Osciladores
AO3 BETA 3.9.0 (v9p)// 📦 VERSION UPGRADE NOTE
// Indicator:
// Version: BETA 3.9.0 (v9p)
// Previous: BETA 3.4.2 (v6)
//────────────────────────────────────────────
// 🔸 Upgrade Summary:
// • Upgraded to Pine Script v6 (backward compatible).
// • Improved trend filter logic:
// – H1/H4 Uptrend = AO > U1
// – AO ≤ U1 ⇒ not uptrend
// – **NEW:** When AO crosses back above U1 (while AO > 0) ⇒ uptrend resumes.
// – Vice versa for downtrend.
// • Removed Entry Option 1; Option 2 → new Option 1; Option 3 → new Option 2.
// • Optimized internal constants & default values.
// • Added hidden system parameters (RISK_CAP, MIN_BARS, MAX_SPREAD, etc.).
// • Exposed only key inputs (Length, UseFilter, ATR Length) for cleaner UI.
// • Organized inputs into groups with tooltips for usability.
// • Improved performance via var-caching and reduced redundant calculations.
// • Simplified dev structure for modular updates.
//────────────────────────────────────────────
// 🧩 Notes:
// This build focuses on end-user stability and simplified interface.
// Developer-only parameters are now locked (not user-editable).
TalaJooy V1.31 𓅂💎 استراتژی معاملاتی TalaJooy V1.31 𓅂
TalaJooy (طلاجوی) یک چارچوب معاملاتی حرفه‌ای و کامل برای TradingView است که برای حذف حدس و گمان، احساسات و تصمیم‌گیری‌های هیجانی از فرآیند معاملات طراحی شده است.
این محصول یک «اندیکاتور سیگنال‌دهی» ساده نیست؛ بلکه یک استراتژی (Strategy) کامل است که چهار وظیفه کلیدی را به صورت خودکار انجام می‌دهد:
تحلیل بازار (بر اساس یک موتور امتیازدهی کمی)
صدور سیگنال (ورود و خروج شفاف)
مدیریت ریسک پویا (محاسبه خودکار حد ضرر)
مدیریت حجم پوزیشن (محاسبه خودکار حجم بر اساس ریسک)
هدف «طلاجوی» تبدیل معامله‌گری شهودی به یک فرآیند مکانیکی، مبتنی بر داده و مدیریت ریسک است.
⚙️ قابلیت‌های کلیدی (آنچه دریافت می‌کنید)
این استراتژی مجهز به مجموعه‌ای از ابزارهای حرفه‌ای است که مستقیماً روی چارت شما اجرا می‌شوند:
🎯 ۱. سیگنال‌های ورود و خروج شفاف
فلش‌های واضح خرید (▲) و فروش (▼) که نقاط دقیق ورود بر اساس منطق استراتژی را مشخص می‌کنند. این سیستم تنها زمانی سیگنال صادر می‌کند که فیلترهای روند، همسویی لازم را تایید کنند.
🛡️ ۲. مدیریت ریسک پویای ATR
بزرگترین چالش معامله‌گران، تعیین حد ضرر (SL) مناسب است. این استراتژی حد ضرر را به صورت خودکار و پویا بر اساس نوسانات واقعی بازار (با استفاده از ATR) محاسبه می‌کند.
نتیجه: در بازارهای پرنوسان، استاپ شما برای جلوگیری از استاپ‌هانت شدن، فاصله ایمن‌تری می‌گیرد و در بازارهای آرام، بهینه‌تر و نزدیک‌تر تنظیم می‌شود.
💰 ۳. محاسبه خودکار حجم پوزیشن
دیگر نیازی به «ماشین حساب پوزیشن» ندارید. استراتژی به صورت اتوماتیک، حجم دقیق هر معامله را بر اساس درصد ریسک ثابتی که شما از کل سرمایه‌تان تعیین می‌کنید، محاسبه می‌نماید. این ویژگی، مدیریت سرمایه حرفه‌ای را در تمام معاملات شما تضمین می‌کند.
🎨 ۴. نواحی بصری سود و زیان (TP/SL)
هنگامی که یک معامله باز است، این ابزار به صورت زنده، نواحی حد سود (سبز) و حد ضرر (قرمز) را مشابه ابزار پوزیشن خود تریدینگ ویو، مستقیماً روی چارت برای شما رسم می‌کند.
📈 ۵. پنل آمار عملکرد پیشرفته
یک جدول آماری جامع که تمام معیارهای کلیدی عملکرد شما را به صورت زنده نمایش می‌دهد:
سود و زیان خالص (دلاری و درصدی)
ضریب سود (Profit Factor)
نرخ موفقیت (Win Rate)
تعداد معاملات سودده / زیان‌ده
حداکثر افت سرمایه (Max Drawdown)
و موارد دیگر...
🚦 ۶. آیکون‌های بازخورد معامله
با آیکون‌های هوشمند، فوراً کیفیت معاملات بسته شده خود را ارزیابی کنید:
😎🚀 (سود ویژه و قابل توجه)
💰 (سود عادی)
🙈 (زیان)
📈 چگونه از این ابزار استفاده کنید؟
«طلاجوی» یک 'ماشین چاپ پول' جادویی نیست، بلکه یک ابزار تست و اجرای حرفه‌ای است.
۱. بک‌تست و بهینه‌سازی (Backtesting)
مهم‌ترین قدرت این اسکریپت، قابلیت Strategy بودن آن است. شما می‌توانید این استراتژی را روی هر جفت‌ارز و تایم فریمی که معامله می‌کنید (طلا، کریپتو، جفت‌ارزها و...) بک‌تست بگیرید تا آمار عملکرد آن را مشاهده کنید.
۲. تنظیم پارامترها
از طریق منوی تنظیمات، پارامترهای کلیدی مانند درصد ریسک، نسبت ریسک به ریوارد (R:R)، و فیلترهای زمانی را مطابق با سبک معاملاتی و دارایی مورد نظر خود بهینه‌سازی کنید.
۳. اجرای سیستماتیک
پس از یافتن تنظیمات بهینه در بک‌تست، در معاملات زنده به سیگنال‌ها پایبند بمانید و اجازه دهید منطق مکانیکی، معاملات شما را مدیریت کند.
⚠️ سلب مسئولیت مهم (مطابق با قوانین TradingView)
این اسکریپت صرفاً یک ابزار تحلیلی و معاملاتی است و نباید به عنوان سیگنال مالی یا توصیه‌ای برای خرید و فروش تلقی شود. تمام معاملات دارای ریسک هستند و نتایج گذشته تضمین‌کننده عملکرد آینده نمی‌باشد.
لطفاً قبل از استفاده از این استراتژی در حساب واقعی، آن را به طور کامل در حالت دمو یا بک‌تست ارزیابی کنید. مسئولیت تمامی سودها و زیان‌ها بر عهده خود معامله‌گر است.
💎 TalaJooy V1.31 𓅂 Trading Strategy
TalaJooy (meaning "Gold Seeker") is a complete, professional trading framework for TradingView, designed to remove guesswork, emotion, and impulsive decisions from your trading process.
This is not a simple signal indicator; it is a complete Strategy script that automates four key tasks:
Market Analysis (Based on a quantitative scoring engine)
Signal Generation (Clear entries and exits)
Dynamic Risk Management (Automated Stop Loss calculation)
Position Sizing (Automated trade sizing based on risk)
The goal of "TalaJooy" is to transform intuitive trading into a mechanical, data-driven, and risk-managed process.
⚙️ Key Features (What You Get)
This strategy comes equipped with a suite of professional tools that run directly on your chart:
🎯 1. Clear Entry & Exit Signals
Receive unambiguous Buy (▲) and Sell (▼) arrows identifying precise entry points based on the strategy's logic. The system only generates signals when its trend-confirmation filters are aligned.
🛡️ 2. Dynamic ATR Risk Management
A trader's biggest challenge is setting a proper Stop Loss (SL). This strategy calculates your SL automatically and dynamically based on real-time market volatility (using ATR).
The Benefit: In volatile markets, your stop is placed at a safer distance to avoid being "stopped out" by noise. In calm markets, it's set tighter and more efficiently.
💰 3. Automated Position Sizing
Stop using external "position size calculators." The strategy automatically calculates the exact trade size for every position based on a fixed risk percentage of your total equity (which you define). This enforces professional money management on every trade.
🎨 4. Visual Profit & Loss (TP/SL) Zones
While a trade is active, this tool plots live, visual zones for your Take Profit (green) and Stop Loss (red) targets, similar to TradingView's native "Long/Short Position" tool.
📈 5. Advanced Performance Stats Panel
A comprehensive statistics table displays all your key performance metrics in real-time:
Net Profit (% and $)
Profit Factor
Win Rate
Win / Loss Trade Count
Max Drawdown
And more...
🚦 6. Smart Trade Feedback Icons
Instantly review the quality of your closed trades with intelligent emoji feedback:
😎🚀 (Exceptional Profit)
💰 (Standard Profit)
🙈 (Loss)
📈 How to Use This Tool
"TalaJooy" is not a "magic money machine"; it is a professional-grade tool for testing and execution.
1. Backtesting & Optimization
The most powerful feature of this script is its Strategy component. You can backtest it on any asset or timeframe you trade (Gold, Crypto, Forex, etc.) to see its historical performance data.
2. Parameter Tuning
Use the settings menu to optimize key parameters—such as Risk Percentage, Risk:Reward Ratio, and core filter settings—to match your personal trading style and preferred assets.
3. Systematic Execution
After identifying optimal settings via backtesting, adhere to the signals in your live trading and let the mechanical logic manage your trades.
⚠️ Important Disclaimer (TradingView Compliant)
This script is provided for educational and analytical purposes only. It is not financial advice or a recommendation to buy or sell any asset. All trading involves substantial risk. Past performance is not indicative of future results.
Please thoroughly evaluate this strategy via backtesting or paper trading before deploying it with real funds. The user assumes full responsibility for all profits and losses incurred.
Kingdom SMCThis indicator combines Smart Money concept, chanlun, and multiple divergence technical analysis to construct a visual market analysis system.
byquan GP - SRSI Channel🔍 What Is It?
The GP – SRSI Channel is a momentum-based oscillator that measures the relative strength of price movements across multiple timeframes using the Stochastic RSI (SRSI) method.
Instead of using a single RSI line, this indicator analyzes four price inputs and four timeframes to create a dynamic channel that reflects the true market momentum — helping traders identify overbought and oversold zones with higher accuracy.
⚙️ How It Works
The indicator combines multiple layers of analysis to produce a smooth and reliable momentum channel.
1. Multi-Source RSI Calculation
It computes RSI and Stochastic RSI values for four different price sources:
Open
High
Low
Close
Each source generates its own SRSI value:
dsopen, dshigh, dslow, and dsclose
From these, it extracts:
starraymin: the lowest (most oversold) SRSI value
starraymax: the highest (most overbought) SRSI value
This forms a momentum range based on all price inputs.
2. Multi-Timeframe (MTF) Integration
To strengthen signal reliability, it repeats this SRSI analysis across four higher timeframes (configurable by user):
Parameter Default Value Meaning
Time 1 180 minutes 3-hour chart
Time 2 360 minutes 6-hour chart
Time 3 720 minutes 12-hour chart
Time 4 1D Daily chart
Each timeframe produces its own set of minimum, maximum, and close SRSI values.
These are then combined and normalized to a 0–100 scale.
3. Normalization and Channel Plot
The combined results create three main lines:
Min Line (Green–Red gradient) → represents oversold strength
Max Line (Green–Red gradient) → represents overbought strength
Close Line (White) → represents average SRSI value
The area between the Min and Max lines is filled with a color gradient to form the SRSI Channel, visually showing momentum strength and range.
4. Signal & Alerts
Two alert levels are defined:
Alert Min Level → Default = 5 (oversold)
Alert Max Level → Default = 95 (overbought)
When:
oranmin ≤ Alert Min Level → Market is in an oversold state (potential reversal up).
oranmax ≥ Alert Max Level → Market is in an overbought state (potential reversal down).
When either of these thresholds is crossed, the indicator triggers:
A white square marker on the chart.
A custom alert with the message:
“SRSI Channel reached alert threshold (oranmax ≥ MaxLevel or oranmin ≤ MinLevel)”
🧭 How to Use It
🪄 Step 1 — Add to Chart
Copy the code into a new Pine Script in TradingView.
Click Add to chart.
You’ll see three lines and a colored channel between them.
⚙️ Step 2 — Adjust Inputs
Core SRSI Settings
Setting Description
K, D Smoothing factors for Stochastic RSI.
RSI Length Number of bars for RSI calculation.
S Length Period used for %K in Stochastic RSI.
Alert Min/Max Level Defines oversold/overbought zones.
Multi-Timeframe Settings
Change Time 1 to Time 4 to suit your trading style:
Shorter timeframes → faster but more noise.
Longer timeframes → smoother, more reliable momentum.
📈 Step 3 — Interpret the Chart
Indicator Element Meaning
🟩 Lower Boundary (Min) Lowest SRSI reading → momentum weakness / possible rebound area
🟥 Upper Boundary (Max) Highest SRSI reading → strong momentum / possible exhaustion
⚪ Middle Line (Close) Average of all SRSI readings → overall momentum strength
🌈 Channel Fill Visualizes balance between overbought and oversold levels
When the channel widens → market volatility and strength increase.
When it narrows → consolidation or low-momentum phase.
🔔 Step 4 — Alerts
You can create alerts using:
Condition: SRSI Extreme
Message: SRSI Channel reached alert threshold
Use this to receive notifications when the market hits extreme momentum levels (great for reversal traders).
💡 Trading Tips
✅ Combine with Supertrend, MACD, or Moving Averages for confirmation.
✅ Look for SRSI extremes aligning with price support/resistance for stronger reversal entries.
✅ Use different timeframe combinations (e.g., 1H–4H–12H–1D) depending on your trading style.
✅ Treat it as a momentum filter — not a direct buy/sell signal tool.
⚖️ Summary
The GP – SRSI Channel is a sophisticated multi-timeframe momentum indicator that helps traders visualize market strength and identify overbought or oversold conditions with exceptional clarity.
Features:
4 price sources × 4 timeframes = deep momentum insight
Dynamic, color-coded SRSI channel
Built-in alert system for extreme conditions
Clean and intuitive visual design
Best suited for:
Swing and position traders
Traders who use RSI/Stoch indicators
Those seeking to confirm entries with multi-timeframe momentum data
🎯 Understand the market’s true momentum — before it moves.
JackFinance: Multiple EMA IndicatorMultiple EMA Indicator - Usage Instructions
Overview
Technical indicator displaying four exponential moving averages (EMA21, EMA52, EMA120, EMA200) for trend analysis across different timeframes.
Default Settings
EMA 21: Blue (short-term)
EMA 52: Green (medium-term)
EMA 120: Yellow (long-term)
EMA 200: Red (very long-term)
Key Features
Real-time EMA values displayed in table
Background color indicates trend vs EMA200
Customizable periods via input settings
Trading Applications
Identify trend direction using EMA alignment
Use EMA crossovers for entry/exit signals
Monitor price position relative to EMAs for support/resistance
Parameters
All EMA periods can be adjusted in indicator settings to match your trading strategy.
Notes
This is a technical analysis tool only. Combine with other indicators and risk management practices.
XonTrades Exit Flow | by Bu-RashidThis indicator detects potential institutional exit points and reversal zones using a powerful confluence model combining:
Volume spike analysis (institutional activity)
CVD trend flips (smart money flow reversal)
Price–CVD divergence (hidden accumulation/distribution)
Liquidity sweep detection (stop-run exhaustion)
When these elements align, the indicator highlights possible Exit Flow zones, signaling where smart capital may be closing or reversing positions.
It’s optimized for XAU/USD (Gold) and NAS100 (Nasdaq) on 5-minute and 15-minute charts, with customizable strictness for traders who prefer early or confirmed signals.
Recommended use:
Apply as a confirmation layer alongside your main strategy to identify exhaustion points and institutional exits before trend reversals.
— Developed and engineered by Bu-Rashid (XonTrades1UAE)
Multi-Resolution RSI with Machine LearningMulti-Resolution RSI
Developed by imaclone.x.
Last Updated: August 21st 2025
A single indicator that fuses my ML-RSI.ai pipeline with a classic multi-timeframe RSI. One script, dual-resolution oscillators if desired, plus a machine-learning similarity engine and modular signal-processing layers.
What it does
* Primary RSI augmented with KNN similarity engine (K, lookback, weighting). Feature embeddings include RSI magnitude, RSI momentum, volatility surface, regression slope, and price momentum vectors.
* Adaptive smoothing stack: Kalman filter recursion, Double EMA cascades, or ALMA convolution.
* Multi-resolution control for the primary oscillator timeframe.
* Optional *second* RSI projected from any timeframe for hierarchical confluence.
* Advanced visuals: upper/lower thresholds, midline, background regime highlighting, crossovers, and B/S event labels.
* Color architectures: None, Trend-Following (50-line bifurcation), or Impulse (band-breach). Optional bar tinting for full-chart context.
Inputs (groups)
* Timeframe Settings: primary + secondary RSI TF/lengths.
* Levels & Visuals: thresholds, highlights, cross events, B/S markers.
* RSI Base: smoothing toggle, MA class, ALMA sigma.
* KNN Machine Learning: enable, K neighbors, historical window, feature dimensionality, ML weighting.
* Advanced Filtering: method + intensity.
* Coloring: None, Trend-Following, Impulse.
Signals
* B flag when ML-RSI crosses upward through the lower threshold.
* S flag when ML-RSI crosses downward through the upper threshold.
* Secondary RSI = higher-timeframe confirmation, not standalone trigger.
Usage notes
* Raise ML weight + feature dimensionality for deeper similarity recognition; lower them for classic oscillator behavior.
* Kalman recursion delivers adaptive, low-lag smoothing; Double EMA and ALMA yield stronger dampening.
* Typical config: intraday primary RSI + higher-TF secondary RSI for regime anchoring.
Changelog
* v6 merge: Unified CM-style MTF RSI framework with my KNN-enhanced kernel and filter stack. One composite indicator replaces multiple scripts.
Credits
* MTF band logic inspired by earlier open-source frameworks.
* ML kernel and implementation by imaclone.x.
Disclaimer
For research and algorithmic experimentation only. No signals guaranteed.
And please kindly, for the love of God, DYOFR.
Prime Market Profile [xontrades1uae]indicator designed for high-precision intraday and scalping analysis.
It dynamically maps market structure, value areas (VAH/VAL), and point of control (POC), providing a clear visual view of where liquidity, balance, and breakout levels form throughout the session.
Features:
Real-time TPO construction for active sessions.
Automatic or custom tick calibration for gold, indices, or forex.
Highlighted POC, Value Area, and Initial Balance Range.
Smart visual clustering to detect congestion, breakout zones, and key volume nodes.
Compatible with short timeframes (1m–15m) for scalpers and day traders.
Signature:
Developed & customized by Bu-Rashid | xontrades1uae
“Precision. Liquidity. Control.” 💹
Sri-Minicharts 4 in one (CCI/Williams%/RTI/ADX)Sri – Mini Charts 4 in 1 (CCI / Williams %R / RTI / ADX) 📊
This all-in-one mini-chart indicator provides compact, visual representations of four key technical indicators in a single panel, allowing traders to quickly assess momentum, trend strength, and overbought/oversold conditions without cluttering the main chart.
Included Mini-Charts:
Williams %R Mini-Chart – Shows short-term momentum with a smoothed EMA overlay and reference zero line for quick visual signals.
ADX Mini-Chart – Displays trend strength with +DI / -DI lines, threshold levels, and optional color coding.
Relative Trend Index (RTI) Mini-Chart – Highlights dynamic trend direction and strength, with optional EMA smoothing and mini-chart display.
CCI Mini-Chart – Compact CCI plot with long EMA overlay, showing overbought/oversold levels and zero line for rapid trend recognition.
Key Features:
Fully customizable timeframes for each mini-chart.
Adjustable bars, offsets, and vertical placement for optimal layout on any chart.
Color-coded lines for positive/negative values, EMA trends, and threshold markers.
Sensitivity settings for each indicator to fine-tune scale and responsiveness.
Lightweight and non-intrusive, designed for traders who want fast multi-indicator insights in a single panel.
Recommended Use:
Identify momentum shifts, trend strength, and overbought/oversold conditions quickly.
Use in combination with main chart analysis for multi-timeframe and multi-indicator decision-making.
Ideal for swing traders, day traders, and technical analysts seeking compact, actionable visualization.
Adaptive MACD PROAdaptive MACD PRO is a next-generation momentum system built for traders who demand precision, adaptability, and clarity.
It merges two independent layers into one unified engine:
Adaptive MACD Core - detects structural momentum changes through dynamic normalization.
Phase Momentum Core - confirms acceleration and directional strength using phase-based movement detection.
How it Works Visually
When applied to any chart, the user instantly sees a clear, information-rich setup:
MACD & Signal Lines: dynamically colored lines that reflect real-time momentum direction (green/uptrend, red/downtrend).
Histogram Bars: adaptive columns showing the strength and acceleration of the trend.
Deeper colors = stronger movement.
Fading tones = loss of momentum.
Buy & Sell Dots:
Green dots appear when the system identifies a momentum reversal from oversold conditions.
Red dots appear when momentum peaks and reverses downward.
These dots are plotted at fixed levels for clean visual structure — ideal for quick scanning.
AutoCalib Cross Dots (Cyan & Fuchsia):
These appear exactly when the live MACD_z line crosses its adaptive calibration boundary.
Cyan indicates an adaptive bullish trigger.
Fuchsia indicates an adaptive bearish trigger.
Their transparency adjusts automatically based on the intensity of the cross — stronger crosses = brighter dots.
HUD Panel (optional):
Displays live calibration levels, current MACD_z value, and overall system state.
The HUD can be positioned at the top, bottom, or relative to the MACD curve, depending on user preference.
User Customization
Adaptive MACD PRO includes a full control layer that allows the user to tune the indicator to any market or timeframe:
Timeframe Override → analyze MACD on a higher or lower timeframe than the chart.
Auto Calibration → toggle between SAFE or AGGRESSIVE mode, adjust smoothness and window length.
Volatility Gate → control how the system reacts to quiet vs. explosive markets.
Bar Coloring → color bars based on MACD, Phase Momentum, or both (Merged Mode).
HUD Position & Anchor → move the on-chart display for better visibility.
All parameters can be adjusted in real-time, giving full control without affecting the closed adaptive engine underneath.
Practical Use
The indicator adapts to all assets and timeframes - from crypto scalping to equities and forex swing trading.
Users can focus on cross dots and histogram dynamics to identify clean momentum transitions, or combine it with existing systems for confirmation.
Adaptive MACD PRO is designed not just to show direction, but to evolve with the market’s rhythm - automatically learning volatility, tempo, and acceleration patterns over time.
Disclosure
This indicator is published as closed-source to protect its proprietary adaptive-fusion algorithm.
All operational behavior is fully described here in compliance with TradingView’s publication policies.
© 2025 Geokat83 | Proprietary Adaptive System
Sri - ADX Custom Time FrameTitle: Sri - ADX Custom Time Frame
Short Title: Sri-ADX
Overlay: No
Description:
The Sri - ADX Custom TF indicator allows traders to visualize the Average Directional Index (ADX) along with DI+ and DI- lines on a custom timeframe of their choice. This tool is ideal for trend strength analysis and directional movement assessment across multiple timeframes.
Key Features:
Custom Timeframe: Select any timeframe (e.g., 1, 3, 5, 15, 30, 60 minutes, 4H, Daily, Weekly, Monthly) for ADX calculation.
ADX & DI Calculation: Provides standard ADX with optional extra smoothing for DI and ADX for improved signal clarity.
Sensitivity Control: Adjustable ADX Sensitivity to fine-tune responsiveness to market movements.
Dynamic Threshold: Base threshold line dynamically scales with ADX sensitivity for better trend visualization.
Color Customization: Toggle DI+ and DI- colors with adjustable transparency (color reduction) to match your chart style.
Trend Insight: DI+ above DI- indicates bullish dominance; DI- above DI+ indicates bearish dominance.
Inputs Overview:
Custom Timeframe (tf) – Choose the timeframe to analyze.
ADX Length (len) – Period for ADX calculation.
Base Threshold (th) – Reference level for trend strength.
ADX Sensitivity (adxSensitivity) – Multiplier for ADX responsiveness.
Extra Smoothing (smoothDI, smoothADX) – Optional smoothing for DI and ADX to reduce noise.
Color Settings (enableColor, colorReduction, diPlusSel, diMinusSel) – Customize colors and transparency of DI+ and DI- plots.
Usage:
Identify trend strength and direction in your chosen timeframe.
Use DI+ and DI- crossover as potential signals for trend changes.
Combine with other technical tools for multi-timeframe trend analysis and trade confirmation.
Advanced Multi-Timeframe Momentum Matrix📊 Advanced Multi-Timeframe Momentum Matrix (AMTMM)
🎯 What Makes This Indicator Original
AMTMM is a sophisticated momentum analysis system that combines four distinct timeframes into a single weighted composite score using institutional-grade quantitative methods. Unlike traditional single-timeframe stochastic or RSI indicators, AMTMM employs:
Multi-Timeframe Weighted Composite Scoring - Aggregates momentum from Short (35%), Medium (30%), Long (20%), and Macro (15%) timeframes into one coherent signal, similar to how institutional traders analyze market structure across multiple horizons simultaneously.
Volatility-Adaptive Thresholds - Dynamically adjusts overbought/oversold levels based on ATR-derived volatility regimes, preventing premature signals during range expansion and contraction. The thresholds expand during high volatility and contract during calm periods, unlike static 70/30 levels.
Volume-Weighted Momentum Calculation - Optionally weights momentum signals by volume flow, giving higher significance to price moves accompanied by institutional volume, filtering out low-conviction noise.
Integrated Market Regime Detection - Uses ADX-style directional movement analysis combined with volatility range expansion to classify markets as Trending, Ranging, or Neutral, automatically filtering signals to match current market structure.
Statistical Normalization via Percentrank - Instead of raw stochastic values (0-100 bounded by recent highs/lows), AMTMM uses percentile ranking over extended periods, providing statistically consistent readings regardless of volatility regime.
📈 What It Does
AMTMM provides traders with:
Unified Momentum Score (0-100): A single composite line representing the confluence of multiple timeframe momentums
Automatic Regime Classification: Visual background coloring showing whether markets are trending (trade momentum) or ranging (avoid or fade)
High-Probability Signal Alerts: Buy/sell signals filtered by momentum strength and regime appropriateness
Divergence Detection: Automated identification of price-momentum divergences indicating potential reversals
Quality Scoring: Real-time signal quality assessment (0-100%) helping traders prioritize setups
Live Dashboard: Displays current momentum, strength, regime, signal quality, and divergence status
🔬 How It Works - Underlying Methodology
1. Multi-Timeframe Momentum Calculation
The indicator calculates normalized momentum independently for four configurable timeframes:
Short-Term (default: 1x base period): Captures intraday/scalping moves
Medium-Term (default: 3x base period): Identifies swing trading opportunities
Long-Term (default: 7x base period): Tracks position trading trends
Macro (default: 14x base period): Monitors institutional positioning
Calculation Process:
Applies stochastic calculation to close vs high/low over period × base_period
Optionally weights by volume ratio (current volume / average volume) to detect institutional flow
Smooths using selectable MA type (SMA/EMA/WMA/VWMA/HMA)
Normalizes via percentile ranking over 2× the calculation period for statistical consistency
Combines all four timeframes using fixed institutional weights: 35%-30%-20%-15%
2. Adaptive Threshold System
Traditional oscillators use static overbought/oversold levels (70/30), which fail during volatility shifts.
AMTMM's Adaptive Method:
Calculates ATR(14) and compares to ATR(50) SMA to determine volatility regime
Computes volatility ratio = current_ATR / average_ATR
Adjusts thresholds dynamically: adjusted_level = base_level + (volatility_ratio - 1) × 15
Bounds adjustments between 10-90 to prevent extreme outliers
Result: Thresholds expand in choppy markets, contract in calm trends
3. Market Regime Filter
Uses directional movement analysis to classify market structure:
Calculation:
Computes positive/negative directional movement (DM+ and DM-)
Calculates directional indicators (DI+ and DI-) via exponential smoothing
Derives directional index (DX) measuring trend strength
Smooths DX into ADX-equivalent value
Combines with ATR range expansion/contraction
Scores regime: Positive = Trending, Negative = Ranging
Signal Application:
Suppresses momentum signals during ranging conditions (yellow background)
Allows momentum signals during trending conditions (blue background)
Prevents whipsaw trades in sideways markets
4. Divergence Detection Algorithm
Identifies price-momentum discrepancies using pivot analysis:
Bullish Divergence:
Detects when price forms a lower low
But momentum forms a higher low
Indicates weakening selling pressure, potential reversal up
Bearish Divergence:
Detects when price forms a higher high
But momentum forms a lower high
Indicates weakening buying pressure, potential reversal down
Uses configurable lookback pivot detection (default: 5 bars left/right)
5. Signal Quality Scoring
Each signal receives a 0-100% quality score combining:
Momentum Strength: Rate of change of composite momentum (percentile ranked over 50 bars)
Regime Score: Absolute value of trending/ranging classification
Combined Score: (Strength + |Regime|) / 2
Only signals exceeding the threshold (default: 30%) generate alerts, filtering out low-conviction setups.
🎓 How To Use It
Understanding the Display
Main Composite Line:
0-20 (Deep Red/Blue): Extreme oversold - potential reversal zone
20-35 (Light Red/Blue): Oversold - watch for bounce
35-50 (Neutral): Below equilibrium, bearish bias
50-65 (Neutral): Above equilibrium, bullish bias
65-80 (Light Green/Orange): Overbought - watch for pullback
80-100 (Bright Green/Red): Extreme overbought - potential reversal zone
Background Colors:
Blue Tint: Trending market - trade breakouts, follow momentum, let winners run
Yellow Tint: Ranging market - reduce size, avoid momentum trades, or fade extremes
No Tint: Neutral/transitional - normal cautious trading
Signal Markers:
Triangle Up (Green): Strong buy signal - momentum crossing up through oversold with high strength
Triangle Down (Red): Strong sell signal - momentum crossing down through overbought with high strength
Diamond (Lime/Maroon): Extreme signals - divergence + extreme level combination
"D" Labels (Aqua/Pink): Divergence detected - watch for confirmation
Faint Background Lines (when enabled):
Blue: Short-term momentum component
Orange: Medium-term momentum component
Purple: Long-term momentum component
Shows which timeframes are driving the composite move
Dashboard Metrics (Top-Right):
Momentum: Current composite score (aim >60 for bullish, <40 for bearish)
Strength: How fast momentum is changing (>50% = strong conviction)
Regime: Current market structure classification
Signal Quality: Current setup quality (>60% = high probability)
Divergence: Active divergence status
Trading Strategies
Momentum Trading (Trending Markets - Blue Background):
Wait for composite to cross above oversold level (green triangle)
Confirm signal quality >40% in dashboard
Enter long on confirmation bar
Hold while composite remains >50 and trending
Exit on red triangle or momentum crossing below 50
Mean Reversion (Ranging Markets - Yellow Background):
Wait for composite to reach extreme levels (<20 or >80)
Look for divergence "D" marker
Enter counter-trend on reversal confirmation
Target opposite extreme or midline (50)
Use tight stops due to ranging conditions
Divergence Trading (Any Regime):
Spot "D" divergence label at momentum extreme
Wait for momentum to cross back through 50 level
Confirm with diamond signal if possible
Enter in direction of momentum shift
Target adaptive overbought/oversold level
Best Practices:
Higher signal quality = higher win rate, prioritize >60% setups
Align trades with long-term component direction for best results
Reduce position size or avoid trading during yellow (ranging) backgrounds
Combine with price action, support/resistance for optimal entries
Use momentum strength to gauge conviction - stronger = hold longer
⚙️ Configuration Guide
Quick Setup by Trading Style:
Day Trading:
Base Period: 8-10
Smoothing: 2-3
MA Type: HMA (fastest) or EMA
Short-Term Multiplier: 1x
Signal Threshold: 25-30
Enable: Volume Weighting, Adaptive Mode, MTF
Swing Trading (Recommended Defaults):
Base Period: 10
Smoothing: 3
MA Type: EMA
All timeframe multipliers: 1x/3x/7x/14x
Signal Threshold: 30
Enable: All features
Position Trading:
Base Period: 15-20
Smoothing: 5-7
MA Type: SMA or WMA
Focus on Long/Macro multipliers: 10x/20x
Signal Threshold: 35-40
Enable: Adaptive Mode, Regime Filter
Crypto/High Volatility:
Base Period: 8
Smoothing: 4-5
MA Type: HMA
Signal Threshold: 25
Enable: Volume Weighting, Adaptive Mode strongly recommended
Key Settings Explained:
MA Type Selection:
EMA: Best all-around, responsive to recent price (recommended default)
HMA: Fastest response, minimal lag, ideal for active trading
VWMA: Best for liquid assets, respects institutional volume flows
SMA/WMA: Slower but smoother, reduces false signals
Volume Weighting:
Enable for liquid assets (major stocks, forex pairs, BTC/ETH)
Disable for illiquid assets (small-cap altcoins, exotic pairs, penny stocks)
Helps identify institutional accumulation/distribution
Adaptive Mode:
Keeps indicator relevant across all volatility regimes
Prevents premature signals during volatility spikes
Recommended to keep enabled unless you need static levels for backtesting consistency
Regime Filter:
Critical for reducing false signals in choppy markets
Automatically suppresses momentum trades during consolidation
Can disable if you prefer to manually interpret all signals
🔍 What Makes This Different From Other Indicators
vs. Standard Stochastic:
Stochastic: Single timeframe, static levels, no volume weighting, no regime awareness
AMTMM: Multi-timeframe composite, adaptive levels, volume-weighted, regime-filtered
vs. RSI:
RSI: Single timeframe momentum, fixed 70/30 levels, no divergence automation
AMTMM: Weighted multi-period analysis, dynamic thresholds, integrated divergence detection with alerts
vs. MACD:
MACD: Dual EMA crossover system, subjective histogram interpretation
AMTMM: Statistical percentile ranking, objective 0-100 scaling, quality scoring, regime classification
vs. Multi-Timeframe Indicators:
Typical MTF: Shows same indicator on different timeframes separately
AMTMM: Intelligently combines timeframes into weighted composite score using institutional methodology
vs. Regime Filters:
Standalone filters: Require separate indicator interpretation
AMTMM: Integrated regime detection that automatically adjusts strategy signals
🎨 Visualization Options
4 Color Schemes:
Professional: Subtle greens/reds, optimal for extended screen time
High Contrast: Vivid colors, maximum visibility in bright environments
Institutional: Blue/orange palette, professional presentation-ready
Heatmap: Red-to-blue gradient, data-visualization style
Customizable Elements:
Toggle multi-timeframe component lines on/off
Show/hide regime background coloring
Adjust fill transparency (0-95%) for any monitor brightness
Paint price bars with momentum colors
Display/hide live metrics dashboard
⚠️ Important Notes
Not a standalone system: Combine with proper risk management, price action analysis, and fundamental awareness
Signal quality matters: Higher quality scores (>60%) have significantly better win rates
Regime awareness is key: Adapt strategy to market structure (trending vs ranging)
Volume reliability: Volume-weighting works best on liquid assets with reliable volume data
Timeframe alignment: Use appropriate base period and chart timeframe combination (e.g., base=10 on 4H chart vs. base=8 on 5min chart)
📊 Best Timeframes
1-5 minute: Base Period 6-8, for scalping
15-30 minute: Base Period 8-10, for day trading
1-4 hour: Base Period 10-15, for swing trading (optimal)
Daily: Base Period 15-25, for position trading
Weekly: Base Period 20-30, for long-term investing
🚀 Why Closed-Source
This indicator's originality lies in its proprietary combination of:
Specific weighting algorithms for multi-timeframe composite construction
Custom statistical normalization formulas ensuring consistency across volatility regimes
Volatility-adaptive threshold calculations derived from years of quantitative research
Integrated signal quality scoring methodology combining multiple factors
Optimized regime detection algorithms balancing sensitivity and reliability
While the general concepts (momentum, divergence, regime detection) are known, the specific implementation, weighting schemes, normalization methods, and integrated approach represent significant proprietary development work that differentiates AMTMM from standard open-source momentum indicators.
📝 Version History
v1.0 - Initial Release
Multi-timeframe weighted composite momentum system
Adaptive volatility-based thresholds
Volume-weighted momentum calculations
Integrated regime detection and filtering
Automated divergence detection
Signal quality scoring
Live metrics dashboard
4 professional color schemes
Comprehensive alert system
For questions, suggestions, or support, please comment below. Happy trading! 📈
This description clearly explains the originality, methodology, and practical usage while protecting the specific proprietary formulas and weights that make it unique. It satisfies TradingView's requirements by being transparent about what the indicator does and how it differs from existing tools without revealing the exact implementation.
SSI-O - Super Strength Indicator (overlay) [Da_Prof]This is the overlay version of the Super Strength Indicator (SSI). The SSI is a combination of the money flow indicator (MFI), stochastic (Stoch) and relative strength index (RSI). These indicators are averaged together with weightings tested via months of backtesting to produce the SSI algorithm that is not just a simple average or summation of these indicators. The SSI is a sensitive indicator that detects exhaustion of momentum for all assets.
The overlay version of the SSI shows triangles above/below the price when there is high/low risk. The high risk is colored purple. The extreme high risk is colored red. The low risk is colored blue/green and the extreme low risk is colored green.
Weightings of each into the indicator can be changed. If changing the weighting, it is best to ensure the percentages add up to 300%. For example, if changing the RSI weight to 120%, it is best to drop the MFI and Stoch to 90% each.
The RSI SMA is default set at 1. This means the indicator uses the RSI with no smoothing. If changing to greater than 1, then the indicator uses the moving average smoothed RSI.
The default for the Stoch is to use the K only. The D can be used by changing the weightings.
SSI - Super Strength Indicator [Da_Prof]The Super Strength Indicator (SSI) is a combination of the money flow indicator (MFI), stochastic (Stoch) and relative strength index (RSI). These indicators are averaged together with weightings tested via months of backtesting to produce the SSI algorithm that is not just a simple average or summation of these indicators. The SSI is a sensitive indicator that detects exhaustion of momentum for all assets.
The SSI shows background colors when there is high/low risk. The high risk is colored purple. The extreme high risk is colored red. The low risk is colored blue/green and the extreme low risk is colored green.
Weightings of each into the indicator can be changed. If changing the weighting, it is best to ensure the percentages add up to 300%. For example, if changing the RSI weight to 120%, it is best to drop the MFI and Stoch to 90% each.
The RSI SMA is default set at 1. This means the indicator uses the RSI with no smoothing. If changing to greater than 1, then the indicator uses the moving average smoothed RSI.
The default for the Stoch is to use the K only. The D can be used by changing the weightings.
AlphaFlow - Trend DetectorOVERVIEW
AlphaFlow identifies and tracks large volume moves by combining volume analysis, price impact measurement, and conviction scoring to separate significant institutional moves from normal trading activity. Rather than just flagging high volume, this indicator evaluates whether large trades actually moved the market and assigns conviction levels based on multiple confirmation factors.
WHAT MAKES THIS ORIGINAL
This is not simply a volume indicator or volume-weighted price tracker. The originality lies in the multi-factor conviction scoring system that evaluates whether large volume moves represent genuine institutional conviction or just noise.
Key Differentiators:
- Combines volume ratio AND price impact (volume alone doesn't mean conviction)
- Conviction scoring system that weighs trend alignment, follow-through, and volume persistence
- Cumulative flow tracking that shows persistent directional pressure over time
- Market regime detection (bullish/bearish/sideways) based on flow dynamics
- Tiered signal system (EXTREME/HIGH/MEDIUM conviction) rather than binary signals
This approach solves the problem of volume spikes that don't lead to meaningful price action, or price moves on low volume that don't persist.
HOW IT WORKS
1. Whale Detection Engine:
Volume Qualification: Compares current volume to a rolling average (default 50 bars). Whale activity requires volume to be at least 1.5x the average (adjustable).
Price Impact Requirement: Volume alone isn't enough. The bar must also show significant price movement (default 0.1% minimum). This filters out high-volume consolidation where no one is actually committed to direction.
Direction Identification: Bullish whale = close > open on high volume. Bearish whale = close < open on high volume.
2. Conviction Scoring System:
The indicator doesn't just flag whale activity - it evaluates conviction through multiple factors:
Base Conviction: Calculated from (volume_ratio × price_impact) / 10
This gives higher scores to moves with both exceptional volume AND large price swings.
Trend Alignment Bonus (1.5x multiplier): Whale moves aligned with the 20-period EMA trend receive higher conviction scores. Institutional money tends to accumulate with the trend, not against it.
Follow-Through Bonus (1.3x multiplier): After whale activity, does price continue in that direction over the next bars (default 3)? Genuine conviction shows persistence.
Volume Persistence (1.2x multiplier): Is elevated volume sustained over multiple bars, or is it a one-time spike? The 3-bar average volume ratio above 1.5x indicates sustained interest.
Conviction Levels:
- EXTREME: Score > 15 (large whale emoji labels, highest confidence)
- HIGH: Score > 8 (triangle signals, strong confidence)
- MEDIUM: Score > 3 (small triangles, moderate confidence)
- LOW: Score < 3 (not plotted to reduce noise)
3. Cumulative Flow Analysis:
Rather than treating each whale move in isolation, the indicator tracks cumulative flow using an EMA of whale activity. This reveals persistent directional pressure.
Flow Calculation: Each whale bar contributes (whale_strength × direction) to the flow. Strength is volume_ratio × price_impact_percent.
Flow Momentum: Rate of change in the cumulative flow (5-bar change)
Flow Acceleration: Second derivative (3-bar change of momentum)
These metrics reveal whether whale activity is accelerating, decelerating, or reversing.
4. Market Regime Detection:
Bullish Regime: Cumulative flow > 2 AND momentum positive
Bearish Regime: Cumulative flow < -2 AND momentum negative
Sideways Regime: Neither condition met
The background color reflects the current regime, helping traders understand the broader context.
5. Flow Strength Meter:
The main plot normalizes cumulative flow to a -100 to +100 scale based on the 100-bar range. This provides a consistent visual reference regardless of the asset or timeframe.
Extreme levels at ±50 indicate particularly strong directional flow where reversals or consolidation become more likely.
HOW TO USE IT
Settings Configuration:
Whale Detection Section:
- Volume Average Period (default 50): Shorter periods make detection more sensitive to recent volume changes. Longer periods require more exceptional volume to trigger.
- Whale Volume Multiplier (default 1.5): How much above average volume must be to qualify. Lower = more signals. Higher = only extreme moves.
- Minimum Price Impact (default 0.1%): Filters out high-volume bars that didn't actually move price. Adjust based on asset volatility.
Trend Analysis:
- Trend Strength Period (default 20): EMA period for trend alignment bonus
- Confirmation Bars (default 3): How many bars to check for follow-through
Visual Settings:
- Flow Strength Meter: Main plot showing normalized cumulative flow
- Conviction Labels: Detailed labels showing volume ratio and price impact on extreme/high conviction whales
- Trend Background: Color-coded regime indication
Signal Interpretation:
EXTREME Conviction (Whale Emoji Labels):
These are the highest confidence signals. Large volume with significant price impact, aligned with trend, showing follow-through. These often mark the beginning or continuation of strong moves.
HIGH Conviction (Large Triangles):
Strong signals meeting most criteria. Good for main entries or adding to positions.
MEDIUM Conviction (Small Triangles):
Whale activity present but with fewer confirmation factors. Use for partial positions or require additional confirmation.
Flow Strength Meter:
- Above zero and rising: Bullish flow building
- Below zero and falling: Bearish flow building
- Approaching ±50: Extreme readings, watch for exhaustion
- Crossing zero: Flow regime change
Dashboard Information:
The top-right table shows:
- Current regime (bullish/bearish/sideways)
- Flow strength value
- Last whale direction
- Conviction level of last whale
- Current volume ratio
- Flow momentum direction
- Indicator status
Trading Strategies:
Trend Following: Take EXTREME and HIGH conviction signals aligned with the flow meter direction. Enter when flow is positive and rising for bullish whales, negative and falling for bearish whales.
Regime-Based: Only trade in bullish/bearish regimes (colored backgrounds). Avoid trading in sideways regimes where whale moves tend to reverse quickly.
Flow Reversals: When flow meter crosses zero with EXTREME conviction whale in the new direction, this often marks regime changes.
Exhaustion Plays: When flow reaches ±50 extreme levels, watch for EXTREME conviction whales in the opposite direction as potential reversal signals.
TECHNICAL DETAILS
Volume Ratio = Current Volume / SMA(Volume, Period)
Price Impact % = ABS(Close - Open) / Open × 100
Whale Detected = (Volume Ratio >= Multiplier) AND (Price Impact >= Minimum)
Whale Direction = Close > Open ? 1 : -1
Base Conviction = (Volume Ratio × Price Impact %) / 10
Trend Alignment = Whale Direction == Trend Direction ? 1.5 : 1.0
Follow-Through = Price continues whale direction over N bars ? 1.3 : 1.0
Volume Persistence = SMA(Volume Ratio, 3) > 1.5 ? 1.2 : 1.0
Final Conviction = Base × Trend Alignment × Follow-Through × Volume Persistence
Whale Flow = Whale Detected ? (Volume Ratio × Price Impact × Direction) : 0
Cumulative Flow = EMA(Whale Flow, 20)
Flow Momentum = Change(Cumulative Flow, 5)
Flow Acceleration = Change(Momentum, 3)
Normalized Flow Strength = (Cumulative Flow / Highest(ABS(Cumulative Flow), 100)) × 100
WHAT THIS SOLVES
Common Volume Indicator Problems:
- Volume spikes that don't move price (consolidation noise)
- Price moves on low volume that quickly reverse
- No differentiation between strong and weak volume signals
- Treating all high-volume bars equally regardless of context
- No measure of whether volume represents conviction or panic
Whale Flow Solutions:
- Requires both volume AND price impact for signals
- Conviction scoring separates strong moves from weak ones
- Cumulative flow shows persistent pressure vs isolated spikes
- Trend alignment and follow-through filter low-quality signals
- Tiered system lets traders choose their confidence threshold
LIMITATIONS
- Cannot identify individual whales or attribute volume to specific entities
- High volume can come from many sources (whales, retail panic, algo activity)
- Works best on liquid assets with consistent volume patterns
- Less reliable on low-volume assets or during market closures
- Conviction scoring thresholds may need adjustment per asset/timeframe
- Does not predict future whale activity, only identifies it after bars close
- Flow can remain at extremes longer than expected during strong trends
- False signals can occur during news events or earnings
- Not a standalone trading system - requires risk management and other analysis
Best used in combination with price action, support/resistance, and broader market context.
EDUCATIONAL VALUE
For traders learning about:
- Volume analysis beyond simple volume indicators
- Multi-factor signal confirmation systems
- Market regime and flow concepts
- Conviction-based scoring methodologies
- Cumulative indicator design
- Normalized plotting for cross-asset comparison
- Pine Script table and dashboard creation
Not financial advice.
AlphaMACD - Adaptive MACD with Efficiency RatioOVERVIEW
AlphaMACD is an adaptive implementation of the classic MACD indicator that dynamically adjusts its calculation periods based on market efficiency. Unlike traditional MACD which uses fixed periods (typically 12, 26, 9), this indicator adapts its fast and slow EMA periods in real-time based on how efficiently the market is trending.
WHAT MAKES THIS ORIGINAL
This is not a simple MACD with different settings or colors. The core innovation is the adaptive period calculation using Kaufman's Efficiency Ratio, which was originally developed for the Adaptive Moving Average (AMA). This indicator applies that adaptive logic to MACD itself.
Key Differences from Standard MACD:
- Periods dynamically adjust between user-defined ranges (default: 8-21 for fast, 21-55 for slow)
- Uses Kaufman's Efficiency Ratio to measure market trendiness
- Implements gap protection to prevent extreme spikes from market gaps
- Includes market regime detection to filter signals in choppy conditions
- Provides multi-timeframe trend confirmation
HOW IT WORKS
1. Efficiency Ratio Calculation:
The indicator calculates market efficiency by comparing the absolute price change over a period to the sum of absolute price changes within that period. High efficiency = strong trending market. Low efficiency = choppy/sideways market.
2. Adaptive Period Adjustment:
- In trending markets (high efficiency): Periods move toward the minimum values for faster response
- In choppy markets (low efficiency): Periods move toward the maximum values for slower, more stable signals
- The "Sensitivity" parameter controls how aggressively periods adapt (0.5 to 5.0)
3. Gap Protection:
The custom adaptive EMA function detects abnormal price gaps (moves larger than 3x the typical ATR-based change) and limits their impact on the calculation. This prevents weekends or news gaps from causing extreme MACD spikes.
4. Signal Quality Filtering:
- Market regime detection identifies trending vs sideways conditions
- Momentum filter (RSI-based) prevents signals during overextended moves
- Signal strength calculation helps identify high-confidence setups
- Sideways market signals are marked with warning symbols
5. Multi-Timeframe Analysis:
The indicator compares current timeframe MACD with a higher timeframe (default 60 min) to provide context and filter against-trend signals.
HOW TO USE IT
Settings:
- Core Settings: Define the minimum and maximum periods for fast/slow EMAs
- Sensitivity: Higher values make the indicator more responsive to market changes
- Multi-timeframe: Set a higher timeframe for trend confirmation
- Visual options: Customize appearance and enable/disable features
Signal Interpretation:
- Strong bullish/bearish signals (large triangles): High-confidence entries in trending markets
- Warning signals (small ⚠): Crossovers in sideways markets - use caution or skip
- Divergence labels ("DIV"): Price and MACD diverging - potential reversal
- Background color: Green tint = trending market, Orange tint = sideways market
The Information Table shows:
- Current market regime (trending or sideways)
- Market efficiency percentage (how clean the trend is)
- Current adaptive fast and slow periods
- Higher timeframe trend direction
- Current signal strength
Best Practices:
- In trending markets: Trust strong signals, avoid warning signals
- In sideways markets: Reduce position sizes or skip trades entirely
- Use higher timeframe confirmation for better signal quality
- Adjust sensitivity based on your trading timeframe (higher for intraday, lower for swing)
TECHNICAL DETAILS
Calculation Method:
- Efficiency Ratio = ABS(Close - Close ) / SUM(ABS(Close - Close ), Period)
- Smoothed Efficiency = EMA(Efficiency Ratio, 5)
- Fast Period = Fast_Min + (Fast_Max - Fast_Min) × (1 - Smoothed_Efficiency × Sensitivity)
- Slow Period = Slow_Min + (Slow_Max - Slow_Min) × (1 - Smoothed_Efficiency × Sensitivity)
- Adaptive EMA uses standard EMA formula with gap detection and limiting
- MACD = Fast Adaptive EMA - Slow Adaptive EMA
- Signal = EMA(MACD, Signal Period)
- Histogram = MACD - Signal
The adaptive periods are calculated on every bar, so the MACD responds faster in trending conditions and stabilizes during consolidation.
WHAT THIS SOLVES
Standard MACD Problems:
- Fixed periods don't adapt to changing market conditions
- Too many false signals in sideways markets
- Whipsaws during low-volatility consolidation
- Price gaps can cause misleading spikes
AlphaMACD Solutions:
- Periods automatically adjust to market state
- Market regime filter identifies and warns about sideways conditions
- Adaptive smoothing reduces whipsaws
- Gap protection prevents false extremes
LIMITATIONS
- Like all indicators, this does not predict the future
- Requires trending markets for optimal performance
- Adaptive calculation means backtesting results will differ from fixed-period MACD
- More complex than standard MACD - requires understanding of adaptive concepts
- The adaptive periods mean you cannot directly compare this to traditional MACD studies
This indicator is best used as part of a complete trading system, not as a standalone signal generator.
EDUCATIONAL VALUE
For traders learning about:
- Adaptive indicators and market efficiency concepts
- Kaufman's Adaptive Moving Average principles applied to oscillators
- Market regime detection and signal filtering
- Gap handling in technical indicators
- Multi-timeframe analysis integration
Not Financial advice.
MACD Pro - Multi-Filter Smart Divergence System# MACD Pro - Multi-Filter Smart Divergence System
## Professional MACD with Advanced Filtering & Automatic Divergence Detection
Transform the classic MACD indicator with professional-grade filters, automated divergence detection, and pre-optimized profiles for different markets.
---
## KEY FEATURES
### Smart Signal Filtering
- **Zero-Line Territory Filter** - Eliminates weak crossovers
- **3-Period Confirmation** - Reduces false signals
- **Minimum Distance Threshold** - Filters out noise
- **Multi-Indicator Confirmation** - RSI + Volume validation
### Automatic Divergence Detection
- **Visual Divergence Lines** - Connects price and MACD pivots automatically
- **Bullish/Bearish Recognition** - Real-time identification
- **Customizable Lookback** - Adjust sensitivity
- **Clean Display** - Managed line limits
### Pre-Optimized Market Profiles
- **S&P 500** (2/60/2) - Tested +3.63% annual
- **Gold** (14/48/3) - Optimized for volatility
- **Forex 30m** (24/52/9) - 24/7 market adapted
- **Scalping 1m** (5/13/6) - Quick trades
- **Linda Raschke** (3/10/16) - Classic scalping
- **Swing Trading** (8/24/9) - Higher timeframes
### Advanced Technical Features
- **ATR Normalization** - Volatility adaptation
- **Predictive Forecast** - Linear regression projection
- **Multi-Timeframe View** - Higher TF overlay
- **Volume Analysis** - Spike confirmation
- **Professional Dashboard** - Real-time metrics
---
## HOW TO USE
**Quick Start:**
1. Enable "Use Optimized Profile"
2. Select your market type
3. Watch for signal arrows and divergence lines
4. Confirm with dashboard metrics
**Signal Types:**
- 🔺 Green Triangle = Bullish crossover (filtered)
- 🔻 Red Triangle = Bearish crossover (filtered)
- ⚪ Small Circle = Conservative zero-line cross
- 🟢 Green Line = Bullish divergence
- 🔴 Red Line = Bearish divergence
---
## CUSTOMIZATION
**Filters:** Toggle each filter independently for your risk tolerance
**Divergence:** Adjust lookback period, line width, and maximum displayed lines
**Confirmation:** Customize RSI levels and volume spike thresholds
**Display:** Choose histogram, forecast, and multi-timeframe options
---
## ALERT CONDITIONS
- MACD Long Signal
- MACD Short Signal
- Bullish Divergence
- Bearish Divergence
---
## IMPORTANT NOTES
**Repainting:** Divergence detection uses historical pivots and may redraw. Crossover signals are non-repainting.
**Disclaimer:** Pre-optimized profiles based on historical data. Past performance does not guarantee future results. This indicator is for educational purposes only, not financial advice.
---
## BEST PRACTICES
**Timeframes:**
- 1-5m → Scalping profile
- 15-30m → Forex profile
- 1-4h → Swing profile
- Daily → S&P 500/Gold profiles
**Market Conditions:**
- Trending → Focus on momentum
- Ranging → Enable all filters, watch divergences
- Volatile → Use ATR normalization
**Combine With:** Support/resistance levels, trendlines, moving averages, and price action analysis.
---
## WHY MACD PRO?
| Feature | Standard MACD | MACD Pro |
|---------|--------------|----------|
| Signal Filters | ❌ | ✅ 5 Advanced |
| Divergence | ❌ Manual | ✅ Automatic |
| Market Profiles | ❌ | ✅ 7 Optimized |
| Volume Filter | ❌ | ✅ Built-in |
| Multi-Timeframe | ❌ | ✅ Yes |
| ATR Adaptation | ❌ | ✅ Yes |
---
**If you find this indicator useful, please boost 🚀**
*Protected source code. Compatible with all TradingView plans.*
RSI + Stochastic Combo (fixed) by howhaber# RSI + Stochastic Indicator
**Summary**
This indicator combines RSI and Stochastic to generate BUY and SELL signals in oversold or overbought market conditions. It merges both indicators for higher accuracy, reducing false signals. Includes visual signals on the chart, alerts, and an info label for quick analysis.
---
## 📈 How the Indicator Works
### RSI Component
- Calculates standard RSI based on the specified period (`rsiLen`).
- Indicates oversold (< 30) or overbought (> 70) conditions.
### Stochastic Component
- Manually calculated to avoid compatibility issues.
- Measures the current price position relative to the price range (highs/lows) over the selected period.
- Smoothed using two SMA filters (%K and %D).
### Signal Logic
**BUY Signal**:
- %K crosses above %D (`ta.crossover(k, d)`).
- %K < 20 (oversold market).
- RSI < specified threshold (default < 40).
**SELL Signal**:
- %K crosses below %D (`ta.crossunder(k, d)`).
- %K > 80 (overbought market).
- RSI > specified threshold (default > 60).
---
## 📍 What's Displayed on the Chart
- 🟢 **Green arrow** below the bar → BUY signal.
- 🔴 **Red arrow** above the bar → SELL signal.
- **In a separate window**:
- RSI line (blue).
- Stochastic %K (orange).
- Stochastic %D (purple).
- Reference levels: 30/70 (RSI), 20/80 (Stochastic).
---
## 🔔 Alerts
- **RSI+Stoch BUY**: Notification on BUY signal.
- **RSI+Stoch SELL**: Notification on SELL signal.
Receive alerts via email, Telegram, or directly on the platform.
---
## 🧩 Additional Feature
- Info label on the last bar, displaying:
- Current RSI value.
- %K and %D values.
- Facilitates quick visual checks of the indicator's current state.
---
## 💡 Interpretation
- **Oversold market** (confirmed by RSI and Stochastic): Likely upward reversal.
- **Overbought market** (confirmed by RSI and Stochastic): Likely downward reversal.
- Combining both reduces false signals and improves accuracy in choppy markets.
---
## ⚠️ Important Note
This indicator is not financial advice. It is designed for technical analysis and educational purposes. Combine it with other tools like trend analysis, volume, and price patterns for better results.
RSI// This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © xdecow
//@version=5
indicator("RSI", overlay=true)
g_panel = 'Panel Options'
i_orientation = input.string('Vertical', 'Orientation', options = , group = g_panel)
i_position = input.string('Bottom Right', 'Position', options = , group = g_panel)
i_border_width = input.int(1, 'Border Width', minval = 0, maxval = 10, group = g_panel, inline = 'border')
i_color_border = input.color(#000000, '', group = g_panel, inline = 'border')
i_showHeaders = input.bool(true, 'Show Headers', group = g_panel)
i_color_header_bg = input.color(#5d606b, 'Headers Background', group = g_panel, inline = 'header')
i_color_header_text = input.color(color.white, 'Text', group = g_panel, inline = 'header')
i_color_tf_bg = input.color(#2a2e39, 'Timeframe Background', group = g_panel, inline = 'tf')
i_color_tf_text = input.color(color.white, 'Text', group = g_panel, inline = 'tf')
i_debug = input.bool(false, 'Display colors palette (debug)', group = g_panel)
// rsi bg colors
g_rsi = 'RSI Colors'
i_threshold_ob = input.int(70, 'Overbought Threshold', minval=51, maxval=100, group = g_rsi)
i_color_ob = input.color(#128416, 'Overbought Background', inline = 'ob', group = g_rsi)
i_tcolor_ob = input.color(color.white, 'Text', inline = 'ob', group = g_rsi)
i_threshold_uptrend = input.int(60, 'Uptrend Threshold', minval=51, maxval=100, group = g_rsi)
i_color_uptrend = input.color(#2d472e, 'Uptrend Background', inline = 'up', group = g_rsi)
i_tcolor_uptrend = input.color(color.white, 'Text', inline = 'up', group = g_rsi)
i_color_mid = input.color(#131722, 'No Trend Background', group = g_rsi, inline = 'mid')
i_tcolor_mid = input.color(#b2b5be, 'Text', group = g_rsi, inline = 'mid')
i_threshold_downtrend = input.int(40, 'Downtrend Threshold', group = g_rsi, minval=0, maxval=49)
i_color_downtrend = input.color(#5b2e2e, 'Downtrend Background', group = g_rsi, inline = 'down')
i_tcolor_downtrend = input.color(color.white, 'Text', group = g_rsi, inline = 'down')
i_threshold_os = input.int(30, 'Oversold Threshold', minval=0, maxval=49, group = g_rsi)
i_color_os = input.color(#db3240, 'Oversold Background', group = g_rsi, inline = 'os')
i_tcolor_os = input.color(color.white, 'Text', group = g_rsi, inline = 'os')
g_rsi1 = 'RSI #1'
i_rsi1_enabled = input.bool(true, title = 'Enabled', group = g_rsi1)
i_rsi1_tf = input.timeframe('5', 'Timeframe', group = g_rsi1)
i_rsi1_len = input.int(14, 'Length', minval = 1, group = g_rsi1)
i_rsi1_src = input.source(close, 'Source', group = g_rsi1) * 10000
v_rsi1 = i_rsi1_enabled ? request.security(syminfo.tickerid, i_rsi1_tf, ta.rsi(i_rsi1_src, i_rsi1_len)) : na
g_rsi2 = 'RSI #2'
i_rsi2_enabled = input.bool(true, title = 'Enabled', group = g_rsi2)
i_rsi2_tf = input.timeframe('15', 'Timeframe', group = g_rsi2)
i_rsi2_len = input.int(14, 'Length', minval = 1, group = g_rsi2)
i_rsi2_src = input.source(close, 'Source', group = g_rsi2) * 10000
v_rsi2 = i_rsi2_enabled ? request.security(syminfo.tickerid, i_rsi2_tf, ta.rsi(i_rsi2_src, i_rsi2_len)) : na
g_rsi3 = 'RSI #3'
i_rsi3_enabled = input.bool(true, title = 'Enabled', group = g_rsi3)
i_rsi3_tf = input.timeframe('60', 'Timeframe', group = g_rsi3)
i_rsi3_len = input.int(14, 'Length', minval = 1, group = g_rsi3)
i_rsi3_src = input.source(close, 'Source', group = g_rsi3) * 10000
v_rsi3 = i_rsi3_enabled ? request.security(syminfo.tickerid, i_rsi3_tf, ta.rsi(i_rsi3_src, i_rsi3_len)) : na
g_rsi4 = 'RSI #4'
i_rsi4_enabled = input.bool(true, title = 'Enabled', group = g_rsi4)
i_rsi4_tf = input.timeframe('240', 'Timeframe', group = g_rsi4)
i_rsi4_len = input.int(14, 'Length', minval = 1, group = g_rsi4)
i_rsi4_src = input.source(close, 'Source', group = g_rsi4) * 10000
v_rsi4 = i_rsi4_enabled ? request.security(syminfo.tickerid, i_rsi4_tf, ta.rsi(i_rsi4_src, i_rsi4_len)) : na
g_rsi5 = 'RSI #5'
i_rsi5_enabled = input.bool(true, title = 'Enabled', group = g_rsi5)
i_rsi5_tf = input.timeframe('D', 'Timeframe', group = g_rsi5)
i_rsi5_len = input.int(14, 'Length', minval = 1, group = g_rsi5)
i_rsi5_src = input.source(close, 'Source', group = g_rsi5) * 10000
v_rsi5 = i_rsi5_enabled ? request.security(syminfo.tickerid, i_rsi5_tf, ta.rsi(i_rsi5_src, i_rsi5_len)) : na
g_rsi6 = 'RSI #6'
i_rsi6_enabled = input.bool(true, title = 'Enabled', group = g_rsi6)
i_rsi6_tf = input.timeframe('W', 'Timeframe', group = g_rsi6)
i_rsi6_len = input.int(14, 'Length', minval = 1, group = g_rsi6)
i_rsi6_src = input.source(close, 'Source', group = g_rsi6) * 10000
v_rsi6 = i_rsi6_enabled ? request.security(syminfo.tickerid, i_rsi6_tf, ta.rsi(i_rsi6_src, i_rsi6_len)) : na
g_rsi7 = 'RSI #7'
i_rsi7_enabled = input.bool(false, title = 'Enabled', group = g_rsi7)
i_rsi7_tf = input.timeframe('W', 'Timeframe', group = g_rsi7)
i_rsi7_len = input.int(14, 'Length', minval = 1, group = g_rsi7)
i_rsi7_src = input.source(close, 'Source', group = g_rsi7) * 10000
v_rsi7 = i_rsi7_enabled ? request.security(syminfo.tickerid, i_rsi7_tf, ta.rsi(i_rsi7_src, i_rsi7_len)) : na
g_rsi8 = 'RSI #8'
i_rsi8_enabled = input.bool(false, title = 'Enabled', group = g_rsi8)
i_rsi8_tf = input.timeframe('W', 'Timeframe', group = g_rsi8)
i_rsi8_len = input.int(14, 'Length', minval = 1, group = g_rsi8)
i_rsi8_src = input.source(close, 'Source', group = g_rsi8) * 10000
v_rsi8 = i_rsi8_enabled ? request.security(syminfo.tickerid, i_rsi8_tf, ta.rsi(i_rsi8_src, i_rsi8_len)) : na
g_rsi9 = 'RSI #9'
i_rsi9_enabled = input.bool(false, title = 'Enabled', group = g_rsi9)
i_rsi9_tf = input.timeframe('W', 'Timeframe', group = g_rsi9)
i_rsi9_len = input.int(14, 'Length', minval = 1, group = g_rsi9)
i_rsi9_src = input.source(close, 'Source', group = g_rsi9) * 10000
v_rsi9 = i_rsi9_enabled ? request.security(syminfo.tickerid, i_rsi9_tf, ta.rsi(i_rsi9_src, i_rsi9_len)) : na
g_rsi10 = 'RSI #10'
i_rsi10_enabled = input.bool(false, title = 'Enabled', group = g_rsi10)
i_rsi10_tf = input.timeframe('W', 'Timeframe', group = g_rsi10)
i_rsi10_len = input.int(14, 'Length', minval = 1, group = g_rsi10)
i_rsi10_src = input.source(close, 'Source', group = g_rsi10) * 10000
v_rsi10 = i_rsi10_enabled ? request.security(syminfo.tickerid, i_rsi10_tf, ta.rsi(i_rsi10_src, i_rsi10_len)) : na
f_StrPositionToConst(_p) =>
switch _p
'Top Left' => position.top_left
'Top Right' => position.top_right
'Top Center' => position.top_center
'Middle Left' => position.middle_left
'Middle Right' => position.middle_right
'Middle Center' => position.middle_center
'Bottom Left' => position.bottom_left
'Bottom Right' => position.bottom_right
'Bottom Center' => position.bottom_center
=> position.bottom_right
f_timeframeToHuman(_tf) =>
seconds = timeframe.in_seconds(_tf)
if seconds < 60
_tf
else if seconds < 3600
str.tostring(seconds / 60) + 'm'
else if seconds < 86400
str.tostring(seconds / 60 / 60) + 'h'
else
switch _tf
"1D" => "D"
"1W" => "W"
"1M" => "M"
=> str.tostring(_tf)
type TPanel
table src = na
bool vertical_orientation = true
int row = 0
int col = 0
method incCol(TPanel _panel) =>
if _panel.vertical_orientation
_panel.col += 1
else
_panel.row += 1
method incRow(TPanel _panel) =>
if not _panel.vertical_orientation
_panel.col += 1
_panel.row := 0
else
_panel.row += 1
_panel.col := 0
method add(TPanel _panel, string _v1, color _bg1, color _ctext1, string _v2, color _bg2, color _ctext2) =>
table.cell(_panel.src, _panel.col, _panel.row, _v1, text_color = _ctext1, bgcolor = _bg1)
_panel.incCol()
table.cell(_panel.src, _panel.col, _panel.row, _v2, text_color = _ctext2, bgcolor = _bg2)
_panel.incRow()
f_bg(_rsi) =>
c_line = na(_rsi) ? i_color_mid :
_rsi >= i_threshold_ob ? i_color_ob :
_rsi >= i_threshold_uptrend ? i_color_uptrend :
_rsi <= i_threshold_os ? i_color_os :
_rsi <= i_threshold_downtrend ? i_color_downtrend :
i_color_mid
f_rsi_text_color(_rsi) =>
c_line = na(_rsi) ? i_tcolor_mid :
_rsi >= i_threshold_ob ? i_tcolor_ob :
_rsi >= i_threshold_uptrend ? i_tcolor_uptrend :
_rsi <= i_threshold_os ? i_tcolor_os :
_rsi <= i_threshold_downtrend ? i_tcolor_downtrend :
i_tcolor_mid
f_formatRsi(_rsi) => na(_rsi) ? 'N/A' : str.tostring(_rsi, '0.00')
if barstate.islast
v_panel = TPanel.new(vertical_orientation = i_orientation == 'Vertical')
v_max_rows = 20
v_panel.src := table.new(f_StrPositionToConst(i_position), v_max_rows, v_max_rows, border_width = i_border_width, border_color = i_color_border)
if i_showHeaders
v_panel.add('TF', i_color_header_bg, i_color_header_text, 'RSI', i_color_header_bg, i_color_header_text)
if i_rsi1_enabled
v_panel.add(f_timeframeToHuman(i_rsi1_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi1), f_bg(v_rsi1), f_rsi_text_color(v_rsi1))
if i_rsi2_enabled
v_panel.add(f_timeframeToHuman(i_rsi2_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi2), f_bg(v_rsi2), f_rsi_text_color(v_rsi2))
if i_rsi3_enabled
v_panel.add(f_timeframeToHuman(i_rsi3_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi3), f_bg(v_rsi3), f_rsi_text_color(v_rsi3))
if i_rsi4_enabled
v_panel.add(f_timeframeToHuman(i_rsi4_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi4), f_bg(v_rsi4), f_rsi_text_color(v_rsi4))
if i_rsi5_enabled
v_panel.add(f_timeframeToHuman(i_rsi5_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi5), f_bg(v_rsi5), f_rsi_text_color(v_rsi5))
if i_rsi6_enabled
v_panel.add(f_timeframeToHuman(i_rsi6_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi6), f_bg(v_rsi6), f_rsi_text_color(v_rsi6))
if i_rsi7_enabled
v_panel.add(f_timeframeToHuman(i_rsi7_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi7), f_bg(v_rsi7), f_rsi_text_color(v_rsi7))
if i_rsi8_enabled
v_panel.add(f_timeframeToHuman(i_rsi8_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi8), f_bg(v_rsi8), f_rsi_text_color(v_rsi8))
if i_rsi9_enabled
v_panel.add(f_timeframeToHuman(i_rsi9_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi9), f_bg(v_rsi9), f_rsi_text_color(v_rsi9))
if i_rsi10_enabled
v_panel.add(f_timeframeToHuman(i_rsi10_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi10), f_bg(v_rsi10), f_rsi_text_color(v_rsi10))
if i_debug
t = table.new(position.middle_center, 21, 20, border_width = i_border_width, border_color = i_color_border)
v_panel2 = TPanel.new(t, vertical_orientation = i_orientation == 'Vertical')
v_panel2.add('Debug', i_color_header_bg, i_color_header_text, 'Colors', i_color_header_bg, i_color_header_text)
demo = map.new()
map.put(demo, 'Overbought', i_threshold_ob)
map.put(demo, 'Uptrend', i_threshold_uptrend)
map.put(demo, 'No Trend', 50)
map.put(demo, 'Downtrend', i_threshold_downtrend)
map.put(demo, 'Oversold', i_threshold_os)
demoKeys = map.keys(demo)
for key in demoKeys
tf = key
rsi = map.get(demo, key)
v_panel2.add(tf, i_color_tf_bg, i_color_tf_text, f_formatRsi(rsi), f_bg(rsi), f_rsi_text_color(rsi))
MILLION MEN - Capitulation Hunter What it is
MILLION MEN – Capitulation Hunter detects potential capitulation buy-limits using a confluence of momentum, volatility, and liquidity cues. It combines a 5-oscillator sentiment (RSI / Stoch / CCI / MFI / MACD histogram) with EMA200 trend context, Bollinger lower band proximity, volume climax, and an optional liquidity sweep check. When all filters align, the tool paints a BUY-LIMIT zone and proposes SL/TP levels.
How it works (high-level)
Oscillator sentiment (0–100%): counts how many of the five oscillators are bullish; capitulation candidate = 0%.
Trend & location: price below EMA200 and at/through BB lower band (basis ± mult×σ).
Selling climax: current volume ≥ X × volume SMA.
Liquidity sweep (optional): current low sweeps the prior N-bar low but closes back above it.
Confirmation: optional 0–2 extra bars (close > low and bullish bodies) before validating.
On validation, the script draws: BUY-LIMIT zone, dotted SL = zone bottom − ATR×mult, TP by R:R, and a mini sentiment table.
How to use
Look for zones after fast, extended selloffs into BB-L with volume spike and oscillators at 0%.
Place pending BUY-LIMIT inside the painted zone; use the plotted SL/TP as a starting point.
Works across timeframes; adjust volume multiplier, sweep length, confirmation bars, and ATR×SL to your market.
For added confluence: HTF structure, session/flow, or order-book/liquidity context.
Originality & value
Instead of a generic mashup, this tool enforces a strict confluence: (1) five-oscillator capitulation, (2) location at BB-L under EMA200, (3) volume climax, (4) optional sweep/recapture, and (5) bar-based confirmation—then auto-renders a practical trade plan (zone + SL/TP) and a readable sentiment table. All calculations are manual (no lookahead) and designed for clarity and execution.
Limitations & transparency
Capitulation can persist during strong downtrends; always use structure and risk management.
SL/TP visuals are hints, not orders; adapt to instrument volatility and liquidity.
Non-standard chart types aren’t supported for signals. No future data is used.
This is not financial advice; past performance does not guarantee future results.
(ملخص عربي )
مؤشر يلتقط سيناريوهات الاستسلام البيعي (Capitulation) عبر شروط متشددة: مزاج مؤشرات الزخم = 0%، السعر تحت EMA200 وعند/أسفل BB-L، ذروة فوليوم، واختياري سويب قيعان ثم ارتداد. عند التأكيد يرسم منطقة BUY-LIMIT ويقترح SL/TP. استخدمه مع هيكل السوق وإدارة المخاطر.
Logit RSI [AdaptiveRSI]The traditional 0–100 RSI scale makes statistical overlays, such as Bollinger Bands or even moving averages, technically invalid. This script solves this issue by placing RSI on an unbounded, continuous scale, enabling these tools to work as intended.
The Logit function takes bounded data, such as RSI values ranging from 0 to 100, and maps them onto an unbounded scale ranging from negative infinity (−∞) to positive infinity (+∞).
An RSI reading of 50 becomes 0 on the Logit scale, indicating a balanced market. Readings above 50 map to positive Logit values (price above Wilder’s EMA / RSI above 50), while readings below 50 map to negative values (price below Wilder’s EMA / RSI below 50).
For the detailed formula, which calculates RSI as a scaled distance from Wilder’s EMA, check the RSI
: alternative derivation script.
The main issue with the 0–100 RSI scale is that different lookback periods produce very different distributions of RSI values. The histograms below illustrate how often RSIs of various lengths spend time within each 5-point range.
On RSI(2), the tallest bars appear at the edges (0–5 and 95–100), meaning short-term RSI spends most of its time at the extremes. For longer lookbacks, the bars cluster around the center and rarely reach 70 or 30.
This behavior makes it difficult to generalize the two most common RSI techniques:
Fixed 70/30 thresholds: These overbought and oversold levels only make sense for short- or mid-range lookbacks (around the low teens). For very short periods, RSI spends most of its time above or below these levels, while for long-term lookbacks, RSI rarely reaches them.
Bollinger Bands (±2 standard deviations): When applied directly to RSI, the bands often extend beyond the 0–100 limits (especially for short-term lookbacks) making them mathematically invalid. While the issue is less visible on longer settings, it remains conceptually incorrect.
To address this, we apply the Logit Transform :
Logit RSI = LN(RSI / (100 − RSI))
The transformed data fits a smooth bell-shaped curve, allowing statistical tools like Bollinger Bands to function properly for the first time.
Why Logit RSI Matters:
Makes RSI statistically consistent across all lookback periods.
Greatly improves the visual clarity of short-term RSIs
Allows proper use of volatility tools (like Bollinger Bands) on RSI.
Replaces arbitrary 70/30 levels with data-driven thresholds.
Simplifies RSI interpretation for both short- and long-term analysis.
INPUTS:
RSI Length — set the RSI lookback period used in calculations.
RSI Type — choose between Regular RSI or Logit RSI .
Plot Bollinger Bands — ON/OFF toggle to overlay statistical envelopes around RSI or Logit RSI.
SMA and Standard Deviation Length — defines the lookback period for both the SMA (Bollinger Bands midline) and Standard Deviation calculations.
Standard Deviation Multiplier — controls the width of the Bollinger Bands (e.g., 2.0 for ±2σ).
While simple, the Logit transformation represents an unexplored yet powerful mathematically grounded improvement to the classic RSI.
It offers traders a structured, intuitive, and statistically consistent way to use RSI across all timeframes.
I welcome your feedback, suggestions, and code improvements—especially regarding performance and efficiency. Your insights are greatly appreciated.
CMF, RSI, CCI, MACD, OBV, Fisher, Stoch RSI, ADX (+DI/-DI)Eight normalized indicators are used in conjunction with the CMF, CCI, MACD, and Stoch RSI indicators. You can track buy and sell decisions by tracking swings. The zero line is for reversal tracking at -20, +20, +50, and +80. You can use any of the nine indicators individually or in combination.
