Dual-Frame Momentum OscillatorDual-Frame Momentum Oscillator (DFMO)
This is not just another oscillator. This is a confluence engine, built for the discerning trader who reads the story of price action and needs an objective tool to confirm the climax.
The Dual-Frame Momentum Oscillator was designed to solve a specific problem: how to differentiate a genuine, sustainable breakout from an exhaustive liquidity grab. It provides a visual confirmation for high-probability reversal and scalp setups by measuring momentum across two distinct time frames simultaneously.
This tool is for the trader who understands that indicators should not dictate trades, but rather confirm a well-defined thesis based on market structure, volume, and liquidity.
The Core Concept: Context Meets Trigger
The DFMO fuses a slow, methodical Stochastic with a hyper-sensitive RSI to give you a complete picture of momentum.
The Context (Slow Stochastic %K - default 40,4,4): This acts as your long-term momentum gauge. It tells you if the underlying trend is healthy or nearing exhaustion. A high reading suggests the market is overextended and vulnerable, while a low reading suggests the opposite.
The Trigger (Fast RSI - default 3): This is your immediate impulse reader. It measures the velocity and intensity of the current price thrust, making it incredibly sensitive to exhaustive moves, spikes, and bounces.
By themselves, they are useful. Together, they are formidable.
The Confluence Engine: Your Visual Edge
The true power of the DFMO lies in its "Confluence Engine." The indicator's background highlights in real-time when both oscillators are in agreement, visually flagging moments of maximum opportunity.
Bearish Confluence Zone (Red): The background turns red only when the Stochastic is overbought AND the RSI is overbought. This is your signal that the broader trend is exhausted and the current buying impulse has reached a climax. It is the ideal confirmation for a short entry following a liquidity sweep above a key high.
Bullish Confluence Zone (Green): The background turns green only when the Stochastic is oversold AND the RSI is oversold. This signals that the downtrend is tired and the immediate selling pressure is exhaustive, providing high-probability confirmation for a long entry at a key support level.
When these zones appear, the indicator is telling you that both the context and the trigger are aligned. This removes ambiguity and allows for decisive, confident execution.
Practical Application: The Liquidity Sweep
Imagine you're stalking a short on a futures contract like MCL or MES. You've marked the high of the day (HOD) as a key resistance level where liquidity is resting. You see a sharp, vertical impulse move that breaks the HOD, clearing out the stops.
Is this a real breakout, or is it a manipulation move—a classic liquidity grab?
You glance down at the DFMO. The moment price swept the high, the background flashed red. That's your objective confirmation. The slow Stoch was already overbought, and the fast RSI spiking confirmed the exhaustive, terminal nature of that price thrust. You now have the confidence to enter your short scalp, knowing you are aligned with the probable direction of the market's next move.
This is how you move from "feeling" the market to systematically executing a high-probability edge. This is how you aspire for greatness.
Add the Dual-Frame Momentum Oscillator to your toolkit and transform your ability to time entries with surgical precision.
中心震盪指標
Fibo RSIThis is a customized Relative Strength Index (RSI) indicator designed to replicate TradingView’s default RSI while adding additional reference levels for deeper market analysis.
🔹 Features:
RSI length set to 8 by default (user adjustable).
Calculates RSI using the standard ta.rsi() function.
Plots the RSI line in a clean, separate panel.
Adds 7 key levels for analysis: 0, 20, 30, 50, 70, 80, 100.
Levels are drawn as thin, solid straight lines for a cleaner look (instead of default dashed).
🔹 Use cases:
Identify momentum shifts with enhanced precision.
Use intermediate levels (20, 30, 50, 70, 80) as potential support/resistance zones.
Ideal for traders who want a Fibonacci-like structure in RSI analysis.
Swing Oracle Stock 2.0- Gradient Enhanced# 🌈 Swing Oracle Pro - Advanced Gradient Trading Indicator
**Transform your technical analysis with stunning gradient visualizations that make market trends instantly recognizable.**
## 🚀 **What Makes This Indicator Special?**
The **Swing Oracle Pro** revolutionizes traditional technical analysis by combining advanced NDOS (Normalized Distance from Origin of Source) calculations with a sophisticated gradient color system. This isn't just another indicator—it's a complete visual trading experience that adapts colors based on market strength, making trend identification effortless and intuitive.
## 🎨 **10 Professional Gradient Themes**
Choose from carefully crafted color schemes designed for optimal visual clarity:
- **🌅 Sunset** - Warm oranges and purples for classic elegance
- **🌊 Ocean** - Cool blues and teals for calm analysis
- **🌲 Forest** - Natural greens and browns for organic feel
- **✨ Aurora** - Ethereal greens and magentas for mystique
- **⚡ Neon** - Vibrant electric colors for high-energy trading
- **🌌 Galaxy** - Deep purples and cosmic hues for night sessions
- **🔥 Fire** - Intense reds and golds for volatile markets
- **❄️ Ice** - Cool whites and blues for clear-headed decisions
- **🌈 Rainbow** - Full spectrum for comprehensive analysis
- **⚫ Monochrome** - Professional grays for focused trading
## 📊 **Core Features**
### **Advanced NDOS System**
- Normalized Distance from Origin of Source calculation with 231-period length
- Smoothed with customizable EMA for reduced noise
- Multi-timeframe confirmation with H1 filter option
- Dynamic gradient coloring based on oscillator position
### **Intelligent Visual Feedback**
- **Primary Gradient Line** - Main NDOS plot with dynamic color transitions
- **Gradient Fill Zones** - Beautiful color-coded areas for bullish, neutral, and bearish regions
- **Smart Transparency** - Colors adjust intensity based on market volatility
- **Dynamic Backgrounds** - Subtle gradient backgrounds that respond to market conditions
### **Enhanced EMA Projection System**
- 75/760 period EMA normalization with 50-period lookback
- Gradient-colored projection line for trend forecasting
- Toggleable display with advanced gradient controls
- Price tracking for precise level identification
### **Multi-Timeframe Analysis Table**
- Real-time trend analysis across 6 timeframes (1m, 3m, 5m, 15m, 1H, 4H)
- Gradient-colored cells showing trend strength
- Customizable table size and position
- Professional emoji indicators (🚀 UP, 📉 DOWN, ➡️ FLAT)
### **Signal System**
- **Gradient Buy Signals** - Triangle up arrows with intensity-based coloring
- **Gradient Sell Signals** - Triangle down arrows with strength indicators
- **Alert Conditions** - Built-in alerts for all signal types
- **7-Day Cycle Tracking** - Tuesday-to-Tuesday weekly cycle visualization
## ⚙️ **Customization Controls**
### **🎨 Gradient Controls**
- **Gradient Intensity** - Adjust color vibrancy (0.1-1.0)
- **Gradient Smoothing** - Control color transition smoothness (1-10 periods)
- **Dynamic Background** - Toggle animated background gradients
- **Advanced Gradients** - Enable/disable EMA projection and enhanced features
### **🛠️ Custom Color System**
- **Bullish Colors** - Define custom start/end colors for bull markets
- **Bearish Colors** - Set personalized bear market gradients
- **Full Theme Override** - Create completely custom color schemes
- **Real-time Preview** - See changes instantly on your chart
## 📈 **How to Use**
1. **Choose Your Theme** - Select from 10 professional gradient themes
2. **Configure Levels** - Adjust high/low levels (default 60/40) for your timeframe
3. **Set Smoothing** - Fine-tune gradient smoothing for your trading style
4. **Enable Features** - Toggle background gradients, candlestick coloring, and advanced EMA projection
5. **Monitor Signals** - Watch for gradient buy/sell arrows and multi-timeframe confirmations
## 🎯 **Trading Applications**
- **Swing Trading** - Perfect for identifying medium-term trend changes
- **Scalping** - Multi-timeframe table provides quick trend confirmation
- **Position Sizing** - Gradient intensity shows signal strength for risk management
- **Market Analysis** - Beautiful visualizations make complex data instantly understandable
- **Education** - Ideal for learning market dynamics through visual feedback
## ⚡ **Performance Optimized**
- **Smart Rendering** - Colors update only on significant changes
- **Efficient Calculations** - Optimized algorithms for smooth performance
- **Memory Management** - Minimal resource usage even with complex gradients
- **Real-time Updates** - Responsive to market changes without lag
## 🚨 **Alert System**
Built-in alert conditions notify you when:
- NDOS crosses above high level (Buy Signal)
- NDOS crosses below low level (Sell Signal)
- Multi-timeframe confirmations align
- Customizable alert messages with emoji indicators
## 🔧 **Technical Specifications**
- **PineScript Version**: v6 (Latest)
- **Overlay**: True (plots on main chart)
- **Calculations**: NDOS, EMA normalization, volatility-based transparency
- **Timeframes**: Compatible with all timeframes
- **Markets**: Stocks, Forex, Crypto, Commodities, Indices
## 💡 **Why Choose Swing Oracle Pro?**
This isn't just another technical indicator—it's a complete visual transformation of your trading experience. The gradient system provides instant visual feedback that traditional indicators simply can't match. Whether you're a beginner learning to read market trends or an experienced trader seeking clearer signals, the Swing Oracle Pro delivers professional-grade analysis with unprecedented visual clarity.
**Experience the future of technical analysis. Your charts will never look the same.**
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*⚠️ Disclaimer: This indicator is for educational and informational purposes only. Past performance does not guarantee future results. Always conduct your own research and consider risk management before making trading decisions.*
**🔔 Like this indicator? Please leave a comment and boost! Your feedback helps improve future updates.**
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**📝 Tags:** #GradientTrading #SwingTrading #NDOS #MultiTimeframe #TechnicalAnalysis #VisualTrading #TrendAnalysis #ColorCoded #ProfessionalCharts #TradingToo
High-and-Tight Impulse + Micro ConsolidationThis indicator detects a specific bullish continuation setup on daily charts:
- An impulse move (X% rise within N bars, mostly green candles)
- Immediately followed by a tight consolidation (small ranges, small bodies)
- Closes holding in the top zone of the impulse
On the chart, signals are plotted as orange dots above bars.
Labels show the last detected setup date, and a counter displays total matches in history.
Useful for backtesting "high-and-tight flag" type momentum patterns or any symbol.
Adjust inputs (impulse % threshold, bars, ATR ratios, top zone %) to make it stricter or looser.
Alerts are included when a new setup is detected.
This tool is not financial advice. For educational and research purposes only.
by fiyatherseydir
AA1 MACD 09.2025this is a learing project i want to share
the script is open for anyone
I combain some ema's mcad and more indicators to help find stocks in momentum
Trend-Strong Candle - 3 EMAs with Filters# Trend-Strong Candle - Professional Trading Indicator
## 📊 What It Does
Identifies high-probability entries by combining triple EMA trend analysis with strong candle detection. Only signals when all conditions align for maximum accuracy.
## 🎯 Core Features
- Triple EMA System: Fast (20) / Medium (50) / Slow (200) for trend confirmation
- Strong Candle Filter: ATR-based sizing ensures genuine momentum
- Advanced Filters: EMA close validation + trend stability checks
- Live Alerts: Instant notifications for real-time signals
- Session Filter: Trade only during active EU/US market hours
## ⚡ Quick Setup
Scalping (1-5min): Default settings + enable session filter
Day Trading (15-60min): Default settings work perfectly
Swing Trading (4H+): Increase ATR multiplier to 0.8-1.0
## 📈 Trading Rules
Long Signals: Green triangle below candle
- Strong bullish candle during confirmed uptrend
- All EMAs properly aligned (Fast > Medium > Slow)
Short Signals: Red triangle above candle
- Strong bearish candle during confirmed downtrend
- All EMAs properly aligned (Fast < Medium < Slow)
## ⚠️ Critical Success Factors
1. Always Verify the Trend Yourself
The indicator helps identify signals, but YOU must confirm the larger trend context. Check higher timeframes and overall market structure before entering.
2. Understand the "Big Players"
Strong candles in trend direction usually come from institutional money (banks, funds, algorithms). These create the momentum that retail traders can follow. The indicator catches these institutional moves.
3. Distance to Next Value Level
NEVER enter if price is too close to major resistance/support levels:
- Check distance to round numbers (1.1000, 1.1050, etc.)
- Ensure at least 20-30 pips room to next key level
- You need space for profit - tight levels = limited upside
4. Risk Management
- Stop Loss: 1-2 ATR from entry
- Take Profit: 2-3 ATR target (minimum 1:2 R/R)
- Position Size: Risk max 1-2% per trade
## 💡 Pro Tips
- Best Sessions: London open (8-12 UTC) and NY open (13-17 UTC)
- Avoid: Major news, low liquidity periods, choppy markets
- Multiple Timeframes: Confirm signals on higher timeframe
- Value Levels: Always check daily/weekly support/resistance before entering
## 🎯 Success Formula
Trend Confirmation + Strong Institutional Candle + Distance to Value Levels = High Probability Trade
*
Remember: The indicator finds the signals, but successful trading requires your analysis of trend context and value level positioning. Trade smart, not just frequent.
MACD Area on Chart w/ DivergenceMACD Area & Divergence Suite
This is an all-in-one MACD analysis tool that overlays key information directly onto your price chart, helping you visualize momentum and potential trend changes.
Instead of looking at a separate indicator pane, this script brings all the critical data to your main chart.
Features
MACD Histogram Area: The script calculates the cumulative value (the "area") of the MACD histogram for each cycle (from one signal line cross to the next).
Cycle Boxes: It draws a border around the price bars that correspond to each positive (green) and negative (red) MACD histogram cycle.
Area Labels: Displays the calculated area value in the center of each box.
MACD Zero-Line Cross: Automatically draws a vertical dashed line when the main MACD line (not the histogram) crosses the zero line, signaling a major momentum shift.
Full Divergence Detection: This is the core feature. The script automatically finds, draws, and labels both types of divergence:
Regular Divergence: Signals a potential trend reversal.
Hidden Divergence: Signals a potential trend continuation.
Advanced Filtering: Includes a powerful option to validate divergences, ensuring they do not cross the MACD zero line. This helps filter for higher-quality signals.
Highly Customizable: Every feature can be turned on or off in the settings, including a "Divergence Only" mode for a cleaner chart. All colors and transparency are fully adjustable.
Machine Learning Gaussian Mixture Model | AlphaNattMachine Learning Gaussian Mixture Model | AlphaNatt
A revolutionary oscillator that uses Gaussian Mixture Models (GMM) with unsupervised machine learning to identify market regimes and automatically adapt momentum calculations - bringing statistical pattern recognition techniques to trading.
"Markets don't follow a single distribution - they're a mixture of different regimes. This oscillator identifies which regime we're in and adapts accordingly."
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🤖 THE MACHINE LEARNING
Gaussian Mixture Models (GMM):
Unlike K-means clustering which assigns hard boundaries, GMM uses probabilistic clustering :
Models data as coming from multiple Gaussian distributions
Each market regime is a different Gaussian component
Provides probability of belonging to each regime
More sophisticated than simple clustering
Expectation-Maximization Algorithm:
The indicator continuously learns and adapts using the E-M algorithm:
E-step: Calculate probability of current market belonging to each regime
M-step: Update regime parameters based on new data
Continuous learning without repainting
Adapts to changing market conditions
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🎯 THREE MARKET REGIMES
The GMM identifies three distinct market states:
Regime 1 - Low Volatility:
Quiet, ranging markets
Uses RSI-based momentum calculation
Reduces false signals in choppy conditions
Background: Pink tint
Regime 2 - Normal Market:
Standard trending conditions
Uses Rate of Change momentum
Balanced sensitivity
Background: Gray tint
Regime 3 - High Volatility:
Strong trends or volatility events
Uses Z-score based momentum
Captures extreme moves
Background: Cyan tint
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💡 KEY INNOVATIONS
1. Probabilistic Regime Detection:
Instead of binary regime assignment, provides probabilities:
30% Regime 1, 60% Regime 2, 10% Regime 3
Smooth transitions between regimes
No sudden indicator jumps
2. Weighted Momentum Calculation:
Combines three different momentum formulas
Weights based on regime probabilities
Automatically adapts to market conditions
3. Confidence Indicator:
Shows how certain the model is (white line)
High confidence = strong regime identification
Low confidence = transitional market state
Line transparency changes with confidence
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⚙️ PARAMETER OPTIMIZATION
Training Period (50-500):
50-100: Quick adaptation to recent conditions
100: Balanced (default)
200-500: Stable regime identification
Number of Components (2-5):
2: Simple bull/bear regimes
3: Low/Normal/High volatility (default)
4-5: More granular regime detection
Learning Rate (0.1-1.0):
0.1-0.3: Slow, stable learning
0.3: Balanced (default)
0.5-1.0: Fast adaptation
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📊 TRADING STRATEGIES
Visual Signals:
Cyan gradient: Bullish momentum
Magenta gradient: Bearish momentum
Background color: Current regime
Confidence line: Model certainty
1. Regime-Based Trading:
Regime 1 (pink): Expect mean reversion
Regime 2 (gray): Standard trend following
Regime 3 (cyan): Strong momentum trades
2. Confidence-Filtered Signals:
Only trade when confidence > 70%
High confidence = clearer market state
Avoid transitions (low confidence)
3. Adaptive Position Sizing:
Regime 1: Smaller positions (choppy)
Regime 2: Normal positions
Regime 3: Larger positions (trending)
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🚀 ADVANTAGES OVER OTHER ML INDICATORS
vs K-Means Clustering:
Soft clustering (probabilities) vs hard boundaries
Captures uncertainty and transitions
More mathematically robust
vs KNN (K-Nearest Neighbors):
Unsupervised learning (no historical labels needed)
Continuous adaptation
Lower computational complexity
vs Neural Networks:
Interpretable (know what each regime means)
No overfitting issues
Works with limited data
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📈 PERFORMANCE CHARACTERISTICS
Best Market Conditions:
Markets with clear regime shifts
Volatile to trending transitions
Multi-timeframe analysis
Cryptocurrency markets (high regime variation)
Key Strengths:
Automatically adapts to market changes
No manual parameter adjustment needed
Smooth transitions between regimes
Probabilistic confidence measure
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🔬 TECHNICAL BACKGROUND
Gaussian Mixture Models are used extensively in:
Speech recognition (Google Assistant)
Computer vision (facial recognition)
Astronomy (galaxy classification)
Genomics (gene expression analysis)
Finance (risk modeling at investment banks)
The E-M algorithm was developed at Stanford in 1977 and is one of the most important algorithms in unsupervised machine learning.
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💡 PRO TIPS
Watch regime transitions: Best opportunities often occur when regimes change
Combine with volume: High volume + regime change = strong signal
Use confidence filter: Avoid low confidence periods
Multi-timeframe: Compare regimes across timeframes
Adjust position size: Scale based on identified regime
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⚠️ IMPORTANT NOTES
Machine learning adapts but doesn't predict the future
Best used with other confirmation indicators
Allow time for model to learn (100+ bars)
Not financial advice - educational purposes
Backtest thoroughly on your instruments
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🏆 CONCLUSION
The GMM Momentum Oscillator brings institutional-grade machine learning to retail trading. By identifying market regimes probabilistically and adapting momentum calculations accordingly, it provides:
Automatic adaptation to market conditions
Clear regime identification with confidence levels
Smooth, professional signal generation
True unsupervised machine learning
This isn't just another indicator with "ML" in the name - it's a genuine implementation of Gaussian Mixture Models with the Expectation-Maximization algorithm, the same technology used in:
Google's speech recognition
Tesla's computer vision
NASA's data analysis
Wall Street risk models
"Let the machine learn the market regimes. Trade with statistical confidence."
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Developed by AlphaNatt | Machine Learning Trading Systems
Version: 1.0
Algorithm: Gaussian Mixture Model with E-M
Classification: Unsupervised Learning Oscillator
Not financial advice. Always DYOR.
Stockbee Reversal BullishCustom indicator for identifying stocks that meet the Stockbee's Reversal Bullish criteria. This can be used as a standalone indicator or use it to screen for stocks in Pine Screener.
AI-Weighted RSI (Zeiierman)█ Overview
AI-Weighted RSI (Zeiierman) is an adaptive oscillator that enhances classic RSI by applying a correlation-weighted prediction layer. Instead of looking only at RSI values directly, this indicator continuously evaluates how other price- and volume-based features (returns, volatility, volume shifts) correlate with RSI, and then weights them accordingly to project the next RSI state.
The result is a smoother, forward-looking RSI framework that adapts to market conditions in real time.
By leveraging feature correlation instead of static formulas, AI-Weighted RSI behaves like a lightweight learning model, adjusting its emphasis depending on which features are most aligned with RSI behavior during the current regime.
█ How It Works
⚪ Feature Extraction
Each bar, the script computes features: log returns, RSI itself, ATR% (volatility), volume, and volume log-change.
⚪ Correlation Screening
Over a rolling learning window, it measures the correlation of each feature against RSI. The strongest relationships are ranked and selected.
⚪ Adaptive Weighting
Features are standardized (z-scored), then combined using their signed correlations as weights, building a rolling, adaptive prediction of RSI.
⚪ Prediction to RSI Weight
The predicted RSI is mapped back into a “weight” scale (±2 by default). Above 0 = bullish bias, below 0 = bearish bias, with color-graded fills to visualize overbought/oversold pressure.
⚪ Signal Line
A smoothing option (signal length) overlays a moving average of the AI-Weighted RSI for clearer trend confirmation.
█ Why AI-Weighted RSI
⚪ Adaptive to Market Regime
Because the model re-evaluates correlations continuously, it naturally shifts which features dominate, sometimes volatility explains RSI best, sometimes volume, sometimes returns.
⚪ Forward-Looking Bias
Instead of simply reflecting RSI, the model provides a projection, helping anticipate shifts in momentum before RSI itself flips.
█ How to Use
⚪ Directional Bias
Read the RSI relative to 0. Above = bullish momentum bias, below = bearish.
⚪ Overbought / Oversold Zones
Shaded fills beyond +0.5 or -0.5 highlight extremes where RSI pressure often exhausts.
⚪ Divergences
When price makes new highs/lows but AI-Weighted RSI fails to confirm, it often signals weakening momentum.
█ Settings
RSI Length: Lookback for the core RSI calculation.
Signal Length: Smoothing applied to the AI-Weighted RSI output.
Learning Window: Bars used for correlation learning and z-scoring.
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
عكفة الماكد المتقدمة - أبو فارس ©// 🔒 Advanced MACD Curve © 2025
// 💡 Idea & Creativity: Engineer Abu Elias
// 🛠️ Development & Implementation: Abu Fares
// 📜 All intellectual rights reserved - Copying, modifying, or redistributing is not permitted
// 🚫 Any attempt to tamper with this code or violate intellectual property rights is legally prohibited
// 📧 For inquiries and licensing: Please contact the developer, Abu Fares
عكفة الماكد المتقدمة - أبو فارس ©// 🔒 عكفة الماكد المتقدمة © 2025
// 💡 فكرة وإبداع: المهندس أبو الياس
// 🛠️ تطوير وتنفيذ: أبو فارس
// 📜 جميع الحقوق الفكرية محفوظة - لا يُسمح بالنسخ أو التعديل أو إعادة التوزيع
// 🚫 أي محاولة للعبث بهذا الكود أو انتهاك الحقوق الفكرية مرفوضة قانونياً
// 📧 للاستفسارات والتراخيص: يرجى التواصل مع المطور أبو فارس
// 🔒 Advanced MACD Curve © 2025
// 💡 Idea & Creativity: Engineer Abu Elias
// 🛠️ Development & Implementation: Abu Fares
// 📜 All intellectual rights reserved - Copying, modifying, or redistributing is not permitted
// 🚫 Any attempt to tamper with this code or violate intellectual property rights is legally prohibited
// 📧 For inquiries and licensing: Please contact the developer, Abu Fares
Hurst Momentum Oscillator | AlphaNattHurst Momentum Oscillator | AlphaNatt
An adaptive oscillator that combines the Hurst Exponent - which identifies whether markets are trending or mean-reverting - with momentum analysis to create signals that automatically adjust to market regime.
"The Hurst Exponent reveals a hidden truth: markets aren't always trending. This oscillator knows when to ride momentum and when to fade it."
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📐 THE MATHEMATICS
Hurst Exponent (H):
Measures the long-term memory of time series:
H > 0.5: Trending (persistent) behavior
H = 0.5: Random walk
H < 0.5: Mean-reverting behavior
Originally developed for analyzing Nile river flooding patterns, now used in:
Fractal market analysis
Network traffic prediction
Climate modeling
Financial markets
The Innovation:
This oscillator multiplies momentum by the Hurst coefficient:
When trending (H > 0.5): Momentum is amplified
When mean-reverting (H < 0.5): Momentum is reduced
Result: Adaptive signals based on market regime
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💎 KEY ADVANTAGES
Regime Adaptive: Automatically adjusts to trending vs ranging markets
False Signal Reduction: Reduces momentum signals in mean-reverting markets
Trend Amplification: Stronger signals when trends are persistent
Mathematical Edge: Based on fractal dimension analysis
No Repainting: All calculations on historical data
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📊 TRADING SIGNALS
Visual Interpretation:
Cyan zones: Bullish momentum in trending market
Magenta zones: Bearish momentum or mean reversion
Background tint: Blue = trending, Pink = mean-reverting
Gradient intensity: Signal strength
Trading Strategies:
1. Trend Following:
Trade momentum signals when background is blue (trending)
2. Mean Reversion:
Fade extreme readings when background is pink
3. Regime Transition:
Watch for background color changes as early warning
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🎯 OPTIMAL USAGE
Best Conditions:
Strong trending markets (crypto bull runs)
Clear ranging markets (forex sessions)
Regime transitions
Multi-timeframe analysis
Market Applications:
Crypto: Excellent for identifying trend persistence
Forex: Detects when pairs are ranging
Stocks: Identifies momentum stocks
Commodities: Catches persistent trends
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Developed by AlphaNatt | Fractal Market Analysis
Version: 1.0
Classification: Adaptive Regime Oscillator
Not financial advice. Always DYOR.
Ark FCI OscillatorFinancial Conditions Index Oscillator
This indicator tracks week-over-week changes in the National Financial Conditions Index (NFCI), providing a dynamic view of evolving financial conditions in the United States.
Overview
The National Financial Conditions Index (NFCI) is a comprehensive weekly composite index published by the Federal Reserve Bank of Chicago. It measures financial conditions across U.S. money markets, debt and equity markets, and the traditional and shadow banking systems.
Interpretation
Positive values indicate improving financial conditions
Negative values signal deteriorating financial conditions
Risk assets demonstrate particular sensitivity to changes in financial conditions, making this oscillator valuable for market timing and risk assessment.
Alternative Data Source
Users can modify the source to FRED:NFCIRISK to focus specifically on risk dynamics. The NFCIRISK subindex isolates volatility and funding risk measures within the financial sector, capturing market volatility indicators and liquidity shortage probabilities while excluding broader credit and leverage conditions.
Fisher Volume Transform | AlphaNattFisher Volume Transform | AlphaNatt
A powerful oscillator that applies the Fisher Transform - converting price into a Gaussian normal distribution - while incorporating volume weighting to identify high-probability reversal points with institutional participation.
"The Fisher Transform reveals what statistics professors have known for decades: when you transform market data into a normal distribution, turning points become crystal clear."
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🎲 THE MATHEMATICS
Fisher Transform Formula:
The Fisher Transform converts any bounded dataset into a Gaussian distribution:
y = 0.5 × ln((1 + x) / (1 - x))
Where x is normalized price (-1 to 1 range)
Why This Matters:
Market extremes become statistically identifiable
Turning points are amplified and clarified
Removes the skew from price distributions
Creates nearly instantaneous signals at reversals
Volume Integration:
Unlike standard Fisher Transform, this version weights price by relative volume:
High volume moves get more weight
Low volume moves get filtered out
Identifies institutional participation
Reduces false signals from retail chop
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💎 KEY ADVANTAGES
Statistical Edge: Transforms price into normal distribution where extremes are mathematically defined
Volume Confirmation: Only signals with volume support
Early Reversal Detection: Fisher Transform amplifies turning points
Clean Signals: Gaussian distribution reduces noise
No Lag: Mathematical transformation, not averaging
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⚙️ SETTINGS OPTIMIZATION
Fisher Period (5-30):
5-9: Very sensitive, many signals
10: Default - balanced sensitivity
15-20: Moderate smoothing
25-30: Major reversals only
Volume Weight (0.1-1.0):
0.1-0.3: Minimal volume influence
0.5-0.7: Balanced price/volume
0.7: Default - strong volume weight
0.8-1.0: Volume dominant
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📊 TRADING SIGNALS
Primary Signals:
Zero Cross Up: Bullish momentum shift
Zero Cross Down: Bearish momentum shift
Signal Line Cross: Early reversal warning
Extreme Readings (±75): Potential reversal zones
Visual Interpretation:
Cyan zones: Bullish momentum
Magenta zones: Bearish momentum
Gradient intensity: Strength of move
Histogram: Raw momentum power
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🎯 OPTIMAL USAGE
Best Market Conditions:
Range-bound markets (reversals clear)
High volume periods
Major support/resistance levels
Divergence hunting
Trading Strategies:
1. Extreme Reversal:
Enter when oscillator exceeds ±75 and reverses
2. Zero Line Momentum:
Trade crosses of zero line with volume confirmation
3. Signal Line Strategy:
Early entry on signal line crosses
4. Divergence Trading:
Price makes new high/low but Fisher doesn't
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Developed by AlphaNatt | Quantitative Trading Systems
Version: 1.0
Classification: Statistical Transform Oscillator
Not financial advice. Always DYOR.
Argentum Flag [AGP]Ver.2.1Technical Description of the "Argentum Flag " Indicator
The "Argentum Flag " is a multifaceted trading indicator designed to provide a comprehensive view of market dynamics by combining elements of trend, volatility, momentum, and volume analysis. Its architecture is built on the synergy of multiple technical tools, allowing traders to make more informed decisions by reducing market noise and focusing on high-probability inflection points.
1. Dynamic AGP Bands (EMA 36 and Percentage Levels)
The core of the indicator is a 36-period Exponential Moving Average (EMA), which acts as the price's baseline and center of gravity. From this EMA, the script plots dynamic bands at predefined percentages (Base, Prime, and Vortex).
Logic: These bands are not static like Bollinger Bands; they expand and contract in response to the underlying EMA. This methodology helps identify relative volatility and trend strength. When the price trades within these bands, it's considered to be in a range or a controlled consolidation.
Benefit to the Trader: They provide a quick visual of dynamic support and resistance levels. A price movement beyond the Vortex band can signal an extreme market imbalance, suggesting potential trend exhaustion or a high-energy breakout.
2. Breakout Signals (Signals)
The indicator generates plotshape signals when the price stays outside the volatility bands for a specific number of consecutive bars (2 for the Prime band and 3 for the Vortex band).
Logic: These signals act as an overextension detection system. The underlying principle is that once the price breaks and holds outside these zones, the probability of a pullback or a reversal increases significantly. The lastSignalBarIndex logic prevents signal overload and ensures a cooling-off period, eliminating noise from consecutive signals.
Benefit to the Trader: It provides clear visual alerts for taking profits or looking for potential reversals. A trader can use the Vortex band exit signal (⌾) as confirmation to close a long or short position, while the Prime band signal (⍲) can indicate a potential pullback for a trend-following entry.
3. Bar Volume Analysis (Barcolor)
The script introduces a sophisticated bar coloring system that classifies volume activity relative to a 50-period Simple Moving Average (SMA).
Logic: The coloring is based not only on whether the bar is bullish or bearish but also on the magnitude of the volume. For instance, extreme volume (more than 3.5 times the average volume) is colored blue, indicating institutional participation or a high-impact event. High (1.8x) or average (0.6x - 1.7x) volume is distinguished with other colors, providing a visual map of the underlying strength behind each price move.
Benefit to the Trader: It allows for a quick identification of bars with the highest market conviction. A bearish price bar with extreme volume (extreme_volume_bearish) might signal significant liquidation, while a bullish bar with extreme volume (extreme_volume_bullish) could suggest strong accumulation.
4. Real-Time Monitoring Tables (EMA and RSI)
The indicator includes two data tables in the bottom corner of the screen, acting as a dashboard for multi-timeframe analysis.
EMA Table (Fibonacci): This table shows the current values of a series of Fibonacci-based EMAs (13, 21, 34, etc.). The background color of each cell indicates whether the current price is above (white) or below (blue) the corresponding EMA.
Logic: This table allows traders to assess the trend bias across different timeframes, from short to long-term. An alignment of multiple EMAs in the same direction (e.g., all white) confirms a strong trend.
Benefit to the Trader: It provides a quick check for trend confirmation. For example, before opening a long position on a 5-minute chart, a trader can verify if the overall trend on higher timeframes (e.g., 4h or 1D) is also bullish.
RSI Table (Multi-Timeframe): This table shows the Relative Strength Index (RSI) values across multiple timeframes, from 1 minute to monthly. The cell lights up orange if the RSI is in the overbought zone (> 77) or white if it's in the oversold zone (< 23).
Logic: The use of request.security enables the fetching of data from other timeframes on the current bar. This is a crucial component for multi-timeframe divergence analysis.
Benefit to the Trader: It helps identify overbought or oversold conditions across different trading horizons, which is vital for spotting large-scale reversals. If the 1D and 4h RSIs are overbought, a long position on a lower timeframe could be high-risk.
Competitive Advantages for Traders
The "Argentum Flag " is not just a simple indicator; it's a consolidated technical analysis suite that saves time and effort. Instead of overlaying multiple indicators, a trader gets all the relevant information in a single view. The contextualized volume analysis and volatility-based signals are invaluable tools for filtering out low-quality entries and exits. Finally, the real-time monitoring tables provide a multi-timeframe perspective that is fundamental for validating market direction and managing risk.
In trading, the convergence of multiple technical data points is key to increasing the probability of success. This indicator provides precisely that convergence, enabling both novice and experienced traders to make more precise and strategic decisions.
Risk Warning (Disclaimer)
Trading in financial markets carries a significant risk of loss and is not suitable for all investors. The information and signals provided by this indicator are for educational and analysis purposes only and should not be construed as financial advice. The past performance of any trading system or methodology is not necessarily indicative of future results. The user assumes all responsibility for their own trading decisions and any resulting losses or gains.
Momentum+This script provides a colored histogram of recent price action with the price derivative method for finding momentum.
buy sell ultra systemWhat it is
EMA-POC Momentum System Ultra combines a proven trend stack (EMA 20/50/238), a price-of-control layer (POC via Bar-POC or VWAP alternative), and a momentum trigger (RSI) to surface higher-quality entries only when multiple, independent conditions align. This is not a cosmetic mashup; each component gates the others.
How components work together
Trend (EMA 20/50/238): Defines short/medium/long bias and filters counter-trend signals.
POC (Bar-POC or Alt-POC/VWAP): Locates the most-traded/weighted price area; a neutral band around POC helps avoid chop.
Control background: Above POC → buyers likely in control; below → sellers.
Momentum (RSI): Entry arrows print only when RSI confirms with trend and price location vs POC; optional “cross 50” requirement reduces noise.
Optional HTF trend: Confluence with a higher-timeframe EMA stack for stricter filtering.
Why it’s original/useful
Signals require confluence of (1) EMA trend stack, (2) POC location and neutral-zone filtering, (3) momentum confirmation, (4) optional slope and distance-to-POC checks, and (5) optional HTF trend. This reduces false positives compared with using any layer in isolation.
How to use
Markets/TFs: Built for XAUUSD (Gold) and US30. Works 1m–1h for intraday; 2h–4h for swing.
Entries:
Long: EMA stack bullish, price above POC, not in neutral band, RSI condition true → “Buy” arrow.
Short: Opposite conditions → “Sell” arrow.
Stops/Targets (suggested):
Initial stop beyond POC/neutral band or recent swing.
First target around 1R; trail with EMA20/50 or structure breaks.
Settings to tune:
POC Mode: Bar-POC (highest-volume bar’s close over lookback) or Alt-POC (VWAP).
Neutral Band %: 0.10–0.35 typical intraday.
Min distance from POC: 0.10–0.50% helps avoid low-RR entries right at POC.
RSI: Choose “cross 50” for stricter triggers or simple >/< 50 for more signals.
HTF trend: Turn on for extra confluence.
Alerts:
Buy Signal and Sell Signal (separate), or one Combined Buy/Sell alert.
Set to “Once per bar close” if you want only confirmed arrows.
Repainting / limitations
Shapes can move until bar close (standard Pine behavior) when using intrabar conditions; final confirmation at close. No system guarantees profitability—forward test and adapt to your market/instrument.
Clean chart
The published chart contains only this script so outputs are easy to identify.
Versions / updates
Use Publish → Update for minor changes; do not create new publications for small tweaks. If you fork to preserve older behavior, explain why and how your fork differs.
Changelog
v1.1 – Tuning for Gold/US30, neutral-band & distance filters, optional HTF trend, combined alert.
v1.0 – Initial public release (EMA stack + POC modes + RSI + alerts).
License & credits
Open-source for learning and improvement. Please credit on forks and explain modifications in your description.
Momentum Index [BigBeluga]The Momentum Index is an innovative indicator designed to measure the momentum of price action by analyzing the distribution of positive and negative momentum values over a defined period. By incorporating delta-based calculations and smoothing techniques, it provides traders with a clear and actionable representation of market momentum dynamics.
🔵 Key Features:
Delta-Based Momentum Analysis:
Calculates the momentum of price by comparing its current state to its value from a defined number of bars back.
Inside a loop, it evaluates whether momentum values are above or below zero, producing a delta value that reflects the net momentum direction and intensity.
Double EMA Smoothing:
Smooths the raw delta-based momentum values with a double EMA filter, reducing noise and providing a clearer trend signal.
tmi(len) =>
sum = 0.0
sum1 = 0.0
above = 0.0
below = 0.0
src_ = src - src
for i = 0 to len
sum := sum + (src_ > nz(src_ ) ? 1 : -1)
sum1 := sum1 + (sum > 0 ? 1 : -1)
sum1 := emaEma(sum1, 10)
for i = 1 to len
above := above + (sum1 > 0 ? 1 : 0)
below := below + (sum1 > 0 ? 0 : 1)
Directional Momentum Signals:
Generates momentum shift signals and displays them on both the oscillator and the main chart:
- △ Aqua Triangles: Represent upward momentum shifts.
- ▽ Red Triangles: Represent downward momentum shifts.
Dynamic Gradient Display:
Highlights momentum zones with gradient fills:
- Aqua shades for positive momentum (above zero).
- Red shades for negative momentum (below zero).
Dashboard Display:
A dashboard summarizing the count of momentum values above and below zero for the defined period (Sentiment Length e.g. 100), helping traders assess market sentiment at a glance.
🔵 How It Works:
The indicator takes price momentum as its source and evaluates the number of momentum values above and below zero within a defined period.
The delta calculation aggregates this information, providing a net representation of the prevailing market momentum.
A double EMA filter is applied to the delta values, smoothing the momentum line and enhancing signal clarity.
Momentum shifts are highlighted with visual signals on the oscillator and price chart, while the gradient display provides a visual representation of intensity.
🔵 Use Cases:
Momentum Tracking: Identify whether market momentum is predominantly bullish or bearish.
Signal Confirmation: Use chart-based signals to confirm potential trend reversals or continuation.
Analyze Market Strength: Leverage the dashboard to quickly assess the distribution of momentum over the chosen period.
Overbought/Oversold Conditions: Utilize gradient zones to detect areas of momentum extremes and possible price exhaustion.
Momentum Index offers a refined approach to analyzing momentum dynamics, combining delta-based calculations with smoothing techniques and intuitive visuals, making it an essential tool for traders looking to anticipate market movements effectively.
Logit Transform -EasyNeuro-Logit Transform
This script implements a novel indicator inspired by the Fisher Transform, replacing its core arctanh-based mapping with the logit transform. It is designed to highlight extreme values in bounded inputs from a probabilistic and statistical perspective.
Background: Fisher Transform
The Fisher Transform, introduced by John Ehlers , is a statistical technique that maps a bounded variable x (between a and b) to a variable approximately following a Gaussian distribution. The standard form for a normalized input y (between -1 and 1) is F(y) = 0.5 * ln((1 + y)/(1 - y)) = arctanh(y).
This transformation has the following properties:
Linearization of extremes:
Small deviations around the mean are smooth, while movements near the boundaries are sharply amplified.
Gaussian approximation:
After transformation, the variable approximates a normal distribution, enabling analytical techniques that assume normality.
Probabilistic interpretation:
The Fisher Transform can be linked to likelihood ratio tests, where the transform emphasizes deviations from median or expected values in a statistically meaningful way.
In technical analysis, this allows traders to detect turning points or extreme market conditions more clearly than raw oscillators alone.
Logit Transform as a Generalization
The logit function is defined for p between 0 and 1 as logit(p) = ln(p / (1 - p)).
Key properties of the logit transform:
Maps probabilities in (0, 1) to the entire real line, similar to the Fisher Transform.
Emphasizes values near 0 and 1, providing sharp differentiation of extreme states.
Directly interpretable in terms of odds and likelihood ratios: logit(p) = ln(odds).
From a statistical viewpoint, the logit transform corresponds to the canonical link function in binomial generalized linear models (GLMs). This provides a natural interpretation of the transformed variable as the logarithm of the likelihood ratio between success and failure states, giving a rigorous probabilistic framework for extreme value detection.
Theoretical Advantages
Distributional linearization:
For inputs that can be interpreted as probabilities, the logit transform creates a variable approximately linear in log-odds, similar to Fisher’s goal of Gaussianization but with a probabilistic foundation.
Extreme sensitivity:
By amplifying small differences near 0 or 1, it allows for sharper detection of market extremes or overbought/oversold conditions.
Statistical interpretability:
Provides a link to statistical hypothesis testing via likelihood ratios, enabling integration with probabilistic models or risk metrics.
Applications in Technical Analysis
Oscillator enhancement:
Apply to RSI, Stochastic Oscillators, or other bounded indicators to accentuate extreme values with a well-defined probabilistic interpretation.
Comparative study:
Use alongside the Fisher Transform to analyze the effect of different nonlinear mappings on market signals, helping to uncover subtle nonlinearity in price behavior.
Probabilistic risk assessment:
Transforming input series into log-odds allows incorporation into statistical risk models or volatility estimation frameworks.
Practical Considerations
The logit diverges near 0 and 1, requiring careful scaling or smoothing to avoid numerical instability. As with the Fisher Transform, this indicator is not a standalone trading signal and should be combined with complementary technical or statistical indicators.
In summary, the Logit Transform builds upon the Fisher Transform’s theoretical foundation while introducing a probabilistically rigorous mapping. By connecting extreme-value detection to odds ratios and likelihood principles, it provides traders and analysts with a mathematically grounded tool for examining market dynamics.
