes process implementation introduces concepts from stochastic process theory, specifically self-exciting point processes. This provides mathematical framework for understanding why market events cluster and exhibit memory effects.
### Learning Progressive Complexity
**Beginner Mathematical Concepts:**
- **Volatility Dimensions:** Understanding multi-dimensional analysis
- **Regime Classification:** Learning market personality types
- **Signal Democracy:** Algorithmic consensus building
- **Visual Mathematics:** Interpreting mathematical concepts visually
**Intermediate Mathematical Applications:**
- **Mahalanobis Distance:** Statistical distance in multi-dimensional space
- **Rescaled Range Analysis:** Fractal dimension measurement
- **Information Entropy:** Quantifying uncertainty and causality
- **Field Theory:** Understanding mathematical fields in market context
**Advanced Mathematical Integration:**
- **Tensor Field Dynamics:** Multi-dimensional market force analysis
- **Stochastic Self-Excitation:** Event clustering and memory effects
- **Categorical Composition:** Mathematical signal combination theory
- **Topological Market Analysis:** Understanding market shape and connectivity
### Practical Mathematical Intuition
**Developing Market Mathematics Intuition:**
The TMAE serves as a bridge between abstract mathematical concepts and practical trading applications. Traders develop intuitive understanding of:
- **How markets exhibit mathematical structure beneath apparent randomness**
- **Why multi-dimensional analysis reveals patterns invisible to single-variable approaches**
- **How information flows through markets in measurable, predictable ways**
- **Why mathematical models provide probabilistic edges rather than certainties**
---
## 🔬 IMPLEMENTATION AND OPTIMIZATION
### Getting Started Protocol
**Phase 1: Observation (Week 1)**
1. **Apply with defaults:** Use standard settings on your primary trading timeframe
2. **Study visual elements:** Learn to interpret tensor fields, portals, and streams
3. **Monitor dashboard:** Observe how metrics change with market conditions
4. **No trading:** Focus entirely on pattern recognition and understanding
**Phase 2: Pattern Recognition (Week 2-3)**
1. **Identify signal patterns:** Note what market conditions produce different signal qualities
2. **Regime correlation:** Observe how Hurst regimes affect signal performance
3. **Visual confirmation:** Learn to read tensor field expansion and portal signals
4. **Component analysis:** Understand which components drive signals in different markets
**Phase 3: Parameter Optimization (Week 4-5)**
1. **Asset-specific tuning:** Adjust parameters for your specific trading instrument
2. **Timeframe optimization:** Fine-tune for your preferred trading timeframe
3. **Sensitivity adjustment:** Balance signal frequency with quality
4. **Visual customization:** Optimize colors and intensity for your trading environment
**Phase 4: Live Implementation (Week 6+)**
1. **Paper trading:** Test signals with hypothetical trades
2. **Small position sizing:** Begin with minimal risk during learning phase
3. **Performance tracking:** Monitor actual vs. expected signal performance
4. **Continuous optimization:** Refine settings based on real performance data
### Performance Monitoring System
**Signal Quality Tracking:**
- **ELITE Signal Win Rate:** Track highest quality signals separately
- **Component Performance:** Monitor which components provide best signals
- **Regime Performance:** Analyze performance across different market regimes
- **Timeframe Analysis:** Compare performance across different session times
**Mathematical Metric Correlation:**
- **Field Strength vs. Performance:** Higher field strength should correlate with better performance
- **Component Agreement vs. Win Rate:** More component agreement should improve win rates
- **Regime Alignment vs. Success:** Trading with mathematical regime should outperform
### Continuous Optimization Process
**Monthly Review Protocol:**
1. **Performance Analysis:** Review win rates, profit factors, and maximum drawdown
2. **Parameter Assessment:** Evaluate if current settings remain optimal
3. **Market Adaptation:** Adjust for changes in market character or volatility
4. **Component Weighting:** Consider if certain components should receive more/less emphasis
**Quarterly Deep Analysis:**
1. **Mathematical Model Validation:** Verify that mathematical relationships remain valid
2. **Regime Distribution:** Analyze time spent in different market regimes
3. **Signal Evolution:** Track how signal characteristics change over time
4. **Correlation Analysis:** Monitor correlations between different mathematical components
---
## 🌟 UNIQUE INNOVATIONS AND CONTRIBUTIONS
### Revolutionary Mathematical Integration
**First-Ever Implementations:**
1. **Multi-Dimensional Volatility Tensor:** First indicator to implement true tensor analysis for market volatility
2. **Real-Time Hawkes Process:** First trading implementation of self-exciting point processes
3. **Transfer Entropy Trading Signals:** First practical application of information theory for trade generation
4. **Democratic Component Voting:** First algorithmic consensus system for signal generation
5. **Fractal-Projected Signal Quality:** First system to predict signal quality at future price levels
### Advanced Visualization Innovations
**Mathematical Visualization Breakthroughs:**
- **Tensor Field Radiation:** Visual representation of mathematical field energy
- **Dimensional Portal System:** Category theory visualization for regime transitions
- **Information Flow Streams:** Real-time visual display of market information transfer
- **Multi-Layer Fractal Grid:** Intelligent spacing and projection system
- **Regime Intensity Mapping:** Dynamic background showing mathematical regime strength
### Practical Trading Innovations
**Trading System Advances:**
- **Quality-Weighted Signal Generation:** Signals rated by mathematical confidence
- **Regime-Adaptive Strategy Selection:** Automatic strategy optimization based on market personality
- **Anti-Spam Signal Protection:** Mathematical prevention of signal clustering
- **Component Performance Tracking:** Real-time monitoring of algorithmic component success
- **Field-Strength Position Sizing:** Mathematical volatility integration for risk management
---
## ⚖️ RESPONSIBLE USAGE AND LIMITATIONS
### Mathematical Model Limitations
**Understanding Model Boundaries:**
While the TMAE implements sophisticated mathematical concepts, traders must understand fundamental limitations:
- **Markets Are Not Purely Mathematical:** Human psychology, news events, and fundamental factors create unpredictable elements
- **Past Performance Limitations:** Mathematical relationships that worked historically may not persist indefinitely
- **Model Risk:** Complex models can fail during unprecedented market conditions
- **Overfitting Potential:** Highly optimized parameters may not generalize to future market conditions
### Proper Implementation Guidelines
**Risk Management Requirements:**
- **Never Risk More Than 2% Per Trade:** Regardless of signal quality
- **Diversification Mandatory:** Don't rely solely on mathematical signals
- **Position Sizing Discipline:** Use mathematical field strength for sizing, not confidence
- **Stop Loss Non-Negotiable:** Every trade must have predefined risk parameters
**Realistic Expectations:**
- **Mathematical Edge, Not Certainty:** The indicator provides probabilistic advantages, not guaranteed outcomes
- **Learning Curve Required:** Complex mathematical concepts require time to master
- **Market Adaptation Necessary:** Parameters must evolve with changing market conditions
- **Continuous Education Important:** Understanding underlying mathematics improves application
### Ethical Trading Considerations
**Market Impact Awareness:**
- **Information Asymmetry:** Advanced mathematical analysis may provide advantages over other market participants
- **Position Size Responsibility:** Large positions based on mathematical signals can impact market structure
- **Sharing Knowledge:** Consider educational contributions to trading community
- **Fair Market Participation:** Use mathematical advantages responsibly within market framework
### Professional Development Path
**Skill Development Sequence:**
1. **Basic Mathematical Literacy:** Understand fundamental concepts before advanced application
2. **Risk Management Mastery:** Develop disciplined risk control before relying on complex signals
3. **Market Psychology Understanding:** Combine mathematical analysis with behavioral market insights
4. **Continuous Learning:** Stay updated on mathematical finance developments and market evolution
---
## 🔮 CONCLUSION
The Tensor Market Analysis Engine represents a quantum leap forward in technical analysis, successfully bridging the gap between advanced pure mathematics and practical trading applications. By integrating multi-dimensional volatility analysis, fractal market theory, and information flow dynamics, the TMAE reveals market structure invisible to conventional analysis while maintaining visual clarity and practical usability.
### Mathematical Innovation Legacy
This indicator establishes new paradigms in technical analysis:
- **Tensor analysis for market volatility understanding**
- **Stochastic self-excitation for event clustering prediction**
- **Information theory for causality-based trade generation**
- **Democratic algorithmic consensus for signal quality enhancement**
- **Mathematical field visualization for intuitive market understanding**
### Practical Trading Revolution
Beyond mathematical innovation, the TMAE transforms practical trading:
- **Quality-rated signals replace binary buy/sell decisions**
- **Regime-adaptive strategies automatically optimize for market personality**
- **Multi-dimensional risk management integrates mathematical volatility measures**
- **Visual mathematical concepts make complex analysis immediately interpretable**
- **Educational value creates lasting improvement in trading understanding**
### Future-Proof Design
The mathematical foundations ensure lasting relevance:
- **Universal mathematical principles transcend market evolution**
- **Multi-dimensional analysis adapts to new market structures**
- **Regime detection automatically adjusts to changing market personalities**
- **Component democracy allows for future algorithmic additions**
- **Mathematical visualization scales with increasing market complexity**
### Commitment to Excellence
The TMAE represents more than an indicator—it embodies a philosophy of bringing rigorous mathematical analysis to trading while maintaining practical utility and visual elegance. Every component, from the multi-dimensional tensor fields to the democratic signal generation, reflects a commitment to mathematical accuracy, trading practicality, and educational value.
### Trading with Mathematical Precision
In an era where markets grow increasingly complex and computational, the TMAE provides traders with mathematical tools previously available only to institutional quantitative research teams. Yet unlike academic mathematical models, the TMAE translates complex concepts into intuitive visual representations and practical trading signals.
By combining the mathematical rigor of tensor analysis, the statistical power of multi-dimensional volatility modeling, and the information-theoretic insights of transfer entropy, traders gain unprecedented insight into market structure and dynamics.
### Final Perspective
Markets, like nature, exhibit profound mathematical beauty beneath apparent chaos. The Tensor Market Analysis Engine serves as a mathematical lens that reveals this hidden order, transforming how traders perceive and interact with market structure.
Through mathematical precision, visual elegance, and practical utility, the TMAE empowers traders to see beyond the noise and trade with the confidence that comes from understanding the mathematical principles governing market behavior.
Trade with mathematical insight. Trade with the power of tensors. Trade with the TMAE.
*"In mathematics, you don't understand things. You just get used to them." - John von Neumann*
*With the TMAE, mathematical market understanding becomes not just possible, but intuitive.*
— Dskyz, Trade with insight. Trade with anticipation.
Universal Sentiment Oscillator with Trade RecommendationsUniversal Sentiment Oscillator & Strategy Guide
Summary
This all-in-one indicator is designed to be a comprehensive co-pilot for your trading journey. It moves beyond simple buy/sell signals by analyzing the underlying market sentiment and providing a dynamic, risk-assessed guide of potential trading strategies. Whether you're a novice learning the ropes or an expert seeking confirmation, this tool provides a structured framework for making smarter, more informed decisions in stocks, options, and futures.
How It Works
The core of the indicator is the Sentiment Oscillator, which calculates a score from -5 (Extremely Bearish) to +5 (Extremely Bullish) on every bar. This isn't just a single measurement; it's a weighted aggregate of several key technical conditions:
Trend Analysis: Price position relative to the 20, 50, and 200 EMAs.
Momentum Analysis: The current RSI value.
Hybrid Analysis: The state of the MACD and its signal line.
These factors are intelligently combined and normalized to produce a single, intuitive sentiment score, giving you an at-a-glance understanding of the market's pulse.
Core Features
Dynamic Trade Recommendation Table:
The informational heart of the indicator. This on-chart table provides a list of potential trades perfectly aligned with the current sentiment score.
Risk-Ranked Strategies:
All suggested trades are logically ordered by risk, helping you quickly identify strategies that match your comfort level.
Adjusted Trade Suggestions:
The indicator analyzes sentiment momentum (the score vs. its signal line) to provide proactive, forward-looking trade ideas based on where the market might be heading next.
Customizable Trading Styles:
Tell the indicator if you are a Conservative, Neutral, or Aggressive trader, and the "Adjusted Trade Suggestion" will automatically tailor its recommendations to your personal risk preference.
Context-Aware Futures Mode:
When viewing a futures contract, enable this mode to switch all recommendations from stock/options to futures-specific actions (e.g., "Cautious Long," "Monitor Range").
Predictive Sentiment Cone:
Visualize the potential short-term path of sentiment based on current momentum, helping you anticipate future conditions.
Fully Customizable:
Every parameter—from EMA lengths to trade filters—can be adjusted, allowing you to fine-tune the indicator to your exact specifications.
How to Use This Indicator
This tool is flexible and can be integrated into many trading systems. Here is a powerful, professional approach:
Top-Down Analysis (for Swing or Position Trading):
Establish the Trend: Start on the higher timeframes (Monthly, Weekly, Daily). Use the oscillator's color and score to define the dominant, long-term market sentiment. You only want to look for trades that align with this macro trend.
Refine the Entry: Drop down to the medium timeframes (4-Hour, 1-Hour). Wait for the sentiment on these charts to come into alignment with the higher-timeframe trend. This pullback or consolidation is your "zone of interest."
Pinpoint the Execution: Move to a lower timeframe (e.g., 15-Minute). Use the Adjusted Trade Suggestion and Sentiment Momentum to find a precise entry as momentum begins to shift back in the direction of the primary trend. You can set alerts on the oscillator's zero-line for early warnings of a sentiment shift.
As a Confirmation Tool: If you have an existing trade idea, use the indicator to validate it. Does the sentiment score align with your bullish or bearish thesis? Does the momentum confirm that now is a good time to enter?
As an Idea Generation Tool: Unsure what to trade? Browse different assets and let the indicator's "Primary Trades" and "Adjusted Trade Suggestion" present you with a list of risk-assessed ideas that you can then investigate further.
Disclaimer: This is an analysis tool and should not be considered financial advice. All forms of trading involve substantial risk. You should not trade with money you cannot afford to lose. Always perform your own due diligence and use this indicator as one component of a complete trading plan.
SIP Evaluator and Screener [Trendoscope®]The SIP Evaluator and Screener is a Pine Script indicator designed for TradingView to calculate and visualize Systematic Investment Plan (SIP) returns across multiple investment instruments. It is tailored for use in TradingView's screener, enabling users to evaluate SIP performance for various assets efficiently.
🎲 How SIP Works
A Systematic Investment Plan (SIP) is an investment strategy where a fixed amount is invested at regular intervals (e.g., monthly or weekly) into a financial instrument, such as stocks, mutual funds, or ETFs. The goal is to build wealth over time by leveraging the power of compounding and mitigating the impact of market volatility through disciplined, consistent investing. Here’s a breakdown of how SIPs function:
Regular Investments : In an SIP, an investor commits to investing a fixed sum at predefined intervals, regardless of market conditions. This consistency helps inculcate a habit of saving and investing.
Cost Averaging : By investing a fixed amount regularly, investors purchase more units when prices are low and fewer units when prices are high. This approach, known as dollar-cost averaging, reduces the average cost per unit over time and mitigates the risk of investing a large amount at a peak price.
Compounding Benefits : Returns generated from the invested amount (e.g., capital gains or dividends) are reinvested, leading to exponential growth over the long term. The longer the investment horizon, the greater the potential for compounding to amplify returns.
Dividend Reinvestment : In some SIPs, dividends received from the underlying asset can be reinvested to purchase additional units, further enhancing returns. Taxes on dividends, if applicable, may reduce the reinvested amount.
Flexibility and Accessibility : SIPs allow investors to start with small amounts, making them accessible to a wide range of individuals. They also offer flexibility in terms of investment frequency and the ability to adjust or pause contributions.
In the context of the SIP Evaluator and Screener , the script simulates an SIP by calculating the number of units purchased with each fixed investment, factoring in commissions, dividends, taxes and the chosen price reference (e.g., open, close, or average prices). It tracks the cumulative investment, equity value, and dividends over time, providing a clear picture of how an SIP would perform for a given instrument. This helps users understand the impact of regular investing and make informed decisions when comparing different assets in TradingView’s screener. It offers insights into key metrics such as total invested amount, dividends received, equity value, and the number of installments, making it a valuable resource for investors and traders interested in understanding long-term investment outcomes.
🎲 Key Features
Customizable Investment Parameters: Users can define the recurring investment amount, price reference (e.g., open, close, HL2, HLC3, OHLC4), and whether fractional quantities are allowed.
Commission Handling: Supports both fixed and percentage-based commission types, adjusting calculations accordingly.
Dividend Reinvestment: Optionally reinvests dividends after a user-specified period, with the ability to apply tax on dividends.
Time-Bound Analysis: Allows users to set a start year for the analysis, enabling historical performance evaluation.
Flexible Dividend Periods: Dividends can be evaluated based on bars, days, weeks, or months.
Visual Outputs: Plots key metrics like total invested amount, dividends, equity value, and remainder, with customizable display options for clarity in the data window and chart.
🎲 Using the script as an indicator on Tradingview Supercharts
In order to use the indicator on charts, do the following.
Load the instrument of your choice - Preferably a stable stocks, ETFs.
Chose monthly timeframe as lower timeframes are insignificant in this type of investment strategy
Load the indicator SIP Evaluator and Screener and set the input parameters as per your preference.
Indicator plots, investment value, dividends and equity on the chart.
🎲 Visualizations
Installments : Displays the number of SIP installments (gray line, visible in the data window).
Invested Amount : Shows the cumulative amount invested, excluding reinvested dividends (blue area plot).
Dividends : Tracks total dividends received (green area plot).
Equity : Represents the current market value of the investment based on the closing price (purple area plot).
Remainder : Indicates any uninvested cash after each installment (gray line, visible in the data window).
🎲 Deep dive into the settings
The SIP Evaluator and Screener offers a range of customizable settings to tailor the Systematic Investment Plan (SIP) simulation to your preferences. Below is an explanation of each setting, its purpose, and how it impacts the analysis:
🎯 Duration
Start Year (Default: 2020) : Specifies the year from which the SIP calculations begin. When Start Year is enabled via the timebound option, the script only considers data from the specified year onward. This is useful for analyzing historical SIP performance over a defined period. If disabled, the script uses all available data.
Timebound (Default: False) : A toggle to enable or disable the Start Year restriction. When set to False, the SIP calculation starts from the earliest available data for the instrument.
🎯 Investment
Recurring Investment (Default: 1000.0) : The fixed amount invested in each SIP installment (e.g., $1000 per period). This represents the regular contribution to the SIP and directly influences the total invested amount and quantity purchased.
Allow Fractional Qty (Default: True) : When enabled, the script allows the purchase of fractional units (e.g., 2.35 shares). If disabled, only whole units are purchased (e.g., 2 shares), with any remaining funds carried forward as Remainder. This setting impacts the precision of investment allocation.
Price Reference (Default: OPEN): Determines the price used for purchasing units in each SIP installment. Options include:
OPEN : Uses the opening price of the bar.
CLOSE : Uses the closing price of the bar.
HL2 : Uses the average of the high and low prices.
HLC3 : Uses the average of the high, low, and close prices.
OHLC4 : Uses the average of the open, high, low, and close prices. This setting affects the cost basis of each purchase and, consequently, the total quantity and equity value.
🎯 Commission
Commission (Default: 3) : The commission charged per SIP installment, expressed as either a fixed amount (e.g., $3) or a percentage (e.g., 3% of the investment). This reduces the amount available for purchasing units.
Commission Type (Default: Fixed) : Specifies how the commission is calculated:
Fixed ($) : A flat fee is deducted per installment (e.g., $3).
Percentage (%) : A percentage of the investment amount is deducted as commission (e.g., 3% of $1000 = $30). This setting affects the net amount invested and the overall cost of the SIP.
🎯 Dividends
Apply Tax On Dividends (Default: False) : When enabled, a tax is applied to dividends before they are reinvested or recorded. The tax rate is set via the Dividend Tax setting.
Dividend Tax (Default: 47) : The percentage of tax deducted from dividends if Apply Tax On Dividends is enabled (e.g., 47% tax reduces a $100 dividend to $53). This reduces the amount available for reinvestment or accumulation.
Reinvest Dividends After (Default: True, 2) : When enabled, dividends received are reinvested to purchase additional units after a specified period (e.g., 2 units of time, defined by Dividends Availability). If disabled, dividends are tracked but not reinvested. Reinvestment increases the total quantity and equity over time.
Dividends Availability (Default: Bars) : Defines the time unit for evaluating when dividends are available for reinvestment. Options include:
Bars : Based on the number of chart bars.
Weeks : Based on weeks.
Months : Based on months (approximated as 30.5 days). This setting determines the timing of dividend reinvestment relative to the Reinvest Dividends After period.
🎯 How Settings Interact
These settings work together to simulate a realistic SIP. For example, a $1000 recurring investment with a 3% commission and fractional quantities enabled will calculate the number of units purchased at the chosen price reference after deducting the commission. If dividends are reinvested after 2 months with a 47% tax, the script fetches dividend data, applies the tax, and adds the net dividend to the investment amount for that period. The Start Year and Timebound settings ensure the analysis aligns with the desired timeframe, while the Dividends Availability setting fine-tunes dividend reinvestment timing.
By adjusting these settings, users can model different SIP scenarios, compare performance across instruments in TradingView’s screener, and gain insights into how commissions, dividends, and price references impact long-term returns.
🎲 Using the script with Pine Screener
The main purpose of developing this script is to use it with Tradingview Pine Screener so that multiple ETFs/Funds can be compared.
In order to use this as a screener, the following things needs to be done.
Add SIP Evaluator and Screener to your favourites (Required for it to be added in pine screener)
Create a watch list containing required instruments to compare
Open pine screener from Tradingview main menu Products -> Screeners -> Pine or simply load the URL - www.tradingview.com
Select the watchlist created from Watchlist dropdown.
Chose the SIP Evaluator and Screener from the "Choose Indicator" dropdown
Set timeframe to 1 month and update settings as required.
Press scan to display collected data on the screener.
🎲 Use Case
This indicator is ideal for educational purposes, allowing users to experiment with SIP strategies across different instruments. It can be applied in TradingView’s screener to compare SIP performance for stocks, ETFs, or other assets, helping users understand how factors like commissions, dividends, and price references impact returns over time.
MTF Pivot Zones
## 📘 **User Guide: MTF Pivot Zones**
**Script Name:** MTF Pivot Zones
Multi Time Frame Pivot
---
### 🧭 Overview
**MTF Pivot Zones** is a multi-timeframe analysis tool that detects and merges swing highs and lows across four key timeframes:
**Weekly, Daily, 4H, and 1H**.
It plots clear **Support** and **Resistance** zones on the chart based on pivot point clustering. Zones are displayed as dashed lines, color-coded by type.
---
### ⚙️ Settings
| Input Name | Description |
| ---------------------- | --------------------------------------------------------------------- |
| `Lookback Bars Per TF` | Number of bars to scan for pivot highs/lows per timeframe |
| `Pivot Left Bars` | Number of bars to the left required to confirm a pivot |
| `Pivot Right Bars` | Number of bars to the right required to confirm a pivot |
| `Merge Tolerance ($)` | Distance threshold in dollars to merge nearby pivot levels into zones |
| `Show TF Labels` | Toggle the text label next to each zone (e.g., “Res Zone”) |
---
### 🛠️ How It Works
1. **Pivot Detection**
The script scans each timeframe using `ta.pivothigh()` and `ta.pivotlow()`.
2. **Zone Merging**
Pivot levels within the specified `Merge Tolerance` are averaged and treated as a single zone.
3. **Zone Plotting**
* **Red dashed lines** = Resistance Zones
* **Green dashed lines** = Support Zones
* Optional labels show zone type if `Show TF Labels` is enabled
---
### 📈 Usage Tips
* Use zones to guide entries, exits, and stop-loss placement.
* Combine with trend tools or candlestick confirmation near zones.
* Adjust merge tolerance to match instrument volatility and timeframe.
---
Let me know if you want this formatted for **TradingView publishing**, or included in a `study()` title block comment.
Prev Week POC Buy/Sell Signals
Hi, I’m Edward. I created a straightforward strategy for swing traders (4hr or 8hr timeframe users). This strategy is for traders that are not interested to look at charts all day long, 2 times a day max, but still be profitable.
The indicator:
Print a buy signal when the price closes above the previous week's Point of Control (POC).
Stay in the trade until the price closes below the previous week's POC, then print a sell signal.
The indicator calculates the weekly POC using a basic volume profile method, then tracks the previous week's POC for signals.
Previous week POC is valid from Monday to Thursday. By close of business on Thursday, the current week trend and POC should be well established and should be used make buy or sell decisions. Enjoy!
Ultimate Regression Channel v5.0 [WhiteStone_Ibrahim]Ultimate Regression Channel v5.0: Comprehensive User Guide
This indicator is designed to visualize the current trend, potential support/resistance levels, and market volatility through a statistical analysis of price action. At its core, it plots a regression line (a trend line) based on prices over a specific period and adds channels based on standard deviation around this line.
1. Core Features and Settings
Length Mode:
Numerical (Manual): You define the number of bars to be used for the regression channel calculation. You can use lower values (e.g., 50-100) for short-term analysis and higher values (e.g., 200-300) to identify long-term trends.
Automatic (Based on Market Structure): This mode automatically draws the channel starting from the highest high or lowest low that has formed within the Auto Scan Period. This allows the indicator to adapt itself to significant market turning points (swing points), which is highly useful.
Regression Model:
Linear: Calculates the trend as a straight line. It generally works well in stable, short-to-medium-term trends.
Logarithmic: Calculates the trend as a curved line. It more accurately reflects price action, especially on long-term charts or for assets that experience exponential growth/decline (like cryptocurrencies or growth stocks).
Channel Widths:
These settings determine how far from the central trend line (in terms of standard deviations) the channels will be drawn.
The 0 (Inner), 1 (Middle), and 2 (Outer) channels represent the "normal" range of price movement and the "extreme" zones. Statistically, about 95% of all price action occurs within the outer channels (2nd standard deviation).
2. Visual Extras and Their Interpretation
Breakout Style:
This feature alerts you when the price closes above the uppermost channel (Channel 2) with a green arrow/background or below the lowermost channel with a red arrow/background.
This is a very important signal. A breakout can signify that the current trend is strengthening and likely to continue (a breakout/trend-following strategy) or that the market has become overextended and may be due for a reversal (an exhaustion/top-bottom signal). It is critical to confirm this signal with other indicators (e.g., RSI, Volume).
Info Label:
This provides an at-a-glance summary of the channel on the right side of the chart:
Trend Status: Identifies the trend as "Uptrend," "Downtrend," or "Sideways" based on the slope of the centerline. The Horizontal Threshold setting allows you to filter out noise by treating very small slopes as "Sideways."
Regression Model and Length: Shows your current settings.
Trend Slope: A numerical value representing how steep or weak the trend is.
Channel Width: Shows the price difference between the outermost channels. This is a measure of current volatility. A widening channel indicates increasing volatility, while a narrowing one indicates decreasing volatility.
3. What Users Should Pay Attention To & Best Practices
Define Your Strategy: Mean Reversion or Breakout?
Mean Reversion: If the market is in a ranging or gently trending phase, the price will tend to revert to the centerline after hitting the outer channels (overbought/oversold zones). In this case, the outer channels can be considered opportunities to sell (upper channel) or buy (lower channel).
Breakout: If a strong trend is in place, a price close beyond an outer channel can be a sign that the trend is accelerating. In this scenario, one might consider taking a position in the direction of the breakout. Correctly analyzing the current market state (ranging vs. trending) is key to deciding which strategy to employ.
Don't Use It in Isolation: No indicator is a holy grail. Use the Regression Channel in conjunction with other tools. Confirm signals with RSI divergences for overbought/oversold conditions, Moving Averages for the overall trend direction, or Volume indicators to confirm the strength of a breakout.
Choose the Right Model: On shorter-term charts (e.g., 1-hour, 4-hour), the Linear model is often sufficient. However, on long-term charts like the daily, weekly, or monthly, the Logarithmic model will provide much more accurate results, especially for assets with parabolic movements.
The Power of Automatic Mode: The Automatic length mode is often the most practical choice because it finds the most logical starting point for you. It saves you the trouble of adjusting settings, especially when analyzing different assets or timeframes.
Use the Alerts: If you don't want to miss the moment the price touches a key channel line, set up an alert from the Alert Settings section for your desired line (e.g., only the "Outer Channels"). This helps you catch opportunities even when you are not in front of the screen.
Cycle Composite 3.6 WeightedThe Cycle Composite is a multi-factor market cycle model designed to classify long-term market behavior into distinct phases using normalized and weighted data inputs.
It combines ten key on-chain, dominance, volatility, sentiment, and trend-following metrics into a single composite output. The goal is to provide a clearer understanding of where the market may stand in the broader cycle (e.g., accumulation, early bull, late bull, or euphoria).
This version (3.4) introduces flexible weighting, trend strength markers, and additional context-aware signals such as risk-on confirmations and altseason flags.
Phases Identified:
The model categorizes the market into one of five zones:
Euphoria (> 85)
Late Bull (70 – 85)
Mid Bull (50 – 70)
Early Bull (30 – 50)
Fear (< 30)
Each phase is determined by a smoothed EMA of the weighted composite score.
Data Sources and Metrics Used (10 total):
BTC Dominance (CRYPTOCAP:BTC.D)
Stablecoin Dominance (USDT + USDC average) (inverted for risk-on)
ETH Dominance (CRYPTOCAP:ETH.D)
BBWP (normalized Bollinger Band Width % over 1-year window)
WVF (Williams VIX Fix for volatility spike detection)
NUPL (Net Unrealized Profit/Loss, external source)
CMF (Chaikin Money Flow, smoothed volume accumulation)
CEX Open Interest (custom input from DAO / external source)
Whale Inflows (custom input from whale exchange transfer data)
Google Trends Average (BTC, Crypto, Altcoin terms)
All inputs are normalized over a 200-bar window and combined via weighted averaging, where each weight is user-configurable.
Additional Features:
Phase Labels: Labels are printed only when a new phase is entered.
Bull Continuation Marker: Triangle up when composite makes higher highs and NUPL increases.
Weakening Marker: Triangle down when composite rolls over in Late Bull and NUPL falls.
Risk-On Signal: Green circle appears when CMF and Google Trends are both rising.
Altseason Flag: Orange diamond appears when dominance of "others.d" exceeds BTC.D and ETH.D and composite is above 50.
Background Shading: Each phase is shaded with a semi-transparent background color.
Timeframe-Aware Display: All markers and signals are shown only on weekly timeframe for clarity.
Intended Use:
This script is intended for educational and macro-trend analysis purposes.
It can be used to:
Identify macro cycle position (accumulation, bull phases, euphoria, etc.)
Spot long-term trend continuation or weakening signals
Add context to price action with external on-chain and sentiment data
Time rotation events such as altseason risk
Disclaimer:
This script does not constitute financial advice.
It is intended for informational and research purposes only.
Users should conduct their own due diligence and analysis before making investment decisions.
Intraweek Highs & Lows🔎 Track and analyze intraweek price extremes with full flexibility.
The indicator detects weekly highs or lows for any selected weekday and monitors when other days break those levels.
⚙️ Inputs
Select day
Pick which weekday’s extreme you want to monitor.
Find Low/High
Select whether you want to track Lows or Highs.
Use candle Wick/Body
Choose if extremes are calculated by full wick or candle body.
Cutoff date
Toggle the date-based filter and choose the starting date for event display.
[FS] Time & Cycles Time & Cycles
A comprehensive trading session indicator that helps traders identify and track key market sessions and their price levels. This tool is particularly useful for forex and futures traders who need to monitor multiple trading sessions.
Key Features:
• Multiple Session Support:
- London Session
- New York Session
- Sydney Session
- Asia Session
- Customizable TBD Session
• Session Visualization:
- Clear session boxes with customizable colors
- Session labels with adjustable visibility
- Support for sessions crossing midnight
- Timezone-aware calculations
• Price Level Tracking:
- Daily High/Low levels
- Weekly High/Low levels
- Previous session High/Low levels
- Customizable history depth for each level type
• Customization Options:
- Adjustable colors for each session
- Customizable border styles
- Label visibility controls
- Timezone selection
- History level depth settings
• Technical Features:
- High-performance calculation engine
- Support for multiple timeframes
- Efficient memory usage
- Clean and intuitive visual display
Perfect for:
• Forex traders monitoring multiple sessions
• Futures traders tracking market hours
• Swing traders identifying key session levels
• Day traders planning their trading hours
• Market analysts studying session patterns
The indicator helps traders:
- Identify active trading sessions
- Track session-specific price levels
- Monitor market activity across different time zones
- Plan trades based on session boundaries
- Analyze price action within specific sessions
Note: This indicator is designed to work across all timeframes and is optimized for performance with minimal impact on chart loading times.
Rolling Z-Score Trend [QuantAlgo]🟢 Overview
The Rolling Z-Score Trend measures how far the current price deviates from its rolling mean in terms of standard deviations. It transforms price data into standardized scores to identify overbought and oversold conditions while tracking momentum shifts.
The indicator displays a Z-Score line showing price deviation from statistical norms, with background momentum columns showing the rate of change in these deviations. This helps traders and investors identify mean reversion opportunities and momentum shifts across different asset classes and timeframes.
🟢 How It Works
The indicator uses the Z-Score formula: Z = (X - μ) / σ, where X is the current closing price, μ is the rolling mean, and σ is the rolling standard deviation over a user-defined lookback period. This creates a dynamic baseline that adapts to changing market conditions and standardizes price movements for interpretation across different assets and volatility conditions. The raw Z-Score undergoes 3-period EMA smoothing to reduce noise while maintaining responsiveness to market signals.
Beyond the basic Z-Score calculation, the indicator measures the rate of change in Z-Score values between successive bars, displayed as background momentum columns. This momentum component shows acceleration and deceleration of statistical deviations. All calculations are processed through confirmation filters, displaying signals only on confirmed bars to reduce premature signals based on incomplete price action.
🟢 How to Use
1. Z-Score Interpretation and Threshold Zones
Positive Values (Above Zero) : Price trading above statistical mean, suggesting bullish momentum or potential overbought conditions
Negative Values (Below Zero) : Price trading below statistical mean, suggesting bearish momentum or potential oversold conditions
Zero Line Crosses : Signal transitions between statistical regimes and potential trend changes
Upper Threshold Zone : Area above entry threshold (default 1.5) indicating potential overbought conditions
Lower Threshold Zone : Area below negative entry threshold (default -1.5) indicating potential oversold conditions
Extreme Values (±2.0 or higher) : Statistically significant deviations that may indicate reversal opportunities
2. Momentum Background Analysis and Info Table
Green Columns : Accelerating positive momentum in Z-Score values
Red Columns : Accelerating negative momentum in Z-Score values
Column Height : Magnitude of momentum change between bars
Momentum Divergence : When columns contradict primary Z-Score direction, often signals impending reversals
Info Table : Displays real-time numerical values for both Z-Score and momentum, including trend direction indicators and bar-to-bar change calculations for position management
3. Preconfigured Settings
Default : Balanced performance across multiple timeframes and asset classes for general trading and medium-term position management.
Scalping : Responsive setup for ultra-short-term trading on 1-15 minute charts with frequent signals and increased sensitivity to quick price movements.
Swing Trading : Optimized for multi-day positions with noise filtering, focusing on larger price swings. Most effective on 1-4 hour and daily timeframes.
Trend Following : Maximum smoothing that prioritizes established trends over short-term volatility. Generates fewer signals for daily and weekly charts.
Yelober - Sector Rotation Detector# Yelober - Sector Rotation Detector: User Guide
## Overview
The Yelober - Sector Rotation Detector is a TradingView indicator designed to track sector performance and identify market rotations in real-time. It monitors key sector ETFs, calculates performance metrics, and provides actionable stock recommendations based on sector strength and weakness.
## Purpose
This indicator helps traders identify when capital is moving from one sector to another (sector rotation), which can provide valuable trading opportunities. It also detects risk-off conditions in the market and highlights sectors with abnormal trading volume.
## Table Columns Explained
### 1. Sector
Displays the sector name being monitored. The indicator tracks six primary sectors plus the S&P 500:
- Energy (XLE)
- Financial (XLF)
- Technology (XLK)
- Consumer Staples (XLP)
- Utilities (XLU)
- Consumer Discretionary (XLY)
- S&P 500 (SPY)
### 2. Perf %
Shows the daily percentage performance of each sector ETF. Values are color-coded:
- Green: Positive performance
- Red: Negative performance
Positive values display with a "+" sign (e.g., +1.25%)
### 3. RSI
Displays the Relative Strength Index value for each sector, which helps identify overbought or oversold conditions:
- Values above 70 (highlighted in red): Potentially overbought
- Values below 30 (highlighted in green): Potentially oversold
- Values between 30-70 (highlighted in blue): Neutral territory
### 4. Vol Ratio
Shows the volume ratio, which compares today's volume to the average volume over the lookback period:
- Values above 1.5x (highlighted in yellow): Indicates abnormally high trading volume
- Values below 1.5x (highlighted in blue): Normal trading volume
This helps identify sectors with unusual activity that may signal important price movements.
### 5. Trend
Displays the current price trend direction with symbols:
- ▲ (green): Uptrend (today's close > yesterday's close)
- ▼ (red): Downtrend (today's close < yesterday's close)
- ◆ (gray): Neutral (today's close = yesterday's close)
## Summary & Recommendations Section
The summary section provides:
1. **Sector Rotation Detection**: Identifies when there's a significant performance gap (>2%) between the strongest and weakest sectors.
2. **Risk-Off Mode Detection**: Alerts when defensive sectors (Consumer Staples and Utilities) are positive while Technology is negative, which often signals investors are moving to safer assets.
3. **Strong Volume Detection**: Indicates when any sector shows abnormally high trading volume.
4. **Stock Recommendations**: Suggests specific stocks to consider for long positions (from the strongest sectors) and short positions (from the weakest sectors).
## Example Interpretations
### Example 1: Sector Rotation
If you see:
- Technology: -1.85%
- Financial: +2.10%
- Summary shows: "SECTOR ROTATION DETECTED: Rotation from Technology to Financial"
**Interpretation**: Capital is moving out of tech stocks and into financial stocks. This could be due to rising interest rates, which typically benefit banks while pressuring high-growth tech companies. Consider looking at financial stocks like JPM, BAC, and WFC for potential long positions.
### Example 2: Risk-Off Conditions
If you see:
- Consumer Staples: +0.80%
- Utilities: +1.20%
- Technology: -1.50%
- Summary shows: "RISK-OFF MODE DETECTED"
**Interpretation**: Investors are seeking safety in defensive sectors while selling growth-oriented tech stocks. This often occurs during market uncertainty or ahead of economic concerns. Consider reducing exposure to high-beta stocks and possibly adding defensive names like PG, KO, or NEE.
### Example 3: Volume Spike
If you see:
- Energy: +3.20% with Volume Ratio 2.5x (highlighted in yellow)
- Summary shows: "STRONG VOLUME DETECTED"
**Interpretation**: The energy sector is making a strong move with significantly higher-than-average volume, suggesting conviction behind the price movement. This could indicate the beginning of a sustained trend in energy stocks. Consider names like XOM, CVX, and COP.
## How to Use the Indicator
1. Apply the indicator to any chart (works best on daily timeframes).
2. Customize settings if needed:
- Timeframe: Choose between intraday (60 or 240 minutes), daily, or weekly
- Lookback Period: Adjust the historical comparison period (default: 20)
- RSI Period: Modify the RSI calculation period (default: 14)
3. To refresh the data: Click the settings icon, increase the "Click + to refresh data" counter, and click "OK".
4. Identify opportunities based on sector performance, RSI levels, volume ratios, and the summary recommendations.
This indicator helps traders align with market rotation trends and identify which sectors (and specific stocks) may outperform or underperform in the near term.
Luma DCA Tracker (BTC)Luma DCA Tracker (BTC) – User Guide
Function
This indicator simulates a regular Bitcoin investment strategy (Dollar Cost Averaging). It calculates and visualizes:
Accumulated BTC amount
Average entry price
Total amount invested
Current portfolio value
Profit/loss in absolute and percentage terms
Settings
Investment per interval
Fixed amount to be invested at each interval (e.g., 100 USD)
Start date
The date when DCA simulation begins
Investment interval
Choose between:
daily, weekly, every 14 days, or monthly
Show investment data
Displays additional chart lines (total invested, value, profit, etc.)
Chart Elements
Orange line: Average DCA entry price
Grey dots: Entry points based on selected interval
Info box (bottom left): Live summary of all key values
Notes
Purchases are simulated at the closing price of each interval
No fees, slippage, or taxes are included
The indicator is a simulation only and not linked to an actual portfolio
Flux Capacitor (FC)# Flux Capacitor
**A volume-weighted, outlier-resistant momentum oscillator designed to expose hidden directional pressure from institutional participants.**
---
### Why "Flux Capacitor"?
The name pays homage to the fictional energy core in *Back to the Future* — an invisible engine that powers movement. Similarly, this indicator detects whether price movement is being powered by real market participation (volume) or if it's coasting without conviction.
---
### Methodology
The Flux Capacitor fuses three statistical layers:
- **Normalized Momentum**: `(Close – Open) / ATR`
Controls for raw price size and volatility.
- **Volume Scaling**:
Amplifies the effect of price moves that occur with elevated volume.
- **Robust Normalization**:
- *Winsorization* caps outlier spikes.
- *MAD-Z scoring* normalizes the signal across assets (crypto, futures, stocks).
- This produces consistent scaling across timeframes and symbols.
The result is a smooth oscillator that reliably indicates **liquidity-backed momentum** — not just price movement.
---
### Signal Events
- **Divergence (D)**: Price makes higher highs or lower lows, but Flux does not.
- **Absorption (A)**: Candle shows high volume and small body, while Flux opposes the candle direction — indicates smart money stepping in.
- **Compression (◆)**: High volume with low momentum — potential breakout zone.
- **Zero-Cross**: Indicates directional regime flip.
- **Flux Acceleration**: Histogram shows pressure rate of change.
- **Regime Background**: Color fades with weakening trend conviction.
All signals are color-coded and visually compact for easy pattern recognition.
---
### Interpreting Divergence & Absorption Correctly
Signal strength improves significantly when it appears **in the correct zone**:
#### Divergence:
| Signal | Zone | Meaning | Strength |
|--------|------------|------------------------------------------|--------------|
| Green D | Below 0 | Bullish reversal forming in weakness | **Strong** |
| Green D | Above 0 | Bullish, but less convincing | Moderate |
| Red D | Above 0 | Bearish reversal forming in strength | **Strong** |
| Red D | Below 0 | Bearish continuation — low warning value | Weak |
#### Absorption:
| Signal | Zone | Meaning | Strength |
|--------|------------|-----------------------------------------|--------------|
| Green A | Below 0 | Buyers absorbing panic-selling | **Strong** |
| Green A | Above 0 | Support continuation | Moderate |
| Red A | Above 0 | Sellers absorbing FOMO buying | **Strong** |
| Red A | Below 0 | Trend continuation — not actionable | Weak |
Look for **absorption or divergence signals in “enemy territory”** for the most actionable entries.
---
### Reducing Visual Footprint
If your chart shows a long line of numbers across the top of the Flux Capacitor pane (e.g. "FC 14 20 9 ... Bottom Right"), it’s due to TradingView’s *status line input display*.
**To fix this**:
Right-click the indicator pane → **Settings** → **Status Line** tab → uncheck “Show Indicator Arguments”.
This frees up vertical space so top-edge signals (like red `D` or yellow `◆`) remain visible and unobstructed.
---
### Features
- Original MAD-Z based momentum design
- True volume-based divergence and absorption logic
- Built-in alerts for all signal types
- Works across timeframes (1-min to weekly)
- Minimalist, responsive layout
- 25+ customizable parameters
- No future leaks, no repainting
---
### Usage Scenarios
- **Trend confirmation**: Flux > 0 confirms bullish trend strength
- **Reversal detection**: Divergence or absorption in opposite territory = high-probability reversal
- **Breakout anticipation**: Compression signal inside range often precedes directional move
- **Momentum shifts**: Watch for zero-crosses + flux acceleration spikes
---
### ⚠ Visual Note for BTC, ETH, Crude Oil & Futures
These high-priced or rapidly accelerating instruments can visually compress any linear oscillator. You may notice the Flux Capacitor’s line appears "flat" or muted on these assets — especially over long lookbacks.
> **This does not affect signal validity.** Divergence, absorption, and compression triggers still fire based on underlying logic — only the line’s amplitude appears reduced due to scaling constraints.
---
### Disclaimer
This indicator is for educational purposes only. It is not trading advice. Past results do not guarantee future performance. Use in combination with your own risk management and analysis.
Magnificent 7 OscillatorThe Magnificent 7 Oscillator is a sophisticated momentum-based technical indicator designed to analyze the collective performance of the seven largest technology companies in the U.S. stock market (Apple, Microsoft, Alphabet, Amazon, NVIDIA, Tesla, and Meta). This indicator incorporates established momentum factor research and provides three distinct analytical modes: absolute momentum tracking, equal-weighted market comparison, and relative performance analysis. The tool integrates five different oscillator methodologies and includes advanced breadth analysis capabilities.
Theoretical Foundation
Momentum Factor Research
The indicator's foundation rests on seminal momentum research in financial markets. Jegadeesh and Titman (1993) demonstrated that stocks with strong price performance over 3-12 month periods tend to continue outperforming in subsequent periods¹. This momentum effect was later incorporated into formal factor models by Carhart (1997), who extended the Fama-French three-factor model to include a momentum factor (UMD - Up Minus Down)².
The momentum calculation methodology follows the academic standard:
Momentum(t) = / P(t-n) × 100
Where P(t) is the current price and n is the lookback period.
The focus on the "Magnificent 7" stocks reflects the increasing market concentration observed in recent years. Fama and French (2015) noted that a small number of large-cap stocks can drive significant market movements due to their substantial index weights³. The combined market capitalization of these seven companies often exceeds 25% of the total S&P 500, making their collective momentum a critical market indicator.
Indicator Architecture
Core Components
1. Data Collection and Processing
The indicator employs robust data collection with error handling for missing or invalid security data. Each stock's momentum is calculated independently using the specified lookback period (default: 14 periods).
2. Composite Oscillator Calculation
Following Fama-French factor construction methodology, the indicator offers two weighting schemes:
- Equal Weight: Each active stock receives identical weighting (1/n)
- Market Cap Weight: Reserved for future enhancement
3. Oscillator Transformation Functions
The indicator provides five distinct oscillator types, each with established technical analysis foundations:
a) Momentum Oscillator (Default)
- Pure rate-of-change calculation
- Centered around zero
- Direct implementation of Jegadeesh & Titman methodology
b) RSI (Relative Strength Index)
- Wilder's (1978) relative strength methodology
- Transformed to center around zero for consistency
- Scale: -50 to +50
c) Stochastic Oscillator
- George Lane's %K methodology
- Measures current position within recent range
- Transformed to center around zero
d) Williams %R
- Larry Williams' range-based oscillator
- Inverse stochastic calculation
- Adjusted for zero-centered display
e) CCI (Commodity Channel Index)
- Donald Lambert's mean reversion indicator
- Measures deviation from moving average
- Scaled for optimal visualization
Operational Modes
Mode 1: Magnificent 7 Analysis
Tracks the collective momentum of the seven constituent stocks. This mode is optimal for:
- Technology sector analysis
- Growth stock momentum assessment
- Large-cap performance tracking
Mode 2: S&P 500 Equal Weight Comparison
Analyzes momentum using an equal-weighted S&P 500 reference (typically RSP ETF). This mode provides:
- Broader market momentum context
- Size-neutral market analysis
- Comparison baseline for relative performance
Mode 3: Relative Performance Analysis
Calculates the momentum differential between Magnificent 7 and S&P 500 Equal Weight. This mode enables:
- Sector rotation analysis
- Style factor assessment (Growth vs. Value)
- Relative strength identification
Formula: Relative Performance = MAG7_Momentum - SP500EW_Momentum
Signal Generation and Thresholds
Signal Classification
The indicator generates three signal states:
- Bullish: Oscillator > Upper Threshold (default: +2.0%)
- Bearish: Oscillator < Lower Threshold (default: -2.0%)
- Neutral: Oscillator between thresholds
Relative Performance Signals
In relative performance mode, specialized thresholds apply:
- Outperformance: Relative momentum > +1.0%
- Underperformance: Relative momentum < -1.0%
Alert System
Comprehensive alert conditions include:
- Threshold crossovers (bullish/bearish signals)
- Zero-line crosses (momentum direction changes)
- Relative performance shifts
- Breadth Analysis Component
The indicator incorporates market breadth analysis, calculating the percentage of constituent stocks with positive momentum. This feature provides insights into:
- Strong Breadth (>60%): Broad-based momentum
- Weak Breadth (<40%): Narrow momentum leadership
- Mixed Breadth (40-60%): Neutral momentum distribution
Visual Design and User Interface
Theme-Adaptive Display
The indicator automatically adjusts color schemes for dark and light chart themes, ensuring optimal visibility across different user preferences.
Professional Data Table
A comprehensive data table displays:
- Current oscillator value and percentage
- Active mode and oscillator type
- Signal status and strength
- Component breakdowns (in relative performance mode)
- Breadth percentage
- Active threshold levels
Custom Color Options
Users can override default colors with custom selections for:
- Neutral conditions (default: Material Blue)
- Bullish signals (default: Material Green)
- Bearish signals (default: Material Red)
Practical Applications
Portfolio Management
- Sector Allocation: Use relative performance mode to time technology sector exposure
- Risk Management: Monitor breadth deterioration as early warning signal
- Entry/Exit Timing: Utilize threshold crossovers for position sizing decisions
Market Analysis
- Trend Identification: Zero-line crosses indicate momentum regime changes
- Divergence Analysis: Compare MAG7 performance against broader market
- Volatility Assessment: Oscillator range and frequency provide volatility insights
Strategy Development
- Factor Timing: Implement growth factor timing strategies
- Momentum Strategies: Develop systematic momentum-based approaches
- Risk Parity: Use breadth metrics for risk-adjusted portfolio construction
Configuration Guidelines
Parameter Selection
- Momentum Period (5-100): Shorter periods (5-20) for tactical analysis, longer periods (50-100) for strategic assessment
- Smoothing Period (1-50): Higher values reduce noise but increase lag
- Thresholds: Adjust based on historical volatility and strategy requirements
Timeframe Considerations
- Daily Charts: Optimal for swing trading and medium-term analysis
- Weekly Charts: Suitable for long-term trend analysis
- Intraday Charts: Useful for short-term tactical decisions
Limitations and Considerations
Market Concentration Risk
The indicator's focus on seven stocks creates concentration risk. During periods of significant rotation away from large-cap technology stocks, the indicator may not represent broader market conditions.
Momentum Persistence
While momentum effects are well-documented, they are not permanent. Jegadeesh and Titman (1993) noted momentum reversal effects over longer time horizons (2-5 years).
Correlation Dynamics
During market stress, correlations among the constituent stocks may increase, reducing the diversification benefits and potentially amplifying signal intensity.
Performance Metrics and Backtesting
The indicator includes hidden plots for comprehensive backtesting:
- Individual stock momentum values
- Composite breadth percentage
- S&P 500 Equal Weight momentum
- Relative performance calculations
These metrics enable quantitative strategy development and historical performance analysis.
References
¹Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. Journal of Finance, 48(1), 65-91.
Carhart, M. M. (1997). On persistence in mutual fund performance. Journal of Finance, 52(1), 57-82.
Fama, E. F., & French, K. R. (2015). A five-factor asset pricing model. Journal of Financial Economics, 116(1), 1-22.
Wilder, J. W. (1978). New concepts in technical trading systems. Trend Research.
1 Candle SMT Divergence (Nephew_Sam_)📊 1 Candle SMT Divergence Detector
3-Way Smart Money Theory (SMT) Divergence Scanner for Multi-Symbol Analysis
This indicator identifies 1-candle SMT divergences by comparing one primary symbol against up to 2 correlation symbols across multiple timeframes simultaneously. Perfect for detecting institutional smart money moves and market inefficiencies.
🎯 Key Features:
3-Way Comparison: Compare 1 "From" symbol vs 2 "To" symbols (configurable)
5 Symbol Pairs: Pre-configure up to 5 different symbol combinations
Multi-Timeframe: Scan 5 timeframes simultaneously (Chart, 1H, 4H, Daily, Weekly)
Smart Filtering: Only displays timeframes equal to or higher than your chart
Real-Time Detection: Compares current vs previous candle highs/lows
Visual Alerts: Clean table display with color-coded divergence status
Line Drawing: Optional trend lines connecting divergence points
Replay Compatible: Works with TradingView's replay mode
📈 How It Works:
Detects when one symbol makes a higher high while correlated symbols make lower highs (and vice versa for lows). This creates SMT divergence signals that often precede significant market moves.
Events assistantThis script gives an ability to manually add events to your charts. There is no option to define events for different pairs. I trade only 2-3 pairs and it helps me a lot. It also draws vertical lines that separate trading period of your selection: daily, weekly and monthly. It is also possible to strictly define trading period. I use trading period every time during backtesting so it is easy to know when to start and when to finish. It also helps to remember that I already written down trading news during selected period.
Breakout TrendTiltFolio Breakout Trend indicator
The Breakout Trend indicator is designed to help traders clearly visualize trend direction by combining two complementary techniques: moving averages and Donchian-style breakout logic.
Rather than relying on just one type of signal, this indicator merges short-term and long-term moving averages with breakout levels based on recent highs and lows. The moving averages define the broader trend regime, while the breakout logic pinpoints moments when price confirms directional momentum. This layered approach filters out many false signals while still capturing high-conviction moves.
Yes, these are lagging indicators by design — and that’s the point. Instead of predicting every wiggle, the Breakout Trend waits for confirmation, offering higher signal quality and fewer whipsaws. When the price breaks above a recent high and sits above the long-term moving average, the trend is more likely to persist. That’s when this indicator shines.
While it performs best on higher timeframes (daily/weekly), it's also adaptable to shorter timeframes for intraday traders who value clean, systematic trend signals.
For early signal detection, we recommend pairing this with TiltFolio’s Buying/Selling Proxy, which anticipates pressure buildups—albeit with more noise.
It's easy to read and built for real-world trading discipline.
Trendline Breakouts With Volume Strength [TradeDots]Trendline Breakouts With Volume Strength is an innovative indicator designed to identify potential market turning points using pivot-based trendline detection and volume confirmation. By merging dynamic trendline analysis with multi-tiered volume filters, this tool helps traders quickly spot breakouts or breakdowns that may signal significant shifts in price action.
📝 HOW IT WORKS
1. Pivot-Based Trendline Detection
The script automatically scans for recent pivot highs and lows over a user-defined lookback period.
When it finds higher pivot lows, it plots green uptrend lines; when it finds lower pivot highs, it plots red downtrend lines.
These dynamic lines update as new pivots form, providing continuously refreshed trend guidance.
2. Volume Ratio Analysis
A moving average of volume is compared against the current bar’s volume to calculate a ratio (e.g., 1.5×, 2×).
Higher ratios suggest above-average volume, often interpreted as stronger participation.
The script applies color-coded cues to highlight the intensity of volume surges.
3. Breakout & Breakdown Detection
Each trendline is monitored for a defined “break threshold,” which helps avoid minor penetrations that can trigger premature signals.
When price closes beyond a threshold below an uptrend line, the indicator labels it a “BREAKDOWN.” If it closes above a threshold on a downtrend line, it labels it a “BREAKOUT.”
Volume surges accompanying these breaks are highlighted with contextual emojis and distinct color gradients for quick visual reference.
4. Trend Direction Table
A small on-chart table provides a snapshot of the current market trend—Uptrend, Downtrend, or Sideways—based on a simple moving average slope and the number of active uptrend or downtrend lines.
This table also displays quick stats on how many lines are actively tracked, helping traders assess the broader market posture at a glance.
🛠️ HOW TO USE
1. Choose a Timeframe
This script works on multiple timeframes. Intraday traders can monitor minute or hourly charts for frequent pivot updates, while swing and position traders may prefer daily or weekly intervals to reduce noise.
2. Observe Trendlines & Labels
Watch for newly drawn green/red lines connecting pivots.
When you see a “BREAKOUT” or “BREAKDOWN” label, confirm whether volume was abnormally high based on the ratio or color-coded bars.
3. Consult the Trend Table
Use the table in the bottom-right corner to quickly check if the market is trending or range-bound.
Look at the count of active uptrend vs. downtrend lines to gauge broader sentiment.
4. Employ Additional Analysis
Combine these signals with other tools (e.g., candlestick patterns, oscillators, or fundamental analysis).
Validate potential breakouts using standard techniques like retests or support/resistance checks.
❗️LIMITATIONS
Delayed Pivots: Trendlines only adjust once new pivot highs or lows form, which can introduce a slight lag in highly volatile environments.
Choppy Markets: Rapid, back-and-forth price moves may produce conflicting trendline signals and frequent breakouts/breakdowns.
Volume Data Reliability: Gaps in volume data or unusual market conditions (holidays, low-liquidity sessions) can skew ratio readings.
RISK DISCLAIMER
Trading any financial instrument involves substantial risk, and this indicator does not guarantee profits or prevent losses. All signals and visual cues are for educational and informational purposes only; past performance does not assure future outcomes. You retain full responsibility for your trading decisions, including proper risk management, position sizing, and the use of additional confirmation methods. Always consider the possibility of losing some or all of your original investment.
ALEX - ATR Extensions + ADR + TableALEX - ATR Extensions + ADR + Table
Overview
The ALEX ATR Extensions indicator is a comprehensive volatility and momentum analysis tool that combines Average True Range (ATR), Average Daily Range (ADR), and moving average distance calculations in a single, customizable display. This indicator helps traders assess current price action relative to historical volatility and key moving averages, providing crucial context for risk management and trade planning.
Key Features
Multi-Metric Analysis
- ATR Percentage: Current ATR as a percentage of price for volatility assessment
- ADR Percentage: Average Daily Range as a percentage for typical daily movement
- Low of Day Distance: Distance from current price to daily low
- Moving Average Distance: ATR-normalized distance from 21 and 50 period moving averages
Flexible Moving Average Options
- Configurable MA Types: Choose between EMA or SMA for both 21 and 50 period averages
- Customizable Periods: Adjust moving average lengths to suit your trading style
- Daily Timeframe Data: Uses daily moving averages regardless of chart timeframe
ATR Extension Levels
- Dynamic Price Targets: Calculate extension levels based on ATR multiples from moving averages
- Visual Reference Lines: Optional overlay lines showing ATR extension targets
- Customizable Multipliers: Adjust ATR multipliers for different risk/reward scenarios
Smart Visual Alerts
- Color-Coded Distance Metrics: Automatic color changes based on distance thresholds
- Symbol Plotting: Customizable chart symbols when distance thresholds are exceeded
- Threshold-Based Alerts: Visual cues when price reaches significant ATR distances
Comprehensive Data Table
- Real-Time Metrics: Live updating table with all key measurements
- Customizable Display: Toggle individual metrics on/off based on preference
- Professional Styling: Adjustable colors, fonts, and transparency
How to Use
Volatility Assessment
- High ATR%: Indicates elevated volatility, larger position sizing considerations
- Low ATR%: Suggests compressed volatility, potential for expansion
- ADR% Comparison: Compare current day's range to historical average
Moving Average Analysis
- ATR Distance 21/50: Normalized distance showing how extended price is from key levels
- Positive Values: Price above moving average (bullish positioning)
- Negative Values: Price below moving average (bearish positioning)
- Color Changes: Automatic alerts when reaching threshold levels
Extension Target Planning
- ATR Extension Lines: Visual price targets based on volatility-adjusted projections
- Risk/Reward Planning: Use extension levels for profit target placement
- Breakout Confirmation: Extension levels can confirm breakout validity
Symbol Alert System
- Chart Symbols: Automatic plotting when distance thresholds are breached
- Customizable Triggers: Set your own threshold levels for alerts
- Visual Scanning: Quick identification of extended conditions across multiple charts
Settings
Display Controls
- Show ADR%: Toggle average daily range percentage display
- Show ATR%: Toggle average true range percentage display
- Show LoD Distance: Toggle low of day distance calculation
- Show LoD Price: Toggle actual low of day price display
- Show ATR Distance from 21/50 DMA: Toggle moving average distance metrics
- Show 21/50 DMA Price: Toggle actual moving average price display
- Show ATR Extension Levels: Toggle extension target display in table
Moving Average Configuration
- 21/50 DMA Type: Choose between EMA or SMA calculation methods
- 21/50 DMA Period: Customize moving average lengths
- ADR/ATR Length: Adjust calculation periods for range measurements
Color Thresholds
- Threshold Levels: Set distance levels for color changes (default 2.0 and 5.0)
- Custom Colors: Choose colors for different threshold breaches
- Separate 21/50 Settings: Independent color schemes for each moving average
Symbol Settings
- Show Char Symbol: Toggle symbol plotting for each moving average
- Custom Symbols: Choose any character for chart plotting
- Symbol Colors: Customize colors for visual distinction
- Threshold Levels: Set trigger points for symbol appearance
ATR Extension Lines
- Show Extension Lines: Toggle visual extension level lines
- ATR Multipliers: Customize extension distance (default 2.0x)
- Line Colors: Choose colors for extension level visualization
Table Customization
- Background Color: Adjust table transparency and color
- Text Color: Customize default text appearance
- Font Size: Choose from tiny to huge font options
Advanced Applications
Trend Strength Analysis
- Large ATR distances suggest strong trending moves
- Small ATR distances indicate potential consolidation or reversal zones
- Compare current readings to recent historical ranges
Risk Management
- Use ATR% for position sizing calculations
- Extension levels provide natural profit target zones
- Distance metrics help identify overextended conditions
Multi-Timeframe Context
- Apply to different timeframes for comprehensive analysis
- Daily data provides consistency across all chart intervals
- Combine with weekly/monthly analysis for broader context
Market Regime Identification
- High volatility periods: Increased ATR% readings
- Low volatility periods: Compressed ATR% readings
- Trending markets: Sustained high distance readings
- Consolidating markets: Low distance readings with frequent color changes
Best Practices
Volatility-Adjusted Trading
- Increase position sizes during low volatility periods
- Reduce position sizes during high volatility periods
- Use ATR% for stop-loss placement relative to normal market movement
Extension Level Usage
- Primary targets: 1.5-2.0x ATR extensions
- Secondary targets: 2.5-3.0x ATR extensions
- Avoid chasing prices beyond 3x ATR extensions
Threshold Optimization
- Backtest different threshold levels for your trading style
- Consider market conditions when setting alert levels
- Adjust thresholds based on instrument volatility characteristics
Integration Strategies
- Combine with momentum indicators for confirmation
- Use alongside support/resistance levels
- Incorporate into systematic trading approaches
Technical Specifications
- Compatible with Pine Script v6
- Uses daily timeframe data for consistency
- Optimized for real-time performance
- Works on all chart types and timeframes
- Supports all tradeable instruments
Ideal For
- Swing traders using daily charts
- Position traders seeking volatility context
- Day traders needing intraday reference levels
- Risk managers requiring volatility metrics
- Systematic traders building rule-based strategies
Disclaimer
This indicator is for educational and informational purposes only. It should not be used as the sole basis for trading decisions. Always combine with other forms of analysis, proper risk management techniques, and consider your individual trading plan and risk tolerance. Past performance does not guarantee future results.
Compatible with Pine Script v6 | Optimized for daily timeframe analysis | Works across all markets and instruments
21DMA Structure Counter (EMA/SMA Option)21DMA Structure Counter (EMA/SMA Option)
Overview
The 21DMA Structure Counter is an advanced technical indicator that tracks consecutive periods where price action remains above a 21-period moving average structure. This indicator helps traders identify momentum phases and potential trend exhaustion points using statistical analysis.
Key Features
Moving Average Structure
- Configurable MA Type: Choose between EMA (Exponential Moving Average) or SMA (Simple Moving Average)
- 21-Period Default: Optimized for the widely-watched 21-period moving average
- Triple MA Structure: Tracks high, close, and low moving averages for comprehensive analysis
Statistical Analysis
- Cycle Counting: Automatically counts consecutive periods above the MA structure
- Historical Data: Maintains up to 2,500 historical cycles (approximately 10 years of daily data)
- Z-Score Calculation: Provides statistical context using mean and standard deviation
- Multiple Standard Deviation Levels: Displays +1, +2, and +3 standard deviation thresholds
Visual Indicators
Color-Coded Bars:
- Gray: Below 10-year average
- Yellow: Between average and +1 standard deviation
- Orange: Between +1 and +2 standard deviations
- Red: Between +2 and +3 standard deviations
- Fuchsia: Above +3 standard deviations (extreme readings)
Breadth Integration
- Multiple Breadth Options: NDFI, NDTH, NDTW (NASDAQ breadth indicators), or VIX
- Background Shading: Visual alerts when breadth reaches extreme levels
- High/Low Thresholds: Customizable levels for breadth analysis
- Real-time Display: Current breadth value shown in data table
Smart Reset Logic
- High Below Structure Reset: Automatically resets count when daily high falls below the lowest MA
- Flexible Hold Period: Continues counting during temporary weakness as long as structure isn't violated
- Precise Entry/Exit: Strict criteria for starting cycles, flexible for maintaining them
How to Use
Trend Identification
- Rising Counts: Indicate sustained momentum above key moving average structure
- Extreme Readings: Z-scores above +2 or +3 suggest potential trend exhaustion
- Historical Context: Compare current cycles to 10-year statistical averages
Risk Management
- Breadth Confirmation: Use breadth shading to confirm market-wide strength/weakness
- Statistical Extremes: Exercise caution when readings reach +3 standard deviations
- Reset Signals: Pay attention to structure violations for potential trend changes
Multi-Timeframe Application
- Daily Charts: Primary timeframe for swing trading and position management
- Weekly/Monthly: Longer-term trend analysis
- Intraday: Shorter-term momentum assessment (adjust MA period accordingly)
Settings
Moving Average Options
- Type: EMA or SMA selection
- Period: Default 21 (customizable)
- Reset Days: Days below structure required for reset
Visual Customization
- Standard Deviation Lines: Toggle and customize colors for +1, +2, +3 SD
- Breadth Selection: Choose from NDFI, NDTH, NDTW, or VIX
- Threshold Levels: Set custom high/low breadth thresholds
- Table Styling: Customize text colors, background, and font size
Technical Notes
- Data Retention: Maintains 2,500 historical cycles for robust statistical analysis
- Real-time Updates: Calculations update with each new bar
- Breadth Integration: Uses security() function to pull external breadth data
- Performance Optimized: Efficient array management prevents memory issues
Best Practices
1. Combine with Price Action: Use alongside support/resistance and chart patterns
2. Monitor Breadth Divergences: Watch for breadth weakness during strong readings
3. Respect Statistical Extremes: Exercise caution at +2/+3 standard deviation levels
4. Context Matters: Consider overall market environment and sector rotation
5. Risk Management: Use appropriate position sizing, especially at extreme readings
Disclaimer
This indicator is for educational and informational purposes only. It should not be used as the sole basis for trading decisions. Always combine with other forms of analysis and proper risk management techniques.
Compatible with Pine Script v6 | Optimized for daily timeframes | Best used on major indices and liquid stocks
