Gap % Distribution Table (2% Bins)Description
This indicator displays a Gap % Distribution Table categorized in 2% bins ranging from `< -20%` to `> +20%`. It calculates the gap between today’s open and the previous day’s close, and groups occurrences into defined bins. The table includes:
Gap range, count, and percentage for each bin
A total row summarizing all entries
Customizable appearance including:
Font color, cell background fill (with transparency), and table border color
Column headers and full outer border
Date filtering using selectable start and end dates
Position control for placing the table on the chart area
Ideal for analyzing the historical behavior of opening gaps for any instrument.
Göstergeler ve stratejiler
Devils MarkThe Devil’s Mark Indicator identifies bullish or bearish candlesticks with no opposing wick, plotting a horizontal line at the open/low (bullish) or open/high (bearish) price to mark the inefficiency.
This line highlights the level where price is expected to retrace to form the missing wick, serving as a visual cue.
The line is automatically removed from the chart once price crosses it, confirming the inefficiency has been rebalanced.
Strategic LevelsIntroduction
The Strategic Levels indicator plots key high and low price levels for monthly, weekly, daily, and Monday (current week) timeframes. It draws horizontal lines with consolidated labels to highlight significant support and resistance zones.
How to use it ?
Identify critical price levels for trade entries, exits, and risk management.
These prices levels (monthly, weekly, daily open/close) are significant inflection points during short term price movements.
Perfect for swing traders, day traders, or anyone using support/resistance strategies.
Best used for trades lasting no more than a few days.
Contrarian with 5 Levels5 Levels application was inspired and adapted from Predictive Ranges indicator developed by Lux Algo. So much credit to their work.
Indicator Description: Contrarian with 5 Levels
Overview
The "Contrarian with 5 Levels" indicator is a powerful tool designed for traders seeking to identify potential reversal points in the market by combining contrarian trading principles with dynamic support and resistance levels. This indicator overlays a Simple Moving Average (SMA) shadow and five adaptive price levels, integrating Institutional Concepts of Structure (ICT) such as Break of Structure (BOS) and Market Structure Shift (MSS) to provide clear buy and sell signals. It is ideal for traders looking to capitalize on overextended price movements, particularly on the daily timeframe, though it is adaptable to other timeframes with proper testing.
How It Works
The indicator operates on two core components:
Contrarian SMA Shadow: A shaded region between the SMA of highs and lows (default length: 100) acts as a dynamic zone to identify overbought or oversold conditions. When the price moves significantly outside this shadow, it signals potential exhaustion, aligning with contrarian trading principles.
Five Adaptive Levels: Using a modified ATR-based calculation, the indicator plots five key levels (two resistance, one average, and two support) that adjust dynamically to market volatility. These levels serve as critical zones for potential reversals.
ICT Structure Analysis: The indicator incorporates BOS and MSS logic to detect shifts in market structure, plotting bullish and bearish breaks with customizable colors for clarity.
Buy and sell signals are generated when the price crosses key levels while outside the SMA shadow, indicating potential reversal opportunities. The signals are visualized as small circles above (sell) or below (buy) the price bars, making them easy to interpret.
Mathematical Concepts
SMA Shadow: The indicator calculates the SMA of the highest highs and lowest lows over a user-defined period (default: 100). This creates a dynamic range that highlights extreme price movements, which contrarian traders often target for reversals.
Five Levels Calculation: The five levels are derived using a volatility-adjusted formula based on the Average True Range (ATR). The average level (central pivot) is calculated as a smoothed price, with two upper (resistance) and two lower (support) levels offset by a multiple of the ATR (default multiplier: 6.0). This adaptive approach ensures the levels remain relevant across varying market conditions.
ICT BOS/MSS Logic: The indicator identifies pivot highs and lows on a user-defined timeframe (default: daily) to detect structural breaks. A BOS occurs when the price breaks a prior pivot high (bullish) or low (bearish), while an MSS signals a shift in market direction, providing context for potential reversals.
Entry and Exit Rules
Buy Signal (Blue Dot Below Bar): Triggered when the closing price is below both the SMA shadow (smaLow) and the average level (avg), and the price crosses under either the first or second support level (prS1 or prS2). This suggests the market may be oversold, indicating a potential reversal upward.
Sell Signal (White Dot Above Bar): Triggered when the closing price is above both the SMA shadow (smaHigh) and the average level (avg), and the price crosses over either the first or second resistance level (prR1 or prR2). This suggests the market may be overbought, indicating a potential reversal downward.
Recommended Usage
This indicator is optimized for the daily timeframe, where it has been designed to capture significant reversal opportunities in trending or ranging markets. However, it can be adapted to other timeframes (e.g., 1H, 4H, 15M) with proper testing of settings such as SMA length, ATR multiplier, and structure timeframe. Users are encouraged to backtest and optimize parameters to suit their trading style and asset class.
Customization Options
SMA Length: Adjust the SMA period (default: 100) to control the sensitivity of the shadow.
Five Levels Length and Multiplier: Modify the length (default: 200) and ATR multiplier (default: 6.0) to fine-tune the support/resistance levels.
Timeframe Settings: Set separate timeframes for structure analysis and five levels to align with your trading strategy.
Color and Signal Display: Customize colors for BOS/MSS lines and toggle buy/sell signals on or off for a cleaner chart.
Why Use This Indicator?
The "Contrarian with 5 Levels" indicator combines the power of contrarian trading with dynamic levels and market structure analysis, offering a unique perspective for identifying high-probability reversal setups. Its intuitive design, customizable settings, and clear signal visualization make it suitable for both novice and experienced traders. Whether you're trading forex, stocks, or cryptocurrencies, this indicator provides a robust framework for spotting potential turning points in the market.
We hope you find the "Contrarian with 5 Levels" indicator a valuable addition to your trading toolkit! Happy trading!
Please leave feedback in the comments section.
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.
80% Rule Indicator (ETH Session + SVP Prior Session)I created this script to show the 80% opportunity on chart if setting lines up.
"80% rule: Open outside the vah or Val. Spend 30 mins outside there then break back inside spend 15 mins below or above depending which way u broke. Then come back and retest the vah/val and take it to the poc as a first target with the final target being the other Val/vah "
📌 Script Summary
The "80% Rule Indicator (ETH Session + SVP Prior Session)" overlays your chart with prior session value area levels (VAH, VAL, and POC) calculated from extended-hours 30-minute data. It tracks when the price reenters the value area and confirms 80% Rule setups during your chosen trading session. You can optionally trigger alerts, show/hide market sessions, and fine-tune line appearance for a clean, modular workflow.
⚙️ Options & Settings Breakdown
- Use 24-Hour Session (All Markets)
When checked, the indicator ignores time zones and tracks signals during a full 24-hour period (0000-0000), helpful if you're outside U.S. trading hours or want consistent behavior globally.
- Market Session
Dropdown to select one of three key market zones:
- New York (09:30–16:00 ET)
- London (08:00–16:30 local)
- Tokyo (09:00–15:00 local)
Used to gate entry signals during relevant hours unless you choose the 24-hour option.
- Show PD VAH/VAL/POC Lines
Toggle to show or hide prior day’s levels (based on the 30-min extended session). Turning this off removes both the lines and their white text labels.
- Extend Lines Right
When enabled, the VAH/VAL/POC lines extend into the current day’s session. If disabled, they appear only at their anchor point.
- Highlight Selected Session
Adds a soft blue background to help visualize the active session you selected.
- Enable Alert Conditions
Allows TradingView alerts to be created for long/short 80% Rule entries.
- Enable Audible Alerts
Plays an in-chart sound with a popup message (“80% Rule LONG” or “SHORT”) when signals trigger. Requires the chart to be active and sounds enabled in TradingView.
Percent Change IndicatorPercent Change Indicator Description
Overview:
The Percent Change Indicator is a Pine Script (version 6) indicator designed for TradingView to calculate and visualize the percentage change of the current close price relative to a user-selected reference price. It provides a customizable interface to display percentage changes as candlesticks or a line plot, with optional horizontal lines and labels for key levels. The indicator also includes visual signals and alerts for user-defined percentage thresholds, making it useful for identifying significant price movements.
Key Features:
1. Percentage Change Calculation:
- Computes the percentage change of the current close price compared to a reference price, scaled by a user-defined length parameter.
- Formula: percentChange = (close - refPrice) / refPrice * len
- The reference price is sourced from a user-selected timeframe (default: 1D) and price type (Open, High, Low, Close, HL2, HLC3, or HLCC4).
2. Visualization Options:
- Candlestick Plot: Displays percentage change as candlesticks, colored green for rising values and red for falling values.
- Line Plot: Plots the percentage change as a line, with the same color logic.
- Horizontal Lines: Optional horizontal lines at key percentage levels (0%, ±0.2%, ±0.5%, ±0.8%, ±1%) for reference.
- Labels: Optional labels for percentage levels (0, ±15%, ±35%, ±50%, ±65%, ±85%, ±100%) displayed at the chart's right edge.
- All visualizations are toggleable via input settings.
3. Signal and Alert System:
- Threshold-Based Signals: Plots green triangles below bars for long signals (percent change above a user-defined threshold) and red triangles above bars for short signals (percent change below the threshold).
- Alerts: Configurable alerts for long and short conditions, triggered when the percentage change crosses the user-defined threshold (default: 2%). Alert messages include the threshold value for clarity.
4. Customizable Inputs:
- Show Labels: Toggle visibility of percentage level labels (default: true).
- Show Percentage Change: Toggle the line plot of percentage change (default: true).
- Show HLines: Toggle visibility of horizontal reference lines (default: false).
- Show Candle Plot: Toggle the candlestick plot (default: true).
- Percent Change Length: Adjust the scaling factor for percentage change (default: 14).
- Plot Timeframe: Select the timeframe for the reference price (default: 1D).
- Price Type: Choose the reference price type (Open, High, Low, Close, HL2, HLC3, HLCC4; default: Open).
- Percentage Threshold: Set the threshold for long/short signals and alerts (default: 0.02 or 2%).
How It Works:
- The indicator fetches the reference price using request.security() based on the selected timeframe and price type.
- It calculates the percentage change and scales it by the user-defined length.
- Visuals (candlesticks, lines, labels, horizontal lines) are plotted based on user preferences.
- Long and short signals are generated when the percentage change exceeds or falls below the user-defined threshold, with corresponding triangles plotted and alerts triggered.
Use Cases:
- Trend Identification: Monitor significant price movements relative to a reference price.
- Signal Generation: Identify potential entry/exit points based on percentage change thresholds.
- Custom Analysis: Analyze price changes across different timeframes and price types for various trading strategies.
- Alert Notifications: Receive alerts for significant price movements to stay informed without constant chart monitoring.
Setup Instructions:
1. Add the indicator to a TradingView chart.
2. Adjust input settings (timeframe, price type, threshold, etc.) to suit your analysis.
3. Enable/disable visualization options (candlesticks, lines, labels, horizontal lines) as needed.
4. Set up alerts in TradingView:
- Go to the "Alerts" tab and select "Percent Change Indicator."
- Choose "Long Alert" or "Short Alert" to monitor threshold crossings.
- Configure alert frequency and notification method (e.g., email, webhook).
Notes:
- The indicator is non-overlay, displayed in a separate pane below the main chart.
- Alerts trigger on bar close by default; adjust TradingView alert settings for real-time notifications if needed.
- The indicator is released under the Mozilla Public License 2.0.
Author: Dshergill
This indicator is ideal for traders seeking a flexible tool to track percentage-based price movements with customizable visuals and alerts.
Greer Value Yields Dashboard🧾 Greer Value Yields Dashboard – v1.0
Author: Sean Lee Greer
Release Date: June 22, 2025
🧠 Overview
The Greer Value Yields Dashboard visualizes and evaluates four powerful valuation metrics for any publicly traded company:
📘 Earnings per Share Yield
💵 Free Cash Flow Yield
💰 Revenue Yield
🏦 Book Value Yield
Each yield is measured as a percentage of current stock price and compared against its historical average. The script assigns 1 point per metric when the current yield exceeds its long-term average. The total score (0 to 4) is displayed as a color-coded column chart, helping long-term investors quickly assess fundamental valuation strength.
✅ Key Features
📊 Real-time calculation of 4 yield-based valuation metrics
⚖ Historical average tracking for each yield
🎯 Visual scoring system:
🟥 0–1 = Weak
🟨 2 = Neutral
🟩 4 = Strong (all metrics above average)
🎛️ Toggle visibility of each yield independently
🧮 Fully compatible with other Greer Financial Toolkit indicators
🛠 Ideal For
Long-term value investors
Dividend and cash-flow-focused investors
Analysts seeking clean yield visualizations
Greer Toolkit users combining with Greer Value and BuyZone
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.
AdvancedOFPIAnalyzerLibrary "AdvancedOFPIAnalyzer"
Advanced Order Flow Pressure Index Analyzer Library
Implements sophisticated volume distribution analysis with candle microstructure
Provides comprehensive order flow assessment for institutional activity detection
analyzeAdvancedOrderFlow(priceOpen, priceHigh, priceLow, priceClose, volumeData, analysisWindow, institutionalSensitivity)
Performs comprehensive order flow analysis with advanced institutional detection
Parameters:
priceOpen (float) : float Opening price for analysis
priceHigh (float) : float High price for range calculation
priceLow (float) : float Low price for support detection
priceClose (float) : float Closing price for trend assessment
volumeData (float) : float Volume data for flow analysis
analysisWindow (int) : int Analysis window period
institutionalSensitivity (float) : float Institutional detection sensitivity
Returns: OFPI, momentum, institutional detected, strength, phase, overall strength, class, volume available, trend, efficiency, market structure
calculateMicrostructurePressure(priceOpen, priceHigh, priceLow, priceClose, volumeData, microWindow)
Calculates sophisticated order flow pressure with comprehensive candle microstructure analysis
Parameters:
priceOpen (float) : float Opening price for pressure calculation
priceHigh (float) : float High price for range analysis
priceLow (float) : float Low price for support detection
priceClose (float) : float Closing price for trend assessment
volumeData (float) : float Volume data for pressure analysis
microWindow (int) : int Microstructure analysis window
Returns: Pressure index, buying pressure, selling pressure, body ratio, upper wick ratio, lower wick ratio, microstructure confidence, volume confirmation, institutional pressure, pressure velocity, microstructure quality
generateInstitutionalAlerts(priceClose, volumeData, alertSensitivity, lookbackPeriod)
Generates sophisticated volume-weighted institutional activity alerts
Parameters:
priceClose (float) : float Close price for analysis
volumeData (float) : float Volume data for detection
alertSensitivity (float) : float Alert sensitivity threshold
lookbackPeriod (int) : int Analysis lookback period
Returns: Institutional detected, alert level, phase, strength, volume signature, pressure signature, time signature, absorption signature, impact signature, reliability, active methods, priority
EnhancedSignalGeneratorLibrary "EnhancedSignalGenerator"
Enhanced Signal Generator – clean v6 implementation (UDT-based)
generateAdvancedSignal(unifiedScore, trendComp, momInd, volFactor, qualScore, cyclePos, regime)
Generates advanced signal analysis with multi-pathway evaluation
Parameters:
unifiedScore (float) : Unified market score input
trendComp (float) : Trend component analysis factor
momInd (float) : Momentum indicator value
volFactor (float) : Volatility adjustment factor
qualScore (float) : Quality assessment metric
cyclePos (float) : Market cycle position (0.0-1.0, where 0.5 = neutral cycle phase)
regime (string) : Market regime classification string ("bull", "bear", "sideways", "volatile")
Returns: Signal Comprehensive signal analysis result
analyzePatternSignals(h, l, c, v, w, reg)
Analyzes pattern-based signal components with multi-dimensional price action evaluation
Parameters:
h (float) : High price value for range analysis
l (float) : Low price value for support/resistance detection
c (float) : Close price value for momentum assessment
v (float) : Volume data for confirmation analysis
w (int) : Analysis window period for pattern formation timeframe
reg (string) : Market regime string for context-aware pattern interpretation
Returns: Signal Pattern analysis signal with comprehensive technical evaluation
optimizeSignalParameters(s, p, w, m)
Optimizes signal generation parameters through advanced statistical analysis
Parameters:
s (array) : Signal array input for performance evaluation
p (array) : Parameter array input for optimization target values
w (int) : Window period for rolling optimization analysis
m (string) : Optimization method string ("sharpe", "sortino", "calmar", "variance")
Returns: float Optimization result score representing parameter fitness
Signal
Signal data structure for market analysis
Fields:
dir (series int) : Signal direction: +1 bull, -1 bear, 0 flat
strength (series float) : Signal strength magnitude (0-1)
conf (series float) : Confidence level (0-1)
rationale (series string) : Human-readable explanation
source (series string) : Signal source classification
quality (series float) : Blended quality assessment score
Scanner Candles v2.01The "Scanner Candle v.2.01" is an indicator classifies candles based on the body/range ratio: indecisive (small body, ≤50%), decisive (medium body), explosive (large body, ≥70%). It includes EMAs to identify trends and "Reset Candles" (RC), small-bodied candles near EMAs, signaling potential reversals or continuations. Useful for analyzing volatility, breakouts, reversals, and risk management.
Description of the indicator:
The "Scanner Candle v.2.01" indicator classifies candles into three categories based on the proportion of the candle's body to its range (high-low):
Indecisive: candles with a small body (≤ set threshold, default 50%), indicating low volatility or market uncertainty.
Decisive: candles with a medium body, reflecting a clear but not extreme price movement.
Explosive: candles with a large body (≥ set threshold, default 70%), signaling strong directional moves.
Additionally, the indicator includes:
Customizable exponential moving averages (EMAs) to identify trends and support/resistance levels.
Detection of "Reset Candles" (RC), specific candles (e.g., dojis, ) with a small bodies body near EMAs, useful for identifying potential reversal or continuation points.
Coloring and visualization:
Candles are colored by category (white for indecisive, orange for decisive, purple for explosive).
Reset Candles are marked with circles above/below the candle (green for bullish, red for bearish).
Potential uses:
Volatility analysis: Identifying uncertain (indecisive), directional (decisive), or impulsive (explosive) market phases.
Breakout trading: Explosive candles can signal entry opportunities on strong moves.
Reversal detection: Reset Candles near EMAs can indicate turning points or trend continuation.
Trend-following support: Integrated EMAs contextualize candles within the main trend.
Risk management: Indecisive candles suggest avoiding trades in low-directionality phases.
The indicator is customizable (thresholds, colors, thresholdsEMAs, ) and adaptable to various timeframes and strategies, from day trading to swing trading.
Reset Candles:
Reset Candles (RC) are specific candles signaling potential reversals or continuations, often near EMAs. They are defined by:
Small body: Body < 5% of the range of the last 10 candles, indicating low volatility (e.g., doji).
EMA proximity: The candle is near or crosses a defined EMA (e.g., 10, 60, or 223 periods).
Trend conditions: Follows a red candle, with the close of the previous previous candles above a specific EMA, suggesting a potential bullish resumption or stabilization.
Limited spike: The candle has minimal tails (spikes, ) below a set threshold (default 1%).
Minimum timeframe: Appears on timeframes ≥ set value (default 5 minutes) or daily charts.
Non-consecutive: Not preceded by other RCs in the last 3 candles.
Types:
Doji_fin: Green circle above, signaling a bullish bullish setup near longer EMAs.
Dojifin_2: Yellow Red circle below, signaling a bearish setup near shorter EMAs.
Trading uses:
Reversal: RCs near EMAs signal bounces or rejections, ideal for counter-trend trades.
Continuation: In trends, RCs indicate pauses before trend resumption, offering low-risk entries.
Support/resistance confirmation: EMA proximity strengthens the level's significance.
Risk management: Small bodies and EMA proximity allow tight stop-losses.
Limitations:
False signals: Common in volatile or sideways markets; use with additional confirmation.
Timeframe dependency: More reliable on higher timeframes (e.g., 1-hour or daily).
Customization needed: Thresholds (e.g., spike, timeframe) must be tailored to the market.
Conclusion:
Reset Candles highlight low-volatility moments near technical levels (EMAs) that may precede significant moves. They are ideal for precise entries with tight stops in reversal or continuation strategies but require clear market context and additional confirmation for optimal effectiveness.
#ema #candlepattern #scalping
Movement WatcherMovement Watcher – Intraday Price Change Alert
This indicator tracks the percentage price movement of a selected symbol (e.g., VIX) from a configurable start time. If the intraday movement crosses a defined threshold (up or down), it triggers a one-time alert per day.
Key Features:
Monitors intraday % change from the specified start time.
Triggers one-time alerts for upper or lower threshold crossings.
Optional end time for monitoring period.
Visual plots and alert markers.
Useful for automated trading via webhook integrations.
This script was designed to work with automated trading tools such as the Trading Automation Toolbox. You can use it to generate alerts based on intraday volatility and route them via webhook for automated strategies.
Support & ResistanceWhat is this script ?
Pivot points are tools used to identify potential support and resistance levels in trading. They are calculated using the previous period’s high, low, and close prices. This script leverages pivot points to plot up to four support levels and four resistance levels, helping traders visualize key price zones.
How to Use the Script?
Support and resistance levels represent price zones where significant liquidity often exists due to past price interactions. These levels are critical for traders to:
Assess Trend Continuation or Reversal: Prices may pause, reverse, or break through at these levels, signaling potential trend changes or continuations.
Manage Risk: Support and resistance levels are ideal for placing stop-loss orders or setting profit targets, as they indicate areas where price reactions are likely.
Plan Entries and Exits: Traders can buy near support levels, sell near resistance levels, or trade breakouts when prices move decisively beyond these zones.
Risk and Position Sizing📏 Why Position Size Should Be Based on Risk?
Let’s say you are ready to lose 1,000 in a trade. Based on your stop loss level, you can calculate how many shares (or quantity) to buy, so that if the stop hits, you only lose that ₹1,000.
This is called risk-based position sizing. It makes your trade size dynamic — small when SL is wide, bigger when SL is tight. No more random position sizes — just systematic.
Portfolio size is multiplied by the selected risk % to get money risk per trade.
This amount is then used to calculate how many shares can be bought for the given stop-loss.
So chose your portfolio size in settings. Default Portfolio size is 1,00,000 .
You can select your risk % per portfolio in the settings — for example:
0.25% for conservative style
0.5% to 1% for balanced traders
1.25% or 1.5% for aggressive ones (not recommended for beginners)
This script will automatically calculate how much quantity you should buy, for each stop-loss scenario.
📈 Progressive & Inverse-Progressive Risk Styles
Some traders follow progressive position sizing — they start with small risk when the trend is just starting, and increase the risk % as the trend confirms.
Others follow inverse-progressive sizing — they take high risk at early stages of a bull market, and reduce risk as the trend matures (when upside becomes limited).
📌 This script allows you to manually control the risk % in settings, so you can adjust it based on your trading phase and style.
📋 Three SL Scenarios – Choose What Matches Your Style
The table shows three different stop-loss conditions, and for each one it calculates:
Today’s Low – tightest stop loss
Yesterday’s Low – slightly safer, ideal for short-term swing trades
EMA Stop (configurable) – gives more breathing room.
You can visually compare all 3 in the table and choose whichever fits your strategy and comfort.
Also, you can customize:
Theme: dark or light
Font size
Table position (upper/lower corners)
🧠 Designed for traders who take risk management seriously.
Let this script handle the math. You focus on execution.
Happy Trading!
– LensOfChartist
LilSpecCodes1. Killzone Background Highlighting:
It highlights 4 key market sessions:
Killzone Time (EST) Color
Silver Bullet 9:30 AM – 12:00 PM Light Blue
London Killzone 2:00 AM – 5:00 AM Light Green
NY PM Killzone 1:30 PM – 4:00 PM Light Purple
Asia Open 7:00 PM – 11:00 PM Light Red
These are meant to help you focus during high-probability trading times.
__________________________________________________
2. Previous Day High/Low (PDH/PDL):
Plots green line = PDH
Plots red line = PDL
Tracks the current day’s session high/low and sets it as PDH/PDL on a new trading day
CHANGES WITH ETH/RTH
3. Inside Bar Marker:
Plots a small black triangle under bars where the high is lower than the previous bar’s high and the low is higher than the previous bar’s low (inside bars)
Useful for spotting potential breakout or continuation setups
4. Vertical Time Markers (White Dashed Lines)
Time (EST) Label
4:00 AM End of London Silver Bullet
9:30 AM NYSE Open
10:00 AM Start of NY Silver Bullet
11:00 AM End of NY Silver Bullet
11:30 AM (Customizable Input)
3:00 PM PM Killzone Ends
3:15 PM Futures Market Close
7:15 PM Asia Session Watch
LabelManagementLabel management with fluent configuration, change tracking, and named registry
LabelManagement is a Pine Script library for creating and managing dynamic chart labels. Built with a fluent-style API , it simplifies label creation, styling, positioning, and content updates through method chaining and centralized control.
Manage 'sticky' labels easily across bars with expressive, readable code that reduces clutter and improves code clarity.
Example usage:
// Close label – to the right of the last bar
labels.get("close")
.style(label.style_label_left)
.bgColor(color.gray)
.xy(bar_index, close)
.textValue("C: " + str.tostring(close, "#.##"))
.textColor(color.white)
.tooltip("This is the close price")
.apply()
Key features:
Fluent API – Build and update labels using a chainable configuration flow
Named label registry – Access and manage labels by name, e.g., "entry", "stop", "target"
Change tracking – Update only when necessary to reduce redraws
Deferred application – Apply all changes in one efficient operation
Centralized control – Works well in modular or multi-label environments
This library is designed for Pine developers who want more control and less boilerplate when managing visual elements on the chart.
method clone(this)
Creates a new LabelConfig by copying all properties from this instance
Namespace types: LabelConfig
Parameters:
this (LabelConfig) : (LabelConfig) The LabelConfig instance
Returns: (LabelConfig) New LabelConfig instance with identical properties
method applyTo(this, target)
Applies configuration to specified label (required parameter)
Namespace types: LabelConfig
Parameters:
this (LabelConfig) : (LabelConfig) The LabelConfig instance
target (label) : (label) Label to apply config to
Returns: (LabelConfig) Self-reference for method chaining
method update(this, updates)
Creates a new LabelUpdater with change tracking for this label
Namespace types: series label
Parameters:
this (label) : (label) The label instance
updates (LabelConfig) : (LabelConfig) Optional existing config to apply and reuse (if provided, applies to label first)
Returns: (LabelUpdater) New LabelUpdater with blank configs for change tracking
method x(this, value)
Sets the X coordinate with change tracking (fluent interface)
Namespace types: LabelUpdater
Parameters:
this (LabelUpdater) : (LabelUpdater) The LabelUpdater instance
value (int) : (int) New X coordinate
Returns: (LabelUpdater) Self-reference for method chaining
method y(this, value)
Sets the Y coordinate with change tracking (fluent interface)
Namespace types: LabelUpdater
Parameters:
this (LabelUpdater) : (LabelUpdater) The LabelUpdater instance
value (float) : (float) New Y coordinate
Returns: (LabelUpdater) Self-reference for method chaining
method xy(this, x, y)
Sets both X and Y coordinates with change tracking (fluent interface)
Namespace types: LabelUpdater
Parameters:
this (LabelUpdater) : (LabelUpdater) The LabelUpdater instance
x (int) : (int) New X coordinate
y (float) : (float) New Y coordinate
Returns: (LabelUpdater) Self-reference for method chaining
method textValue(this, value)
Sets the text content with change tracking (fluent interface)
Namespace types: LabelUpdater
Parameters:
this (LabelUpdater) : (LabelUpdater) The LabelUpdater instance
value (string) : (string) New text content
Returns: (LabelUpdater) Self-reference for method chaining
method textColor(this, value)
Sets the text color with change tracking (fluent interface)
Namespace types: LabelUpdater
Parameters:
this (LabelUpdater) : (LabelUpdater) The LabelUpdater instance
value (color) : (color) New text color
Returns: (LabelUpdater) Self-reference for method chaining
method textSize(this, value)
Sets the text size with change tracking (fluent interface)
Namespace types: LabelUpdater
Parameters:
this (LabelUpdater) : (LabelUpdater) The LabelUpdater instance
value (string) : (string) New text size
Returns: (LabelUpdater) Self-reference for method chaining
method bgColor(this, value)
Sets the background color with change tracking (fluent interface)
Namespace types: LabelUpdater
Parameters:
this (LabelUpdater) : (LabelUpdater) The LabelUpdater instance
value (color) : (color) New background color
Returns: (LabelUpdater) Self-reference for method chaining
method style(this, value)
Sets the label style with change tracking (fluent interface)
Namespace types: LabelUpdater
Parameters:
this (LabelUpdater) : (LabelUpdater) The LabelUpdater instance
value (string) : (string) New style
Returns: (LabelUpdater) Self-reference for method chaining
method yloc(this, value)
Sets the Y location mode with change tracking (fluent interface)
Namespace types: LabelUpdater
Parameters:
this (LabelUpdater) : (LabelUpdater) The LabelUpdater instance
value (string) : (string) New yloc
Returns: (LabelUpdater) Self-reference for method chaining
method xloc(this, value)
Sets the X location mode with change tracking (fluent interface)
Namespace types: LabelUpdater
Parameters:
this (LabelUpdater) : (LabelUpdater) The LabelUpdater instance
value (string) : (string) New xloc
Returns: (LabelUpdater) Self-reference for method chaining
method tooltip(this, value)
Sets the tooltip content with change tracking (fluent interface)
Namespace types: LabelUpdater
Parameters:
this (LabelUpdater) : (LabelUpdater) The LabelUpdater instance
value (string) : (string) New tooltip content
Returns: (LabelUpdater) Self-reference for method chaining
method size(this, value)
Sets the text size with change tracking (fluent interface) - alias for textSize
Namespace types: LabelUpdater
Parameters:
this (LabelUpdater) : (LabelUpdater) The LabelUpdater instance
value (string) : (string) New text size
Returns: (LabelUpdater) Self-reference for method chaining
method size(this)
Gets the count of registered labels
Namespace types: LabelManager
Parameters:
this (LabelManager) : (LabelManager) The LabelManager instance
Returns: (int) Number of labels in the registry
method apply(this)
Applies pending changes to linked label and updates tracking
Namespace types: LabelUpdater
Parameters:
this (LabelUpdater) : (LabelUpdater) The LabelUpdater instance
Returns: (LabelUpdater) Self-reference for method chaining
method get(this, name)
Gets or creates a LabelUpdater for the specified name
Namespace types: LabelManager
Parameters:
this (LabelManager) : (LabelManager) The LabelManager instance
name (string) : (string) Unique identifier for the label
Returns: (LabelUpdater) Existing or newly created LabelUpdater for the name
method has(this, name)
Checks if a label with the specified name exists
Namespace types: LabelManager
Parameters:
this (LabelManager) : (LabelManager) The LabelManager instance
name (string) : (string) Name to check for existence
Returns: (bool) True if label exists, false otherwise
method remove(this, name)
Removes a label from the registry and deletes the underlying Pine Script label
Namespace types: LabelManager
Parameters:
this (LabelManager) : (LabelManager) The LabelManager instance
name (string) : (string) Name of the label to remove
Returns: (LabelManager) Self-reference for method chaining
method clear(this)
Removes all labels from registry and deletes all underlying Pine Script labels
Namespace types: LabelManager
Parameters:
this (LabelManager) : (LabelManager) The LabelManager instance
Returns: (LabelManager) Self-reference for method chaining
newManager()
Creates a new LabelManager with empty registry
Returns: (LabelManager) New LabelManager instance ready for use
LabelConfig
LabelConfig Configuration object for label appearance and positioning
Fields:
x (series int) : (series int) X-coordinate (na = unchanged)
y (series float) : (series float) Y-coordinate (na = unchanged)
style (series string) : (series string) Label style (na = unchanged)
yloc (series string) : (series string) Y-location type (na = unchanged)
xloc (series string) : (series string) X-location type (na = unchanged)
bgColor (series color) : (series color) Background color (na = unchanged)
textValue (series string) : (series string) Label text content (na = unchanged)
textSize (series string) : (series string) Text size (na = unchanged)
textColor (series color) : (series color) Text color (na = unchanged)
tooltip (series string) : (series string) Tooltip text (na = unchanged)
LabelUpdater
LabelUpdater Smart label updater with change tracking and minimal updates
Fields:
label (series label) : (label) Reference to the label being updated
latest (LabelConfig) : (LabelConfig) Current known state of the label
updates (LabelConfig) : (LabelConfig) Pending changes to apply
LabelManager
LabelManager Central registry for managing named labels with automatic creation
Fields:
registry (map) : (map) Internal storage mapping names to LabelUpdater instances
LotSize Calculator - psyploThis indicator provides a convenient on-chart lot size calculator designed to assist traders with precise position sizing based on account balance, risk tolerance, and trade parameters.
Key Features:
Custom Account Sizing: Define your account size and risk percentage per trade.
Flexible Risk Units: Choose between percentage or fixed currency risk models.
Support for Multiple Currencies: Select from a wide range of currencies including USD, EUR, GBP, INR, and even crypto options like USDT.
Dual Sizing Methods: Configure position size using either quantity or lot-based models, with optional rounding.
Visual Trade Levels: Displays configurable entry, stop loss (SL), and take profit (TP) lines on the chart.
Style Customization: Customize the color, line style, and visibility of each level for better chart readability.
Ideal Use Case:
Designed for manual traders seeking real-time clarity and consistency in risk management without needing to calculate lot size externally.
Disclaimer:
This tool is for informational purposes only. Always practice responsible risk management and perform due diligence before trading.
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.
CAGR + Log Slope ColorThis custom TradingView indicator combines two important analytical concepts to help traders identify strong trends with visual clarity:
CAGR (Compound Annual Growth Rate):
Measures the geometric average annual return of the asset over a specified period. It smooths out short-term fluctuations and provides a long-term growth perspective.
Logarithmic Slope Coloring:
The slope of the log-scaled price is calculated and visualized with color gradients. Steeper upward slopes indicate stronger momentum and are highlighted with more intense colors. Downward slopes are shown in contrasting colors for easier identification of bearish trends.
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.
Volume Zones IndicatorVolume Zones Indicator — VWAP with Dynamic Monthly Volume Zones
This indicator is an enhanced version of the classic VWAP (Volume Weighted Average Price), designed to create clear monthly zones around VWAP based on average price range (ATR) and volume activity.
The core idea is to highlight key zones where price is more likely to reverse or consolidate, based on where significant trading volume occurs.
How does it work?
VWAP is calculated over the last N days (set by the lookbackPeriod input).
Four zones are plotted above and below VWAP, spaced using a multiple of ATR.
Each zone has its own color for clarity:
Blue — closest to VWAP
Red — second band
Green — third band
Orange — outer band (potential breakout or exhaustion zone)
If the current volume exceeds the moving average of volume, it is highlighted directly on the chart. This helps detect accumulation or distribution moments more easily.
What does the trader see?
You see horizontal colored bands on the chart that update at the start of each new month. These zones:
Remain fixed throughout the month
Automatically adjust based on recent volume and volatility
Act as dynamic support/resistance levels
Best used for:
Mean reversion strategies — identifying pullbacks toward value areas
Support and resistance mapping — automatic SR zones based on price/volume behavior
Breakout filtering — when price reaches zone 3 or 4, trend continuation or reversal is likely
Adding volume context to price action — works well with candlestick and pattern analysis
Settings
Lookback Period (Days): VWAP and volume smoothing length
Volume Area Threshold %: Reserved for future functionality
Works on any timeframe; best suited for 4H timeframe.
Zones are calculated and fixed monthly for clean visual context
Combines price structure with actual volume flow for more reliable decision-making
Share SizePurpose: The "Share Size" indicator is a powerful risk management tool designed to help traders quickly determine appropriate share/contract sizes based on their predefined risk per trade and the current market's volatility (measured by ATR). It calculates potential dollar differences from recent highs/lows and translates them into a recommended share/contract size, accounting for a user-defined ATR-based offset. This helps you maintain consistent risk exposure across different instruments and market conditions.
How It Works: At its core, the indicator aims to answer the question: "How many shares/contracts can I trade to keep my dollar risk within limits if my stop loss is placed at a recent high or low, plus an ATR-based buffer?"
Price Difference Calculation: It first calculates the dollar difference between the current close price and the high and low of the current bar (Now) and the previous 5 bars (1 to 5).
Tick Size & Value Conversion: These price differences are then converted into dollar values using the instrument's specific tickSize and tickValue. You can select common futures contracts (MNQ, MES, MGC, MCL), a generic "Stock" setting, or define custom values.
ATR Offset: An Average True Range (ATR) based offset is added to these dollar differences. This offset acts as a buffer, simulating a stop loss placed beyond the immediate high/low, accounting for market noise or volatility.
Risk-Based Share Size: Finally, using your Default Risk ($) input, the indicator calculates how many shares/contracts you can take for each of the 6 high/low scenarios (current bar, 5 previous bars) to ensure your dollar risk per trade remains constant.
Dynamic Table: All these calculations are presented in a clear, real-time table at the bottom-left of your chart. The table dynamically adjusts its "Label" to show the selected symbol preset, making it easy to see which instrument's settings are currently being used. The "Shares" rows indicate the maximum shares/contracts you can trade for a given risk and stop placement. The cells corresponding to the largest dollar difference (and thus smallest share size) for both high and low scenarios are highlighted, drawing your attention to the most conservative entry points.
Key Benefits:
Consistent Risk: Helps maintain a consistent dollar risk per trade, regardless of the instrument or its current price/volatility.
Dynamic Sizing: Automatically adjusts share/contract size based on market volatility and your chosen stop placement.
Quick Reference: Provides a real-time, easy-to-read table directly on your chart, eliminating manual calculations.
Informed Decision Making: Assists in quickly assessing trade opportunities and potential position sizes.
Setup Parameters (Inputs)
When you add the "Share Size" indicator to your chart, you'll see a settings dialog with the following parameters:
1. Symbol Preset:
Purpose: This is the primary setting to define the tick size and value for your chosen trading instrument.
Options:
MNQ (Micro Nasdaq 100 Futures)
MES (Micro E-mini S&P 500 Futures)
MGC (Micro Gold Futures)
MCL (Micro Crude Oil Futures)
Stock (Generic stock setting, with tick size/value of 0.01)
Custom (Allows you to manually input tick size and value)
Default: MNQ
Importance: Crucial for accurate dollar calculations. Ensure this matches the instrument you are trading.
2. Tick Size (Manual Override):
Purpose: Only used if Symbol Preset is set to Custom. This defines the smallest price increment for your instrument.
Type: Float
Default: 0.25
Hidden: This input is hidden (display=display.none) unless "Custom" is selected. You might need to change display=display.none to display=display.inline in the code if you want to see and adjust it directly in the settings for "Custom" mode.
3. Tick Value (Manual Override):
Purpose: Only used if Symbol Preset is set to Custom. This defines the dollar value of one tickSize increment.
Type: Float
Default: 0.50
Hidden: This input is hidden (display=display.none) unless "Custom" is selected. Similar to Tick Size, you might need to adjust its display property if you want it visible.
4. Default Risk ($):
Purpose: This is your maximum desired dollar risk per trade. All share size calculations will be based on this value.
Type: Float
Default: 50.0
Hidden: This input is hidden (display=display.none). It's a critical setting, so consider making it visible by changing display=display.none to display=display.inline in the code if you want users to easily adjust their risk.
ATR Offset Settings (Group): This group of settings allows you to fine-tune the ATR-based buffer added to your potential stop loss.
5. ATR Offset Length:
Purpose: Defines the lookback period for the Average True Range (ATR) calculation used for the offset.
Type: Integer
Default: 7
Hidden: This input is hidden (display=display.none).
6. ATR Offset Timeframe:
Purpose: Specifies the timeframe on which the ATR for the offset will be calculated. This allows you to use ATR from a higher timeframe for your stop buffer, even if your chart is on a lower timeframe.
Type: Timeframe string (e.g., "1" for 1 minute, "60" for 1 hour, "D" for Daily)
Default: "1" (1 Minute)
Hidden: This input is hidden (display=display.none).
7. ATR Offset Multiplier (x ATR):
Purpose: Multiplies the calculated ATR value to determine the final dollar offset added to your high/low price difference. A value of 1.0 means one full ATR is added. A value of 0.5 means half an ATR is added.
Type: Float
Minimum Value: 0 (no offset)
Default: 1.0
Hidden: This input is hidden (display=display.none).
