Tradeable Candle Detection By Raja SaienTradeable Candle Detection By Raja Saien
Overview:
This advanced candle detection tool is designed to help traders identify high-quality trade setups and avoid fake moves, based on candle structure, volume, and RSI conditions. Unlike many indicators that are limited to specific sessions, this script works across all market sessions, giving you full flexibility to trade 24/7.
🔍 Key Features:
All Session Support (24/7 Trading)
Detects tradeable setups during any time of the day, including Asian, London, New York, and overlapping hours.
No restriction to any specific session — trade when the opportunity is there!
Fake Move Detection 🚫
Identifies candles with long wicks, small bodies, and low volume — typical signs of manipulation or indecision.
Displays a “No Trade Zone – Fake Move” label to help you avoid poor entries.
Real Move Detection ✅
Highlights candles with strong bodies, short wicks, and high volume — ideal conditions for trade entries.
Helps you focus only on high-probability, momentum-driven moves.
RSI-Based Confirmation
Uses RSI to ensure trade entries align with momentum:
Bullish Entry Allowed: Candle is bullish + RSI between 50–75.
Bearish Entry Allowed: Candle is bearish + RSI between 25–50.
Avoid Trades: RSI is overbought/oversold or showing divergence.
Divergence Detection
Detects bearish divergence in bullish setups and bullish divergence in bearish setups — warns against risky entries.
Visual Zones & Candle Highlights
Plots horizontal lines at candle highs/lows and extended zones based on candle range.
Dominant candles are highlighted in black for quick visual spotting.
⚙️ Custom Inputs:
Minimum Body Size Threshold
Wick-to-Body Ratio for Fake Move
Volume Strength Multiplier
Candle Dominance Precision (% of range)
RSI Period and Source
Optional session filter (can be turned off to enable all-session detection)
🛎️ Alerts Included:
✅ Long Entry Confirmed – Strong bullish candle with supporting RSI
✅ Short Entry Confirmed – Strong bearish candle with supporting RSI
🚫 Fake Move Detected – Weak structure + low volume, no trade
🧠 How to Use:
Wait for a dominant black candle to appear.
Read the label to understand:
✅ Green = Trade Allowed
⚠️ Orange = Avoid (due to RSI or divergence)
🚫 Red = Fake Move (stay out)
Combine with support/resistance, SMC, or price action strategy for confluence.
🟢 "Trade any session, any time – with confidence, precision, and control. Powered by Raja Saien."
Built for traders who value smart entries and reliable signals across all time zones.
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ATR % Line from LoD/HoDATR % Line Trading Indicator - Entry Filter Tool
This Pine Script creates a sophisticated ATR (Average True Range) percentage-based entry filter indicator for TradingView that helps traders avoid buying overextended stocks and identify optimal entry zones based on volatility.
Core Functionality - Entry Discipline
The script calculates a maximum entry threshold by taking a percentage of the Average True Range (ATR) and projecting it from the current day's low. This creates a dynamic "no-buy zone" that adapts to market volatility, helping traders avoid purchasing stocks that have already moved too far from their daily base.
Key Calculation:
Measures the ATR over a specified period (default: 14 bars)
Takes a user-defined percentage of that ATR (default: 25%)
Projects this distance from the day's low to establish a maximum entry threshold
Entry Rule: Avoid buying when price exceeds this ATR% level from the daily low or high.
Visual Features
Entry Threshold Line:
Draws a horizontal line at the calculated maximum entry level
Line extends forward for clear visualization of the "no-buy zone"
Red zones above this line indicate overextended conditions
Fully customizable appearance with color, width, and style options
Smart Entry Alerts:
Optional labels show the ATR percentage threshold and exact price level
Visual confirmation when stocks are trading in acceptable entry zones vs. extended areas
Real-Time Monitoring Table:
Displays current distance from daily low as ATR percentage
Shows whether current price is in "safe entry zone" or "extended territory"
Customizable display options for clean chart analysis
Practical Applications for Entry Management
Avoiding Extended Entries:
Primary Use: Don't initiate long positions when price is more than X% ATR from the daily low
Prevents buying stocks that have already made their daily move
Reduces risk of buying at temporary tops within the trading session
Entry Zone Identification:
Price trading below the ATR% line = potential entry opportunity
Price trading above the ATR% line = wait for pullback or skip the trade
Combines volatility analysis with momentum discipline
Risk Management Benefits:
Improved Entry Timing: Enter closer to daily support levels
Better Risk/Reward: Shorter distance to stop loss (daily low)
Reduced Chasing: Systematic approach prevents FOMO-driven entries
Volatility Awareness: Higher volatility stocks get wider acceptable entry ranges
Configuration for Entry Filtering
Key Settings for Entry Management:
ATR Percentage: Set your maximum acceptable extension (15-30% common for day trading)
Reference Point: Use "Low" to measure extension from daily base
Line Style: Make highly visible to clearly see entry threshold
Alert Integration: Visual confirmation of entry-friendly zones
Typical Usage Scenarios:
Conservative Entries: 15-20% ATR from daily low
Moderate Extensions: 25-35% ATR for stronger momentum plays
Aggressive Setups: 40%+ ATR for breakout situations (use with caution)
Entry Strategy Integration
Pre-Market Planning:
Set ATR% threshold based on stock's typical volatility
Identify key levels where entries become unfavorable
Plan alternative entry strategies for extended stocks
Intraday Execution:
Monitor real-time ATR% extension from daily low
Avoid new long positions when threshold is exceeded
Wait for pullbacks to re-enter acceptable entry zones
This tool transforms volatility analysis into practical entry discipline, helping traders maintain consistent entry standards and avoid the costly mistake of chasing overextended stocks. By respecting ATR-based extension limits, traders can improve their entry timing and overall trade profitability.
Dynamic S/R System - Pivot + ChannelDynamic S/R System - Pivot + Channel
A comprehensive Support & Resistance indicator combining dual methodologies for institutional-grade price level analysis
📊 CORE FEATURES
Dual Detection System
• Pivot-Based Levels - Historical turning points with intelligent touch counting
• Dynamic Channel S/R - Trend-aware linear regression boundaries
• Smart Level Management - Auto-merges similar levels, removes weak/outdated ones
Volume Integration
• Multi-timeframe volume analysis using EMA oscillator and spike detection
• Volume confirmation for all breakout signals to filter false moves
• Real-time volume status (Normal/High/Spike) in live information panel
Intelligent Touch Counting
• Automatic level validation through touch frequency analysis
• Strength classification with visual differentiation (colors/thickness)
• Level labels showing exact touch count (S3, R5, etc.)
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🎨 VISUAL ELEMENTS
Line System
Solid Lines: Pivot-based S/R levels
Dashed Lines: Dynamic channel boundaries
Color Coding:
• 🔵 Blue/🔴 Red: Standard support/resistance
• 🟠 Orange: Strong levels (multiple touches)
• 🟣 Purple: Channel S/R levels
Signal Labels
• "B" - Pivot S/R breakout with volume confirmation
• "CB" - Channel boundary breakout
• "Bull/Bear Wick" - False breakout detection (wick rejections)
Information Panel
Real-time analysis displays:
• Total resistance/support levels detected
• Closest S/R levels to current price
• Volume status and position relative to levels
• Current market position assessment
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✅ KEY ADVANTAGES
Multi-Method Validation
Combines historical pivot analysis with dynamic trend channels for comprehensive market view
False Breakout Protection
• Volume confirmation requirements
• Wick analysis to identify failed attempts
• Multiple validation criteria before signal generation
Adaptive Level Management
• Automatically updates as new pivots form
• Removes outdated/weak levels
• Maintains clean, relevant level display
Institutional-Grade Analysis
• Touch counting reveals institutional respect levels
• Volume integration shows smart money activity
• Strength classification identifies high-probability zones
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⏰ OPTIMAL USE CASES
Best Timeframes
• Daily - Primary recommendation for swing trading
• 4-Hour - Intraday analysis and entries
• Weekly - Long-term position planning
Ideal Markets
• Crypto pairs (especially ETH/BTC, BTC/USD)
• Forex majors with good volume data
• Large-cap stocks with institutional participation
Trading Applications
• Entry/exit planning around key S/R levels
• Breakout confirmation with volume validation
• Risk management using nearest S/R for stops
• Trend analysis through channel dynamics
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⚙️ CONFIGURATION GUIDELINES
Conservative Setup (Higher Confidence)
Min Pivot Strength: 3-4
Volume Threshold: 25-30%
Max Levels: 6-8
Aggressive Setup (More Signals)
Min Pivot Strength: 2
Volume Threshold: 15-20%
Max Levels: 10-12
🔔 ALERT SYSTEM
Breakout Alerts
• Resistance/Support breaks with volume confirmation
• Channel boundary violations
• Approaching strong S/R levels
Advanced Notifications
• Strong level approaches (within 0.5% of price)
• False breakout detection
• Volume spike confirmations
📈 TRADING STRATEGY GUIDE
Entry Strategy
1. Wait for price to approach identified S/R level
2. Confirm with volume analysis (spike/high volume preferred)
3. Watch for wick formations indicating rejection
4. Enter on confirmed breakout with volume or bounce with rejection
Risk Management
• Use nearest S/R level for stop placement
• Scale position size based on level strength (touch count)
• Monitor volume confirmation for exit signals
Market Context
• Combine with higher timeframe trend analysis
• Consider overall market sentiment and volatility
• Use channel direction for bias confirmation
Transform complex S/R analysis into actionable trading intelligence with institutional-level insights for professional trading decisions.
Momentum DivergenceOverview
The Momentum Divergence Oscillator is a valuable tool designed for traders who are familiar with basic charting but want to deepen their market insights. This indicator combines a momentum calculation with divergence detection, presenting the data in an intuitive way with a blue momentum line and colored divergence signals ("Bull" and "Bear"). It’s perfect for refining entry and exit points across various timeframes, especially for scalping or swing trading strategies.
Understanding the Concepts
What is Momentum?
Momentum measures the speed and strength of a price movement by comparing the current closing price to a previous close over a set period. In this indicator, it’s calculated as the difference between the current close and the close from a user-defined number of bars ago (default: 10). A rising momentum line indicates accelerating upward momentum, while a falling line suggests slowing momentum or a potential reversal. This helps you gauge whether a trend is gaining power or losing steam, making it a key indicator for spotting overbought or oversold conditions.
What is a Divergence?
A divergence occurs when the price action and the momentum indicator move in opposite directions, often signaling a potential trend reversal. The Momentum Divergence Oscillator highlights two types:
Bullish Divergence: When the price forms a lower low (indicating weakness), but the momentum shows a higher low (suggesting underlying strength). This can foreshadow an upward reversal.
Bearish Divergence: When the price reaches a higher high (showing strength), but the momentum records a lower high (indicating fading momentum). This may hint at an impending downward turn.
How the Indicator Works
The indicator plots a momentum line in a separate pane below your chart, giving you a clear view of price momentum over time. It also scans for divergences using adjustable lookback periods (default: 5 bars left and right) and a range window (default: 5-60 bars) to ensure relevance. When a divergence is detected, it’s visually highlighted, and you can customize the sensitivity through input settings like the momentum length and pivot lookback. Alerts are included to notify you of new divergence signals in real-time, saving you from constant monitoring.
How to Apply It
Identifying Opportunities: Use bullish divergences ("Bull") as a cue to consider long positions, especially when confirmed by support levels or a moving average crossover. Bearish divergences ("Bear") can signal short opportunities, particularly near resistance zones.
Combining with Other Tools: Pair this oscillator with indicators like the Relative Strength Index (RSI) or volume analysis to filter out false signals and increase confidence in your trades. For example, a bullish divergence with rising volume can be a stronger buy signal.
Timeframe Flexibility: Test it on shorter timeframes (e.g., 5-minute charts) for quick scalping trades or longer ones (e.g., 1-hour or 4-hour charts) for swing trading, adjusting the momentum length to suit the market’s pace.
Alert Setup: Enable the built-in alerts to get notified when a divergence forms, allowing you to react promptly without staring at the screen all day.
Strategy Example
Spot a bullish divergence on a 15-minute chart where the price hits a lower low, but the momentum rises.
Confirm with a break above a 20-period EMA and increasing volume.
Enter a long position with a stop-loss below the recent low and a take-profit near the next resistance level.
Customization Tips
Adjust the "Momentum Length" (default: 10) to make the oscillator more or less sensitive—shorter lengths react faster, while longer ones smooth out noise.
Tweak the "Pivot Lookback" settings to widen or narrow the divergence detection range based on your trading style.
Use the "Range Upper/Lower" inputs to focus on divergences within a specific timeframe that matches your strategy.
Important Considerations
b]This indicator is a technical analysis tool, not a guaranteed trading system. Always pair it with a solid strategy and strict risk management, such as setting stop-losses.
In strong trending markets, divergences can sometimes produce false signals. Consider adding a trend filter (e.g., ADX below 25) to avoid whipsaws.
Experiment with the settings on a demo account or backtest to find what works best for your preferred markets and timeframes.
JHW Volume Based Buy and Sell MomentumThe JHW Volume-Based Buy and Sell Momentum indicator is a custom momentum oscillator designed to capture market sentiment based on volume dynamics and price rate of change (ROC). It aims to identify bullish or bearish momentum by analyzing how price reacts to increasing or decreasing trading volume.
Core Logic:
The indicator calculates the Rate of Change (ROC) of the closing price.
It then accumulates this ROC separately based on whether the current volume is lower or higher than the previous bar:
If volume decreases, the ROC is added to a "negative volume index" accumulator.
If volume increases, the ROC is added to a "positive volume index" accumulator.
These two accumulators are combined to form a net momentum line.
Smoothing:
A Simple Moving Average (SMA) is applied to both accumulators over a user-defined period (default: 25 bars).
The sum of these smoothed values forms the signal line.
Visualization:
The indicator plots:
The net momentum line (yellow).
The smoothed signal line (blue).
The area between the two lines is filled with color:
Yellow when momentum is above the signal (bullish).
Blue when momentum is below the signal (bearish).
Bar colors are also adjusted to reflect the current momentum state.
Use Case:
This indicator helps traders:
Detect volume-driven momentum shifts.
Identify potential buy or sell zones based on volume behavior.
Confirm trends or spot early reversals.
Supertrend with ADX & MTF MA Filter# **Supertrend with ADX & MTF MA Filter - Comprehensive Explanation**
---
## **1. Purpose of This Indicator**
This indicator combines three powerful technical analysis tools to create a robust trading system:
✅ **Supertrend** (Trend-following)
✅ **ADX Filter** (Trend strength confirmation)
✅ **MTF MA Filter** (Multi-timeframe trend direction confirmation)
**Primary Goals:**
✔ **Identify high-probability trend reversals** with confirmation from multiple indicators
✔ **Filter out weak trends** using ADX (Average Directional Index)
✔ **Add higher timeframe context** with MTF (Multi-TimeFrame) Moving Average
✔ **Reduce false signals** by requiring confluence between all three components
---
## **2. Core Logic & Components**
### **A. Supertrend (Base Indicator)**
- **Calculation:**
```pine
up = hl2 - (Multiplier * ATR(Periods))
dn = hl2 + (Multiplier * ATR(Periods))
```
- **Bullish trend** when price > `up` (green line)
- **Bearish trend** when price < `dn` (red line)
- **Why Supertrend?**
- Simple yet effective trend-following system
- Adapts to volatility via ATR (Average True Range)
---
### **B. ADX Filter (Trend Strength Confirmation)**
- **ADX Calculation:**
```pine
= calcADX(adxLength, adxSmoothing)
strongTrend = adxVal >= adxThreshold
```
- **ADX > Threshold (Default: 20)** = Strong trend
- **DI+ > DI-** = Bullish momentum
- **DI- > DI+** = Bearish momentum
- **Why ADX?**
- Avoids trading in choppy markets (low ADX = weak trend)
- Confirms if Supertrend signals occur in a strong trend
---
### **C. MTF MA Filter (Higher Timeframe Trend Alignment)**
- **Moving Average Calculation:**
```pine
= getMA(maSource, maLength, maType, maTF)
```
- **MA Type:** SMA, EMA, WMA, or DEMA
- **Timeframe:** Any (1m, 5m, 1H, 4H, D, W, M)
- **Trend Direction:**
- **Buy Signal:** MA must be **rising**
- **Sell Signal:** MA must be **falling**
- **Why MTF MA?**
- Aligns trades with the **higher timeframe trend**
- Reduces counter-trend entries
---
## **3. How to Use This Indicator**
### **A. Buy Conditions (All Must Be True)**
1. **Supertrend turns bullish** (price crosses above `up` line)
2. **ADX ≥ Threshold** (trend is strong)
3. **Higher timeframe MA is rising** (confirms bullish bias)
### **B. Sell Conditions (All Must Be True)**
1. **Supertrend turns bearish** (price crosses below `dn` line)
2. **ADX ≥ Threshold** (trend is strong)
3. **Higher timeframe MA is falling** (confirms bearish bias)
### **C. Recommended Settings**
| Parameter | Recommended Value | Description |
|-----------|------------------|-------------|
| **ATR Period** | 14 | Sensitivity of Supertrend |
| **Multiplier** | 1.5-3.0 | Adjust for volatility |
| **ADX Threshold** | 20-25 | Higher = stricter trend filter |
| **MA Length** | 20-50 | Smoothness of trend filter |
| **MA Timeframe** | 1H/D | Align with trading style |
---
## **4. Trading Strategies**
### **A. Trend-Following Strategy**
- **Enter:** When all 3 conditions align (Supertrend + ADX + MA)
- **Exit:** When Supertrend flips or ADX drops below threshold
### **B. Pullback Strategy**
- **Wait for:**
- Supertrend in trend direction
- ADX remains strong
- MA still aligned
- **Enter:** On pullback to Supertrend line
### **C. Multi-Timeframe Confirmation**
- **Intraday traders:** Use 4H/D MA for trend bias
- **Swing traders:** Use D/W MA for trend bias
---
## **5. Advantages Over Standard Supertrend**
✔ **Fewer false signals** (ADX filters weak trends)
✔ **Higher timeframe alignment** (avoids trading against larger trends)
✔ **Customizable MA types** (SMA, EMA, WMA, DEMA)
✔ **Works on all markets** (stocks, forex, crypto)
---
### **Final Thoughts**
This indicator is designed for traders who want **high-confidence trend signals** by combining:
🔹 **Supertrend** (entry trigger)
🔹 **ADX** (trend strength filter)
🔹 **MTF MA** (higher timeframe trend alignment)
By requiring all three components to align, it significantly improves signal quality compared to standalone Supertrend systems.
**→ Best for:** Swing trading, trend-following, and avoiding choppy markets.
Reversal Point Dynamics⇋ Reversal Point Dynamics (RPD)
This is not an indicator; it is a complete system for deconstructing the mechanics of a market reversal. Reversal Point Dynamics (RPD) moves far beyond simplistic pattern recognition, venturing into a deep analysis of the underlying forces that cause trends to exhaust, pause, and turn. It is engineered from the ground up to identify high-probability reversal points by quantifying the confluence of market dynamics in real-time.
Where other tools provide a static signal, RPD delivers a dynamic probability. It understands that a true market turning point is not a single event, but a cascade of failing momentum, structural breakdown, and a shift in market order. RPD's core engine meticulously analyzes each of these dynamic components—the market's underlying state, its velocity and acceleration, its degree of chaos (entropy), and its structural framework. These forces are synthesized into a single, unified Probability Score, offering you an unprecedented, transparent view into the conviction behind every potential reversal.
This is not a "black box" system. It is an open-architecture engine designed to empower the discerning trader. Featuring real-time signal projection, an integrated Fibonacci R2R Target Engine, and a comprehensive dashboard that acts as your Dynamics Control Center , RPD gives you a complete, holistic view of the market's state.
The Theoretical Core: Deconstructing Market Dynamics
RPD's analytical power is born from the intelligent synthesis of multiple, distinct theoretical models. Each pillar of the engine analyzes a different facet of market behavior. The convergence of these analyses—the "Singularity" event referenced in the dashboard—is what generates the final, high-conviction probability score.
1. Pillar One: Quantum State Analysis (QSA)
This is the foundational analysis of the market's current state within its recent context. Instead of treating price as a random walk, QSA quantizes it into a finite number of discrete "states."
Formulaic Concept: The engine establishes a price range using the highest high and lowest low over the Adaptive Analysis Period. This range is then divided into a user-defined number of Analysis Levels. The current price is mapped to one of these states (e.g., in a 9-level system, State 0 is the absolute low, and State 8 is the absolute high).
Analytical Edge: This acts as a powerful foundational filter. The engine will only begin searching for reversal signals when the market has reached a statistically stretched, extreme state (e.g., State 0 or 8). The Edge Sensitivity input allows you to control exactly how close to this extreme edge the price must be, ensuring you are trading from points of maximum potential exhaustion.
2. Pillar Two: Price State Roc (PSR) - The Dynamics of Momentum
This pillar analyzes the kinetic forces of the market: its velocity and acceleration. It understands that it’s not just where the price is, but how it got there that matters.
Formulaic Concept: The psr function calculates two derivatives of price.
Velocity: (price - price ). This measures the speed and direction of the current move.
Acceleration: (velocity - velocity ). This measures the rate of change in that speed. A negative acceleration (deceleration) during a strong rally is a critical pre-reversal warning, indicating momentum is fading even as price may be pushing higher.
Analytical Edge: The engine specifically hunts for exhaustion patterns where momentum is clearly decelerating as price reaches an extreme state. This is the mechanical signature of a weakening trend.
3. Pillar Three: Market Entropy Analysis - The Dynamics of Order & Chaos
This is RPD's chaos filter, a concept borrowed from information theory. Entropy measures the degree of randomness or disorder in the market's price action.
Formulaic Concept: The calculateEntropy function analyzes recent price changes. A market moving directionally and smoothly has low entropy (high order). A market chopping back and forth without direction has high entropy (high chaos). The value is normalized between 0 and 1.
Analytical Edge: The most reliable trades occur in low-entropy, ordered environments. RPD uses the Entropy Threshold to disqualify signals that attempt to form in chaotic, unpredictable conditions, providing a powerful shield against whipsaw markets.
4. Pillar Four: The Synthesis Engine & Probability Calculation
This is where all the dynamic forces converge. The final probability score is a weighted calculation that heavily rewards confluence.
Formulaic Concept: The calculateProbability function intelligently assembles the final score:
A Base Score is established from trend strength and entropy.
An Entropy Score adds points for low entropy (order) and subtracts for high entropy (chaos).
A significant Divergence Bonus is awarded for a classic momentum divergence.
RSI & Volume Bonuses are added if momentum oscillators are in extreme territory or a volume spike confirms institutional interest.
MTF & Adaptive Bonuses add further weight for alignment with higher timeframe structure.
Analytical Edge: A signal backed by multiple dynamic forces (e.g., extreme state + decelerating momentum + low entropy + volume spike) will receive an exponentially higher probability score. This is the very essence of analyzing reversal point dynamics.
The Command Center: Mastering the Inputs
Every input is a precise lever of control, allowing you to fine-tune the RPD engine to your exact trading style, market, and timeframe.
🧠 Core Algorithm
Predictive Mode (Early Detection):
What It Is: Enables the engine to search for potential reversals on the current, unclosed bar.
How It Works: Analyzes intra-bar acceleration and state to identify developing exhaustion. These signals are marked with a ' ? ' and are tentative.
How To Use It: Enable for scalping or very aggressive day trading to get the earliest possible indication. Disable for swing trading or a more conservative approach that waits for full bar confirmation.
Live Signal Mode (Current Bar):
What It Is: A highly aggressive mode that plots tentative signals with a ' ! ' on the live bar based on projected price and momentum. These signals repaint intra-bar.
How It Works: Uses a linear regression projection of the close to anticipate a reversal.
How To Use It: For advanced users who use intra-bar dynamics for execution and understand the nature of repainting signals.
Adaptive Analysis Period:
What It Is: The main lookback period for the QSA, PSR, and Entropy calculations. This is the engine's "memory."
How It Works: A shorter period makes the engine highly sensitive to local price swings. A longer period makes it focus only on major, significant market structure.
How To Use It: Scalping (1-5m): 15-25. Day Trading (15m-1H): 25-40. Swing Trading (4H+): 40-60.
Fractal Strength (Bars):
What It Is: Defines the strength of the pivot detection used for confirming reversal events.
How It Works: A value of '2' requires a candle's high/low to be more extreme than the two bars to its left and right.
How To Use It: '2' is a robust standard. Increase to '3' for an even stricter definition of a structural pivot, which will result in fewer signals.
MTF Multiplier:
What It Is: Integrates pivot data from a higher timeframe for confluence.
How It Works: A multiplier of '4' on a 15-minute chart will pull pivot data from the 1-hour chart (15 * 4 = 60m).
How To Use It: Set to a multiple that corresponds to your preferred higher timeframe for contextual analysis.
🎯 Signal Settings
Min Probability %:
What It Is: Your master quality filter. A signal is only plotted if its score exceeds this threshold.
How It Works: Directly filters the output of the final probability calculation.
How To Use It: High-Quality (80-95): For A+ setups only. Balanced (65-75): For day trading. Aggressive (50-60): For scalping.
Min Signal Distance (Bars):
What It Is: A noise filter that prevents signals from clustering in choppy conditions.
How It Works: Enforces a "cooldown" period of N bars after a signal.
How To Use It: Increase in ranging markets to focus on major swings. Decrease on lower timeframes.
Entropy Threshold:
What It Is: Your "chaos shield." Sets the maximum allowable market randomness for a signal.
How It Works: If calculated entropy is above this value, the signal is invalidated.
How To Use It: Lower values (0.1-0.5): Extremely strict. Higher values (0.7-1.0): More lenient. 0.85 is a good balance.
Adaptive Entropy & Aggressive Mode:
What It Is: Toggles for dynamically adjusting the engine's core parameters.
How It Works: Adaptive Entropy can slightly lower the required probability in strong trends. Aggressive Mode uses more lenient settings across the board.
How To Use It: Keep Adaptive on. Use Aggressive Mode sparingly, primarily for scalping highly volatile assets.
📊 State Analysis
Analysis Levels:
What It Is: The number of discrete "states" for the QSA.
How It Works: More levels create a finer-grained analysis of price location.
How To Use It: 6-7 levels are ideal. Increasing to 9 can provide more precision on very volatile assets.
Edge Sensitivity:
What It Is: Defines how close to the absolute top/bottom of the range price must be.
How It Works: '0' means price must be in the absolute highest/lowest state. '3' allows a signal within the top/bottom 3 states.
How To Use It: '3' provides a good balance. Lower it to '1' or '0' if you only want to trade extreme exhaustion.
The Dashboard: Your Dynamics Control Center
The dashboard provides a transparent, real-time view into the engine's brain. Use it to understand the context behind every signal and to gauge the current market environment at a glance.
🎯 UNIFIED PROB SCORE
TOTAL SCORE: The highest probability score (either Peak or Valley) the engine is currently calculating. This is your main at-a-glance conviction metric. The "Singularity" header refers to the event where market dynamics align—the event RPD is built to detect.
Quality: A human-readable interpretation of the Total Score. "EXCEPTIONAL" (🌟) is a rare, A+ confluence event. "STRONG" (💪) is a high-quality, tradable setup.
📊 ORDER FLOW & COMPONENT ANALYSIS
Volume Spike: Shows if the current volume is significantly higher than average (YES/NO). A 'YES' adds major confirmation.
Peak/Valley Conf: This breaks down the probability score into its directional components, showing you the separate confidence levels for a potential top (Peak) versus a bottom (Valley).
🌌 MARKET STRUCTURE
HTF Trend: Shows the direction of the underlying trend based on a Supertrend calculation.
Entropy: The current market chaos reading. "🔥 LOW" is an ideal, ordered state for trading. "😴 HIGH" is a warning of choppy, unpredictable conditions.
🔮 FIB & R2R ZONE (Large Dashboard)
This section gives you the status of the Fibonacci Target Engine. It shows if an Active Channel (entry zone) or Stop Zone (invalidation zone) is active and displays the precise price levels for the static entry, target, and stop calculated at the time of the signal.
🛡️ FILTERS & PREDICTIVES (Large Dashboard)
This panel provides a status check on all the bonus filters. It shows the current RSI Status, whether a Divergence is present, and if a Live Pending signal is forming.
The Visual Interface: A Symphony of Data
Every visual element is designed for instant, intuitive interpretation of market dynamics.
Signal Markers: These are the primary outputs of the engine.
▼/▲ b: A fully confirmed signal that has passed all filters.
? b: A tentative signal generated in Predictive Mode, indicating developing dynamics.
◈ b: This diamond icon replaces the standard triangle when the signal is confirmed by a strong momentum divergence, highlighting it as a superior setup where dynamics are misaligned with price.
Harmonic Wave: The flowing, colored wave around the price.
What It Represents: The market's "flow dynamic" and volatility.
How to Interpret It: Expanding waves show increasing volatility. The color is tied to the "Quantum Color" in your theme, representing the underlying energy field of the market.
Entropy Particles: The small dots appearing above/below price.
What They Represent: A direct visualization of the "order dynamic."
How to Interpret Them: Their presence signifies a low-entropy, ordered state ideal for trading. Their color indicates the direction of momentum (PSR velocity). Their absence means the market is too chaotic (high entropy).
The Fibonacci Target Engine: The dynamic R2R system appearing post-signal.
Static Fib Levels: Colored horizontal lines representing the market's "structural dynamic."
The Green "Active Channel" Box: Your zone of consideration. An area to manage a potential entry.
Development Philosophy
Reversal Point Dynamics was engineered to answer a fundamental question: can we objectively measure the forces behind a market turn? It is a synthesis of concepts from market microstructure, statistics, and information theory. The objective was never to create a "perfect" system, but to build a robust decision-support tool that provides a measurable, statistical edge by focusing on the principle of confluence.
By demanding that multiple, independent market dynamics align simultaneously, RPD filters out the vast majority of market noise. It is designed for the trader who thinks in terms of probability and risk management, not in terms of certainties. It is a tool to help you discount the obvious and bet on the unexpected alignment of market forces.
"Markets are constantly in a state of uncertainty and flux and money is made by discounting the obvious and betting on the unexpected."
— George Soros
Trade with insight. Trade with anticipation.
— Dskyz, for DAFE Trading Systems
Kase Convergence Divergence [BackQuant]Kase Convergence Divergence
The Kase Convergence Divergence is a sophisticated oscillator designed to measure directional market strength through the lens of volatility-adjusted log return structures. Inspired by Cynthia Kase’s work on statistical momentum and price projection ranges, this unique indicator offers a hybrid framework that merges signal processing, multi-length sweep logic, and adaptive smoothing techniques.
Unlike traditional momentum oscillators like MACD or RSI, which rely on static moving average differences, KCD introduces a dual-process system combining:
Kase-style statistical range projection (via log returns and volatility),
A sweeping loop of lookback lengths for robustness,
First and second derivative modes to capture both velocity and acceleration of price movement.
Core Logic & Computation
The KCD calculation is centered on two volatility-normalized transforms:
KSDI Up: Measures how far the current high has moved relative to a past low, normalized by return volatility.
KSDI Down: Measures how far the current low has moved relative to a past high, also normalized.
For every length in a user-defined sweep range (e.g., 25–35), both KSDI_up and KSDI_dn are computed, and their maximum values across the loop are retained. The difference between these two max values produces the raw signal:
KPO (Kase Projection Oscillator): Measures directional skew.
KCD (Kase Convergence Divergence): Defined as KPO – MA(KPO) — similar in spirit to MACD but structurally different.
Users can choose to visualize either the first derivative (KPO) , or the second derivative (KCD) , depending on market conditions or strategy style.
Key Features
✅ Multi-Length Sweep Logic: Improves signal reliability by aggregating statistical range projections across a set of lookbacks.
✅ Advanced Smoothing Modes: Supports DEMA, HMA, TEMA, LINREG, WMA and more for dynamic adaptation.
✅ Dual Derivative Modes: Choose between speed (first derivative) or smoothness (second derivative) to fit your trading regime.
✅ Color-Encoded Signal Bands: Heatmap-style oscillator coloring enhances visual feedback on trend strength.
✅ Candlestick Painting: Optional bar coloring makes it easy to spot trend shifts on the main chart.
✅ Adaptive Fill Zones: Green and red fills between the oscillator and zero line help distinguish bullish and bearish regimes at a glance.
Practical Applications
📈 Trend Confirmation: Use KCD as a secondary confirmation layer after breakout or pullback entries.
📉 Momentum Shifts: Crossover and crossunder of the zero line highlight potential regime changes.
📊 Strategy Filters: Incorporate into algos to avoid trendless or mean-reverting environments.
🧪 Derivative Switching: Flip between KPO and KCD modes depending on whether you want to measure acceleration or deceleration of price flow.
Alerts & Signals
Two built-in alerts help you catch regime shifts in real time:
Long Signal: Triggered when the selected oscillator crosses above zero.
Short Signal: Triggered when it crosses below zero.
These events can be used to generate entries, exits, or trend validation cues in multi-layer systems.
Conclusion
The Kase Convergence Divergence goes beyond traditional oscillators by offering a volatility-normalized, derivative-aware signal engine with enhanced visual dynamics. Its sweeping architecture and dynamic fill logic make it especially powerful for identifying trending environments, filtering chop, and adding statistical rigor to your trading toolkit.
Whether you’re a discretionary trader seeking precision, or a quant looking to model more robust return structures, KCD offers a creative yet analytically grounded solution.
Pattern Detector [theUltimator5]🎯 Overview
The Pattern Detector is a comprehensive technical analysis indicator that automatically identifies and visualizes multiple pattern types on your charts. Built with advanced ZigZag technology and sophisticated pattern recognition algorithms, this tool helps traders spot high-probability trading opportunities across all timeframes and markets.
✨ Key Features
🔍 Multi-Pattern Detection System
Harmonic Patterns: Butterfly, Gartley, Bat, and Crab patterns with precise Fibonacci ratios
Classic Reversal Patterns: Head & Shoulders and Inverse Head & Shoulders
Double Patterns: Double Tops and Double Bottoms with extreme validation
Wedge Patterns: Rising and Falling Wedges with volume confirmation
📊 Advanced ZigZag Engine
Customizable sensitivity (5-50 levels)
Depth multiplier for multi-timeframe analysis
Real-time pivot detection with noise filtering
Option to display ZigZag lines only for pure price action analysis
🎨 Visualization
Clean pattern lines with distinct color coding
Point labeling system (X, A, B, C, D for harmonics / LS, H, RS for H&S)
Pattern name displays with bullish/bearish direction
Price target projections with arrow indicators
Subtle pattern fills for enhanced visibility
🛠️ Settings & Configuration
Core ZigZag Settings
ZigZag Sensitivity (5-50): Controls pattern detection sensitivity. Lower values detect more patterns but may include noise. Higher values focus on major swings only.
ZigZag Depth Multiplier (1-5): Multiplies sensitivity for deeper analysis. Level 1 = most responsive, Level 5 = major swings only.
Pattern Detection Toggles
Show ZigZag Lines Only: Displays pure ZigZag without pattern detection for price structure analysis
Detect Harmonic Patterns: Enable/disable Fibonacci-based harmonic pattern detection
Detect Head & Shoulders: Toggle classic reversal pattern identification
Detect Double Tops/Bottoms: Enable double pattern detection with extreme validation
Detect Wedge Patterns: Toggle wedge pattern detection with volume confirmation
Display Options
Show Pattern Names: Display pattern names directly on chart (e.g., "Butterfly (Bullish)")
Show Point Labels: Add lettered labels at key pattern points for structure identification
Project Harmonic Targets: Show projected completion points for incomplete harmonic patterns
📈 Pattern Types Explained
Harmonic Patterns 🦋
Advanced Fibonacci-based patterns that provide high-probability reversal signals:
Butterfly: AB=0.786 XA, BC=0.382-0.886 AB, CD=1.618-2.24 BC
Gartley: AB=0.618 XA, BC=0.382-0.886 AB, CD=1.272-1.618 BC
Bat: AB=0.382-0.50 XA, BC=0.382-0.886 AB, CD=1.618-2.24 BC
Crab: AB=0.382-0.618 XA, BC=0.382-0.886 AB, CD=2.24-3.618 BC
Head & Shoulders 👤
Classic three-peak reversal pattern indicating trend exhaustion:
Standard H&S: Bearish reversal at tops
Inverse H&S: Bullish reversal at bottoms
Automatic neckline validation and price target calculation
Double Patterns 📊
Powerful reversal patterns with extreme validation:
Double Top: Two similar highs with valley between (bearish)
Double Bottom: Two similar lows with peak between (bullish)
Includes lookback period validation to ensure patterns are significant extremes
Wedge Patterns 📐
Continuation/reversal patterns with converging trend lines:
Rising Wedge: Converging upward slopes (typically bearish)
Falling Wedge: Converging downward slopes (typically bullish)
Volume confirmation required for increased accuracy
🎯 Trading Applications
Entry Signals
Harmonic Patterns: Enter at point D completion with targets at point A
H&S Patterns: Enter on neckline break with calculated targets
Double Patterns: Enter on support/resistance break with measured moves
Wedge Patterns: Enter on breakout direction with volume confirmation
Risk Management
Use pattern structure for logical stop placement
Pattern invalidation levels provide clear exit rules
Multiple pattern confirmation increases probability
Multi-Timeframe Analysis
Higher ZigZag depth for longer-term patterns
Lower sensitivity for short-term trading patterns
Combine with other timeframes for confluence
⚙️ Optimal Settings
For Day Trading (1m-15m charts)
ZigZag Sensitivity: 5-9
Depth Multiplier: 1-2
Enable all pattern types for maximum opportunities
For Swing Trading (1H-4H charts)
ZigZag Sensitivity: 9-15
Depth Multiplier: 2-3
Focus on harmonic and H&S patterns
For Position Trading (Daily+ charts)
ZigZag Sensitivity: 15-25
Depth Multiplier: 3-5
Emphasize major harmonic and double patterns
🔧 Technical Specifications
Maximum Lookback: 5000 bars for comprehensive analysis
Pattern Overlap Prevention: Intelligent filtering prevents duplicate patterns
Performance Optimized: Efficient algorithms for real-time detection
Volume Integration: Advanced volume analysis for wedge confirmation
Fibonacci Precision: 10% tolerance for harmonic ratio validation
📚 How to Use
Add to Chart: Apply indicator to any timeframe/market
Configure Settings: Adjust sensitivity based on trading style
Enable Patterns: Toggle desired pattern types
Analyze Results: Look for completed patterns with clear structure
Plan Trades: Use price targets and pattern invalidation for trade management
Perfect for both novice and experienced traders seeking systematic pattern recognition with visualization and entry/exit signals.
Risk Distribution HistogramStatistical risk visualization and analysis tool for any ticker 📊
The Risk Distribution Histogram visualizes the statistical distribution of different risk metrics for any financial instrument. It converts risk data into histograms with quartile-based color coding, so that traders can understand their risk, tail-risks, exposure patterns and make data-driven decisions based on empirical evidence rather than assumptions.
The indicator supports multiple risk calculation methods, each designed for different aspects of market analysis, from general volatility assessment to tail risk analysis.
Risk Measurement Methods
Standard Deviation
Captures raw daily price volatility by measuring the dispersion of price movements. Ideal for understanding overall market conditions and timing volatility-based strategies.
Use case: Options trading and volatility analysis.
Average True Range (ATR)
Measures true range as a percentage of price, accounting for gaps and limit moves. Valuable for position sizing across different price levels.
Use case: Position sizing and stop-loss placement.
The chart above illustrates how ATR statistical distribution can be used by looking at the ATR % of price distribution. For example, 90% of the movements are below 5%.
Downside Deviation
Only considers negative price movements, making it ideal for checking downside risk and capital protection rather than capturing upside volatility.
Use case: Downside protection strategies and stop losses.
Drawdown Analysis
Tracks peak-to-trough declines, providing insight into maximum loss potential during different market conditions.
Use case: Risk management and capital preservation.
The chart above illustrates tale risk for the asset (TQQQ), showing that it is possible to have drawdowns higher than 20%.
Entropy-Based Risk (EVaR)
Uses information theory to quantify market uncertainty. Higher entropy values indicate more unpredictable price action, valuable for detecting regime changes.
Use case: Advanced risk modeling and tail-risk.
VIX Histogram
Incorporates the market's fear index directly into analysis, showing how current volatility expectations compare to historical patterns. The CAPITALCOM:VIX histogram is independent from the ticker on the chart.
Use case: Volatility trading and market timing.
Visual Features
The histogram uses quartile-based color coding that immediately shows where current risk levels stand relative to historical patterns:
Green (Q1): Low Risk (0-25th percentile)
Yellow (Q2): Medium-Low Risk (25-50th percentile)
Orange (Q3): Medium-High Risk (50-75th percentile)
Red (Q4): High Risk (75-100th percentile)
The data table provides detailed statistics, including:
Count Distribution: Historical observations in each bin
PMF: Percentage probability for each risk level
CDF: Cumulative probability up to each level
Current Risk Marker: Shows your current position in the distribution
Trading Applications
When current risk falls into upper quartiles (Q3 or Q4), it signals conditions are riskier than 50-75% of historical observations. This guides position sizing and portfolio adjustments.
Key applications:
Position sizing based on empirical risk distributions
Monitoring risk regime changes over time
Comparing risk patterns across timeframes
Risk distribution analysis improves trade timing by identifying when market conditions favor specific strategies.
Enter positions during low-risk periods (Q1)
Reduce exposure in high-risk periods (Q4)
Use percentile rankings for dynamic stop-loss placement
Time volatility strategies using distribution patterns
Detect regime shifts through distribution changes
Compare current conditions to historical benchmarks
Identify outlier events in tail regions
Validate quantitative models with empirical data
Configuration Options
Data Collection
Lookback Period: Control amount of historical data analyzed
Date Range Filtering: Focus on specific market periods
Sample Size Validation: Automatic reliability warnings
Histogram Customization
Bin Count: 10-50 bins for different detail levels
Auto/Manual Bin Width: Optimize for your data range
Visual Preferences: Custom colors and font sizes
Implementation Guide
Start with Standard Deviation on daily charts for the most intuitive introduction to distribution-based risk analysis.
Method Selection: Begin with Standard Deviation
Setup: Use daily charts with 20-30 bins
Interpretation: Focus on quartile transitions as signals
Monitoring: Track distribution changes for regime detection
The tool provides comprehensive statistics including mean, standard deviation, quartiles, and current position metrics like Z-score and percentile ranking.
Enjoy, and please let me know your feedback! 😊🥂
Pullback Pro Dow Strategy v7 (ADX Filter)
### **Strategy Description (For TradingView)**
#### **Title:** Pullback Pro: Dow Theory & ADX Strategy
---
#### **1. Summary**
This strategy is designed to identify and trade pullbacks within an established trend, based on the core principles of Dow Theory. It uses market structure (pivot highs and lows) to determine the trend direction and an Exponential Moving Average (EMA) to pinpoint pullback entry opportunities.
To enhance trade quality and avoid ranging markets, an ADX (Average Directional Index) filter is integrated to ensure that entries are only taken when the trend has sufficient momentum.
---
#### **2. Core Logic: How It Works**
The strategy's logic is broken down into three main steps:
**Step 1: Trend Determination (Dow Theory)**
* The primary trend is identified by analyzing recent pivot points.
* An **Uptrend** is confirmed when the script detects a pattern of higher highs and higher lows (HH/HL).
* A **Downtrend** is confirmed by a pattern of lower highs and lower lows (LH/LL).
* If neither pattern is present, the strategy considers the market to be in a range and will not seek trades.
**Step 2: Entry Signal (Pullback to EMA)**
* Once a clear trend is established, the strategy waits for a price correction.
* **Long Entry:** In a confirmed uptrend, a long position is initiated when the price pulls back and crosses *under* the specified EMA.
* **Short Entry:** In a confirmed downtrend, a short position is initiated when the price rallies and crosses *over* the EMA.
**Step 3: Confirmation & Risk Management**
* **ADX Filter:** To ensure the trend is strong enough to trade, an entry signal is only validated if the ADX value is above a user-defined threshold (e.g., 25). This helps filter out weak signals during choppy or consolidating markets.
* **Stop Loss:** The initial Stop Loss is automatically and logically placed at the last market structure point:
* For long trades, it's placed at the `lastPivotLow`.
* For short trades, it's placed at the `lastPivotHigh`.
* **Take Profit:** Two Take Profit levels are calculated based on user-defined Risk-to-Reward (R:R) ratios. The strategy allows for partial profit-taking at the first target (TP1), moving the remainder of the position to the second target (TP2).
---
#### **3. Input Settings Explained**
**① Dow Theory Settings**
* **Pivot Lookback Period:** Determines the sensitivity for detecting pivot highs and lows. A smaller number makes it more sensitive to recent price swings; a larger number focuses on more significant, longer-term pivots.
**② Entry Logic (Pullback)**
* **Pullback EMA Length:** Sets the period for the Exponential Moving Average used to identify pullback entries.
**③ Risk & Exit Management**
* **Take Profit 1 R:R:** Sets the Risk-to-Reward ratio for the first take-profit target.
* **Take Profit 1 (%):** The percentage of the position to be closed when TP1 is hit.
* **Take Profit 2 R:R:** Sets the Risk-to-Reward ratio for the final take-profit target.
**④ Filters**
* **Use ADX Trend Filter:** A master switch to enable or disable the ADX filter.
* **ADX Length:** The lookback period for the ADX calculation.
* **ADX Threshold:** The minimum ADX value required to confirm a trade signal. Trades will only be placed if the ADX is above this level.
---
#### **4. Best Practices & Recommendations**
* This is a trend-following system. It is designed to perform best in markets that exhibit clear, sustained trending behavior.
* It may underperform in choppy, sideways, or strongly ranging markets. The ADX filter is designed to help mitigate this, but no filter is perfect.
* **Crucially, you must backtest this strategy thoroughly** on your preferred financial instrument and timeframe before considering any live application.
* Experiment with the `Pivot Lookback Period`, `Pullback EMA Length`, and `ADX Threshold` to optimize performance for a specific market's characteristics.
---
#### **DISCLAIMER**
This script is provided for educational and informational purposes only. It does not constitute financial advice. All trading involves a high level of risk, and past performance is not indicative of future results. You are solely responsible for your own trading decisions. The author assumes no liability for any financial losses you may incur from using this strategy. Always conduct your own research and due diligence.
NY Open Breakout [ATR-5000]# **New York Open Breakout Indicator **
## **📌 Overview**
This **Pine Script** indicator identifies high-probability breakout opportunities at the **New York market open (13:30 UTC)** based on **volatility filters** using **customizable ATR periods and thresholds**.
### **🔹 Key Features**
✅ **Fully Customizable ATR Periods** (2 to **5000** bars)
✅ **Adjustable Thresholds** (0.01% to 5.00%)
✅ **Opening Range (OR) Filter** (0.01% to 5.00%)
✅ **Clean Visuals** – Only highlights the **13:30 UTC candle** when conditions are met
✅ **Real-Time Info Panel** – Displays current ATR & threshold settings
✅ **Automatic Daily Reset** – Fresh signals every trading day
---
## **📊 How It Works**
### **1️⃣ Volatility Check (13:25 UTC)**
- Calculates **two ATR values** (user-defined periods)
- Compares them against **custom % thresholds**
- Only proceeds if **both ATRs exceed** their required volatility levels
### **2️⃣ Opening Range Confirmation (13:30 UTC)**
- Measures the **high-low range** of the 13:30 candle
- Validates if the range meets the **minimum % threshold**
- If all conditions pass → **Highlights the candle** in your chosen color
### **3️⃣ Visual Feedback**
- **🟣 Colored Candle** → Valid breakout signal
- **📊 Info Table** → Shows current ATR settings & thresholds
---
## **⚙️ Customization Options**
| **Setting** | **Default** | **Adjustable Range** |
|---------------------------|------------|----------------------|
| **First ATR Period** | 14 | **2–5000** bars |
| **Second ATR Period** | 161 | **2–5000** bars |
| **First ATR Threshold** | 0.42% | **0.01%–5.00%** |
| **Second ATR Threshold** | 0.40% | **0.01%–5.00%** |
| **OR Range Threshold** | 0.42% | **0.01%–5.00%** |
| **Candle Color** | Purple | **Any color** |
---
## **📈 Best Use Cases**
✔ **Forex (EURUSD, GBPUSD)** – Captures NY session momentum
✔ **Indices (SPX, NASDAQ)** – Works well with opening volatility
✔ **Commodities (Gold, Oil)** – Filters out low-energy days
---
## **🔧 How to Adjust Settings**
1. **Click the gear icon (⚙️)** on your TradingView chart
2. **Modify ATR periods & thresholds** as needed
3. **Change the candle color** for better visibility
---
## **🚀 Why This Indicator?**
- **No repainting** – Signals lock in after candle close
- **No clutter** – Only marks valid 13:30 candles
- **Adaptable** – Works on **any market & timeframe**
- **Fully automated** – No manual adjustments needed
---
### **📥 Apply & Start Trading!**
Simply **load the script** on TradingView and customize it to fit your strategy! 🚀
Asset Premium/Discount Monitor📊 Overview
The Asset Premium/Discount Monitor is a tool for analyzing the relative value between two correlated assets. It measures when one asset is trading at a premium or discount compared to its historical relationship with another asset, helping traders identify potential mean reversion opportunities, or pairs trading opportunities.
🎯 Use Cases
Perfect for analyzing:
NASDAQ:MSTR vs CRYPTO:BTCUSD - MicroStrategy's premium/discount to Bitcoin
NASDAQ:COIN vs BITSTAMP:BTCUSD - Coinbase's relative value to Bitcoin
NASDAQ:TSLA vs NASDAQ:QQQ - Tesla's premium to tech sector
Regional banks AMEX:KRE vs AMEX:XLF - Individual bank stocks vs financial sector
Any two correlated assets where relative value matters
Example of a trade: MSTR vs BTC - When indicator shows MSTR at 95% percentile (extreme premium): Short MSTR, Buy BTC. Then exit when the spread reverts to the mean, say 40-60% percentile.
🔧 How It Works
Core Calculation
Ratio Analysis: Calculates the price ratio between your asset and the correlated asset
Historical Baseline: Establishes the "normal" relationship using a 252-day moving average. You can change this.
Premium Measurement: Measures current deviation from historical average as a percentage
Statistical Context: Provides percentile rankings and standard deviation bands
The Math
Premium % = (Current Ratio / Historical Average Ratio - 1) × 100
🎨 Customization Options
Correlated Asset: Choose any symbol for comparison
Lookback Period: Adjust historical baseline (50-1000 days)
Smoothing: Reduce noise with moving average (1-50 days)
Visual Toggles: Show/hide bands and percentile lines
Color Themes: Customize premium/discount colors
📊 Interpretation Guide
Premium/Discount Reading
Positive %: Asset trading above historical relationship (premium)
Negative %: Asset trading below historical relationship (discount)
Near 0%: Asset at fair value relative to correlation
Percentile Ranking
90%+: Near recent highs - potential selling opportunity
10% and below: Near recent lows - potential buying opportunity
25-75%: Normal trading range
Signal Classifications
🔴 SELL PREMIUM: Asset expensive relative to recent range
🟡 Premium Rich: Moderately expensive, monitor for reversal
⚪ NEUTRAL: Fair value territory
🟡 Discount Opportunity: Moderately cheap, potential accumulation zone
🟢 BUY DISCOUNT: Asset cheap relative to recent range
🚨 Built-in Alerts
Extreme Premium Alert: Triggers when percentile > 95%
Extreme Discount Alert: Triggers when percentile < 5%
⚠️ Important Notes
Works best with highly correlated assets
Historical relationships can change - monitor correlation strength
Not investment advice - use as one factor in your analysis
Backtest thoroughly before implementing any strategy
🔄 Updates & Future Features
This indicator will be continuously improved based on user feedback. So... please give me your feedback!
VoVix DEVMA🌌 VoVix DEVMA: A Deep Dive into Second-Order Volatility Dynamics
Welcome to VoVix+, a sophisticated trading framework that transcends traditional price analysis. This is not merely another indicator; it is a complete system designed to dissect and interpret the very fabric of market volatility. VoVix+ operates on the principle that the most powerful signals are not found in price alone, but in the behavior of volatility itself. It analyzes the rate of change, the momentum, and the structure of market volatility to identify periods of expansion and contraction, providing a unique edge in anticipating major market moves.
This document will serve as your comprehensive guide, breaking down every mathematical component, every user input, and every visual element to empower you with a profound understanding of how to harness its capabilities.
🔬 THEORETICAL FOUNDATION: THE MATHEMATICS OF MARKET DYNAMICS
VoVix+ is built upon a multi-layered mathematical engine designed to measure what we call "second-order volatility." While standard indicators analyze price, and first-order volatility indicators (like ATR) analyze the range of price, VoVix+ analyzes the dynamics of the volatility itself. This provides insight into the market's underlying state of stability or chaos.
1. The VoVix Score: Measuring Volatility Thrust
The core of the system begins with the VoVix Score. This is a normalized measure of volatility acceleration or deceleration.
Mathematical Formula:
VoVix Score = (ATR(fast) - ATR(slow)) / (StDev(ATR(fast)) + ε)
Where:
ATR(fast) is the Average True Range over a short period, representing current, immediate volatility.
ATR(slow) is the Average True Range over a longer period, representing the baseline or established volatility.
StDev(ATR(fast)) is the Standard Deviation of the fast ATR, which measures the "noisiness" or consistency of recent volatility.
ε (epsilon) is a very small number to prevent division by zero.
Market Implementation:
Positive Score (Expansion): When the fast ATR is significantly higher than the slow ATR, it indicates a rapid increase in volatility. The market is "stretching" or expanding.
Negative Score (Contraction): When the fast ATR falls below the slow ATR, it indicates a decrease in volatility. The market is "coiling" or contracting.
Normalization: By dividing by the standard deviation, we normalize the score. This turns it into a standardized measure, allowing us to compare volatility thrust across different market conditions and timeframes. A score of 2.0 in a quiet market means the same, relatively, as a score of 2.0 in a volatile market.
2. Deviation Analysis (DEV): Gauging Volatility's Own Volatility
The script then takes the analysis a step further. It calculates the standard deviation of the VoVix Score itself.
Mathematical Formula:
DEV = StDev(VoVix Score, lookback_period)
Market Implementation:
This DEV value represents the magnitude of chaos or stability in the market's volatility dynamics. A high DEV value means the volatility thrust is erratic and unpredictable. A low DEV value suggests the change in volatility is smooth and directional.
3. The DEVMA Crossover: Identifying Regime Shifts
This is the primary signal generator. We take two moving averages of the DEV value.
Mathematical Formula:
fastDEVMA = SMA(DEV, fast_period)
slowDEVMA = SMA(DEV, slow_period)
The Core Signal:
The strategy triggers on the crossover and crossunder of these two DEVMA lines. This is a profound concept: we are not looking at a moving average of price or even of volatility, but a moving average of the standard deviation of the normalized rate of change of volatility.
Bullish Crossover (fastDEVMA > slowDEVMA): This signals that the short-term measure of volatility's chaos is increasing relative to the long-term measure. This often precedes a significant market expansion and is interpreted as a bullish volatility regime.
Bearish Crossunder (fastDEVMA < slowDEVMA): This signals that the short-term measure of volatility's chaos is decreasing. The market is settling down or contracting, often leading to trending moves or range consolidation.
⚙️ INPUTS MENU: CONFIGURING YOUR ANALYSIS ENGINE
Every input has been meticulously designed to give you full control over the strategy's behavior. Understanding these settings is key to adapting VoVix+ to your specific instrument, timeframe, and trading style.
🌀 VoVix DEVMA Configuration
🧬 Deviation Lookback: This sets the lookback period for calculating the DEV value. It defines the window for measuring the stability of the VoVix Score. A shorter value makes the system highly reactive to recent changes in volatility's character, ideal for scalping. A longer value provides a smoother, more stable reading, better for identifying major, long-term regime shifts.
⚡ Fast VoVix Length: This is the lookback period for the fastDEVMA. It represents the short-term trend of volatility's chaos. A smaller number will result in a faster, more sensitive signal line that reacts quickly to market shifts.
🐌 Slow VoVix Length: This is the lookback period for the slowDEVMA. It represents the long-term, baseline trend of volatility's chaos. A larger number creates a more stable, slower-moving anchor against which the fast line is compared.
How to Optimize: The relationship between the Fast and Slow lengths is crucial. A wider gap (e.g., 20 and 60) will result in fewer, but potentially more significant, signals. A narrower gap (e.g., 25 and 40) will generate more frequent signals, suitable for more active trading styles.
🧠 Adaptive Intelligence
🧠 Enable Adaptive Features: When enabled, this activates the strategy's performance tracking module. The script will analyze the outcome of its last 50 trades to calculate a dynamic win rate.
⏰ Adaptive Time-Based Exit: If Enable Adaptive Features is on, this allows the strategy to adjust its Maximum Bars in Trade setting based on performance. It learns from the average duration of winning trades. If winning trades tend to be short, it may shorten the time exit to lock in profits. If winners tend to run, it will extend the time exit, allowing trades more room to develop. This helps prevent the strategy from cutting winning trades short or holding losing trades for too long.
⚡ Intelligent Execution
📊 Trade Quantity: A straightforward input that defines the number of contracts or shares for each trade. This is a fixed value for consistent position sizing.
🛡️ Smart Stop Loss: Enables the dynamic stop-loss mechanism.
🎯 Stop Loss ATR Multiplier: Determines the distance of the stop loss from the entry price, calculated as a multiple of the current 14-period ATR. A higher multiplier gives the trade more room to breathe but increases risk per trade. A lower multiplier creates a tighter stop, reducing risk but increasing the chance of being stopped out by normal market noise.
💰 Take Profit ATR Multiplier: Sets the take profit target, also as a multiple of the ATR. A common practice is to set this higher than the Stop Loss multiplier (e.g., a 2:1 or 3:1 reward-to-risk ratio).
🏃 Use Trailing Stop: This is a powerful feature for trend-following. When enabled, instead of a fixed stop loss, the stop will trail behind the price as the trade moves into profit, helping to lock in gains while letting winners run.
🎯 Trail Points & 📏 Trail Offset ATR Multipliers: These control the trailing stop's behavior. Trail Points defines how much profit is needed before the trail activates. Trail Offset defines how far the stop will trail behind the current price. Both are based on ATR, making them fully adaptive to market volatility.
⏰ Maximum Bars in Trade: This is a time-based stop. It forces an exit if a trade has been open for a specified number of bars, preventing positions from being held indefinitely in stagnant markets.
⏰ Session Management
These inputs allow you to confine the strategy's trading activity to specific market hours, which is crucial for day trading instruments that have defined high-volume sessions (e.g., stock market open).
🎨 Visual Effects & Dashboard
These toggles give you complete control over the on-chart visuals and the dashboard. You can disable any element to declutter your chart or focus only on the information that matters most to you.
📊 THE DASHBOARD: YOUR AT-A-GLANCE COMMAND CENTER
The dashboard centralizes all critical information into one compact, easy-to-read panel. It provides a real-time summary of the market state and strategy performance.
🎯 VOVIX ANALYSIS
Fast & Slow: Displays the current numerical values of the fastDEVMA and slowDEVMA. The color indicates their direction: green for rising, red for falling. This lets you see the underlying momentum of each line.
Regime: This is your most important environmental cue. It tells you the market's current state based on the DEVMA relationship. 🚀 EXPANSION (Green) signifies a bullish volatility regime where explosive moves are more likely. ⚛️ CONTRACTION (Purple) signifies a bearish volatility regime, where the market may be consolidating or entering a smoother trend.
Quality: Measures the strength of the last signal based on the magnitude of the DEVMA difference. An ELITE or STRONG signal indicates a high-conviction setup where the crossover had significant force.
PERFORMANCE
Win Rate & Trades: Displays the historical win rate of the strategy from the backtest, along with the total number of closed trades. This provides immediate feedback on the strategy's historical effectiveness on the current chart.
EXECUTION
Trade Qty: Shows your configured position size per trade.
Session: Indicates whether trading is currently OPEN (allowed) or CLOSED based on your session management settings.
POSITION
Position & PnL: Displays your current position (LONG, SHORT, or FLAT) and the real-time Profit or Loss of the open trade.
🧠 ADAPTIVE STATUS
Stop/Profit Mult: In this simplified version, these are placeholders. The primary adaptive feature currently modifies the time-based exit, which is reflected in how long trades are held on the chart.
🎨 THE VISUAL UNIVERSE: DECIPHERING MARKET GEOMETRY
The visuals are not mere decorations; they are geometric representations of the underlying mathematical concepts, designed to give you an intuitive feel for the market's state.
The Core Lines:
FastDEVMA (Green/Maroon Line): The primary signal line. Green when rising, indicating an increase in short-term volatility chaos. Maroon when falling.
SlowDEVMA (Aqua/Orange Line): The baseline. Aqua when rising, indicating a long-term increase in volatility chaos. Orange when falling.
🌊 Morphism Flow (Flowing Lines with Circles):
What it represents: This visualizes the momentum and strength of the fastDEVMA. The width and intensity of the "beam" are proportional to the signal strength.
Interpretation: A thick, steep, and vibrant flow indicates powerful, committed momentum in the current volatility regime. The floating '●' particles represent kinetic energy; more particles suggest stronger underlying force.
📐 Homotopy Paths (Layered Transparent Boxes):
What it represents: These layered boxes are centered between the two DEVMA lines. Their height is determined by the DEV value.
Interpretation: This visualizes the overall "volatility of volatility." Wider boxes indicate a chaotic, unpredictable market. Narrower boxes suggest a more stable, predictable environment.
🧠 Consciousness Field (The Grid):
What it represents: This grid provides a historical lookback at the DEV range.
Interpretation: It maps the recent "consciousness" or character of the market's volatility. A consistently wide grid suggests a prolonged period of chaos, while a narrowing grid can signal a transition to a more stable state.
📏 Functorial Levels (Projected Horizontal Lines):
What it represents: These lines extend from the current fastDEVMA and slowDEVMA values into the future.
Interpretation: Think of these as dynamic support and resistance levels for the volatility structure itself. A crossover becomes more significant if it breaks cleanly through a prior established level.
🌊 Flow Boxes (Spaced Out Boxes):
What it represents: These are compact visual footprints of the current regime, colored green for Expansion and red for Contraction.
Interpretation: They provide a quick, at-a-glance confirmation of the dominant volatility flow, reinforcing the background color.
Background Color:
This provides an immediate, unmistakable indication of the current volatility regime. Light Green for Expansion and Light Aqua/Blue for Contraction, allowing you to assess the market environment in a split second.
📊 BACKTESTING PERFORMANCE REVIEW & ANALYSIS
The following is a factual, transparent review of a backtest conducted using the strategy's default settings on a specific instrument and timeframe. This information is presented for educational purposes to demonstrate how the strategy's mechanics performed over a historical period. It is crucial to understand that these results are historical, apply only to the specific conditions of this test, and are not a guarantee or promise of future performance. Market conditions are dynamic and constantly change.
Test Parameters & Conditions
To ensure the backtest reflects a degree of real-world conditions, the following parameters were used. The goal is to provide a transparent baseline, not an over-optimized or unrealistic scenario.
Instrument: CME E-mini Nasdaq 100 Futures (NQ1!)
Timeframe: 5-Minute Chart
Backtesting Range: March 24, 2024, to July 09, 2024
Initial Capital: $100,000
Commission: $0.62 per contract (A realistic cost for futures trading).
Slippage: 3 ticks per trade (A conservative setting to account for potential price discrepancies between order placement and execution).
Trade Size: 1 contract per trade.
Performance Overview (Historical Data)
The test period generated 465 total trades , providing a statistically significant sample size for analysis, which is well above the recommended minimum of 100 trades for a strategy evaluation.
Profit Factor: The historical Profit Factor was 2.663 . This metric represents the gross profit divided by the gross loss. In this test, it indicates that for every dollar lost, $2.663 was gained.
Percent Profitable: Across all 465 trades, the strategy had a historical win rate of 84.09% . While a high figure, this is a historical artifact of this specific data set and settings, and should not be the sole basis for future expectations.
Risk & Trade Characteristics
Beyond the headline numbers, the following metrics provide deeper insight into the strategy's historical behavior.
Sortino Ratio (Downside Risk): The Sortino Ratio was 6.828 . Unlike the Sharpe Ratio, this metric only measures the volatility of negative returns. A higher value, such as this one, suggests that during this test period, the strategy was highly efficient at managing downside volatility and large losing trades relative to the profits it generated.
Average Trade Duration: A critical characteristic to understand is the strategy's holding period. With an average of only 2 bars per trade , this configuration operates as a very short-term, or scalping-style, system. Winning trades averaged 2 bars, while losing trades averaged 4 bars. This indicates the strategy's logic is designed to capture quick, high-probability moves and exit rapidly, either at a profit target or a stop loss.
Conclusion and Final Disclaimer
This backtest demonstrates one specific application of the VoVix+ framework. It highlights the strategy's behavior as a short-term system that, in this historical test on NQ1!, exhibited a high win rate and effective management of downside risk. Users are strongly encouraged to conduct their own backtests on different instruments, timeframes, and date ranges to understand how the strategy adapts to varying market structures. Past performance is not indicative of future results, and all trading involves significant risk.
🔧 THE DEVELOPMENT PHILOSOPHY: FROM VOLATILITY TO CLARITY
The journey to create VoVix+ began with a simple question: "What drives major market moves?" The answer is often not a change in price direction, but a fundamental shift in market volatility. Standard indicators are reactive to price. We wanted to create a system that was predictive of market state. VoVix+ was designed to go one level deeper—to analyze the behavior, character, and momentum of volatility itself.
The challenge was twofold. First, to create a robust mathematical model to quantify these abstract concepts. This led to the multi-layered analysis of ATR differentials and standard deviations. Second, to make this complex data intuitive and actionable. This drove the creation of the "Visual Universe," where abstract mathematical values are translated into geometric shapes, flows, and fields. The adaptive system was intentionally kept simple and transparent, focusing on a single, impactful parameter (time-based exits) to provide performance feedback without becoming an inscrutable "black box." The result is a tool that is both profoundly deep in its analysis and remarkably clear in its presentation.
⚠️ RISK DISCLAIMER AND BEST PRACTICES
VoVix+ is an advanced analytical tool, not a guarantee of future profits. All financial markets carry inherent risk. The backtesting results shown by the strategy are historical and do not guarantee future performance. This strategy incorporates realistic commission and slippage settings by default, but market conditions can vary. Always practice sound risk management, use position sizes appropriate for your account equity, and never risk more than you can afford to lose. It is recommended to use this strategy as part of a comprehensive trading plan. This was developed specifically for Futures
"The prevailing wisdom is that markets are always right. I take the opposite view. I assume that markets are always wrong. Even if my assumption is occasionally wrong, I use it as a working hypothesis."
— George Soros
— Dskyz, Trade with insight. Trade with anticipation.
Fibonacci Retracement Engine (DFRE) [PhenLabs]📊 Fibonacci Retracement Engine (DFRE)
Version: PineScript™ v6
📌 Description
Dynamic Fibonacci Retracement Engine (DFRE) is a sophisticated technical analysis tool that automatically detects important swing points and draws precise Fibonacci retracement levels on various timeframes. The intelligent indicator eliminates the subjectivity of manual Fibonacci drawing using intelligent swing detection algorithms combined with multi timeframe confluence analysis.
Built for professional traders who demand accuracy and consistency, DFRE provides real time Fibonacci levels that adapt to modifications in market structure without sacrificing accuracy in changing market conditions. The indicator excels at identifying key support and resistance levels where price action is more likely to react, giving traders a potent edge in entry and exit timing.
🚀 Points of Innovation
Intelligent Swing Detection Algorithm : Advanced pivot detection with customizable confirmation bars and minimum swing percentage thresholds
Multi-Timeframe Confluence Engine : Simultaneous analysis across three timeframes to identify high-probability zones
Dynamic Level Management : Automatically updates and manages multiple Fibonacci sets while maintaining chart clarity
Adaptive Visualization System : Smart labeling that shows only the most relevant levels based on user preferences
Real-Time Confluence Detection : Identifies zones where multiple Fibonacci levels from different timeframes converge
Automated Alert System : Comprehensive notifications for level breakouts and confluence zone formations
🔧 Core Components
Swing Point Detection Engine : Uses pivot high/low calculations with strength confirmation to identify significant market turns
Fibonacci Calculator : Automatically computes standard retracement levels (0.236, 0.382, 0.5, 0.618, 0.786, 0.886) plus extensions (1.272, 1.618)
Multi-Timeframe Security Function : Safely retrieves Fibonacci data from higher timeframes without repainting
Confluence Analysis Module : Mathematically identifies zones where multiple levels cluster within specified thresholds
Dynamic Drawing Management : Efficiently handles line and label creation, updates, and deletion to maintain performance
🔥 Key Features
Customizable Swing Detection : Adjust swing length (3-50 bars) and strength confirmation (1-10 bars) to match your trading style
Selective Level Display : Choose which Fibonacci levels to show, from core levels to full extensions
Multi-Timeframe Analysis : Analyze up to 3 different timeframes simultaneously for confluence identification
Intelligent Labeling System : Options to show main levels only or all levels, with latest-set-only functionality
Visual Customization : Adjustable line width, colors, and extension options for optimal chart clarity
Performance Optimization : Limit maximum Fibonacci sets (1-5) to maintain smooth chart performance
Comprehensive Alerting : Get notified on level breakouts and confluence zone formations
🎨 Visualization
Dynamic Fibonacci Lines : Color-coded lines (green for uptrends, red for downtrends) with customizable width and extension
Smart Level Labels : Precise level identification with both ratio and price values displayed
Confluence Zone Highlighting : Visual emphasis on areas where multiple timeframe levels converge
Clean Chart Management : Automatic cleanup of old drawing objects to prevent chart clutter
Responsive Design : All visual elements adapt to different chart sizes and timeframes
📖 Usage Guidelines
Swing Detection Settings
Swing Detection Length - Default: 25 | Range: 3-50 | Controls the lookback period for identifying pivot points. Lower values detect more frequent swings but may include noise, while higher values focus on major market turns.
Swing Strength (Confirmation Bars) - Default: 2 | Range: 1-10 | Number of bars required to confirm a swing point. Higher values reduce false signals but increase lag.
Minimum Swing % Change - Default: 1.0% | Range: 0.1-10.0% | Minimum percentage change required to register a valid swing. Filters out insignificant price movements.
Fibonacci Level Settings
Individual Level Toggles : Enable/disable specific Fibonacci levels (0.236, 0.382, 0.5, 0.618, 0.786, 0.886)
Extensions : Show projection levels (1.272, 1.618) for target identification
Multi-Timeframe Settings
Timeframe Selection : Choose three higher timeframes for confluence analysis
Confluence Threshold : Percentage tolerance for level clustering (0.5-5.0%)
✅ Best Use Cases
Swing Trading : Identify optimal entry and exit points at key retracement levels
Confluence Trading : Focus on high-probability zones where multiple timeframe levels align
Support/Resistance Trading : Use dynamic levels that adapt to changing market structure
Breakout Trading : Monitor level breaks for momentum continuation signals
Target Setting : Utilize extension levels for profit target placement
⚠️ Limitations
Lagging Nature : Requires confirmed swing points, which means levels appear after significant moves
Market Condition Dependency : Works best in trending markets; less effective in extremely choppy conditions
Multiple Signal Complexity : Multiple timeframe analysis may produce conflicting signals requiring experience to interpret
Performance Considerations : Multiple Fibonacci sets and MTF analysis may impact indicator loading time on slower devices
💡 What Makes This Unique
Automated Precision : Eliminates manual drawing errors and subjective level placement
Multi-Timeframe Intelligence : Combines analysis from multiple timeframes for superior confluence detection
Adaptive Management : Automatically updates and manages multiple Fibonacci sets as market structure evolves
Professional-Grade Alerts : Comprehensive notification system for all significant level interactions
🔬 How It Works
Step 1 - Swing Point Identification : Scans price action using pivot high/low calculations with specified lookback periods, applies confirmation logic to eliminate false signals, and calculates swing strength based on surrounding price action for quality assessment.
Step 2 - Fibonacci Level Calculation : Automatically computes retracement and extension levels between confirmed swing points, creates dynamic level sets that update as new swing points are identified, and maintains multiple active Fibonacci sets for comprehensive market analysis.
Step 3 - Multi-Timeframe Confluence : Retrieves Fibonacci data from higher timeframes using secure request functions, analyzes level clustering across different timeframes within specified thresholds, and identifies high-probability zones where multiple levels converge.
💡 Note: This indicator works best when combined with other technical analysis tools and proper risk management. The multi-timeframe confluence feature provides the highest probability setups, but always confirm signals with additional analysis before entering trades.
Normalized EMA Cycle (NEC)Normalized EMA Cycle (NEC)
The Normalized EMA Cycle (NEC) is a versatile momentum and trend reversal tool designed to detect high-probability turning points and gauge the strength of price cycles.
It combines fast and slow Exponential Moving Averages (EMAs), dynamic normalization, and adaptive transparency to create clear, intuitive reversal signals on the chart.
🔹 How It Works
EMA Differencing
The NEC calculates the difference between a fast EMA and a slower EMA:
Fast EMA Length (default 6) captures short-term momentum.
Slow EMA Length (default 16) tracks broader trends.
The slope of this difference identifies accelerating or decelerating momentum.
Normalization to 0–100 Scale
The raw EMA difference is scaled relative to the recent Alpha Period range (default 6 bars).
This transforms the value into a normalized oscillator ranging between 0 and 100.
A 3-period Hull Moving Average (HMA) smooths this series to reduce noise.
Overbought and Oversold Thresholds
By default:
Overbought Level: 75
Oversold Level: 25
Crossovers of these levels are used to detect potential reversals.
Adaptive Alpha Adjustment
The normalized value is transformed into an “Alpha Schaff” line, dynamically shifting between price and normalized cycles.
This helps the model adjust to different volatility regimes.
Trend Reversal Logic
Bullish Reversal:
Normalized oscillator crosses above the Oversold Level.
EMA difference slope is positive.
Bearish Reversal:
Normalized oscillator crosses below the Overbought Level.
EMA difference slope is negative.
Additional confirmation comes when price crosses the Alpha Schaff line in the direction of momentum.
Dynamic Confidence Visualization
The indicator calculates a trend confidence score based on the normalized separation of the EMAs.
The transparency of reversal markers dynamically adjusts:
Strong trends = more opaque signals
Weak trends = more transparent signals
🔹 How to Use
✅ Entries
Long Signal: Aqua upward label appears below a bar.
Conditions:
Bullish reversal or price crossing above Alpha Schaff
Normalized slope is rising
Short Signal: Fuchsia downward label appears above a bar.
Conditions:
Bearish reversal or price crossing below Alpha Schaff
Normalized slope is falling
✅ Trend Strength
The less transparent the signal marker, the more significant the trend.
✅ Customization
Use the inputs to fine-tune sensitivity:
Shorter EMAs: Faster signals
Longer EMAs: Smoother trends
Alpha Period: Adjusts the lookback range for normalization
🟢 Best Practices
NEC is best used in combination with other trend confirmation tools (e.g., price structure, volume, or higher timeframe EMAs).
Avoid relying on signals in extremely low-volume or choppy ranges.
⚠️ Disclaimer
This script is intended for educational purposes only and does not constitute financial advice. Trading involves substantial risk, and you should consult your financial advisor before making any investment decisions.
Aetherium Institutional Market Resonance EngineAetherium Institutional Market Resonance Engine (AIMRE)
A Three-Pillar Framework for Decoding Institutional Activity
🎓 THEORETICAL FOUNDATION
The Aetherium Institutional Market Resonance Engine (AIMRE) is a multi-faceted analysis system designed to move beyond conventional indicators and decode the market's underlying structure as dictated by institutional capital flow. Its philosophy is built on a singular premise: significant market moves are preceded by a convergence of context , location , and timing . Aetherium quantifies these three dimensions through a revolutionary three-pillar architecture.
This system is not a simple combination of indicators; it is an integrated engine where each pillar's analysis feeds into a central logic core. A signal is only generated when all three pillars achieve a state of resonance, indicating a high-probability alignment between market organization, key liquidity levels, and cyclical momentum.
⚡ THE THREE-PILLAR ARCHITECTURE
1. 🌌 PILLAR I: THE COHERENCE ENGINE (THE 'CONTEXT')
Purpose: To measure the degree of organization within the market. This pillar answers the question: " Is the market acting with a unified purpose, or is it chaotic and random? "
Conceptual Framework: Institutional campaigns (accumulation or distribution) create a non-random, organized market environment. Retail-driven or directionless markets are characterized by "noise" and chaos. The Coherence Engine acts as a filter to ensure we only engage when institutional players are actively steering the market.
Formulaic Concept:
Coherence = f(Dominance, Synchronization)
Dominance Factor: Calculates the absolute difference between smoothed buying pressure (volume-weighted bullish candles) and smoothed selling pressure (volume-weighted bearish candles), normalized by total pressure. A high value signifies a clear winner between buyers and sellers.
Synchronization Factor: Measures the correlation between the streams of buying and selling pressure over the analysis window. A high positive correlation indicates synchronized, directional activity, while a negative correlation suggests choppy, conflicting action.
The final Coherence score (0-100) represents the percentage of market organization. A high score is a prerequisite for any signal, filtering out unpredictable market conditions.
2. 💎 PILLAR II: HARMONIC LIQUIDITY MATRIX (THE 'LOCATION')
Purpose: To identify and map high-impact institutional footprints. This pillar answers the question: " Where have institutions previously committed significant capital? "
Conceptual Framework: Large institutional orders leave indelible marks on the market in the form of anomalous volume spikes at specific price levels. These are not random occurrences but are areas of intense historical interest. The Harmonic Liquidity Matrix finds these footprints and consolidates them into actionable support and resistance zones called "Harmonic Nodes."
Algorithmic Process:
Footprint Identification: The engine scans the historical lookback period for candles where volume > average_volume * Institutional_Volume_Filter. This identifies statistically significant volume events.
Node Creation: A raw node is created at the mean price of the identified candle.
Dynamic Clustering: The engine uses an ATR-based proximity algorithm. If a new footprint is identified within Node_Clustering_Distance (ATR) of an existing Harmonic Node, it is merged. The node's price is volume-weighted, and its magnitude is increased. This prevents chart clutter and consolidates nearby institutional orders into a single, more significant level.
Node Decay: Nodes that are older than the Institutional_Liquidity_Scanback period are automatically removed from the chart, ensuring the analysis remains relevant to recent market dynamics.
3. 🌊 PILLAR III: CYCLICAL RESONANCE MATRIX (THE 'TIMING')
Purpose: To identify the market's dominant rhythm and its current phase. This pillar answers the question: " Is the market's immediate energy flowing up or down? "
Conceptual Framework: Markets move in waves and cycles of varying lengths. Trading in harmony with the current cyclical phase dramatically increases the probability of success. Aetherium employs a simplified wavelet analysis concept to decompose price action into short, medium, and long-term cycles.
Algorithmic Process:
Cycle Decomposition: The engine calculates three oscillators based on the difference between pairs of Exponential Moving Averages (e.g., EMA8-EMA13 for short cycle, EMA21-EMA34 for medium cycle).
Energy Measurement: The 'energy' of each cycle is determined by its recent volatility (standard deviation). The cycle with the highest energy is designated as the "Dominant Cycle."
Phase Analysis: The engine determines if the dominant cycles are in a bullish phase (rising from a trough) or a bearish phase (falling from a peak).
Cycle Sync: The highest conviction timing signals occur when multiple cycles (e.g., short and medium) are synchronized in the same direction, indicating broad-based momentum.
🔧 COMPREHENSIVE INPUT SYSTEM
Pillar I: Market Coherence Engine
Coherence Analysis Window (10-50, Default: 21): The lookback period for the Coherence Engine.
Lower Values (10-15): Highly responsive to rapid shifts in market control. Ideal for scalping but can be sensitive to noise.
Balanced (20-30): Excellent for day trading, capturing the ebb and flow of institutional sessions.
Higher Values (35-50): Smoother, more stable reading. Best for swing trading and identifying long-term institutional campaigns.
Coherence Activation Level (50-90%, Default: 70%): The minimum market organization required to enable signal generation.
Strict (80-90%): Only allows signals in extremely clear, powerful trends. Fewer, but potentially higher quality signals.
Standard (65-75%): A robust filter that effectively removes choppy conditions while capturing most valid institutional moves.
Lenient (50-60%): Allows signals in less-organized markets. Can be useful in ranging markets but may increase false signals.
Pillar II: Harmonic Liquidity Matrix
Institutional Liquidity Scanback (100-400, Default: 200): How far back the engine looks for institutional footprints.
Short (100-150): Focuses on recent institutional activity, providing highly relevant, immediate levels.
Long (300-400): Identifies major, long-term structural levels. These nodes are often extremely powerful but may be less frequent.
Institutional Volume Filter (1.3-3.0, Default: 1.8): The multiplier for detecting a volume spike.
High (2.5-3.0): Only registers climactic, undeniable institutional volume. Fewer, but more significant nodes.
Low (1.3-1.7): More sensitive, identifying smaller but still relevant institutional interest.
Node Clustering Distance (0.2-0.8 ATR, Default: 0.4): The ATR-based distance for merging nearby nodes.
High (0.6-0.8): Creates wider, more consolidated zones of liquidity.
Low (0.2-0.3): Creates more numerous, precise, and distinct levels.
Pillar III: Cyclical Resonance Matrix
Cycle Resonance Analysis (30-100, Default: 50): The lookback for determining cycle energy and dominance.
Short (30-40): Tunes the engine to faster, shorter-term market rhythms. Best for scalping.
Long (70-100): Aligns the timing component with the larger primary trend. Best for swing trading.
Institutional Signal Architecture
Signal Quality Mode (Professional, Elite, Supreme): Controls the strictness of the three-pillar confluence.
Professional: Loosest setting. May generate signals if two of the three pillars are in strong alignment. Increases signal frequency.
Elite: Balanced setting. Requires a clear, unambiguous resonance of all three pillars. The recommended default.
Supreme: Most stringent. Requires perfect alignment of all three pillars, with each pillar exhibiting exceptionally strong readings (e.g., coherence > 85%). The highest conviction signals.
Signal Spacing Control (5-25, Default: 10): The minimum bars between signals to prevent clutter and redundant alerts.
🎨 ADVANCED VISUAL SYSTEM
The visual architecture of Aetherium is designed not merely for aesthetics, but to provide an intuitive, at-a-glance understanding of the complex data being processed.
Harmonic Liquidity Nodes: The core visual element. Displayed as multi-layered, semi-transparent horizontal boxes.
Magnitude Visualization: The height and opacity of a node's "glow" are proportional to its volume magnitude. More significant nodes appear brighter and larger, instantly drawing the eye to key levels.
Color Coding: Standard nodes are blue/purple, while exceptionally high-magnitude nodes are highlighted in an accent color to denote critical importance.
🌌 Quantum Resonance Field: A dynamic background gradient that visualizes the overall market environment.
Color: Shifts from cool blues/purples (low coherence) to energetic greens/cyans (high coherence and organization), providing instant context.
Intensity: The brightness and opacity of the field are influenced by total market energy (a composite of coherence, momentum, and volume), making powerful market states visually apparent.
💎 Crystalline Lattice Matrix: A geometric web of lines projected from a central moving average.
Mathematical Basis: Levels are projected using multiples of the Golden Ratio (Phi ≈ 1.618) and the ATR. This visualizes the natural harmonic and fractal structure of the market. It is not arbitrary but is based on mathematical principles of market geometry.
🧠 Synaptic Flow Network: A dynamic particle system visualizing the engine's "thought process."
Node Density & Activation: The number of particles and their brightness/color are tied directly to the Market Coherence score. In high-coherence states, the network becomes a dense, bright, and organized web. In chaotic states, it becomes sparse and dim.
⚡ Institutional Energy Waves: Flowing sine waves that visualize market volatility and rhythm.
Amplitude & Speed: The height and speed of the waves are directly influenced by the ATR and volume, providing a feel for market energy.
📊 INSTITUTIONAL CONTROL MATRIX (DASHBOARD)
The dashboard is the central command console, providing a real-time, quantitative summary of each pillar's status.
Header: Displays the script title and version.
Coherence Engine Section:
State: Displays a qualitative assessment of market organization: ◉ PHASE LOCK (High Coherence), ◎ ORGANIZING (Moderate Coherence), or ○ CHAOTIC (Low Coherence). Color-coded for immediate recognition.
Power: Shows the precise Coherence percentage and a directional arrow (↗ or ↘) indicating if organization is increasing or decreasing.
Liquidity Matrix Section:
Nodes: Displays the total number of active Harmonic Liquidity Nodes currently being tracked.
Target: Shows the price level of the nearest significant Harmonic Node to the current price, representing the most immediate institutional level of interest.
Cycle Matrix Section:
Cycle: Identifies the currently dominant market cycle (e.g., "MID ") based on cycle energy.
Sync: Indicates the alignment of the cyclical forces: ▲ BULLISH , ▼ BEARISH , or ◆ DIVERGENT . This is the core timing confirmation.
Signal Status Section:
A unified status bar that provides the final verdict of the engine. It will display "QUANTUM SCAN" during neutral periods, or announce the tier and direction of an active signal (e.g., "◉ TIER 1 BUY ◉" ), highlighted with the appropriate color.
🎯 SIGNAL GENERATION LOGIC
Aetherium's signal logic is built on the principle of strict, non-negotiable confluence.
Condition 1: Context (Coherence Filter): The Market Coherence must be above the Coherence Activation Level. No signals can be generated in a chaotic market.
Condition 2: Location (Liquidity Node Interaction): Price must be actively interacting with a significant Harmonic Liquidity Node.
For a Buy Signal: Price must be rejecting the Node from below (testing it as support).
For a Sell Signal: Price must be rejecting the Node from above (testing it as resistance).
Condition 3: Timing (Cycle Alignment): The Cyclical Resonance Matrix must confirm that the dominant cycles are synchronized with the intended trade direction.
Signal Tiering: The Signal Quality Mode input determines how strictly these three conditions must be met. 'Supreme' mode, for example, might require not only that the conditions are met, but that the Market Coherence is exceptionally high and the interaction with the Node is accompanied by a significant volume spike.
Signal Spacing: A final filter ensures that signals are spaced by a minimum number of bars, preventing over-alerting in a single move.
🚀 ADVANCED TRADING STRATEGIES
The Primary Confluence Strategy: The intended use of the system. Wait for a Tier 1 (Elite/Supreme) or Tier 2 (Professional/Elite) signal to appear on the chart. This represents the alignment of all three pillars. Enter after the signal bar closes, with a stop-loss placed logically on the other side of the Harmonic Node that triggered the signal.
The Coherence Context Strategy: Use the Coherence Engine as a standalone market filter. When Coherence is high (>70%), favor trend-following strategies. When Coherence is low (<50%), avoid new directional trades or favor range-bound strategies. A sharp drop in Coherence during a trend can be an early warning of a trend's exhaustion.
Node-to-Node Trading: In a high-coherence environment, use the Harmonic Liquidity Nodes as both entry points and profit targets. For example, after a BUY signal is generated at one Node, the next Node above it becomes a logical first profit target.
⚖️ RESPONSIBLE USAGE AND LIMITATIONS
Decision Support, Not a Crystal Ball: Aetherium is an advanced decision-support tool. It is designed to identify high-probability conditions based on a model of institutional behavior. It does not predict the future.
Risk Management is Paramount: No indicator can replace a sound risk management plan. Always use appropriate position sizing and stop-losses. The signals provided are probabilistic, not certainties.
Past Performance Disclaimer: The market models used in this script are based on historical data. While robust, there is no guarantee that these patterns will persist in the future. Market conditions can and do change.
Not a "Set and Forget" System: The indicator performs best when its user understands the concepts behind the three pillars. Use the dashboard and visual cues to build a comprehensive view of the market before acting on a signal.
Backtesting is Essential: Before applying this tool to live trading, it is crucial to backtest and forward-test it on your preferred instruments and timeframes to understand its unique behavior and characteristics.
🔮 CONCLUSION
The Aetherium Institutional Market Resonance Engine represents a paradigm shift from single-variable analysis to a holistic, multi-pillar framework. By quantifying the abstract concepts of market context, location, and timing into a unified, logical system, it provides traders with an unprecedented lens into the mechanics of institutional market operations.
It is not merely an indicator, but a complete analytical engine designed to foster a deeper understanding of market dynamics. By focusing on the core principles of institutional order flow, Aetherium empowers traders to filter out market noise, identify key structural levels, and time their entries in harmony with the market's underlying rhythm.
"In all chaos there is a cosmos, in all disorder a secret order." - Carl Jung
— Dskyz, Trade with insight. Trade with confluence. Trade with Aetherium.
RSI Divergence (Nikko)RSI Divergence by Nikko
🧠 RSI Divergence Detector — Nikko Edition This script is an enhanced RSI Divergence detector built with Pine Script v6, modified for better visuals and practical usability. It uses linear regression to detect bullish and bearish divergences between the RSI and price action — one of the most reliable early signals in technical analysis.
✅ Improvements from the Original:
- Clean divergence lines using regression fitting.
- Optional label display to reduce clutter (Display Labels toggle).
- Adjustable line thickness (Display Line Width).
- A subtle heatmap background to highlight RSI overbought/oversold zones.
- Uses max accuracy with high calc_bars_count and custom extrapolation window.
🔍 How It Works: The script applies linear regression (least squares method) on both RSI data, and Price (close) data.
It then compares the direction of RSI vs. direction of Price over a set length. If price is making higher highs while RSI makes lower highs, it's a bearish divergence. If price is making lower lows while RSI makes higher lows, it's a bullish divergence. Additional filters (e.g., momentum and slope thresholds) are used to validate only strong divergences.
🔧 Input Parameters: RSI Length: The RSI period (default: 14). RSI Divergence Length: The lookback period for regression (default: 25). Source: Which price data to calculate RSI from (default: close). Display Labels: Show/hide “Bullish” or “Bearish” labels on the chart. Display Line Width: Adjusts how thick the plotted divergence lines appear.
📣 Alerts: Alerts are built-in for both RSI Buy (bullish divergence) and RSI Sell (bearish divergence) so you can use it in automation or notifications.
🚀 Personal Note: I’ve been using this script daily in my own trading, which is why I took time to improve both the logic and visual clarity. If you want a divergence tool that doesn't clutter your chart but gives strong signals, this might be what you're looking for.
BTC Transaction Indicator Name: "Bitcoin On-Chain Volume & Dynamic Parabolic Curve Signals"
Purpose:
This indicator is designed for Bitcoin traders and long-term holders. It combines the analysis of Bitcoin's on-chain transaction volume with price action to generate "Whale" and "Bear" signals. Additionally, it features a unique dynamic parabolic curve that acts as a visual support line, adapting its visibility based on price interaction with a key Exponential Moving Average (EMA).
Key Components:
On-Chain Volume Analysis:
Utilizes Estimated Transaction Volume (ETRAV) data from the Bitcoin blockchain.
Calculates fast and slow Simple Moving Averages (SMAs) of this volume.
Identifies volume trends (up/down) and significant volume increases/decreases.
Employs fixed thresholds (2,500,000 for low volume and 25,000,000 for high volume) to define key activity levels, similar to how historical on-chain analysis defined accumulation and distribution zones.
Price Action Analysis:
Calculates fast and slow SMAs of the price.
Detects price trends (up/down), recoveries, and declines based on these price SMAs.
"Whale" and "Bear" Signals:
Whale Signals (Buy-side): Generated when there's an upward volume trend, significant volume increase, and a downward price trend followed by price recovery. These indicate potential accumulation phases.
Bear Signals (Sell-side): Generated when there's a downward volume trend, significant volume decrease, and an upward price trend followed by price decline. These indicate potential distribution phases.
Visuals: Both types of signals are plotted as small, colored circles directly on the price chart, with corresponding text labels ("Whale," "Buy," "Bear," "Sell," "Price Recovering," "Price Declining").
Dynamic Parabolic Curve:
Concept: A green parabolic (exponential) curve that serves as a dynamic visual support line.
Activation: The curve starts drawing automatically only when the price crosses over the EMA 500 (Exponential Moving Average of 500 periods). The curve's starting point is set at a user-defined percentage below the EMA 500 value at that exact crossover point.
Visibility: The curve remains visible and continues its trajectory only as long as the price stays above the EMA 500.
Deactivation: The curve disappears instantly if the price falls below or equals the EMA 500. It will only reappear if the price crosses above the EMA 500 again.
Customization: The curve's steepness (Tasa Crecimiento Curva) and its initial distance from the EMA 500 (Inicio Curva % por debajo de EMA500) are adjustable.
Dynamic Label: A "Parabólico" text label is plotted near the center of the active curve segment, with an adjustable vertical offset to ensure it stays visually appealing below the curve.
What is PLOTTED on the chart:
The small, colored circle signals for Whale/Buy and Bear/Sell activity.
The green dynamic parabolic curve.
What is NOT PLOTTED:
EMA 200, EMA 500 lines (though they are calculated internally for logic).
Raw volume data or volume Moving Averages (these are only used for signal calculation, not plotted).
Ideal for:
Bitcoin traders and investors focused on long-term trends and cycle analysis, who want visual cues for accumulation/distribution phases based on on-chain activity, complemented by a unique, dynamically appearing parabolic support curve.
Important Notes:
Relies on the availability of external on-chain data (QUANDL:BCHAIN) within TradingView.
Functions best on a daily timeframe for optimal on-chain data relevance.
US30 Stealth StrategyOnly works on US30 (CAPITALCOM) 5 Minute chart
📈 Core Concept:
This is a trend-following strategy that captures strong market continuations by entering on:
The 3rd swing in the current trend,
Confirmed by a volume-verified engulfing candle,
With adaptive SL/TP and position sizing based on risk.
🧠 Entry Logic:
✅ Trend Filter
Uses a 50-period Simple Moving Average (SMA).
Buy only if price is above SMA → Uptrend
Sell only if price is below SMA → Downtrend
✅ Swing Count Logic
For buy: Wait for the 3rd higher low
For sell: Wait for the 3rd lower high
Uses a 5-bar lookback to detect highs/lows
This ensures you’re not buying early — but after trend is confirmed with structure.
✅ Engulfing Candle Confirmation
Bullish engulfing for buys
Bearish engulfing for sells
Candle must engulf previous bar completely (body logic)
✅ Volume Filter
Current candle volume must be greater than the 20-period volume average
Ensures trades only occur with institutional participation
✅ MA Slope Filter
Requires the slope of the 50 SMA over the last 3 candles to exceed 0.1
Avoids chop or flat trends
Adds momentum confirmation to the trade
✅ Session Filter (Time Filter)
Trades only executed between:
2:00 AM to 11:00 PM Oman Time (UTC+4)
Helps avoid overnight chop and illiquidity
📊 Position Sizing & Risk Management
✅ Smart SL (Adaptive Stop Loss)
SL is based on full size of the signal candle (including wick)
But if candle is larger than 25 points, SL is cut to half the size
This prevents oversized risk from long signals during volatile moves.
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.
Trend Gauge [BullByte]Trend Gauge
Summary
A multi-factor trend detection indicator that aggregates EMA alignment, VWMA momentum scaling, volume spikes, ATR breakout strength, higher-timeframe confirmation, ADX-based regime filtering, and RSI pivot-divergence penalty into one normalized trend score. It also provides a confidence meter, a Δ Score momentum histogram, divergence highlights, and a compact, scalable dashboard for at-a-glance status.
________________________________________
## 1. Purpose of the Indicator
Why this was built
Traders often monitor several indicators in parallel - EMAs, volume signals, volatility breakouts, higher-timeframe trends, ADX readings, divergence alerts, etc., which can be cumbersome and sometimes contradictory. The “Trend Gauge” indicator was created to consolidate these complementary checks into a single, normalized score that reflects the prevailing market bias (bullish, bearish, or neutral) and its strength. By combining multiple inputs with an adaptive regime filter, scaling contributions by magnitude, and penalizing weakening signals (divergence), this tool aims to reduce noise, highlight genuine trend opportunities, and warn when momentum fades.
Key Design Goals
Signal Aggregation
Merged trend-following signals (EMA crossover, ATR breakout, higher-timeframe confirmation) and momentum signals (VWMA thrust, volume spikes) into a unified score that reflects directional bias more holistically.
Market Regime Awareness
Implemented an ADX-style filter to distinguish between trending and ranging markets, reducing the influence of trend signals during sideways phases to avoid false breakouts.
Magnitude-Based Scaling
Replaced binary contributions with scaled inputs: VWMA thrust and ATR breakout are weighted relative to recent averages, allowing for more nuanced score adjustments based on signal strength.
Momentum Divergence Penalty
Integrated pivot-based RSI divergence detection to slightly reduce the overall score when early signs of momentum weakening are detected, improving risk-awareness in entries.
Confidence Transparency
Added a live confidence metric that shows what percentage of enabled sub-indicators currently agree with the overall bias, making the scoring system more interpretable.
Momentum Acceleration Visualization
Plotted the change in score (Δ Score) as a histogram bar-to-bar, highlighting whether momentum is increasing, flattening, or reversing, aiding in more timely decision-making.
Compact Informational Dashboard
Presented a clean, scalable dashboard that displays each component’s status, the final score, confidence %, detected regime (Trending/Ranging), and a labeled strength gauge for quick visual assessment.
________________________________________
## 2. Why a Trader Should Use It
Main benefits and use cases
1. Unified View: Rather than juggling multiple windows or panels, this indicator delivers a single score synthesizing diverse signals.
2. Regime Filtering: In ranging markets, trend signals often generate false entries. The ADX-based regime filter automatically down-weights trend-following components, helping you avoid chasing false breakouts.
3. Nuanced Momentum & Volatility: VWMA and ATR breakout contributions are normalized by recent averages, so strong moves register strongly while smaller fluctuations are de-emphasized.
4. Early Warning of Weakening: Pivot-based RSI divergence is detected and used to slightly reduce the score when price/momentum diverges, giving a cautionary signal before a full reversal.
5. Confidence Meter: See at a glance how many sub-indicators align with the aggregated bias (e.g., “80% confidence” means 4 out of 5 components agree ). This transparency avoids black-box decisions.
6. Trend Acceleration/Deceleration View: The Δ Score histogram visualizes whether the aggregated score is rising (accelerating trend) or falling (momentum fading), supplementing the main oscillator.
7. Compact Dashboard: A corner table lists each check’s status (“Bull”, “Bear”, “Flat” or “Disabled”), plus overall Score, Confidence %, Regime, Trend Strength label, and a gauge bar. Users can scale text size (Normal, Small, Tiny) without removing elements, so the full picture remains visible even in compact layouts.
8. Customizable & Transparent: All components can be enabled/disabled and parameterized (lengths, thresholds, weights). The full Pine code is open and well-commented, letting users inspect or adapt the logic.
9. Alert-ready: Built-in alert conditions fire when the score crosses weak thresholds to bullish/bearish or returns to neutral, enabling timely notifications.
________________________________________
## 3. Component Rationale (“Why These Specific Indicators?”)
Each sub-component was chosen because it adds complementary information about trend or momentum:
1. EMA Cross
o Basic trend measure: compares a faster EMA vs. a slower EMA. Quickly reflects trend shifts but by itself can whipsaw in sideways markets.
2. VWMA Momentum
o Volume-weighted moving average change indicates momentum with volume context. By normalizing (dividing by a recent average absolute change), we capture the strength of momentum relative to recent history. This scaling prevents tiny moves from dominating and highlights genuinely strong momentum.
3. Volume Spikes
o Sudden jumps in volume combined with price movement often accompany stronger moves or reversals. A binary detection (+1 for bullish spike, -1 for bearish spike) flags high-conviction bars.
4. ATR Breakout
o Detects price breaking beyond recent highs/lows by a multiple of ATR. Measures breakout strength by how far beyond the threshold price moves relative to ATR, capped to avoid extreme outliers. This gives a volatility-contextual trend signal.
5. Higher-Timeframe EMA Alignment
o Confirms whether the shorter-term trend aligns with a higher timeframe trend. Uses request.security with lookahead_off to avoid future data. When multiple timeframes agree, confidence in direction increases.
6. ADX Regime Filter (Manual Calculation)
o Computes directional movement (+DM/–DM), smoothes via RMA, computes DI+ and DI–, then a DX and ADX-like value. If ADX ≥ threshold, market is “Trending” and trend components carry full weight; if ADX < threshold, “Ranging” mode applies a configurable weight multiplier (e.g., 0.5) to trend-based contributions, reducing false signals in sideways conditions. Volume spikes remain binary (optional behavior; can be adjusted if desired).
7. RSI Pivot-Divergence Penalty
o Uses ta.pivothigh / ta.pivotlow with a lookback to detect pivot highs/lows on price and corresponding RSI values. When price makes a higher high but RSI makes a lower high (bearish divergence), or price makes a lower low but RSI makes a higher low (bullish divergence), a divergence signal is set. Rather than flipping the trend outright, the indicator subtracts (or adds) a small penalty (configurable) from the aggregated score if it would weaken the current bias. This subtle adjustment warns of weakening momentum without overreacting to noise.
8. Confidence Meter
o Counts how many enabled components currently agree in direction with the aggregated score (i.e., component sign × score sign > 0). Displays this as a percentage. A high percentage indicates strong corroboration; a low percentage warns of mixed signals.
9. Δ Score Momentum View
o Plots the bar-to-bar change in the aggregated score (delta_score = score - score ) as a histogram. When positive, bars are drawn in green above zero; when negative, bars are drawn in red below zero. This reveals acceleration (rising Δ) or deceleration (falling Δ), supplementing the main oscillator.
10. Dashboard
• A table in the indicator pane’s top-right with 11 rows:
1. EMA Cross status
2. VWMA Momentum status
3. Volume Spike status
4. ATR Breakout status
5. Higher-Timeframe Trend status
6. Score (numeric)
7. Confidence %
8. Regime (“Trending” or “Ranging”)
9. Trend Strength label (e.g., “Weak Bullish Trend”, “Strong Bearish Trend”)
10. Gauge bar visually representing score magnitude
• All rows always present; size_opt (Normal, Small, Tiny) only changes text size via text_size, not which elements appear. This ensures full transparency.
________________________________________
## 4. What Makes This Indicator Stand Out
• Regime-Weighted Multi-Factor Score: Trend and momentum signals are adaptively weighted by market regime (trending vs. ranging) , reducing false signals.
• Magnitude Scaling: VWMA and ATR breakout contributions are normalized by recent average momentum or ATR, giving finer gradation compared to simple ±1.
• Integrated Divergence Penalty: Divergence directly adjusts the aggregated score rather than appearing as a separate subplot; this influences alerts and trend labeling in real time.
• Confidence Meter: Shows the percentage of sub-signals in agreement, providing transparency and preventing blind trust in a single metric.
• Δ Score Histogram Momentum View: A histogram highlights acceleration or deceleration of the aggregated trend score, helping detect shifts early.
• Flexible Dashboard: Always-visible component statuses and summary metrics in one place; text size scaling keeps the full picture available in cramped layouts.
• Lookahead-Safe HTF Confirmation: Uses lookahead_off so no future data is accessed from higher timeframes, avoiding repaint bias.
• Repaint Transparency: Divergence detection uses pivot functions that inherently confirm only after lookback bars; description documents this lag so users understand how and when divergence labels appear.
• Open-Source & Educational: Full, well-commented Pine v6 code is provided; users can learn from its structure: manual ADX computation, conditional plotting with series = show ? value : na, efficient use of table.new in barstate.islast, and grouped inputs with tooltips.
• Compliance-Conscious: All plots have descriptive titles; inputs use clear names; no unnamed generic “Plot” entries; manual ADX uses RMA; all request.security calls use lookahead_off. Code comments mention repaint behavior and limitations.
________________________________________
## 5. Recommended Timeframes & Tuning
• Any Timeframe: The indicator works on small (e.g., 1m) to large (daily, weekly) timeframes. However:
o On very low timeframes (<1m or tick charts), noise may produce frequent whipsaws. Consider increasing smoothing lengths, disabling certain components (e.g., volume spike if volume data noisy), or using a larger pivot lookback for divergence.
o On higher timeframes (daily, weekly), consider longer lookbacks for ATR breakout or divergence, and set Higher-Timeframe trend appropriately (e.g., 4H HTF when on 5 Min chart).
• Defaults & Experimentation: Default input values are chosen to be balanced for many liquid markets. Users should test with replay or historical analysis on their symbol/timeframe and adjust:
o ADX threshold (e.g., 20–30) based on instrument volatility.
o VWMA and ATR scaling lengths to match average volatility cycles.
o Pivot lookback for divergence: shorter for faster markets, longer for slower ones.
• Combining with Other Analysis: Use in conjunction with price action, support/resistance, candlestick patterns, order flow, or other tools as desired. The aggregated score and alerts can guide attention but should not be the sole decision-factor.
________________________________________
## 6. How Scoring and Logic Works (Step-by-Step)
1. Compute Sub-Scores
o EMA Cross: Evaluate fast EMA > slow EMA ? +1 : fast EMA < slow EMA ? -1 : 0.
o VWMA Momentum: Calculate vwma = ta.vwma(close, length), then vwma_mom = vwma - vwma . Normalize: divide by recent average absolute momentum (e.g., ta.sma(abs(vwma_mom), lookback)), clip to .
o Volume Spike: Compute vol_SMA = ta.sma(volume, len). If volume > vol_SMA * multiplier AND price moved up ≥ threshold%, assign +1; if moved down ≥ threshold%, assign -1; else 0.
o ATR Breakout: Determine recent high/low over lookback. If close > high + ATR*mult, compute distance = close - (high + ATR*mult), normalize by ATR, cap at a configured maximum. Assign positive contribution. Similarly for bearish breakout below low.
o Higher-Timeframe Trend: Use request.security(..., lookahead=barmerge.lookahead_off) to fetch HTF EMAs; assign +1 or -1 based on alignment.
2. ADX Regime Weighting
o Compute manual ADX: directional movements (+DM, –DM), smoothed via RMA, DI+ and DI–, then DX and ADX via RMA. If ADX ≥ threshold, market is considered “Trending”; otherwise “Ranging.”
o If trending, trend-based contributions (EMA, VWMA, ATR, HTF) use full weight = 1.0. If ranging, use weight = ranging_weight (e.g., 0.5) to down-weight them. Volume spike stays binary ±1 (optional to change if desired).
3. Aggregate Raw Score
o Sum weighted contributions of all enabled components. Count the number of enabled components; if zero, default count = 1 to avoid division by zero.
4. Divergence Penalty
o Detect pivot highs/lows on price and corresponding RSI values, using a lookback. When price and RSI diverge (bearish or bullish divergence), check if current raw score is in the opposing direction:
If bearish divergence (price higher high, RSI lower high) and raw score currently positive, subtract a penalty (e.g., 0.5).
If bullish divergence (price lower low, RSI higher low) and raw score currently negative, add a penalty.
o This reduces score magnitude to reflect weakening momentum, without flipping the trend outright.
5. Normalize and Smooth
o Normalized score = (raw_score / number_of_enabled_components) * 100. This yields a roughly range.
o Optional EMA smoothing of this normalized score to reduce noise.
6. Interpretation
o Sign: >0 = net bullish bias; <0 = net bearish bias; near zero = neutral.
o Magnitude Zones: Compare |score| to thresholds (Weak, Medium, Strong) to label trend strength (e.g., “Weak Bullish Trend”, “Medium Bearish Trend”, “Strong Bullish Trend”).
o Δ Score Histogram: The histogram bars from zero show change from previous bar’s score; positive bars indicate acceleration, negative bars indicate deceleration.
o Confidence: Percentage of sub-indicators aligned with the score’s sign.
o Regime: Indicates whether trend-based signals are fully weighted or down-weighted.
________________________________________
## 7. Oscillator Plot & Visualization: How to Read It
Main Score Line & Area
The oscillator plots the aggregated score as a line, with colored fill: green above zero for bullish area, red below zero for bearish area. Horizontal reference lines at ±Weak, ±Medium, and ±Strong thresholds mark zones: crossing above +Weak suggests beginning of bullish bias, above +Medium for moderate strength, above +Strong for strong trend; similarly for bearish below negative thresholds.
Δ Score Histogram
If enabled, a histogram shows score - score . When positive, bars appear in green above zero, indicating accelerating bullish momentum; when negative, bars appear in red below zero, indicating decelerating or reversing momentum. The height of each bar reflects the magnitude of change in the aggregated score from the prior bar.
Divergence Highlight Fill
If enabled, when a pivot-based divergence is confirmed:
• Bullish Divergence : fill the area below zero down to –Weak threshold in green, signaling potential reversal from bearish to bullish.
• Bearish Divergence : fill the area above zero up to +Weak threshold in red, signaling potential reversal from bullish to bearish.
These fills appear with a lag equal to pivot lookback (the number of bars needed to confirm the pivot). They do not repaint after confirmation, but users must understand this lag.
Trend Direction Label
When score crosses above or below the Weak threshold, a small label appears near the score line reading “Bullish” or “Bearish.” If the score returns within ±Weak, the label “Neutral” appears. This helps quickly identify shifts at the moment they occur.
Dashboard Panel
In the indicator pane’s top-right, a table shows:
1. EMA Cross status: “Bull”, “Bear”, “Flat”, or “Disabled”
2. VWMA Momentum status: similarly
3. Volume Spike status: “Bull”, “Bear”, “No”, or “Disabled”
4. ATR Breakout status: “Bull”, “Bear”, “No”, or “Disabled”
5. Higher-Timeframe Trend status: “Bull”, “Bear”, “Flat”, or “Disabled”
6. Score: numeric value (rounded)
7. Confidence: e.g., “80%” (colored: green for high, amber for medium, red for low)
8. Regime: “Trending” or “Ranging” (colored accordingly)
9. Trend Strength: textual label based on magnitude (e.g., “Medium Bullish Trend”)
10. Gauge: a bar of blocks representing |score|/100
All rows remain visible at all times; changing Dashboard Size only scales text size (Normal, Small, Tiny).
________________________________________
## 8. Example Usage (Illustrative Scenario)
Example: BTCUSD 5 Min
1. Setup: Add “Trend Gauge ” to your BTCUSD 5 Min chart. Defaults: EMAs (8/21), VWMA 14 with lookback 3, volume spike settings, ATR breakout 14/5, HTF = 5m (or adjust to 4H if preferred), ADX threshold 25, ranging weight 0.5, divergence RSI length 14 pivot lookback 5, penalty 0.5, smoothing length 3, thresholds Weak=20, Medium=50, Strong=80. Dashboard Size = Small.
2. Trend Onset: At some point, price breaks above recent high by ATR multiple, volume spikes upward, faster EMA crosses above slower EMA, HTF EMA also bullish, and ADX (manual) ≥ threshold → aggregated score rises above +20 (Weak threshold) into +Medium zone. Dashboard shows “Bull” for EMA, VWMA, Vol Spike, ATR, HTF; Score ~+60–+70; Confidence ~100%; Regime “Trending”; Trend Strength “Medium Bullish Trend”; Gauge ~6–7 blocks. Δ Score histogram bars are green and rising, indicating accelerating bullish momentum. Trader notes the alignment.
3. Divergence Warning: Later, price makes a slightly higher high but RSI fails to confirm (lower RSI high). Pivot lookback completes; the indicator highlights a bearish divergence fill above zero and subtracts a small penalty from the score, causing score to stall or retrace slightly. Dashboard still bullish but score dips toward +Weak. This warns the trader to tighten stops or take partial profits.
4. Trend Weakens: Score eventually crosses below +Weak back into neutral; a “Neutral” label appears, and a “Neutral Trend” alert fires if enabled. Trader exits or avoids new long entries. If score subsequently crosses below –Weak, a “Bearish” label and alert occur.
5. Customization: If the trader finds VWMA noise too frequent on this instrument, they may disable VWMA or increase lookback. If ATR breakouts are too rare, adjust ATR length or multiplier. If ADX threshold seems off, tune threshold. All these adjustments are explained in Inputs section.
6. Visualization: The screenshot shows the main score oscillator with colored areas, reference lines at ±20/50/80, Δ Score histogram bars below/above zero, divergence fill highlighting potential reversal, and the dashboard table in the top-right.
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## 9. Inputs Explanation
A concise yet clear summary of inputs helps users understand and adjust:
1. General Settings
• Theme (Dark/Light): Choose background-appropriate colors for the indicator pane.
• Dashboard Size (Normal/Small/Tiny): Scales text size only; all dashboard elements remain visible.
2. Indicator Settings
• Enable EMA Cross: Toggle on/off basic EMA alignment check.
o Fast EMA Length and Slow EMA Length: Periods for EMAs.
• Enable VWMA Momentum: Toggle VWMA momentum check.
o VWMA Length: Period for VWMA.
o VWMA Momentum Lookback: Bars to compare VWMA to measure momentum.
• Enable Volume Spike: Toggle volume spike detection.
o Volume SMA Length: Period to compute average volume.
o Volume Spike Multiplier: How many times above average volume qualifies as spike.
o Min Price Move (%): Minimum percent change in price during spike to qualify as bullish or bearish.
• Enable ATR Breakout: Toggle ATR breakout detection.
o ATR Length: Period for ATR.
o Breakout Lookback: Bars to look back for recent highs/lows.
o ATR Multiplier: Multiplier for breakout threshold.
• Enable Higher Timeframe Trend: Toggle HTF EMA alignment.
o Higher Timeframe: E.g., “5” for 5-minute when on 1-minute chart, or “60” for 5 Min when on 15m, etc. Uses lookahead_off.
• Enable ADX Regime Filter: Toggles regime-based weighting.
o ADX Length: Period for manual ADX calculation.
o ADX Threshold: Value above which market considered trending.
o Ranging Weight Multiplier: Weight applied to trend components when ADX < threshold (e.g., 0.5).
• Scale VWMA Momentum: Toggle normalization of VWMA momentum magnitude.
o VWMA Mom Scale Lookback: Period for average absolute VWMA momentum.
• Scale ATR Breakout Strength: Toggle normalization of breakout distance by ATR.
o ATR Scale Cap: Maximum multiple of ATR used for breakout strength.
• Enable Price-RSI Divergence: Toggle divergence detection.
o RSI Length for Divergence: Period for RSI.
o Pivot Lookback for Divergence: Bars on each side to identify pivot high/low.
o Divergence Penalty: Amount to subtract/add to score when divergence detected (e.g., 0.5).
3. Score Settings
• Smooth Score: Toggle EMA smoothing of normalized score.
• Score Smoothing Length: Period for smoothing EMA.
• Weak Threshold: Absolute score value under which trend is considered weak or neutral.
• Medium Threshold: Score above Weak but below Medium is moderate.
• Strong Threshold: Score above this indicates strong trend.
4. Visualization Settings
• Show Δ Score Histogram: Toggle display of the bar-to-bar change in score as a histogram. Default true.
• Show Divergence Fill: Toggle background fill highlighting confirmed divergences. Default true.
Each input has a tooltip in the code.
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## 10. Limitations, Repaint Notes, and Disclaimers
10.1. Repaint & Lag Considerations
• Pivot-Based Divergence Lag: The divergence detection uses ta.pivothigh / ta.pivotlow with a specified lookback. By design, a pivot is only confirmed after the lookback number of bars. As a result:
o Divergence labels or fills appear with a delay equal to the pivot lookback.
o Once the pivot is confirmed and the divergence is detected, the fill/label does not repaint thereafter, but you must understand and accept this lag.
o Users should not treat divergence highlights as predictive signals without additional confirmation, because they appear after the pivot has fully formed.
• Higher-Timeframe EMA Alignment: Uses request.security(..., lookahead=barmerge.lookahead_off), so no future data from the higher timeframe is used. This avoids lookahead bias and ensures signals are based only on completed higher-timeframe bars.
• No Future Data: All calculations are designed to avoid using future information. For example, manual ADX uses RMA on past data; security calls use lookahead_off.
10.2. Market & Noise Considerations
• In very choppy or low-liquidity markets, some components (e.g., volume spikes or VWMA momentum) may be noisy. Users can disable or adjust those components’ parameters.
• On extremely low timeframes, noise may dominate; consider smoothing lengths or disabling certain features.
• On very high timeframes, pivots and breakouts occur less frequently; adjust lookbacks accordingly to avoid sparse signals.
10.3. Not a Standalone Trading System
• This is an indicator, not a complete trading strategy. It provides signals and context but does not manage entries, exits, position sizing, or risk management.
• Users must combine it with their own analysis, money management, and confirmations (e.g., price patterns, support/resistance, fundamental context).
• No guarantees: past behavior does not guarantee future performance.
10.4. Disclaimers
• Educational Purposes Only: The script is provided as-is for educational and informational purposes. It does not constitute financial, investment, or trading advice.
• Use at Your Own Risk: Trading involves risk of loss. Users should thoroughly test and use proper risk management.
• No Guarantees: The author is not responsible for trading outcomes based on this indicator.
• License: Published under Mozilla Public License 2.0; code is open for viewing and modification under MPL terms.
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## 11. Alerts
• The indicator defines three alert conditions:
1. Bullish Trend: when the aggregated score crosses above the Weak threshold.
2. Bearish Trend: when the score crosses below the negative Weak threshold.
3. Neutral Trend: when the score returns within ±Weak after being outside.
Good luck
– BullByte
MC Geopolitical Tension Events📌 Script Title: Geopolitical Tension Events
📖 Description:
This script highlights key geopolitical and military tension events from 1914 to 2024 that have historically impacted global markets.
It automatically plots vertical dashed lines and labels on the chart at the time of each major event. This allows traders and analysts to visually assess how markets have responded to global crises, wars, and significant political instability over time.
🧠 Use Cases:
Historical backtesting: Understand how market responded to past geopolitical shocks.
Contextual analysis: Add macro context to technical setups.
🗓️ List of Geopolitical Tension Events in the Script
Date Event Title Description
1914-07-28 WWI Begins Outbreak of World War I following the assassination of Archduke Franz Ferdinand.
1929-10-24 Wall Street Crash Black Thursday, the start of the 1929 stock market crash.
1939-09-01 WWII Begins Germany invades Poland, starting World War II.
1941-12-07 Pearl Harbor Japanese attack on Pearl Harbor; U.S. enters WWII.
1945-08-06 Hiroshima Bombing First atomic bomb dropped on Hiroshima by the U.S.
1950-06-25 Korean War Begins North Korea invades South Korea.
1962-10-16 Cuban Missile Crisis 13-day standoff between the U.S. and USSR over missiles in Cuba.
1973-10-06 Yom Kippur War Egypt and Syria launch surprise attack on Israel.
1979-11-04 Iran Hostage Crisis U.S. Embassy in Tehran seized; 52 hostages taken.
1990-08-02 Gulf War Begins Iraq invades Kuwait, triggering U.S. intervention.
2001-09-11 9/11 Attacks Coordinated terrorist attacks on the U.S.
2003-03-20 Iraq War Begins U.S.-led invasion of Iraq to remove Saddam Hussein.
2008-09-15 Lehman Collapse Bankruptcy of Lehman Brothers; peak of global financial crisis.
2014-03-01 Crimea Crisis Russia annexes Crimea from Ukraine.
2020-01-03 Soleimani Strike U.S. drone strike kills Iranian General Qasem Soleimani.
2022-02-24 Ukraine Invasion Russia launches full-scale invasion of Ukraine.
2023-10-07 Hamas-Israel War Hamas launches attack on Israel, sparking war in Gaza.
2024-01-12 Red Sea Crisis Houthis attack ships in Red Sea, prompting Western naval response.
