ND Egitim - AI Oto FibonacciAutomatic Fibonacci & HH/LL Trend Analysis
This indicator automatically determines the optimal lookback bar count based on market conditions and the specific symbol, then identifies the most recent “Higher High” (HH) and “Lower Low” (LL) points on your chart. It draws a Fibonacci system between these two points, allowing you to instantly visualize potential retracement and extension levels that may act as key support and resistance zones. Additionally, the indicator provides a quick overview of the overall market trend and volatility.
What does it do?
• Fibonacci Levels: Classic Fibonacci levels such as 0%, 23.6%, 38.2%, 50%, 61.8%, 78.6%, and 100% are drawn automatically on the chart. Additional extension and negative levels are also displayed as needed.
• Trend Direction: The general market trend (bullish, bearish, or sideways) is visualized based on the relative positioning of HH/LL points and the structure of moving averages.
• Alert Conditions: Built-in alerts notify you when the price breaks key Fibonacci levels.
Análise de Tendência
Wx2 Reversal Signals Key Levels, Entry/Exit ManagementWin Rate 50%
Best Time frame 1Min, 2min, 3Min, 5Min
Entry / Exit = Box
Stop loss is ATR Based
TP1=1.5%
TP2=2%
Step-1
Mark Swing High and Low in Higher Time Frame
Step-2
Entry in the direction of trend
Buy -When HTF is in uptrend
Sell -When HTF is in Downtrend
Step-3
Exit 50% at TP1 and Trail SL on Entry
Step-4
Full Exit at TP2
Supertrend MACD StrategySupertrend MACD Strategy - Description & Usage Guide
🚀 EARLY ACCESS INDICATOR
This is an early access version of my Supertrend MACD Strategy.
📊 What Is This Indicator?
The Supertrend MACD Strategy combines the power of MACD signals with filtering mechanisms to work seamlessly across ALL trading instruments - from forex and crypto to stocks and commodities.
Unlike traditional MACD indicators that only work well on specific assets, this universal version automatically adapts to any market's price structure and volatility characteristics.
Key Features:
✅ Universal Compatibility - Works on ANY trading pair without manual adjustments
✅ Smart Multi-Filter System - Combines MACD, ATR, ADX, and higher timeframe analysis
✅ Non-Repainting Signals - Signals form after candle close and never change
✅ Trend Continuation Tracking - BUY+/SELL+ signals for trend strength
✅ Structure Break Detection - Identifies major market shifts
✅ Visual Signal Line - Clear trend state indicator on chart
🎯 How The Signals Work
Signal Types:
BUY (Green) - Initial buy signal when all filters align
SELL (Red) - Initial sell signal when all filters align
BUY+ (Purple) - Second confirmation signal in uptrend
SELL+ (Purple) - Second confirmation signal in downtrend
Triangle Arrows - Additional trend continuation signals (optional)
Signal Formation:
⚠️ IMPORTANT: All signals form AFTER the second candle closes and MAY NOT REPAINT. Once a signal appears, it's final and will never disappear or change position.
🛠️ How To Use This Indicator
Basic Setup:
Add the indicator to any chart (works on all timeframes)
Default settings work for most instruments
Enable "Show Debug Info" to see real-time filter values
Set up alerts for automated notifications
Entry Strategies:
Conservative Approach:
Enter on BUY+ or SELL+ signals (purple labels)
These are second confirmations with higher probability
Wait for signal line color to match your trade direction
Aggressive Approach:
Enter on first BUY or SELL signals (green/red labels)
Use tight stop losses below/above recent swing points
Scale in with additional positions on BUY+/SELL+ signals
Exit Strategies:
Exit when opposite signal appears
Use trailing stops following the signal line
Take partial profits at key resistance/support levels
🔧 Advanced Filter Explanations
ATR Volatility Filter:
Ensures sufficient market movement before signaling
Percentage-based for universal compatibility
Higher values = fewer but higher quality signals
ADX Trend Strength:
Confirms trend momentum before entry
Default 15 works for most markets
Higher values filter out weak trends
Higher Timeframe Confirmation:
Aligns signals with larger trend direction
Default 1-hour works for most timeframes
Use 4H for daily charts, Daily for weekly charts
Structure Break Detection:
Identifies when price breaks significant levels
BOS+ signals indicate strong momentum
Percentage-based for universal scaling
🚨 Important Disclaimers
Signal Timing:
Signals appear AFTER second candle close only
low chance of repainting - signals never change once formed
Real-time bar shows potential signal until close
Risk Management:
This indicator provides signals, not trade outcomes
Always use proper position sizing and stop losses
Backtest thoroughly before live trading
Markets can remain irrational longer than expected
Early Access Notes:
This is a pre-release version with ongoing improvements
Settings may be refined based on user feedback
Additional features planned for future updates
Report any issues or suggestions for enhancement
as said before this is indicator is in its early days so is subject to big changes
Version 1.0 (22 JUNE 25)
Trade responsibly and always conduct your own analysis before making trading decisions.
Custom Combined Indicator: ALMA + TMA + IchimokuA combination of Three indicators into One indicator .
- ALMA
- TMA
- ICHIMOKU
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.
Wavelet-Trend ML Integration [Alpha Extract]Alpha-Extract Volatility Quality Indicator
The Alpha-Extract Volatility Quality (AVQ) Indicator provides traders with deep insights into market volatility by measuring the directional strength of price movements. This sophisticated momentum-based tool helps identify overbought and oversold conditions, offering actionable buy and sell signals based on volatility trends and standard deviation bands.
🔶 CALCULATION
The indicator processes volatility quality data through a series of analytical steps:
Bar Range Calculation: Measures true range (TR) to capture price volatility.
Directional Weighting: Applies directional bias (positive for bullish candles, negative for bearish) to the true range.
VQI Computation: Uses an exponential moving average (EMA) of weighted volatility to derive the Volatility Quality Index (VQI).
Smoothing: Applies an additional EMA to smooth the VQI for clearer signals.
Normalization: Optionally normalizes VQI to a -100/+100 scale based on historical highs and lows.
Standard Deviation Bands: Calculates three upper and lower bands using standard deviation multipliers for volatility thresholds.
Signal Generation: Produces overbought/oversold signals when VQI reaches extreme levels (±200 in normalized mode).
Formula:
Bar Range = True Range (TR)
Weighted Volatility = Bar Range × (Close > Open ? 1 : Close < Open ? -1 : 0)
VQI Raw = EMA(Weighted Volatility, VQI Length)
VQI Smoothed = EMA(VQI Raw, Smoothing Length)
VQI Normalized = ((VQI Smoothed - Lowest VQI) / (Highest VQI - Lowest VQI) - 0.5) × 200
Upper Band N = VQI Smoothed + (StdDev(VQI Smoothed, VQI Length) × Multiplier N)
Lower Band N = VQI Smoothed - (StdDev(VQI Smoothed, VQI Length) × Multiplier N)
🔶 DETAILS
Visual Features:
VQI Plot: Displays VQI as a line or histogram (lime for positive, red for negative).
Standard Deviation Bands: Plots three upper and lower bands (teal for upper, grayscale for lower) to indicate volatility thresholds.
Reference Levels: Horizontal lines at 0 (neutral), +100, and -100 (in normalized mode) for context.
Zone Highlighting: Overbought (⋎ above bars) and oversold (⋏ below bars) signals for extreme VQI levels (±200 in normalized mode).
Candle Coloring: Optional candle overlay colored by VQI direction (lime for positive, red for negative).
Interpretation:
VQI ≥ 200 (Normalized): Overbought condition, strong sell signal.
VQI 100–200: High volatility, potential selling opportunity.
VQI 0–100: Neutral bullish momentum.
VQI 0 to -100: Neutral bearish momentum.
VQI -100 to -200: High volatility, strong bearish momentum.
VQI ≤ -200 (Normalized): Oversold condition, strong buy signal.
🔶 EXAMPLES
Overbought Signal Detection: When VQI exceeds 200 (normalized), the indicator flags potential market tops with a red ⋎ symbol.
Example: During strong uptrends, VQI reaching 200 has historically preceded corrections, allowing traders to secure profits.
Oversold Signal Detection: When VQI falls below -200 (normalized), a lime ⋏ symbol highlights potential buying opportunities.
Example: In bearish markets, VQI dropping below -200 has marked reversal points for profitable long entries.
Volatility Trend Tracking: The VQI plot and bands help traders visualize shifts in market momentum.
Example: A rising VQI crossing above zero with widening bands indicates strengthening bullish momentum, guiding traders to hold or enter long positions.
Dynamic Support/Resistance: Standard deviation bands act as dynamic volatility thresholds during price movements.
Example: Price reversals often occur near the third standard deviation bands, providing reliable entry/exit points during volatile periods.
🔶 SETTINGS
Customization Options:
VQI Length: Adjust the EMA period for VQI calculation (default: 14, range: 1–50).
Smoothing Length: Set the EMA period for smoothing (default: 5, range: 1–50).
Standard Deviation Multipliers: Customize multipliers for bands (defaults: 1.0, 2.0, 3.0).
Normalization: Toggle normalization to -100/+100 scale and adjust lookback period (default: 200, min: 50).
Display Style: Switch between line or histogram plot for VQI.
Candle Overlay: Enable/disable VQI-colored candles (lime for positive, red for negative).
The Alpha-Extract Volatility Quality Indicator empowers traders with a robust tool to navigate market volatility. By combining directional price range analysis with smoothed volatility metrics, it identifies overbought and oversold conditions, offering clear buy and sell signals. The customizable standard deviation bands and optional normalization provide precise context for market conditions, enabling traders to make informed decisions across various market cycles.
Support & ResistanceWhat is this script ?
Pivot points are tools used to identify potential support and resistance levels in trading. They are calculated using the previous period’s high, low, and close prices. This script leverages pivot points to plot up to four support levels and four resistance levels, helping traders visualize key price zones.
How to Use the Script?
Support and resistance levels represent price zones where significant liquidity often exists due to past price interactions. These levels are critical for traders to:
Assess Trend Continuation or Reversal: Prices may pause, reverse, or break through at these levels, signaling potential trend changes or continuations.
Manage Risk: Support and resistance levels are ideal for placing stop-loss orders or setting profit targets, as they indicate areas where price reactions are likely.
Plan Entries and Exits: Traders can buy near support levels, sell near resistance levels, or trade breakouts when prices move decisively beyond these zones.
Siyonacci-powerWith this indicator:
Volume momentum volume line filters the trend.
ATR bands control volatility.
You get alerts for volume mismatch.
MSB peak-bottom breakouts are visible.
MACD momentum histogram in the bottom panel confirms the strength of the signal.
Static ADR/ATR RangesSee how the price is moving in comparison to ATR and ADR to estimate the price movements intraday and anticipate breakouts, targets and stop losses.
Scanner Candles v2.01The "Scanner Candle v.2.01" is an indicator classifies candles based on the body/range ratio: indecisive (small body, ≤50%), decisive (medium body), explosive (large body, ≥70%). It includes EMAs to identify trends and "Reset Candles" (RC), small-bodied candles near EMAs, signaling potential reversals or continuations. Useful for analyzing volatility, breakouts, reversals, and risk management.
Description of the indicator:
The "Scanner Candle v.2.01" indicator classifies candles into three categories based on the proportion of the candle's body to its range (high-low):
Indecisive: candles with a small body (≤ set threshold, default 50%), indicating low volatility or market uncertainty.
Decisive: candles with a medium body, reflecting a clear but not extreme price movement.
Explosive: candles with a large body (≥ set threshold, default 70%), signaling strong directional moves.
Additionally, the indicator includes:
Customizable exponential moving averages (EMAs) to identify trends and support/resistance levels.
Detection of "Reset Candles" (RC), specific candles (e.g., dojis, ) with a small bodies body near EMAs, useful for identifying potential reversal or continuation points.
Coloring and visualization:
Candles are colored by category (white for indecisive, orange for decisive, purple for explosive).
Reset Candles are marked with circles above/below the candle (green for bullish, red for bearish).
Potential uses:
Volatility analysis: Identifying uncertain (indecisive), directional (decisive), or impulsive (explosive) market phases.
Breakout trading: Explosive candles can signal entry opportunities on strong moves.
Reversal detection: Reset Candles near EMAs can indicate turning points or trend continuation.
Trend-following support: Integrated EMAs contextualize candles within the main trend.
Risk management: Indecisive candles suggest avoiding trades in low-directionality phases.
The indicator is customizable (thresholds, colors, thresholdsEMAs, ) and adaptable to various timeframes and strategies, from day trading to swing trading.
Reset Candles:
Reset Candles (RC) are specific candles signaling potential reversals or continuations, often near EMAs. They are defined by:
Small body: Body < 5% of the range of the last 10 candles, indicating low volatility (e.g., doji).
EMA proximity: The candle is near or crosses a defined EMA (e.g., 10, 60, or 223 periods).
Trend conditions: Follows a red candle, with the close of the previous previous candles above a specific EMA, suggesting a potential bullish resumption or stabilization.
Limited spike: The candle has minimal tails (spikes, ) below a set threshold (default 1%).
Minimum timeframe: Appears on timeframes ≥ set value (default 5 minutes) or daily charts.
Non-consecutive: Not preceded by other RCs in the last 3 candles.
Types:
Doji_fin: Green circle above, signaling a bullish bullish setup near longer EMAs.
Dojifin_2: Yellow Red circle below, signaling a bearish setup near shorter EMAs.
Trading uses:
Reversal: RCs near EMAs signal bounces or rejections, ideal for counter-trend trades.
Continuation: In trends, RCs indicate pauses before trend resumption, offering low-risk entries.
Support/resistance confirmation: EMA proximity strengthens the level's significance.
Risk management: Small bodies and EMA proximity allow tight stop-losses.
Limitations:
False signals: Common in volatile or sideways markets; use with additional confirmation.
Timeframe dependency: More reliable on higher timeframes (e.g., 1-hour or daily).
Customization needed: Thresholds (e.g., spike, timeframe) must be tailored to the market.
Conclusion:
Reset Candles highlight low-volatility moments near technical levels (EMAs) that may precede significant moves. They are ideal for precise entries with tight stops in reversal or continuation strategies but require clear market context and additional confirmation for optimal effectiveness.
#ema #candlepattern #scalping
Precision Momentum Scalper//@version=5
indicator("Precision Momentum Scalper", overlay=true)
// Inputs
emaFastLen = input.int(50, title="EMA Fast")
emaSlowLen = input.int(200, title="EMA Slow")
rsiLen = input.int(14, title="RSI Length")
macdFast = input.int(12, title="MACD Fast")
macdSlow = input.int(26, title="MACD Slow")
macdSignal = input.int(9, title="MACD Signal")
// EMA
emaFast = ta.ema(close, emaFastLen)
emaSlow = ta.ema(close, emaSlowLen)
// RSI
rsi = ta.rsi(close, rsiLen)
// MACD
= ta.macd(close, macdFast, macdSlow, macdSignal)
// Volume Spike
vol = volume
volAvg = ta.sma(volume, 5)
// Buy and Sell Conditions
longCond = close > emaFast and emaFast > emaSlow and rsi > 30 and macdLine > signalLine and volume > volAvg
shortCond = close < emaFast and emaFast < emaSlow and rsi < 70 and macdLine < signalLine and volume > volAvg
plotshape(longCond, title="Buy Signal", location=location.belowbar, color=color.green, style=shape.labelup, text="Buy")
plotshape(shortCond, title="Sell Signal", location=location.abovebar, color=color.red, style=shape.labeldown, text="Sell")
plot(emaFast, title="EMA 50", color=color.orange)
plot(emaSlow, title="EMA 200", color=color.blue)
Marx Current Trend DisplayMarx Current Trend Display
Identify trend direction instantly on any timeframe
This indicator gives you a clear, visual confirmation of the current market trend — Bullish or Bearish — based on price action relative to a customisable Exponential Moving Average (EMA).
⸻
✅ Features
• Dynamically determines trend using a user-defined EMA (default: 200)
• Shows a floating label above price:
• 🟢 “BULLISH TREND” when price is above EMA
• 🔴 “BEARISH TREND” when price is below EMA
• Optional color-coded background to make trend state even more obvious
• Works on any market and timeframe
• Simple, clean, and easy to interpret
⸻
🧠 How It Works
• Bullish Trend: Current price is above the EMA
• Bearish Trend: Current price is below the EMA
• EMA is plotted directly on the chart for additional clarity
⸻
⚙️ Customisable Settings
• EMA length (default: 200)
• Show/hide trend labels
• Toggle background color on/off
⸻
This is a perfect tool for traders who want quick confirmation of trend bias without clutter. Pair it with your entry/exit system or use it as a filter to stay aligned with market momentum.
DSPLN EMA Flip Strategy v6This script is part of the DSPLN Method, a rules-based trend-following system that trades price reactions around the 21 EMA with optional VWAP context and custom session filters.
🔹 Core Logic:
Enters long when price closes above the 21 EMA
Enters short when price closes below the 21 EMA
Exits when price closes back across the 21 EMA (trend shift)
Optional TP/SL levels can be toggled ON/OFF
Immediate re-entry in the opposite direction after exit (flips positions)
Stops trading for the session after a winning trade is hit
Max 5 trades per session
🛠️ Features:
21 EMA & VWAP visual overlays
Customizable session start/end time
TP/SL settings in points
Toggle for using or ignoring TP/SL
Auto-shutdown after first win (discipline enforcement)
Trade log reset at session close
Smart label displays “✅ WIN - No More Trades” when strategy locks in
Use this to master EMA momentum flips with clear logic, strict discipline, and no emotional overtrading. Part of the DSPLN Method — Do So Patiently Listening Now.
RSI + OBV + EMA + ADX FilterThis strategy combines multiple technical indicators to identify high-probability trade setups in trending markets:
🔹 RSI (Relative Strength Index)
Used to identify oversold (< 35) or overbought (> 70) conditions.
🔹 OBV (On-Balance Volume)
Confirms momentum direction through volume shifts.
🔹 EMA (Exponential Moving Average)
Filters trades to align only in the direction of the overall trend (optional).
🔹 ADX (Average Directional Index)
Filters out trades during low-volatility or sideways markets, only triggering when ADX exceeds a user-defined threshold.
🧠 Strategy Logic
Long Entry:
RSI < 35, OBV increasing, (optional: price above EMA), and ADX > threshold
Short Entry:
RSI > 70, OBV decreasing, (optional: price below EMA), and ADX > threshold
Plotting:
Green arrows for long signals
Red arrows for short signals
Optional debug plots (e.g. ADX pass as yellow circles)
⚙️ Parameters (User-Configurable)
RSI Length
EMA Length
ADX Length and Threshold
Enable/disable filters for RSI, OBV, EMA, and ADX
AboBassil Swing Predictor [ROC ADX mix Composite]This indicator—AboBassil Swing Predictor —is a comprehensive multi-factor momentum model designed to highlight high-probability swing setups.
📊 Core Logic: It combines short- and long-term Rate of Change (ROC), dual-layer ADX filtering, RSI, Chaikin Money Flow (CMF), volume confirmation, squeeze zone detection (via Bollinger Bands inside Keltner Channels), and inside bar breakout logic to create actionable entry conditions.
= Highlights:
- Green/purple/red background flags ROC crossover and squeeze zones
- Dynamic plots for ROC, ADX, and RSI to observe trend and signal alignment
- Entry signal arrows (bullish/bearish) based on strict composite conditions
- Real-time visual composite score to track strength and bias
- Clearly marked levels for RSI (30, 50, 70) and ADX threshold
= Best used as a decision-support tool for swing traders momentum setups. Fine-tuned to filter noisy signals and focus only when multiple forces align.
please send me if you suggest some tweak or a specific strategy improvements ,
RSI Divergence Indicator + TrendlinesThe RSI Divergence Indicator with Trendlines is a technical analysis tool that combines the Relative Strength Index (RSI) with price and RSI trendlines to identify potential trend reversals or continuations. It highlights bullish and bearish divergences by comparing the movement of price action against the RSI oscillator, and plots automatic trendlines for visual clarity.
Intermarket Correlation Oscillator (ICO)Intermarket Correlation Oscillator (ICO) - Description
The Intermarket Correlation Oscillator (ICO) is a custom indicator for TradingView that helps you analyze the relationship between the price movements of two financial instruments. It calculates the correlation between the chart’s primary symbol (e.g., the stock or asset you’re viewing) and a secondary symbol (e.g., SPY for the S&P 500). The indicator displays this correlation as an oscillator, which moves between -1 and +1, helping you visualize how closely the two assets move together over time.
This guide explains how the indicator works in simple steps, its settings, and how to interpret its output. It’s designed for educational purposes to assist you in understanding market relationships, not as trading advice.
What Does the Indicator Do?
Measures Correlation: The ICO calculates the correlation coefficient between the closing prices of two assets over a specified number of bars (lookback period).
A value near +1 means the assets move in the same direction.
A value near -1 means the assets move in opposite directions.
A value near 0 means little to no relationship.
Visualizes the Correlation: The correlation is plotted as a line (oscillator) in a separate panel below your chart.
Highlights Key Levels:
Overbought Level (default: +0.8): Indicates a strong positive correlation.
Oversold Level (default: -0.8): Indicates a strong negative correlation.
Midline (0): Represents no correlation.
Zones: Shaded areas highlight when the correlation is above the overbought level or below the oversold level.
Labels and Alerts: The indicator adds labels on the chart when the correlation crosses key levels and provides alert conditions for potential notifications.
How to Use the Indicator
Step 1: Add the Indicator to Your Chart
Open TradingView and load a chart for any symbol (e.g., AAPL, BTCUSD).
Click the Indicators button at the top.
Search for Intermarket Correlation Oscillator (ICO) (or the name you’ve given it).
Click to add it to your chart. It will appear in a separate panel below the price chart.
Step 2: Configure the Settings
When you add the indicator, you can customize its inputs:
Secondary Symbol: Choose the asset to compare with the chart’s symbol (default: SPY, the S&P 500 ETF). For example, enter “BTCUSD” to compare Bitcoin or “GLD” for gold.
Correlation Lookback Period: Set the number of bars to calculate correlation (default: 20). A higher number smooths the oscillator, while a lower number makes it more sensitive.
Overbought Level: Define the threshold for strong positive correlation (default: +0.8).
Oversold Level: Define the threshold for strong negative correlation (default: -0.8).
Show Midline: Check to display the zero line (default: enabled).
Show Overbought/Oversold Zones: Check to highlight zones above +0.8 or below -0.8 (default: enabled).
To adjust these, double-click the indicator’s name on the chart and modify the settings in the pop-up window.
Step 3: Understand the Output
Blue Line: The oscillator shows the correlation value, ranging from -1 to +1.
Red Dotted Line: Marks the overbought level (default: +0.8).
Green Dotted Line: Marks the oversold level (default: -0.8).
Gray Dashed Line: The midline at 0 (if enabled).
Shaded Areas: Red shading above +0.8 or green shading below -0.8 (if zones are enabled).
Labels:
“OB” (Overbought) appears when the oscillator crosses above the overbought level.
“OS” (Oversold) appears when the oscillator crosses below the oversold level.
Boundaries: Solid lines at +1 and -1 show the maximum and minimum correlation values.
Step 4: Set Up Alerts
You can create alerts for specific events:
Click the Alert button (bell icon) in TradingView.
Choose Intermarket Correlation Oscillator (ICO) as the condition.
Select from the following alert types:
Overbought Alert: Triggers when the oscillator crosses above the overbought level.
Oversold Alert: Triggers when the oscillator crosses below the oversold level.
Bullish Correlation: Triggers when the oscillator crosses above the midline (0).
Bearish Correlation: Triggers when the oscillator crosses below the midline (0).
Set your preferred notification method (e.g., email, pop-up).
Click Create to activate the alert.
How to Interpret the Indicator
The ICO helps you understand how two assets move relative to each other:
High Positive Correlation (near +1): The assets tend to move in the same direction. For example, if the oscillator is above +0.8 for AAPL vs. SPY, AAPL is closely following the S&P 500’s movements.
High Negative Correlation (near -1): The assets move in opposite directions. For example, if the oscillator is below -0.8 for USDJPY vs. GLD, when the dollar strengthens, gold may weaken.
No Correlation (near 0): The assets move independently, with no clear relationship.
The overbought and oversold levels highlight extreme correlation states, which may indicate potential shifts in the relationship between the assets. For example, an extremely high positive correlation might weaken over time.
Note: This indicator does not predict price movements or guarantee trading outcomes. Use it as a tool to study market relationships alongside other analysis methods.
Example Use Case
Suppose you’re analyzing Tesla (TSLA) and want to see how it correlates with the S&P 500 (SPY):
Set the chart to TSLA.
Add the ICO indicator and keep the secondary symbol as SPY.
Observe the oscillator:
If it’s above +0.8, TSLA is moving strongly with the S&P 500.
If it’s below -0.8, TSLA is moving opposite to the S&P 500.
If it’s near 0, TSLA’s movements are unrelated to the S&P 500.
Use labels and alerts to track when the correlation becomes unusually strong or weak.
Important Notes
Educational Tool: The ICO is designed to help you study the correlation between assets. It does not provide buy or sell signals or guarantee profits.
Customize for Your Needs: Adjust the lookback period, overbought/oversold levels, and secondary symbol to match your analysis style.
Combine with Other Tools: Use the ICO alongside other indicators or chart patterns for a broader market perspective.
Data Dependency: The indicator relies on price data for both symbols. Ensure the secondary symbol (e.g., SPY) has available data on your chart’s timeframe.
TradingView Compliance: This indicator follows TradingView’s rules by avoiding performance claims, financial advice, or misleading statements.
Troubleshooting
Indicator Not Showing: Ensure the secondary symbol is valid (e.g., “SPY” exists on your exchange) and has data for the selected timeframe.
Alerts Not Triggering: Verify that the alert conditions are set correctly and that your TradingView account supports alerts.
Oscillator Looks Flat: Try reducing the lookback period for more sensitivity or check if the two assets have sufficient price variation.
Overlapping FVG - [Fandesoft Trading Academy]🧠 Overview
This script plots Higher Timeframe Fair Value Gaps (FVGs) with full visibility and precise placement on lower timeframe charts. Each timeframe (30s–15m) has its own independent toggle, custom label, and box styling, giving traders unmatched control and clarity across multiple market structures.
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🎯 What It Does
✅ Identifies Fair Value Gaps using a 3-candle logic (candle 1 high vs candle 3 low, and vice versa).
✅ Plots HTF FVG boxes accurately aligned in LTF charts for clearer intraday decision making.
✅ Custom timeframes: 30s to 15m — individually toggleable.
✅ Set custom labels per timeframe for easier reference.
✅ Full visual customization:
Border color
Bullish/Bearish box opacity
Label font size and color
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✨ Why It’s Unique
🔁 Multi-timeframe plotting from as low as 30 seconds to 15 minutes — all at once.
🖼️ Boxes plotted with fixed pixel-perfect width even on lower timeframes.
🎨 All visual aspects are fully configurable from the UI: labels, colors, borders.
🧩 Modular input system: you can turn off individual timeframes without code edits.
🧠 Smart barstate.isconfirmed usage ensures no repainting and stable historical plotting.
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⚙️ How It Works
The script requests data for each selected timeframe using request.security.
For every confirmed HTF bar:
It checks for an FVG based on simple imbalance logic:
Bullish FVG: low >= high
Bearish FVG: low >= high
If a valid gap exists:
A box is drawn using box.new() between candle 1 and candle 3 with matching label and style.
Timeframe toggles ensure efficient performance (below the request.security limit of 40).
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📈 Use Cases
Scalpers & Intraday Traders: Use 30s–15m HTF levels for precise microstructure guidance.
ICT Traders: Visualize displacement and inefficiency zones aligned with higher timeframe context.
FVG Stacking: Add this layer on top of FVG confluences.
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🔐 This script is invite-only. Contact the author for access.
📩 Perfect for serious traders, algorithmic strategists looking to visualize multi-timeframe imbalances efficiently.
6 gün önce
Sürüm Notları
🧠 Overview
This script plots Higher Timeframe Fair Value Gaps (FVGs) with full visibility and precise placement on lower timeframe charts. Each timeframe (30s–15m) has its own independent toggle, custom label, and box styling, giving traders unmatched control and clarity across multiple market structures.
----------------------------------------------
🎯 What It Does
✅ Identifies Fair Value Gaps using a 3-candle logic (candle 1 high vs candle 3 low, and vice versa).
✅ Plots HTF FVG boxes accurately aligned in LTF charts for clearer intraday decision making.
✅ Custom timeframes: 30s to 15m — individually toggleable.
✅ Set custom labels per timeframe for easier reference.
✅ Full visual customization:
Border color
Bullish/Bearish box opacity
Label font size and color
----------------------------------------------
✨ Why It’s Unique
🔁 Multi-timeframe plotting from as low as 30 seconds to 15 minutes — all at once.
🖼️ Boxes plotted with fixed pixel-perfect width even on lower timeframes.
🎨 All visual aspects are fully configurable from the UI: labels, colors, borders.
🧩 Modular input system: you can turn off individual timeframes without code edits.
🧠 Smart barstate.isconfirmed usage ensures no repainting and stable historical plotting.
----------------------------------------------
⚙️ How It Works
The script requests data for each selected timeframe using request.security.
For every confirmed HTF bar:
It checks for an FVG based on simple imbalance logic:
Bullish FVG: low >= high
Bearish FVG: low >= high
If a valid gap exists:
A box is drawn using box.new() between candle 1 and candle 3 with matching label and style.
Timeframe toggles ensure efficient performance (below the request.security limit of 40).
----------------------------------------------
📈 Use Cases
Scalpers & Intraday Traders: Use 30s–15m HTF levels for precise microstructure guidance.
ICT Traders: Visualize displacement and inefficiency zones aligned with higher timeframe context.
FVG Stacking: Add this layer on top of FVG confluences.
----------------------------------------------
🔐 This script is invite-only. Contact the author for access.
📩 Perfect for serious traders, algorithmic strategists looking to visualize multi-timeframe imbalances efficiently.
Supertrend Strategy v.1.0 (Nikko)This is the well-known Supertrend indicator, adapted for use as a strategy and updated to be compatible with Pine Script v6.
While I am not the original author of this indicator, I was curious to assess its real-world performance. The Supertrend is widely promoted by trading influencers, and I assumed many traders rely on it in their decision-making.
My goal was to stress-test the Supertrend by converting it into a strategy, to evaluate whether it could be a reliable tool to follow.
After testing it across various timeframes and assets, I found that it generally delivers poor results in terms of profitable trades. It performs somewhat better when the number of trades is kept low, but once trade frequency increases, the strategy tends to lose significantly due to its low win rate. This is an important caveat for those considering its use—be cautious, especially in high-frequency setups.
The source code is open for anyone who wants to improve or investigate further. If you identify any optimizations or bugs, feel free to share them with the community so we can all benefit.
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How the Supertrend Indicator Works
The Supertrend indicator is a trend-following tool designed to identify whether the market is in a bullish or bearish phase. It's often used to signal potential entry and exit points for trades.
It is built on the Average True Range (ATR), a measure of volatility, and a user-defined multiplier. These inputs are used to calculate dynamic support and resistance bands:
When the price is above the Supertrend line, the trend is considered bullish.
When the price is below the Supertrend line, the trend is considered bearish.
These trend shifts can offer visual cues for trade direction, but as seen in strategy testing, the effectiveness may vary widely depending on market conditions and timeframes.
Adaptive Cycle Oscillator with EMADescription of the Adaptive Cycle Oscillator with EMA Pine Script
This Pine Script, titled "Adaptive Cycle Oscillator with EMA", is a custom technical indicator designed for TradingView to help traders analyze market cycles and identify potential buy or sell opportunities. It combines an Adaptive Cycle Oscillator (ACO) with multiple Exponential Moving Averages (EMAs), displayed as colorful, wavy lines, and includes features like buy/sell signals and divergence detection. Below is a beginner-friendly explanation of how the script works, adhering to TradingView's Script Publishing Rules.
What This Indicator Does
The Adaptive Cycle Oscillator with EMA helps you:
Visualize market cycles using an oscillator that adapts to price movements.
Track trends with seven EMAs of different lengths, plotted as a rainbow of wavy lines.
Identify potential buy or sell signals when the oscillator crosses predefined thresholds.
Spot divergences between the oscillator and price to anticipate reversals.
Use customizable settings to adjust the indicator to your trading style.
Note: This is a technical analysis tool and does not guarantee profits. Always combine it with other analysis methods and practice risk management.
Step-by-Step Explanation for New Users
1. Understanding the Indicator
Adaptive Cycle Oscillator (ACO): The ACO analyzes price data (based on high, low, and close prices, or HLC3) to detect market cycles. It smooths price movements to create an oscillator that swings between overbought and oversold levels.
EMAs: Seven EMAs of different lengths are applied to the ACO and scaled based on the market's dominant cycle. These EMAs are plotted as colorful, wavy lines to show trend direction.
Buy/Sell Signals: The script generates signals when the ACO crosses above or below user-defined thresholds, indicating potential entry or exit points.
Divergence Detection: The script identifies bullish or bearish divergences between the ACO and the fastest EMA, which may signal potential reversals.
Visual Style: The indicator uses a rainbow of seven colors (red, orange, yellow, green, blue, indigo, violet) for the EMAs, with wavy lines for a unique visual effect. Static levels (zero, overbought, oversold) are also wavy for consistency.
2. How to Add the Indicator to Your Chart
Open TradingView and load the chart of any asset (e.g., stock, forex, crypto).
Click on the Indicators button at the top of the chart.
Search for "Adaptive Cycle Oscillator with EMA" (or paste the script into TradingView’s Pine Editor if you have access to it).
Click to add the indicator to your chart. It will appear in a separate panel below the price chart.
3. Customizing the Indicator
The script offers several input options to tailor it to your needs:
Base Cycle Length (Default: 20): Sets the initial period for calculating the dominant cycle. Higher values make the indicator slower; lower values make it more sensitive.
Alpha Smoothing (Default: 0.07): Controls how much the ACO smooths price data. Smaller values produce smoother results.
Show Buy/Sell Signals (Default: True): Toggle to display green triangles (buy) and red triangles (sell) on the chart.
Threshold (Default: 0.0): Defines overbought (above threshold) and oversold (below threshold) levels. Adjust to widen or narrow signal zones.
EMA Base Length (Default: 10): Sets the starting length for the fastest EMA. Other EMAs are incrementally longer (12, 14, 16, etc.).
Divergence Lookback (Default: 14): Determines how far back the script looks to detect divergences.
To adjust these:
Right-click the indicator on your chart and select Settings.
Modify the inputs in the pop-up window.
Click OK to apply changes.
4. Reading the Indicator
Oscillator and EMAs: The ACO and seven EMAs are plotted in a separate panel. The EMAs (colored lines) move in a wavy pattern:
Red (fastest) to Violet (slowest) represent different response speeds.
When the faster EMAs (e.g., red, orange) are above slower ones (e.g., blue, violet), it suggests bullish momentum, and vice versa.
Zero Line: A gray wavy line at zero acts as a neutral level. The ACO above zero indicates bullish conditions; below zero indicates bearish conditions.
Overbought/Oversold Lines: Red (overbought) and green (oversold) wavy lines mark threshold levels. Extreme ACO values near these lines may suggest reversals.
Buy/Sell Signals:
Green Triangle (Bottom): Appears when the ACO crosses above the oversold threshold, suggesting a potential buy.
Red Triangle (Top): Appears when the ACO crosses below the overbought threshold, suggesting a potential sell.
Divergences:
Green Triangle (Bottom): Indicates a bullish divergence (price makes a lower low, but the EMA makes a higher low), hinting at a potential upward reversal.
Red Triangle (Top): Indicates a bearish divergence (price makes a higher high, but the EMA makes a lower high), hinting at a potential downward reversal.
5. Using Alerts
You can set alerts for key events:
Right-click the indicator and select Add Alert.
Choose a condition (e.g., "ACO Buy Signal", "Bullish Divergence").
Configure the alert settings (e.g., notify via email, app, or pop-up).
Click Create to activate the alert.
Available alert conditions:
ACO Buy Signal: When the ACO crosses above the oversold threshold.
ACO Sell Signal: When the ACO crosses below the overbought threshold.
Bullish Divergence: When a potential upward reversal is detected.
Bearish Divergence: When a potential downward reversal is detected.
6. Tips for Using the Indicator
Combine with Other Tools: Use the indicator alongside support/resistance levels, candlestick patterns, or other indicators (e.g., RSI, MACD) for confirmation.
Test on Different Timeframes: The indicator works on any timeframe (e.g., 1-minute, daily). Shorter timeframes may produce more signals but with more noise.
Practice Risk Management: Never rely solely on this indicator. Set stop-losses and position sizes to manage risk.
Backtest First: Use TradingView’s Strategy Tester (if you convert the script to a strategy) to evaluate performance on historical data.
Compliance with TradingView’s Script Publishing Rules
This description adheres to TradingView’s Script Publishing Rules (as outlined in the provided link):
No Performance Claims: The description avoids promising profits or specific results, emphasizing that the indicator is a tool for analysis.
Clear Instructions: It provides step-by-step guidance for adding, customizing, and using the indicator.
Risk Disclaimer: It notes that trading involves risks and the indicator should be used with other analysis methods.
No Misleading Terms: Terms like “buy” and “sell” are used to describe signals, not guaranteed actions.
Transparency: The description explains the indicator’s components (ACO, EMAs, signals, divergences) without exaggerating its capabilities.
No External Links: The description avoids linking to external resources or soliciting users.
Educational Tone: It focuses on educating users about the indicator’s functionality.
Limitations
Not a Standalone System: The indicator is not a complete trading strategy. It provides insights but requires additional analysis.
Lagging Nature: As with most oscillators and EMAs, signals may lag behind price movements, especially in fast markets.
False Signals: Signals and divergences may not always lead to successful trades, particularly in choppy markets.
Market Dependency: Performance varies across assets and market conditions (e.g., trending vs. ranging markets).
deltaMomentumVERSION = 1.4
2 MA where the average is taken of the high and low of the aformentioned MAs and a 144 period average is applied to this average. The MA average bouncing above or below the GAP indicates accumulation and once it (green line) crosses you will often see a release of stored momentum in the form of relatively large price movement.
On Balance Volume Momentum + Relative StrengthA combination of "On Balance Volume (OBV)", "Volume Oscillator" and Relative Strength indicators.
"OBV Momentum" is a trend momentum indicator, that can be used to identify strong trends and also trend changes based on volume.
High positive values indicate strong volume on the buy side, high negative values indicate strong volume on the sell side.
An increasing OBV momentum indicates a strengthening buy trend or a weakening sell trend,
decvreasing OBV Momentum indicates a strenghening sell trend or weakening buy trend.
OBV Momentum is calculated by comparing a short vs. a long moving average and plotting the difference in volume.
OBV Momentum metric is absolute volume.
The OBV Momentum values are normalized in the interval.
