Volume Cluster Support and Resistance Levels [QuantAlgo]🟢 Overview
This indicator identifies statistically significant support and resistance levels through volume cluster analysis, isolating price zones characterized by elevated trading activity and institutional participation. By quantifying areas where volume concentration exceeded historical norms, it reveals price levels with demonstrated supply-demand imbalances that exhibit persistent influence on subsequent price action. The methodology is asset-agnostic and timeframe-independent, applicable across equities, cryptocurrencies, forex, and commodities from intraday to weekly intervals.
🟢 Key Features
1. Support and Resistance Levels
The indicator scans historical price data to identify bars where volume exceeds a user-defined threshold multiplier relative to the rolling average. For each qualifying bar, a representative price is calculated using the average of high, low, and close. Proximate price levels within a specified percentage range are then aggregated into discrete clusters using volume-weighted averaging, eliminating redundant signals. Clusters are ranked by cumulative volume to determine statistical significance. Finally, the indicator plots horizontal levels at each cluster price: support levels (green) below current price indicate zones where historical buying pressure exceeded selling pressure, while resistance levels (red) above current price mark zones where sellers historically dominated. These levels represent areas of established liquidity and price discovery, where institutional order flow previously concentrated.
The Touch Count (T) metric quantifies historical price interaction frequency, while Total Volume (TV) measures aggregate trading activity at each level, providing objective criteria for assessing level strength and trade execution decisions.
2. Volume Histogram
A histogram appears below the price chart, displaying relative volume for each bar within the lookback period, with bar height scaled to the maximum volume observed. Green bars represent up-periods (close > open) indicating buying pressure, while red bars show down-periods (close < open) indicating selling pressure. This visualization helps you confirm the validity of support/resistance levels by seeing where volume actually spiked, identify accumulation/distribution patterns, and validate breakouts by checking if they occur on above-average volume.
3. Built-in Alerts
Automated alerts trigger when price crosses below support levels or breaks above resistance levels, allowing you to monitor multiple assets without constant chart-watching.
4. Customizable Color Schemes
The indicator provides four preset color configurations (Classic, Aqua, Cosmic, Custom) optimized for visual clarity across different charting environments. Each scheme maintains consistent color mapping for support and resistance zones across both level lines and volume histogram components. The Custom configuration permits full color specification to accommodate individual charting setups, ensuring optimal visual contrast for extended analysis sessions.
Classic:
Aqua:
Cosmic:
Custom:
🟢 Pro Tips
→ Trade entry optimization: Execute long positions at support levels with high touch counts or upon confirmed resistance breakouts accompanied by above-average volume
→ Risk parameter definition: Position stop-loss orders near identified support/resistance zones with statistical significance to minimize premature exits
→ Breakout validation: Require volume confirmation exceeding historical average when price penetrates resistance to filter false breakouts
→ Level strength assessment: Prioritize levels with higher touch counts and total volume metrics for enhanced probability trade setups
→ Multi-timeframe confluence: Synthesize support/resistance levels across multiple timeframes to identify high-conviction zones where daily support aligns with 4-hour resistance structures
XAUUSD
Lot Size Calculator by MR1561Overview
Size your position on GOLD (XAU) directly from your risk in USD and the two lines you place on the chart (Entry & Stop). The script measures that price distance, calculates the lot size, draws clear Risk/Reward boxes, and shows a clean 2-column table with: Risk, Entry, Stop, Target (from R/R), Lots, and Pips.
How to use
Step 1: Add the indicator to an XAU chart (e.g., XAUUSD).
Step 2: In Inputs, set your Risk $.
Step 3: Place/adjust the Entry and Stop lines on the chart.
Step 4: Read "Lots" in the table and trade with consistent sizing.
Features
- GOLD-only display (detects XAU symbols)
- Lot sizing from Risk $ and price distance (Entry vs Stop)
- Auto Target from R/R, plus Risk/Reward boxes
- Compact on-chart table (toggle rows: Risk, Entry, Stop, Target, Lots, Pips)
- Fully customizable colors, opacity, table position, frame/border width
- Lightweight and fast; designed for clean overlays
Inputs
- Risk $: your dollar risk per trade
- Entry Price, Stop Loss: adjustable lines on chart
- R/R: target is auto-calculated from risk distance and ratio
- Appearance - Boxes: colors & opacity for Risk/Reward areas
- Appearance - Table: position (top/bottom, left/right), alternating row colors, frame/border width
- Table - Rows: show/hide each row
- Appearance - Layout: horizontal span (bars) for lines/boxes
حجم معامله روی طلا (XAU) را مستقیماً از «ریسک دلاری» و دو خطی که روی چارت می‌گذارید (Entry و Stop) محاسبه می‌کند. فاصلهٔ قیمتی را اندازه می‌گیرد، حجم (لات) را حساب می‌کند، باکس‌های Risk/Reward را رسم می‌کند و یک جدول دو ستونه از مقادیر مهم نشان می‌دهد: Risk، Entry، Stop، Target (از R/R)، Lots و Pips.
روش استفاده
اندیکاتور را روی چارت XAU (مثل XAUUSD) اضافه کنید.
در تنظیمات مقدار Risk $ را تعیین کنید.
خطوط Entry و Stop را روی چارت جابه‌جا/تنظیم کنید.
مقدار Lots را در جدول بخوانید و با سایز یکپارچه معامله کنید.
ویژگی‌ها
نمایش فقط روی نمادهای XAU
محاسبهٔ حجم از روی Risk $ و فاصلهٔ قیمتی (Entry تا Stop)
محاسبهٔ خودکار Target بر اساس R/R و رسم باکس‌های ریسک/ریوارد
جدول جمع‌وجور با امکان روشن/خاموش کردن سطرها (Risk, Entry, Stop, Target, Lots, Pips)
شخصی‌سازی کامل رنگ‌ها، شفافیت، موقعیت جدول و ضخامت قاب/بوردر
سبک و سریع؛ مناسب برای نمایش تمیز روی چارت
ورودی‌ها
Risk $ (ریسک دلاری هر معامله)
Entry Price و Stop Loss (قابل تنظیم روی چارت)
R/R (تارگت بر اساس نسبت ریسک به ریوارد محاسبه می‌شود)
ظاهر – باکس‌ها، ظاهر – جدول، جدول – ردیف‌ها، ظاهر – چیدمان
Changelog
v1.0 - Initial public release (core lot sizing, risk/reward boxes, compact table, styling options)
Credits
Created by MohammadReza.
Weekly + Daily + H4 Sup and Res ZonesEveryday price move at a set range. Just wait at the zone for candle reversal/continuation pattern formation before entry. Always keep it simple. Patience is key. Just Pick your preferred tf zone. Daily zone highly recommended for less than 100 pips target. H4 for scalpers and Weekly for swingers.
Indian Gold Festival Dates HistoricalIndian Gold Festival Dates (1975-2025)
Marks 8 major Indian festivals associated with gold buying over 50 years of historical data. Essential for analyzing seasonal patterns and cultural demand cycles in gold markets.
Festivals Included:
Dhanteras (Gold) - Most auspicious gold buying day
Diwali (Orange) - Festival of Lights
Akshaya Tritiya (Green) - "Never-ending" prosperity
Dussehra (Red) - Victory and success
Makar Sankranti (Cyan) - Solar new year
Gudi Padwa (Magenta) - Hindu New Year (Maharashtra)
Ugadi (Purple) - Hindu New Year (South India)
Navratri (Yellow) - 9-day festival
Features:
✓ 408 exact historical dates (1975-2025)
✓ Color-coded vertical lines for easy identification
✓ Toggle individual festivals on/off
✓ Adjustable line width and labels
✓ Works on all timeframes (best on daily/weekly)
Perfect for traders analyzing gold seasonality, Indian market sentiment, and cultural demand patterns. Use on XAUUSD, GC1!, or Indian gold futures.
Relative Performance Tracker [QuantAlgo]🟢 Overview
The Relative Performance Tracker is a multi-asset comparison tool designed to monitor and rank up to 30 different tickers simultaneously based on their relative price performance. This indicator enables traders and investors to quickly identify market leaders and laggards across their watchlist, facilitating rotation strategies, strength-based trading decisions, and cross-asset momentum analysis.
🟢 Key Features
1. Multi-Asset Monitoring
Track up to 30 tickers across any market (stocks, crypto, forex, commodities, indices)
Individual enable/disable toggles for each ticker to customize your watchlist
Universal compatibility with any TradingView symbol format (EXCHANGE:TICKER)
2. Ranking Tables (Up to 3 Tables)
Each ticker's percentage change over your chosen lookback period, calculated as:
(Current Price - Past Price) / Past Price × 100
Automatic sorting from strongest to weakest performers
Rank: Position from 1-30 (1 = strongest performer)
Ticker: Symbol name with color-coded background (green for gains, red for losses)
% Change: Exact percentage with color intensity matching magnitude
For example, Rank #1 has the highest gain among all enabled tickers, Rank #30 has the lowest (or most negative) return.
3. Histogram Visualization
Adjustable bar count: Display anywhere from 1 to 30 top-ranked tickers (user customizable)
Bar height = magnitude of percentage change.
Bars extend upward for gains, downward for losses. Taller bars = larger moves.
Green bars for positive returns, red for negative returns.
4. Customizable Color Schemes
Classic: Traditional green/red for intuitive interpretation
Aqua: Blue/orange combination for reduced eye strain
Cosmic: Vibrant aqua/purple optimized for dark mode
Custom: Full personalization of positive and negative colors
5. Built-In Ranking Alerts
Six alert conditions detect when rankings change:
Top 1 Changed: New #1 leader emerges
Top 3/5/10/15/20 Changed: Shifts within those tiers
🟢 Practical Applications
→ Momentum Trading: Focus on top-ranked assets (Rank 1-10) that show strongest relative strength for trend-following strategies
→ Market Breadth Analysis: Monitor how many tickers are above vs. below zero on the histogram to gauge overall market health
→ Divergence Spotting: Identify when previously leading assets lose momentum (drop out of top ranks) as potential trend reversal signals
→ Multi-Timeframe Analysis: Use different lookback periods on different charts to align short-term and long-term relative strength
→ Customized Focus: Adjust histogram bars to show only top 5-10 strongest movers for concentrated analysis, or expand to 20-30 for comprehensive overview
scalping signals 1 min xauusd + eurusd v2Transform Your 1-Minute Scalping with Precision Entry Signals
RSI Signals EUR/USD is a cutting-edge scalping indicator specifically optimized for EUR/USD on the 1-minute timeframe. Designed for active traders seeking quick profits from micro-movements, this indicator delivers crystal-clear entry signals with automatic Stop Loss and Take Profit levels.
What This Indicator Does
🎯 Smart Entry Signals
Get instant visual alerts when high-probability trading opportunities arise. The indicator identifies multiple types of reversal patterns and momentum shifts, displaying clear labels directly on your chart so you never miss a trade.
🎨 Color-Coded Candles
Candlesticks automatically change color based on active signals, making it effortless to track your current position at a glance. Each signal type has its unique color, eliminating confusion in fast-moving markets.
📊 Automatic Risk Management
Every signal comes with pre-calculated Stop Loss and Take Profit levels displayed as dynamic horizontal lines that extend across your chart. Set and forget - no more manual calculations or guesswork.
🎚️ Multiple Take Profit Targets
Maximize your profits with three progressive TP levels (TP1, TP2, TP3) based on optimal risk-reward ratios. Scale out of positions strategically as price moves in your favor.
🛡️ Intelligent Signal Management
When a Stop Loss is triggered, all visual indicators automatically disappear, and candle colors reset until the next fresh signal appears. This keeps your chart clean and focused on what matters.
⚡ Built for Speed
Specifically calibrated for EUR/USD volatility and spread characteristics, ensuring signals are actionable in real-time without lag or repainting.
Good For
Scalpers targeting 5-15 pip moves
Day traders looking for quick in-and-out opportunities
Forex traders focused on EUR/USD pair
Traders who value clear visual cues over complex analysis
Seasonality Heatmap [QuantAlgo]🟢 Overview
The Seasonality Heatmap analyzes years of historical data to reveal which months and weekdays have consistently produced gains or losses, displaying results through color-coded tables with statistical metrics like consistency scores (1-10 rating) and positive occurrence rates. By calculating average returns for each calendar month and day-of-week combination, it identifies recognizable seasonal patterns (such as which months or weekdays tend to rally versus decline) and synthesizes this into actionable buy low/sell high timing possibilities for strategic entries and exits. This helps traders and investors spot high-probability seasonal windows where assets have historically shown strength or weakness, enabling them to align positions with recurring bull and bear market patterns.
🟢 How It Works
1. Monthly Heatmap
How % Return is Calculated:
The indicator fetches monthly closing prices (or Open/High/Low based on user selection) and calculates the percentage change from the previous month:
(Current Month Price - Previous Month Price) / Previous Month Price × 100
Each cell in the heatmap represents one month's return in a specific year, creating a multi-year historical view
Colors indicate performance intensity: greener/brighter shades for higher positive returns, redder/brighter shades for larger negative returns
What Averages Mean:
The "Avg %" row displays the arithmetic mean of all historical returns for each calendar month (e.g., averaging all Januaries together, all Februaries together, etc.)
This metric identifies historically recurring patterns by showing which months have tended to rise or fall on average
Positive averages indicate months that have typically trended upward; negative averages indicate historically weaker months
Example: If April shows +18.56% average, it means April has averaged a 18.56% gain across all years analyzed
What Months Up % Mean:
Shows the percentage of historical occurrences where that month had a positive return (closed higher than the previous month)
Calculated as:
(Number of Months with Positive Returns / Total Months) × 100
Values above 50% indicate the month has been positive more often than negative; below 50% indicates more frequent negative months
Example: If October shows "64%", then 64% of all historical Octobers had positive returns
What Consistency Score Means:
A 1-10 rating that measures how predictable and stable a month's returns have been
Calculated using the coefficient of variation (standard deviation / mean) - lower variation = higher consistency
High scores (8-10, green): The month has shown relatively stable behavior with similar outcomes year-to-year
Medium scores (5-7, gray): Moderate consistency with some variability
Low scores (1-4, red): High variability with unpredictable behavior across different years
Example: A consistency score of 8/10 indicates the month has exhibited recognizable patterns with relatively low deviation
What Best Means:
Shows the highest percentage return achieved for that specific month, along with the year it occurred
Reveals the maximum observed upside and identifies outlier years with exceptional performance
Useful for understanding the range of possible outcomes beyond the average
Example: "Best: 2016: +131.90%" means the strongest January in the dataset was in 2016 with an 131.90% gain
What Worst Means:
Shows the most negative percentage return for that specific month, along with the year it occurred
Reveals maximum observed downside and helps understand the range of historical outcomes
Important for risk assessment even in months with positive averages
Example: "Worst: 2022: -26.86%" means the weakest January in the dataset was in 2022 with a 26.86% loss
2. Day-of-Week Heatmap
How % Return is Calculated:
Calculates the percentage change from the previous day's close to the current day's price (based on user's price source selection)
Returns are aggregated by day of the week within each calendar month (e.g., all Mondays in January, all Tuesdays in January, etc.)
Each cell shows the average performance for that specific day-month combination across all historical data
Formula:
(Current Day Price - Previous Day Close) / Previous Day Close × 100
What Averages Mean:
The "Avg %" row at the bottom aggregates all months together to show the overall average return for each weekday
Identifies broad weekly patterns across the entire dataset
Calculated by summing all daily returns for that weekday across all months and dividing by total observations
Example: If Monday shows +0.04%, Mondays have averaged a 0.04% change across all months in the dataset
What Days Up % Mean:
Shows the percentage of historical occurrences where that weekday had a positive return
Calculated as:
(Number of Positive Days / Total Days Observed) × 100
Values above 50% indicate the day has been positive more often than negative; below 50% indicates more frequent negative days
Example: If Fridays show "54%", then 54% of all Fridays in the dataset had positive returns
What Consistency Score Means:
A 1-10 rating measuring how stable that weekday's performance has been across different months
Based on the coefficient of variation of daily returns for that weekday across all 12 months
High scores (8-10, green): The weekday has shown relatively consistent behavior month-to-month
Medium scores (5-7, gray): Moderate consistency with some month-to-month variation
Low scores (1-4, red): High variability across months, with behavior differing significantly by calendar month
Example: A consistency score of 7/10 for Wednesdays means they have performed with moderate consistency throughout the year
What Best Means:
Shows which calendar month had the strongest average performance for that specific weekday
Identifies favorable day-month combinations based on historical data
Format shows the month abbreviation and the average return achieved
Example: "Best: Oct: +0.20%" means Mondays averaged +0.20% during October months in the dataset
What Worst Means:
Shows which calendar month had the weakest average performance for that specific weekday
Identifies historically challenging day-month combinations
Useful for understanding which month-weekday pairings have shown weaker performance
Example: "Worst: Sep: -0.35%" means Tuesdays averaged -0.35% during September months in the dataset
3. Optimal Timing Table/Summary Table
→ Best Month to BUY: Identifies the month with the lowest average return (most negative or least positive historically), representing periods where prices have historically been relatively lower
Based on the observation that buying during historically weaker months may position for subsequent recovery
Shows the month name, its average return, and color-coded performance
Example: If May shows -0.86% as "Best Month to BUY", it means May has historically averaged -0.86% in the analyzed period
→ Best Month to SELL: Identifies the month with the highest average return (most positive historically), representing periods where prices have historically been relatively higher
Based on historical strength patterns in that month
Example: If July shows +1.42% as "Best Month to SELL", it means July has historically averaged +1.42% gains
→ 2nd Best Month to BUY: The second-lowest performing month based on average returns
Provides an alternative timing option based on historical patterns
Offers flexibility for staged entries or when the primary month doesn't align with strategy
Example: Identifies the next-most favorable historical buying period
→ 2nd Best Month to SELL: The second-highest performing month based on average returns
Provides an alternative exit timing based on historical data
Useful for staged profit-taking or multiple exit opportunities
Identifies the secondary historical strength period
Note: The same logic applies to "Best Day to BUY/SELL" and "2nd Best Day to BUY/SELL" rows, which identify weekdays based on average daily performance across all months. Days with lowest averages are marked as buying opportunities (historically weaker days), while days with highest averages are marked for selling (historically stronger days).
🟢 Examples
Example 1: NVIDIA NASDAQ:NVDA - Strong May Pattern with High Consistency
Analyzing NVIDIA from 2015 onwards, the Monthly Heatmap reveals May averaging +15.84% with 82% of months being positive and a consistency score of 8/10 (green). December shows -1.69% average with only 40% of months positive and a low 1/10 consistency score (red). The Optimal Timing table identifies December as "Best Month to BUY" and May as "Best Month to SELL." A trader recognizes this high-probability May strength pattern and considers entering positions in late December when prices have historically been weaker, then taking profits in May when the seasonal tailwind typically peaks. The high consistency score in May (8/10) provides additional confidence that this pattern has been relatively stable year-over-year.
Example 2: Crypto Market Cap CRYPTOCAP:TOTALES - October Rally Pattern
An investor examining total crypto market capitalization notices September averaging -2.42% with 45% of months positive and 5/10 consistency, while October shows a dramatic shift with +16.69% average, 90% of months positive, and an exceptional 9/10 consistency score (blue). The Day-of-Week heatmap reveals Mondays averaging +0.40% with 54% positive days and 9/10 consistency (blue), while Thursdays show only +0.08% with 1/10 consistency (yellow). The investor uses this multi-layered analysis to develop a strategy: enter crypto positions on Thursdays during late September (combining the historically weak month with the less consistent weekday), then hold through October's historically strong period, considering exits on Mondays when intraweek strength has been most consistent.
Example 3: Solana BINANCE:SOLUSDT - Extreme January Seasonality
A cryptocurrency trader analyzing Solana observes an extraordinary January pattern: +59.57% average return with 60% of months positive and 8/10 consistency (teal), while May shows -9.75% average with only 33% of months positive and 6/10 consistency. August also displays strength at +59.50% average with 7/10 consistency. The Optimal Timing table confirms May as "Best Month to BUY" and January as "Best Month to SELL." The Day-of-Week data shows Sundays averaging +0.77% with 8/10 consistency (teal). The trader develops a seasonal rotation strategy: accumulate SOL positions during May weakness, hold through the historically strong January period (which has shown this extreme pattern with reasonable consistency), and specifically target Sunday exits when the weekday data shows the most recognizable strength pattern.
EquiSense AI Signals🇸🇦 العربي
المتنبئ الذكي المتوازن (AI v7)
وصف قصير:
مؤشر تجميعي ذكي يوازن بين الاتجاه والزخم والحجم والتذبذب وأنماط الشموع، ويحوّلها إلى نظام نقاط ونجوم يولّد إشارات شراء/بيع مؤكَّدة بتقاطع MACD. بعد الإشارة، يعرض أهدافًا ذكية (TP1/TP2/TP3) ووقف خسارة مبنيَّيْن على ATR مع رسومات مستقبلية ولوحة معلومات لإدارة الصفقة.
الإعدادات (Inputs)
الحد الأدنى للنقاط (min_score): افتراضي 6.0 — كلما ارتفع قلّت الإشارات وزادت جودتها.
الحد الأدنى للنجوم (min_stars): افتراضي 2 — فلتر لقوة الإشارة.
عدد الشموع المستقبلية (future_bars): افتراضي 15 — مدى رسم الأهداف والوقف للأمام.
استخدام الأهداف الذكية (use_ai_targets): تفعيل/إيقاف مضاعِف الذكاء الاصطناعي للأهداف والوقف.
كيف يعمل؟
يحسب المؤشر buy_score/sell_score من مجموعة عوامل: EMA8/21/50/200، RSI + متوسطه، MACD + Histogram، Stochastic، ADX/DMI، VWAP، الحجم، MTF 15m، ROC/المومنتَم، Heikin Ashi، وأنماط (ابتلاع/مطرقة/شهاب).
يحوّل الدرجات إلى نجوم (⭐⭐ إلى ⭐⭐⭐⭐⭐) حسب القوة.
تولّد الإشارة فقط إذا توفّر: درجة ≥ الحد + نجوم ≥ الحد + تقاطع MACD (صعودًا للشراء، هبوطًا للبيع).
عند الإشارة يبدأ سيناريو صفقة واحدة فقط حتى تنتهي (TP3 أو SL).
الأهداف والوقف (ذكاء اصطناعي)
تُشتق من ATR ثم تُعدَّل عبر مضاعِف AI مبني على: ATR%، الزخم (ROC)، الحجم مقابل متوسطه، قوة الاتجاه (ADX)، وعدد النجوم.
تقريبيًا:
TP1 ≈ 1.5×ATR × AI
TP2 ≈ 2.5×ATR × AI
TP3 ≈ 4.0×ATR × AI
SL ≈ 1.0×ATR ÷ AI
ماذا سترى على الشارت؟
علامات “شراء/بيع”، نجوم قرب الإشارة، خط دخول (أزرق)، وقف (أحمر منقّط)، TP1/TP2 (أخضر)، TP3 (ذهبي) مع صناديق مناطق للأهداف وخط ربط نحو الهدف النهائي.
وسم AI يعرض نسبة المضاعِف والنجوم بصريًا.
لوحة معلومات تعرض الحالة، القوة، AI%، السعر، الدرجات، وأثناء الصفقة: الدخول، TP1/TP2/TP3، والربح اللحظي.
التنبيهات (Alerts)
شرطان جاهزان: شراء وبيع عند تحقق الإشارة.
أضِف تنبيه: Right click → Add alert → اختر المؤشر → الشرط المطلوب.
أفضل الممارسات
استخدم الإطار المناسب للأصل:
سكالبينغ 5–15m: min_score 8 وmin_stars 3–4.
تأرجحي H1–H4: min_score 7 وmin_stars 3.
يومي/أسهم: min_score 6–7 وmin_stars 2–3.
فضّل التداول مع EMA200 واتجاه MTF 15m.
خفّض المخاطرة وقت الأخبار العالية.
التزم بإدارة مخاطر ثابتة (مثلاً 1% لكل صفقة).
حدود مهمة
الأفضل انتظار إغلاق الشمعة لتأكيد التقاطعات وتجنّب تغيّرها.
صفقة واحدة في المرة بفضل حالة in_trade.
يستخدم request.security مع lookahead_off لإطار 15m؛ التزم بالتقييم عند الإغلاق.
أسئلة شائعة
هل يستخدم منفردًا؟ نعم، لكن مع مناطق سعرية/ترند وخطة مخاطر يصبح أقوى.
لماذا تختلف الأهداف؟ لأن مضاعِف AI يكيّف TP/SL مع ظروف السوق.
إخلاء مسؤولية
هذه أداة تحليلية تعليمية وليست نصيحة استثمارية. اختبر الإعدادات تاريخيًا والتزم بالمخاطرة المناسبة.
ملاحظة للمبرمجين
Pine Script v6، متغيرات var لحفظ الحالة، تنظيف الرسومات على الشمعة الأخيرة، مع حدود مرتفعة للرسوم لتجنّب الأخطاء.
🇬🇧 English
Balanced Smart Predictor (AI v7)
Short description:
A smart, ensemble-style indicator that blends trend, momentum, volume, volatility, and candle patterns into a score & star system that produces Buy/Sell signals confirmed by MACD crosses. After a signal, it projects smart targets (TP1/TP2/TP3) and a stop-loss derived from ATR, with forward drawings and a control panel for trade management.
Inputs
Minimum Score (min_score): default 6.0 — higher = fewer but stronger signals.
Minimum Stars (min_stars): default 2 — extra filter for strength.
Future Bars (future_bars): default 15 — how far targets/SL are drawn ahead.
Use AI Targets (use_ai_targets): toggle the AI multiplier for TP/SL.
How it works
Computes buy_score/sell_score from: EMA8/21/50/200, RSI & its MA, MACD & Histogram, Stochastic, ADX/DMI, VWAP, Volume, 15m MTF tilt, ROC/Momentum, Heikin Ashi, and candle patterns (engulfing/hammer/shooting star).
Converts scores into Stars (⭐⭐ to ⭐⭐⭐⭐⭐) via tiered thresholds.
Signals fire only when: Score ≥ minimum + Stars ≥ minimum + MACD cross (up = Buy, down = Sell).
On a signal, one active trade is managed until TP3 or SL is reached.
Targets & Stop (AI-driven)
Targets and SL are ATR-based, then adjusted by an AI multiplier derived from: ATR%, momentum (ROC), relative volume, trend strength (ADX), and star rating.
Approximate formulas:
TP1 ≈ 1.5×ATR × AI
TP2 ≈ 2.5×ATR × AI
TP3 ≈ 4.0×ATR × AI
SL ≈ 1.0×ATR ÷ AI
What you’ll see on chart
“Buy/Sell” markers with small Star labels, an Entry line (blue), SL (red dotted), TP1/TP2 (green), TP3 (gold) with shaded target boxes and a guide line towards the final target.
A central AI badge showing the multiplier % and star rating.
A top-right Panel showing status, strength, AI%, price, scores, and during trades: entry, TP1/TP2/TP3, and live P/L.
Alerts
Two ready-made conditions: Buy and Sell when the respective signal triggers.
Add alert: Right click → Add alert → choose the indicator → select condition.
Best practices
Match timeframe to instrument:
Scalping 5–15m: min_score 8, min_stars 3–4.
Swing H1–H4: min_score 7, min_stars 3.
Daily/Equities: min_score 6–7, min_stars 2–3.
Prefer trades with EMA200 and 15m MTF trend alignment.
De-risk around major news.
Use fixed risk per trade (e.g., 1%).
Important notes
Prefer bar close confirmation to avoid mid-bar MACD flips.
Single trade at a time via the in_trade state.
15m MTF uses request.security with lookahead_off; evaluate at close for consistency.
FAQ
Use it standalone? You can, but it’s stronger when combined with S/R zones/trendlines and solid risk management.
Why do targets vary? The AI multiplier adapts TP/SL to current market conditions.
Disclaimer
This is an analytical/educational tool, not financial advice. Always backtest and use appropriate risk management.
Developer note
Built in Pine Script v6, uses var for trade state, clears drawings on the last bar to keep the chart tidy, and raises drawing limits to avoid runtime errors.
Supply & Demand Zones [QuantAlgo]🟢 Overview
The Supply & Demand (Support & Resistance) Zones indicator identifies price levels where significant buying and selling pressure historically emerged, using swing point analysis and pattern recognition to mark high-probability reversal and continuation areas. Unlike conventional support/resistance tools that draw arbitrary horizontal lines, this indicator can automatically detect structural zones, offering traders systematic entry and exit levels where institutional order flow likely congregates across any market or timeframe.
🟢 How to Use
# Zone Types:
Green/Demand Zones: Support areas where buying pressure historically emerged, representing potential long entry opportunities where price may bounce or consolidate before moving higher. These zones mark levels where buyers previously overcame sellers.
Red/Supply Zones: Resistance areas where selling pressure historically dominated, indicating potential short entry opportunities where price may reverse or stall before declining. These zones identify levels where sellers previously overwhelmed buyers.
# Zone Pattern Types:
Wick Rejection Zones: Zones created from candles with exceptionally long wicks showing violent price rejection. A demand rejection occurs when price drops sharply but closes well above the low, forming a long lower wick (relative to the total candle range) that demonstrates buyers aggressively defending that level. A supply rejection shows price spiking higher but closing well below the high, with the long upper wick proving sellers rejected that price aggressively. These zones often represent major institutional orders that absorbed significant market pressure. The rejection wick ratio setting controls how prominent the wick must be (higher ratios require more dramatic rejections and produce fewer but higher-quality zones).
Continuation Demand Zones: Areas where price rallied upward, paused in a brief consolidation base, then rallied again. This pattern confirms strong buying continuation (the consolidation represents profit-taking or minor pullbacks that failed to attract meaningful selling). When price returns to these zones, buyers who missed the initial rally often provide support, making them high-probability long entries within established uptrends. These zones follow the classic Rally-Base-Rally structure, demonstrating that buyers remain in control even during temporary pauses.
Reversal Demand Zones: Zones where price dropped, formed a consolidation base, then reversed into a rally. This structure marks potential trend reversals or major swing lows where buyers finally overwhelmed sellers after a decline. The base period represents accumulation by stronger hands, and these zones frequently appear at market bottoms or as significant pullback support within larger uptrends, signaling shifts in market control. These zones follow the Drop-Base-Rally pattern, showing the moment when selling pressure exhausted and buying interest emerged.
Continuation Supply Zones: Areas where price dropped, consolidated briefly, then dropped again. This pattern demonstrates strong selling continuation (the pause represents temporary buying attempts that failed to generate meaningful recovery). When price returns to these zones, sellers who missed the initial decline often provide resistance, creating short entry opportunities within established downtrends. These zones follow the Drop-Base-Drop structure, confirming that sellers maintain dominance even during temporary consolidations.
Reversal Supply Zones: Zones where price rallied upward, formed a consolidation base, then reversed into a decline. This formation identifies potential trend reversals or major swing highs where sellers overcame buyers after an advance. The base period often represents distribution by institutional participants, and these zones commonly appear at market tops or as key pullback resistance within larger downtrends, marking transfers of market control from buyers to sellers. These zones follow the Rally-Base-Drop pattern, capturing the transition point when buying exhaustion meets aggressive selling.
# Zone Mitigation Methods:
Wick Mitigation: Zones become invalidated immediately upon first contact by any wick. This assumes zones work only on their initial test, reflecting the belief that institutional orders concentrated at these levels get completely filled on first touch. Best for traders seeking only the highest-probability, untested zones and willing to accept that zones invalidate frequently in volatile markets. When price touches a zone boundary with even a single wick, that zone is considered "used up" and becomes mitigated.
Close Mitigation: Zones remain valid through wick penetration but become invalidated only when a candle closes through the zone boundary. This method allows price to briefly probe the zone with wicks while requiring actual commitment (a close) for invalidation. Suitable for traders who recognize that zones can withstand initial tests and prefer filtering out false breakouts caused by temporary volatility or liquidity hunts. A zone stays active as long as candles close within or outside it, regardless of wick penetration, until a close occurs beyond the boundary.
Full Body Mitigation: Zones stay valid until an entire candle body exists completely beyond the zone boundary, meaning both the open and close must be outside the zone. This approach maintains zone validity through partial penetrations, accommodating the reality that institutional zones can absorb considerable price action before exhausting. Ideal for volatile markets or traders who believe zones represent price ranges rather than precise levels, and who want zones to persist through aggressive but ultimately rejected breakout attempts. Only when both the open and close of a candle are beyond the zone does it become mitigated.
🟢 Pro Tips for Trading and Investing
→ Preset Selection: Choose presets matching your preferred timeframe - Scalping (M1-M30) for aggressive detection on minute charts, Intraday (H1-H12) for balanced filtering on hourly timeframes, or Swing Trading (1D+) for strict filtering on daily charts. Each preset automatically optimizes swing length, zone strength, and max zone counts for the selected timeframe.
→ Input Calibration: Adjust Swing Length based on market speed (lower values 3-7 for fast markets, higher values 12-20 for slower markets). Set Minimum Zone Strength according to asset volatility (0.05-0.15% for low-volatility assets, 0.25-0.5% for high-volatility assets). Tune Rejection Wick Ratio higher (0.6-0.8) for strict wick filtering or lower (0.3-0.5) to capture more subtle rejections.
→ Zone Pattern Toggle Strategy: Pattern types are mutually exclusive - enable Continuation OR Reversal patterns for each zone type, not both together. Recommended combinations: For trend trading, enable Rejection + Continuation (2-4 toggles total). For reversal trading, enable Rejection + Reversal (2-4 toggles). For scalping, enable only Rejection zones (1-2 toggles). Maximum 3-4 active toggles provides optimal chart clarity. A simple Wick Rejection toggle can also work on virtually any market and timeframe.
→ Mitigation Method Selection: Use Wick mitigation in clean trending markets for strict zone invalidation on first touch. Use Close mitigation in moderate volatility to filter out temporary spikes. Use Full Body mitigation in highly volatile markets to keep zones active through whipsaws and false breakouts.
→ Alert Configuration: Utilize built-in alerts for new zone creation, zone touches, and zone breaks. New zone alerts notify when fresh supply/demand areas form. Zone touch alerts signal potential entry opportunities as price reaches zones. Zone break alerts indicate when levels fail, signaling possible trend acceleration or structure changes.
GOLDSNIPERThe Gold Sniper Indicator is a precision trading tool designed specifically for scalping and intraday trading Gold (XAUUSD) on TradingView.
It automatically plots institutional key levels, detects breakout & retest opportunities, and provides trade management levels (Stop Loss & Take Profit) for structured, disciplined trading.
Aug 6
Release Notes
The Gold Sniper Indicator is a precision trading tool designed specifically for scalping and intraday trading Gold (XAUUSD) on TradingView.
It automatically plots institutional key levels, detects breakout & retest opportunities, and provides trade management levels (Stop Loss & Take Profit) for structured, disciplined trading
Aug 13
Release Notes
The Gold Sniper Indicator is a precision trading tool designed specifically for scalping and intraday trading Gold (XAUUSD) on TradingView.
It automatically plots institutional key levels, detects breakout & retest opportunities, and provides trade management levels (Stop Loss & Take Profit) for structured, disciplined trading.
3 days ago
Release Notes
The Gold Sniper Indicator is a precision TradingView tool for scalping and intraday trading Gold (XAUUSD).
It is built around a break-and-retest strategy with clear trade management: 10 pip Stop Loss, 20 pip TP1, and 35 pip TP2.
The indicator automatically:
• Plots institutional key levels and supply & demand zones
• Detects breakout and retest opportunities in real time
• Provides stop loss and take profit levels for structured, disciplined trading
Whether you’re a scalper or day trader, Gold Sniper helps you catch high-probability setups on XAUUSD with precise risk-to-reward ratios (1:1 and 1:3).
Fisher Transform Trend Navigator [QuantAlgo]🟢 Overview
The Fisher Transform Trend Navigator applies a logarithmic transformation to normalize price data into a Gaussian distribution, then combines this with volatility-adaptive thresholds to create a trend detection system. This mathematical approach helps traders identify high-probability trend changes and reversal points while filtering market noise in the ever-changing volatility conditions.
🟢 How It Works
The indicator's foundation begins with price normalization, where recent price action is scaled to a bounded range between -1 and +1:
highestHigh = ta.highest(priceSource, fisherPeriod)
lowestLow = ta.lowest(priceSource, fisherPeriod)
value1 = highestHigh != lowestLow ? 2 * (priceSource - lowestLow) / (highestHigh - lowestLow) - 1 : 0
value1 := math.max(-0.999, math.min(0.999, value1))
This normalized value then passes through the Fisher Transform calculation, which applies a logarithmic function to convert the data into a Gaussian normal distribution that naturally amplifies price extremes and turning points:
fisherTransform = 0.5 * math.log((1 + value1) / (1 - value1))
smoothedFisher = ta.ema(fisherTransform, fisherSmoothing)
The smoothed Fisher signal is then integrated with an exponential moving average to create a hybrid trend line that balances statistical precision with price-following behavior:
baseTrend = ta.ema(close, basePeriod)
fisherAdjustment = smoothedFisher * fisherSensitivity * close
fisherTrend = baseTrend + fisherAdjustment
To filter out false signals and adapt to market conditions, the system calculates dynamic threshold bands using volatility measurements:
dynamicRange = ta.atr(volatilityPeriod)
threshold = dynamicRange * volatilityMultiplier
upperThreshold = fisherTrend + threshold
lowerThreshold = fisherTrend - threshold
When price momentum pushes through these thresholds, the trend line locks onto the new level and maintains direction until the opposite threshold is breached:
if upperThreshold < trendLine
trendLine := upperThreshold
if lowerThreshold > trendLine
trendLine := lowerThreshold
🟢 Signal Interpretation
Bullish Candles (Green): indicate normalized price distribution favoring bulls with sustained buying momentum = Long/Buy opportunities
Bearish Candles (Red): indicate normalized price distribution favoring bears with sustained selling pressure = Short/Sell opportunities
Upper Band Zone: Area above middle level indicating statistically elevated trend strength with potential overbought conditions approaching mean reversion zones
Lower Band Zone: Area below middle level indicating statistically depressed trend strength with potential oversold conditions approaching mean reversion zones
Built-in Alert System: Automated notifications trigger when bullish or bearish states change, allowing you to act on significant developments without constantly monitoring the charts
Candle Coloring: Optional feature applies trend colors to price bars for visual consistency and clarity
Configuration Presets: Three parameter sets available - Default (balanced settings), Scalping (faster response with higher sensitivity), and Swing Trading (slower response with enhanced smoothing)
Color Customization: Four color schemes including Classic, Aqua, Cosmic, and Custom options for personalized chart aesthetics
Laguerre Filter Trend Navigator [QuantAlgo]🟢 Overview
The Laguerre Filter Trend Navigator employs advanced polynomial filtering mathematics to smooth price data while minimizing lag, creating a responsive yet stable trend-following system. Unlike simple moving averages that apply equal weight to historical data, the Laguerre filter uses recursive calculations with exponentially weighted polynomials to extract meaningful directional signals from noisy market conditions. Combined with dynamic volatility-adjusted boundaries, this creates an adaptive framework for identifying high-probability trend reversals and continuations across all tradable instruments and timeframes.
🟢 How It Works
The indicator leverages Laguerre polynomial filtering, a mathematical technique originally developed for digital signal processing applications. The core mechanism processes price data through four cascaded filter stages (L0, L1, L2, L3), each applying the gamma coefficient to recursively smooth incoming information while preserving phase relationships. This multi-stage architecture eliminates random fluctuations more effectively than traditional moving averages while responding quickly to genuine directional shifts.
The gamma coefficient serves as the primary smoothing control, determining how aggressively the filter dampens noise versus tracking price movements. Lower gamma values reduce smoothing and increase filter responsiveness, while higher values prioritize stability over reaction speed. Each filter stage compounds this effect, creating progressively smoother output that converges toward true underlying trend direction.
Surrounding the filtered price line, the algorithm constructs adaptive boundaries using dynamic volatility regime measurements. These calculations quantify current market turbulence independently of direction, expanding during active trading periods and contracting during quiet phases. By multiplying this volatility assessment by a user-defined scaling factor, the system creates self-adjusting bands that automatically conform to changing market conditions without manual intervention.
The trend-following engine monitors price position relative to these volatility-adjusted boundaries. When the upper band falls below the current trend line, the system shifts downward to track bearish momentum. Conversely, when the lower band rises above the trend line, it elevates to follow bullish movement. These crossover events trigger color transitions between bullish (green) and bearish (red) states, providing clear visual confirmation of directional changes validated by volatility-normalized thresholds.
🟢 How to Use
Green/Bullish Trend Line: Laguerre filter positioned in upward trajectory, indicating momentum-confirmed conditions favorable for establishing or maintaining long positions (buy)
Red/Bearish Trend Line: Laguerre filter trending downward, signaling regime-validated environment suitable for initiating or holding short positions (sell)
Rising Green Line: Accelerating bullish filter with expanding separation from price lows, demonstrating strengthening upward momentum and increasing confidence in trend persistence with optimal long entry timing
Declining Red Line: Steepening bearish filter creating growing distance from price highs, revealing intensifying downside pressure and enhanced probability of continued decline with favorable short positioning opportunities
Flattening Trends: Horizontal or oscillating filter movement regardless of color suggests directional uncertainty where price action contradicts filter positioning, potentially indicating consolidation phases or impending volatility expansion requiring cautious trade management
🟢 Pro Tips for Trading and Investing
→ Preset Selection Framework: Match presets to your trading style - Scalping preset employs aggressive gamma (0.4) with tight volatility bands (1.0x) for rapid signal generation on sub-15-minute charts, Day Trading preset balances responsiveness and stability for hourly timeframes, while Swing Trading preset maximizes smoothing (0.8 gamma) with wide bands (2.5x) to filter intraday noise on daily and weekly charts.
→ Gamma Coefficient Calibration: Adjust gamma based on market personality - reduce values (0.3-0.5) for highly liquid, fast-moving assets like major currency pairs and tech stocks where quick filter adaptation prevents lag-induced losses, increase values (0.7-0.9) for slower instruments or trending markets where excessive sensitivity generates false reversals and whipsaw trades.
→ Volatility Period Optimization: Tailor the volatility measurement window to information cycles. Deploy shorter lookback periods (7-10) for instruments with rapid regime changes like individual equities during earnings seasons, standard periods (14-20) for balanced assessment across general market conditions, and extended periods (21-30) for commodities and indices exhibiting persistent volatility characteristics.
→ Band Width Multiplier Adaptation: Scale boundary distance to current market phase. Contract multipliers (1.0-1.5) during range-bound consolidations to capture early breakout signals as soon as genuine momentum emerges, expand multipliers (2.0-3.0) during trending markets or high-volatility events to avoid premature exits caused by normal retracement activity rather than authentic reversals.
→ Multi-Timeframe Filter Alignment: Implement the indicator across multiple timeframes, using higher intervals (4H/Daily) to identify primary trend direction via filter slope and lower intervals (15min/1H) for precision entry timing when filter colors align, ensuring trades flow with dominant momentum while optimizing execution at favorable price levels.
→ Alert-Driven Systematic Execution: Configure trend change alerts to capture every filter-validated directional shift from bullish to bearish conditions or vice versa, enabling consistent signal response without continuous chart monitoring and eliminating emotional decision-making during critical transition moments.
Bayesian Trend Navigator [QuantAlgo]🟢 Overview
The Bayesian Trend Navigator uses Bayesian statistics to continuously update trend probabilities by combining long-term expectations (prior beliefs) and short-term observations (likelihood evidence), rather than relying solely on recent price data like many conventional indicators. This mathematical framework produces robust directional signals that naturally balance responsiveness with stability, making it suitable for traders and investors seeking statistically-grounded trend identification across diverse market environments and asset types.
🟢 How It Works
The indicator operates on Bayesian inference principles, a statistical method for updating beliefs when new evidence emerges. The system begins by establishing a prior belief - a long-term trend expectation calculated from historical price behavior. This represents the "baseline hypothesis" about market direction before considering recent developments.
Simultaneously, the algorithm collects recent market evidence through short-term trend analysis, representing the likelihood component. This captures what current price action suggests about directional momentum independent of historical context.
The core Bayesian engine then combines these elements using conjugate normal distributions and precision weighting. It calculates prior precision (inverse variance) and likelihood precision, combining them to determine a posterior precision. The resulting posterior mean represents the mathematically optimal trend estimate given both historical patterns and current reality. This posterior calculation includes intervals derived from the posterior variance, providing probabilistic confidence bounds around the trend estimate.
Finally, volatility-based standard deviation bands create adaptive boundaries around the Bayesian estimate. The trend line adjusts within these constraints, generating color transitions between bullish (green) and bearish (red) states when the posterior calculation crosses these probabilistic thresholds.
🟢 How to Use
Green/Bullish Trend Line: Posterior probability favoring upward momentum, indicating statistically favorable conditions for long positions (buy)
Red/Bearish Trend Line: Posterior probability favoring downward momentum, signaling mathematically supported timing for short positions (sell)
Rising Green Line: Strengthening bullish posterior as new evidence reinforces upward beliefs, showing increasing probabilistic confidence in trend continuation with favorable long entry conditions
Declining Red Line: Intensifying bearish posterior with accumulating downside evidence, indicating growing statistical certainty in downtrend persistence and optimal short positioning opportunities
Flattening Trends: Diminishing posterior confidence regardless of color suggests equilibrium between prior beliefs and contradictory evidence, potentially signaling consolidation or insufficient statistical clarity for high-conviction trades
🟢 Pro Tips for Trading and Investing
→ Preset Configuration Strategy: Deploy presets based on your trading horizon - Scalping preset maximizes evidence weight (0.8) for rapid Bayesian updates on 1-15 minute charts, Default preset balances prior and likelihood for general applications, while Swing Trading preset equalizes weights (0.5/0.5) for stable inference on hourly and daily timeframes.
→ Prior Weight Adjustment: Calibrate prior weight according to market regime - increase values (0.5-0.7) in stable trending markets where historical patterns remain predictive, decrease values (0.2-0.3) during regime changes or news-driven volatility when recent evidence should dominate the posterior calculation.
→ Evidence Period Tuning: Modify the evidence period based on information flow velocity. Use shorter periods (5-8 bars) for assets with continuous price discovery like cryptocurrencies, medium periods (10-15) for liquid stocks, and longer periods (15-20) for slower-moving markets to ensure adequate likelihood sample size.
→ Likelihood Weight Optimization: Adjust likelihood weight inversely to market noise levels. Higher values (0.7-0.8) work well in clean trending conditions where recent data is reliable, while lower values (0.4-0.6) help during choppy periods by maintaining stronger reliance on established prior beliefs.
→ Multi-Timeframe Bayesian Confluence: Apply the indicator across multiple timeframes, using higher timeframes (Daily/Weekly) to establish prior belief direction and lower timeframes (Hourly/15-minute) for likelihood-driven entry timing, ensuring posterior probabilities align across temporal scales for maximum statistical confidence.
→ Standard Deviation Multiplier Management: Adapt the multiplier to match current uncertainty levels. Use tighter multipliers (1.0-1.5) during low-volatility consolidations to capture early trend emergence, and wider multipliers (2.0-2.5) during high-volatility events to avoid premature signals caused by statistical noise rather than genuine posterior shifts.
→ Variance-Based Position Sizing: Monitor the implicit posterior variance through trend line stability - smooth consistent movements indicate low uncertainty warranting larger positions, while erratic fluctuations suggest high statistical uncertainty calling for reduced exposure until clearer probabilistic convergence emerges.
→ Alert-Based Probabilistic Execution: Utilize trend change alerts to capture every statistically significant posterior shift from bullish to bearish states or vice versa without constantly monitoring the charts.
MACD Forecast [Titans_Invest]MACD Forecast — The Future of MACD in Trading
The MACD has always been one of the most powerful tools in technical analysis.
But what if you could see where it’s going, instead of just reacting to what has already happened?
Introducing MACD Forecast — the natural evolution of the MACD Full , now taken to the next level. It’s the world’s first MACD designed not only to analyze the present but also to predict the future behavior of momentum.
By combining the classic MACD structure with projections powered by Linear Regression, this indicator gives traders an anticipatory, predictive view, redefining what’s possible in technical analysis.
Forget lagging indicators.
This is the smartest, most advanced, and most accurate MACD ever created.
🍟 WHY MACD FORECAST IS REVOLUTIONARY
Unlike the traditional MACD, which only reflects current and past price dynamics, the MACD Forecast uses regression-based projection models to anticipate where the MACD line, signal line, and histogram are heading.
This means traders can:
• See MACD crossovers before they happen.
• Spot trend reversals earlier than most.
• Gain an unprecedented timing advantage in both discretionary and automated trading.
In other words: this indicator lets you trade ahead of time.
🔮 FORECAST ENGINE — POWERED BY LINEAR REGRESSION
At its core, the MACD Forecast integrates Linear Regression (ta.linreg) to project the MACD’s future behavior with exceptional accuracy.
Projection Modes:
• Flat Projection: Assumes trend continuity at the current level.
• LinReg Projection: Applies linear regression across N periods to mathematically forecast momentum shifts.
This dual system offers both a conservative and adaptive view of market direction.
📐 ACCURACY WITH FULL CUSTOMIZATION
Just like the MACD Full, this new version comes with 20 customizable buy-entry conditions and 20 sell-entry conditions — now enhanced with forecast-based rules that anticipate crossovers and trend reversals.
You’re not just reacting — you’re strategizing ahead of time.
⯁ HOW TO USE MACD FORECAST❓
The MACD Forecast is built on the same foundation as the classic MACD, but with predictive capabilities.
Step 1 — Spot Predicted Crossovers:
Watch for forecasted bullish or bearish crossovers. These signals anticipate when the MACD line will cross the signal line in the future, letting you prepare trades before the move.
Step 2 — Confirm with Histogram Projection:
Use the projected histogram to validate momentum direction. A rising histogram signals strengthening bullish momentum, while a falling projection points to weakening or bearish conditions.
Step 3 — Combine with Multi-Timeframe Analysis:
Use forecasts across multiple timeframes to confirm signal strength (e.g., a 1h forecast aligned with a 4h forecast).
Step 4 — Set Entry Conditions & Automation:
Customize your buy/sell rules with the 20 forecast-based conditions and enable automation for bots or alerts.
Step 5 — Trade Ahead of the Market:
By preparing for future momentum shifts instead of reacting to the past, you’ll always stay one step ahead of lagging traders.
🤖 BUILT FOR AUTOMATION AND BOTS 🤖
Whether for manual trading, quantitative strategies, or advanced algorithms, the MACD Forecast was designed to integrate seamlessly with automated systems.
With predictive logic at its core, your strategies can finally react to what’s coming, not just what already happened.
🥇 WHY THIS INDICATOR IS UNIQUE 🥇
• World’s first MACD with Linear Regression Forecasting
• Predictive Crossovers (before they appear on the chart)
• Maximum flexibility with Long & Short combinations — 20+ fully configurable conditions for tailor-made strategies
• Fully automatable for quantitative systems and advanced bots
This isn’t just an update.
It’s the final evolution of the MACD.
______________________________________________________
🔹 CONDITIONS TO BUY 📈
______________________________________________________
• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
🔹 MACD > Signal Smoothing
🔹 MACD < Signal Smoothing
🔹 Histogram > 0
🔹 Histogram < 0
🔹 Histogram Positive
🔹 Histogram Negative
🔹 MACD > 0
🔹 MACD < 0
🔹 Signal > 0
🔹 Signal < 0
🔹 MACD > Histogram
🔹 MACD < Histogram
🔹 Signal > Histogram
🔹 Signal < Histogram
🔹 MACD (Crossover) Signal
🔹 MACD (Crossunder) Signal
🔹 MACD (Crossover) 0
🔹 MACD (Crossunder) 0
🔹 Signal (Crossover) 0
🔹 Signal (Crossunder) 0
🔮 MACD (Crossover) Signal Forecast
🔮 MACD (Crossunder) Signal Forecast
______________________________________________________
______________________________________________________
🔸 CONDITIONS TO SELL 📉
______________________________________________________
• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
🔸 MACD > Signal Smoothing
🔸 MACD < Signal Smoothing
🔸 Histogram > 0
🔸 Histogram < 0
🔸 Histogram Positive
🔸 Histogram Negative
🔸 MACD > 0
🔸 MACD < 0
🔸 Signal > 0
🔸 Signal < 0
🔸 MACD > Histogram
🔸 MACD < Histogram
🔸 Signal > Histogram
🔸 Signal < Histogram
🔸 MACD (Crossover) Signal
🔸 MACD (Crossunder) Signal
🔸 MACD (Crossover) 0
🔸 MACD (Crossunder) 0
🔸 Signal (Crossover) 0
🔸 Signal (Crossunder) 0
🔮 MACD (Crossover) Signal Forecast
🔮 MACD (Crossunder) Signal Forecast
______________________________________________________
______________________________________________________
🔮 Linear Regression Function 🔮
______________________________________________________
• Our indicator includes MACD forecasts powered by linear regression.
Forecast Types:
• Flat: Assumes prices will stay the same.
• Linreg: Makes a 'Linear Regression' forecast for n periods.
Technical Information:
• Function: ta.linreg()
Parameters:
• source: Source price series.
• length: Number of bars (period).
• offset : Offset.
• return: Linear regression curve.
______________________________________________________
______________________________________________________
⯁ UNIQUE FEATURES
______________________________________________________
Linear Regression: (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
Linear Regression (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
______________________________________________________
📜 SCRIPT : MACD Forecast
🎴 Art by : @Titans_Invest & @DiFlip
👨💻 Dev by : @Titans_Invest & @DiFlip
🎑 Titans Invest — The Wizards Without Gloves 🧤
✨ Enjoy!
______________________________________________________
o Mission 🗺
• Inspire Traders to manifest Magic in the Market.
o Vision 𐓏
• To elevate collective Energy 𐓷𐓏
🎗️ In memory of João Guilherme — your light will live on forever.
Maple Algorithm_GOLDMaple Algorithm – AI-Powered Gold Indicator
Maple Algorithm is an AI-inspired indicator designed specifically around the price behavior of Gold (XAUUSD).
It automatically calculates and plots take-profit (TP) and stop-loss (SL) levels based on dynamic market conditions, allowing traders to capture precise entries and exits.
✨ Key Features
AI-driven adaptive model trained on Gold’s market structure
Auto-generated TP/SL zones for precision trading
Compatible with your own strategies — scale from 1:2 RRR up to even higher setups
Optimized for scalping and short-term momentum bursts
⚠️ Disclaimer:
This indicator is for educational and research purposes only. It does not guarantee future results. Always test thoroughly before applying to live trading.
VOLUME Full [Titans_Invest]VOLUME Full
Designed for traders who want to take volume analysis to the next level.
This version delivers deeper insight into volume activity, integrating multiple customizable filters to highlight key buying and selling pressure. It's a comprehensive solution for volume-based decision-making.
⯁ WHAT IS THE VOLUME❓
The Volume indicator is a fundamental technical analysis tool that measures the number of shares or contracts traded in a security or market during a given period. It helps traders and investors understand the strength or weakness of a price movement, confirm trends, and predict potential reversals. Volume is typically displayed as a histogram below a price chart, with each bar representing the volume traded during a specific time interval.
⯁ HOW TO USE THE VOLUME❓
The Volume indicator can be used in several ways to enhance trading decisions:
• Trend Confirmation: High volume during a price move confirms the strength of that trend, while low volume can indicate a weak or unsustainable trend.
• Breakouts: A price breakout from a pattern or range accompanied by high volume is more likely to be valid and sustainable.
• Divergence: When the price moves in one direction and volume moves in the opposite direction, it can signal a potential reversal.
• Overbought/Oversold Conditions: Extreme volume levels can sometimes indicate that an asset is overbought or oversold, though this is less straightforward than with oscillators like the RSI.
⯁ ENTRY CONDITIONS
The conditions below are fully flexible and allow for complete customization of the signal.
______________________________________________________
🔹 CONDITIONS TO BUY 📈
______________________________________________________
▪︎ Signal Validity: The signal will remain valid for X bars .
▪︎ Signal Sequence: Configurable as AND or OR .
🔹 volume Positive
🔹 volume Negative
🔹 volume > volume
🔹 volume < volume
🔹 volume > volume_MA
🔹 volume > volume_MA * Trigger Signal (close > open)
🔹 volume > volume_MA * Trigger Signal (Keep State P)
🔹 volume > volume_MA * Trigger Signal (close < open)
🔹 volume > volume_MA * Trigger Signal (Keep State N)
______________________________________________________
______________________________________________________
🔸 CONDITIONS TO SELL 📉
______________________________________________________
▪︎ Signal Validity: The signal will remain valid for X bars .
▪︎ Signal Sequence: Configurable as AND or OR .
🔸 volume Positive
🔸 volume Negative
🔸 volume > volume
🔸 volume < volume
🔸 volume > volume_MA
🔸 volume > volume_MA * Trigger Signal (close > open)
🔸 volume > volume_MA * Trigger Signal (Keep State P)
🔸 volume > volume_MA * Trigger Signal (close < open)
🔸 volume > volume_MA * Trigger Signal (Keep State N)
______________________________________________________
______________________________________________________
🤖 AUTOMATION 🤖
• You can automate the BUY and SELL signals of this indicator.
______________________________________________________
______________________________________________________
⯁ UNIQUE FEATURES
______________________________________________________
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Plot Labels in the Graph Above: BUY/SELL
Displays Positive & Negative Volume.
Automate and Monitor Signals/Alerts: BUY/SELL
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Displays Positive & Negative Volume.
Automate & Monitor Signals/Alerts: BUY/SELL
______________________________________________________
📜 SCRIPT : VOLUME Full
🎴 Art by : @Titans_Invest & @DiFlip
👨💻 Dev by : @Titans_Invest & @DiFlip
🎑 Titans Invest — The Wizards Without Gloves 🧤
✨ Enjoy!
______________________________________________________
o Mission 🗺
• Inspire Traders to manifest Magic in the Market.
o Vision 𐓏
• To elevate collective Energy 𐓷𐓏
Apex Edge Sentinel - Stop Loss HUDApex Edge – ATR Sentinel Stop Loss HUD
The Apex Edge – ATR Sentinel is a complete stop-loss intelligence system built as a clean, always-on HUD.
It delivers institutional-level risk guidance by calculating and displaying live ATR-based stop levels for both long and short trades at multiple risk tolerances.
Forget cluttered charts and repainting lines — Sentinel gives you a clear stop-loss reference panel that updates dynamically with every bar.
✅ Features
• Triple ATR Multipliers
User-defined (e.g. x1.5 / x2.0 / x2.5). Compare tight, medium, and wide stops instantly.
• Dual-Side SL Levels
Both Long and Short safe stop prices displayed side by side. No more guessing trend
bias.
• ATR Transparency
HUD shows ATR(length) so you always know the calculation basis. Default = 14, adjustable
to your style.
• ATR Regime Meter
Detects volatility conditions (LOW / NORMAL / HIGH) by comparing ATR to its SMA. Helps
you avoid over-tight stops in high-volatility markets.
• Tick-Aware Rounding
Stop levels auto-rounded to the instrument’s tick size (Gold = 0.10, FX = 0.0001, indices =
whole points).
Custom HUD Design
• Location: Top/Bottom, Left/Right
• Sizes: Compact / Medium / Large (desktop or mobile)
• Opacity control (25% default Apex styling)
How to Use
1. Load Sentinel on your chart.
2. Check the HUD:
• ATR(14): 2.6 → base volatility measure.
• x1.5 / x2.0 / x2.5 → instant SL levels for both long & short trades.
3. Before entering a trade → decide which multiplier matches your style (tight scalper vs wider swing).
4. Manually place your SL at the level displayed in the HUD.
Sentinel works as both:
• A pre-trade check (is ATR stop too wide for my RR?).
• A live risk compass (updated stop levels every bar).
Why Apex Sentinel?
Most ATR stop indicators clutter charts with lagging lines or repainting trails. Sentinel strips it back to what matters:
• The numbers.
• The risk levels.
• The context.
It’s a pure stop-loss HUD, designed for serious traders who want clarity, discipline, and instant reference points across any market or timeframe.
Notes
• This is a HUD-only system (no automatic SL line). Traders manually apply the SL level
shown in the panel.
• Defaults: ATR(14), multipliers 1.5 / 2.0 / 2.5. Adjust to your trading style.
• Best used on intraday pairs like XAUUSD, EURUSD, indices, but works universally.
Apex Edge Philosophy: Clean. Smart. Institutional.
No clutter. No gimmicks. Just precision tools for modern markets.
Bollinger Adaptive Trend Navigator [QuantAlgo]🟢 Overview
The Bollinger Adaptive Trend Navigator synthesizes volatility channel analysis with variable smoothing mechanics to generate trend identification signals. It uses price positioning within Bollinger Band structures to modify moving average responsiveness, while incorporating ATR calculations to establish trend line boundaries that constrain movement during volatile periods. The adaptive nature makes this indicator particularly valuable for traders and investors working across various asset classes including stocks, forex, commodities, and cryptocurrencies, with effectiveness spanning multiple timeframes from intraday scalping to longer-term position analysis.
🟢 How It Works
The core mechanism calculates price position within Bollinger Bands and uses this positioning to create an adaptive smoothing factor:
bbPosition = bbUpper != bbLower ? (source - bbLower) / (bbUpper - bbLower) : 0.5
adaptiveFactor = (bbPosition - 0.5) * 2 * adaptiveMultiplier * bandWidthRatio
alpha = math.max(0.01, math.min(0.5, 2.0 / (bbPeriod + 1) * (1 + math.abs(adaptiveFactor))))
This adaptive coefficient drives an exponential moving average that responds more aggressively when price approaches Bollinger Band extremes:
var float adaptiveTrend = source
adaptiveTrend := alpha * source + (1 - alpha) * nz(adaptiveTrend , source)
finalTrend = 0.7 * adaptiveTrend + 0.3 * smoothedCenter
ATR-based volatility boundaries constrain the final trend line to prevent excessive movement during volatile periods:
volatility = ta.atr(volatilityPeriod)
upperBound = bollingerTrendValue + (volatility * volatilityMultiplier)
lowerBound = bollingerTrendValue - (volatility * volatilityMultiplier)
The trend line direction determines bullish or bearish states through simple slope comparison, with the final output displaying color-coded signals based on the synthesis of Bollinger positioning, adaptive smoothing, and volatility constraints (green = long/buy, red = short/sell).
🟢 Signal Interpretation
Rising Trend Line (Green): Indicates upward direction based on Bollinger positioning and adaptive smoothing = Potential long/buy opportunity
Falling Trend Line (Red): Indicates downward direction based on Bollinger positioning and adaptive smoothing = Potential short/sell opportunity
Built-in Alert System: Automated notifications trigger when bullish or bearish states change, allowing you to act on significant development without constantly monitoring the charts
Candle Coloring: Optional feature applies trend colors to price bars for visual consistency
Configuration Presets: Three parameter sets available - Default (standard settings), Scalping (faster response), and Swing Trading (slower response)
Sine Weighted Trend Navigator [QuantAlgo]🟢 Overview
The Sine Weighted Trend Navigator utilizes trigonometric mathematics to create a trend-following system that adapts to various market volatility. Unlike traditional moving averages that apply uniform weights, this indicator employs sine wave calculations to distribute weights across historical price data, creating a more responsive yet smooth trend measurement. Combined with volatility-adjusted boundaries, it produces actionable directional signals for traders and investors across various market conditions and asset classes.
🟢 How It Works
At its core, the indicator applies sine wave mathematics to weight historical prices. The system generates angular values across the lookback period and transforms them through sine calculations, creating a weight distribution pattern that naturally emphasizes recent price action while preserving smoothness. The phase shift feature allows rotation of this weighting pattern, enabling adjustment of the indicator's responsiveness to different market conditions.
Surrounding this sine-weighted calculation, the system establishes volatility-responsive boundaries through market volatility analysis. These boundaries expand and contract based on current market conditions, creating a dynamic framework that helps distinguish meaningful trend movements from random price fluctuations.
The trend determination logic compares the sine-weighted value against these adaptive boundaries. When the weighted value exceeds the upper boundary, it signals upward momentum. When it drops below the lower boundary, it indicates downward pressure. This comparison drives the color transitions of the main trend line, shifting between bullish (green) and bearish (red) states to provide clear directional guidance on price charts.
🟢 How to Use
Green/Bullish Trend Line: Rising momentum indicating optimal conditions for long positions (buy)
Red/Bearish Trend Line: Declining momentum signaling favorable timing for short positions (sell)
Steepening Green Line: Accelerating bullish momentum with increasing sine-weighted values indicating strengthening upward pressure and high-probability trend continuation
Steepening Red Line: Intensifying bearish momentum with declining sine-weighted calculations suggesting persistent downward pressure and optimal shorting opportunities
Flattening Trend Lines: Gradual reduction in directional momentum regardless of color may indicate approaching consolidation or trend exhaustion requiring position management review
🟢 Pro Tips for Trading and Investing
→ Preset Strategy Selection: Utilize the built-in presets strategically - Scalping preset for ultra-responsive 1-15 minute charts, Default preset for balanced general trading, and Swing Trading preset for 1-4 hour charts and multi-day positions.
→ Phase Shift Optimization: Fine-tune the phase shift parameter based on market bias - use positive values (0.1-0.5) in trending bull markets to enhance uptrend sensitivity, negative values (-0.1 to -0.5) in bear markets for improved downtrend detection, and zero for balanced neutral market conditions.
→ Multiplier Calibration: Adjust the multiplier according to market volatility and trading style. Use lower values (0.5-1.0) for tight, responsive signals in stable markets, higher values (2.0-3.0) during earnings seasons or high-volatility periods to filter noise and reduce whipsaws.
→ Sine Period Adaptation: Customize the sine weighted period based on your trading timeframe and market conditions. Use 5-14 for day trading to capture short-term momentum shifts, 14-25 for swing trading to balance responsiveness with reliability, and 25-50 for position trading to maintain long-term trend clarity.
→ Multi-Timeframe Sine Validation: Apply the indicator across multiple timeframes simultaneously, using higher timeframes (4H/Daily) for overall trend bias and lower timeframes (15m/1H) for entry timing, ensuring sine-weighted calculations align across different time horizons.
→ Alert-Driven Systematic Execution: Leverage the built-in trend change alerts to eliminate emotional decision-making and capture every mathematically-confirmed trend transition, particularly valuable for traders managing multiple instruments or those unable to monitor charts continuously.
→ Risk Management: Increase position sizes during strong directional sine-weighted momentum while reducing exposure during frequent color changes that indicate mathematical uncertainty or ranging market conditions lacking clear directional bias.
RSI Trend Navigator [QuantAlgo]🟢 Overview
The RSI Trend Navigator integrates RSI momentum calculations with adaptive exponential moving averages and ATR-based volatility bands to generate trend-following signals. The indicator applies variable smoothing coefficients based on RSI readings and incorporates normalized momentum adjustments to position a trend line that responds to both price action and underlying momentum conditions.
🟢 How It Works
The indicator begins by calculating and smoothing the RSI to reduce short-term fluctuations while preserving momentum information:
rsiValue = ta.rsi(source, rsiPeriod)
smoothedRSI = ta.ema(rsiValue, rsiSmoothing)
normalizedRSI = (smoothedRSI - 50) / 50
It then creates an adaptive smoothing coefficient that varies based on RSI positioning relative to the midpoint:
adaptiveAlpha = smoothedRSI > 50 ? 2.0 / (trendPeriod * 0.5 + 1) : 2.0 / (trendPeriod * 1.5 + 1)
This coefficient drives an adaptive trend calculation that responds more quickly when RSI indicates bullish momentum and more slowly during bearish conditions:
var float adaptiveTrend = source
adaptiveTrend := adaptiveAlpha * source + (1 - adaptiveAlpha) * nz(adaptiveTrend , source)
The normalized RSI values are converted into price-based adjustments using ATR for volatility scaling:
rsiAdjustment = normalizedRSI * ta.atr(14) * sensitivity
rsiTrendValue = adaptiveTrend + rsiAdjustment
ATR-based bands are constructed around this RSI-adjusted trend value to create dynamic boundaries that constrain trend line positioning:
atr = ta.atr(atrPeriod)
deviation = atr * atrMultiplier
upperBound = rsiTrendValue + deviation
lowerBound = rsiTrendValue - deviation
The trend line positioning uses these band constraints to determine its final value:
if upperBound < trendLine
trendLine := upperBound
if lowerBound > trendLine
trendLine := lowerBound
Signal generation occurs through directional comparison of the trend line against its previous value to establish bullish and bearish states:
trendUp = trendLine > trendLine
trendDown = trendLine < trendLine
if trendUp
isBullish := true
isBearish := false
else if trendDown
isBullish := false
isBearish := true
The final output colors the trend line green during bullish states and red during bearish states, creating visual buy/long and sell/short opportunity signals based on the combined RSI momentum and volatility-adjusted trend positioning.
🟢 Signal Interpretation
Rising Trend Line (Green): Indicates upward momentum where RSI influence and adaptive smoothing favor continued price advancement = Potential buy/long positions
Declining Trend Line (Red): Indicates downward momentum where RSI influence and adaptive smoothing favor continued price decline = Potential sell/short positions
Flattening Trend Lines: Occur when momentum weakens and the trend line slope approaches neutral, suggesting potential consolidation before the next move
Built-in Alert System: Automated notifications trigger when bullish or bearish states change, sending "RSI Trend Bullish Signal" or "RSI Trend Bearish Signal" messages for timely entry/exit
Color Bar Candles Option: Optional candle coloring feature that applies the same green/red trend colors to price bars, providing additional visual confirmation of the current trend direction
Linear Regression Trend Navigator [QuantAlgo]🟢 Overview
The Linear Regression Trend Navigator is a trend-following indicator that combines statistical regression analysis with adaptive volatility bands to identify and track dominant market trends. It employs linear regression mathematics to establish the underlying trend direction, while dynamically adjusting trend boundaries based on standard deviation calculations to filter market noise and maintain trend continuity. The result is a straightforward visual system where green indicates bullish conditions favoring buy/long positions, and red signals bearish conditions supporting sell/short trades.
🟢 How It Works
The indicator operates through a three-phase computational process that transforms raw price data into adaptive trend signals. In the first phase, it calculates a linear regression line over the specified period, establishing the mathematical best-fit line through recent price action to determine the underlying directional bias. This regression line serves as the foundation for trend analysis by smoothing out short-term price variations while preserving the essential directional characteristics.
The second phase constructs dynamic volatility boundaries by calculating the standard deviation of price movements over the defined period and applying a user-adjustable multiplier. These upper and lower bounds create a volatility-adjusted channel around the regression line, with wider bands during volatile periods and tighter bands during stable conditions. This adaptive boundary system operates entirely behind the scenes, ensuring the trend signal remains relevant across different market volatility regimes without cluttering the visual display.
In the final phase, the system generates a simple trend line that dynamically positions itself within the volatility boundaries. When price action pushes the regression line above the upper bound, the trend line adjusts to the upper boundary level. Conversely, when the regression line falls below the lower bound, the trend line moves to the lower boundary. The result is a single colored line that transitions between green (rising trend line = buy/long) and red (declining trend line = sell/short).
🟢 How to Use
Green Trend Line: Upward momentum indicating favorable conditions for long positions, buy signals, and bullish strategies
Red Trend Line: Downward momentum signaling optimal timing for short positions, sell signals, and bearish approaches
Rising Green Line: Accelerating bullish momentum with steepening angles indicating strengthening upward pressure and potential for trend continuation
Declining Red Line: Intensifying bearish momentum with increasing negative slopes suggesting persistent downward pressure and shorting opportunities
Flattening Trend Lines: Gradual reduction in slope regardless of color may indicate approaching consolidation or momentum exhaustion requiring position review
🟢 Pro Tips for Trading and Investing
→ Entry/Exit Timing: Trade exclusively on band color transitions rather than price patterns, as each color change represents a statistically-confirmed shift that has passed through volatility filtering, providing higher probability setups than traditional technical analysis.
→ Parameter Optimization for Asset Classes: Customize the linear regression period based on your trading style. For example, use 5-10 bars for day trading to capture short-term statistical shifts, 14-20 for swing trading to balance responsiveness with stability, and 25-50 for position trading to filter out medium-term noise.
→ Volatility Calibration Strategy: Adjust the standard deviation multiplier according to market volatility. For instance, increase to 2.0+ during high-volatility periods like earnings or news events to reduce false signals, decrease to 1.0-1.5 during stable market conditions to maintain sensitivity to genuine trends.
→ Cross-Timeframe Statistical Validation: Apply the indicator across multiple timeframes simultaneously, using higher timeframes for directional bias and lower timeframes for entry timing.
→ Alert-Based Systematic Trading: Use built-in alerts to eliminate discretionary decision-making and ensure you capture every statistically-significant trend change, particularly effective for traders who cannot monitor charts continuously.
→ Risk Allocation Based on Signal Strength: Increase position sizes during periods of strong directional movement while reducing exposure during frequent band color changes that indicate statistical uncertainty or ranging conditions.
Sequential Pattern Strength [QuantAlgo]🟢 Overview
The Sequential Pattern Strength indicator measures the power and sustainability of consecutive price movements by tracking unbroken sequences of up or down closes. It incorporates sequence quality assessment, price extension analysis, and automatic exhaustion detection to help traders identify when strong trends are losing momentum and approaching potential reversal or continuation points.
🟢 How It Works
The indicator's key insight lies in its sequential pattern tracking system, where pattern strength is measured by analyzing consecutive price movements and their sustainability:
if close > close
upSequence := upSequence + 1
downSequence := 0
else if close < close
downSequence := downSequence + 1
upSequence := 0
The system calculates sequence quality by measuring how "perfect" the consecutive moves are:
perfectMoves = math.max(upSequence, downSequence)
totalMoves = math.abs(bar_index - ta.valuewhen(upSequence == 1 or downSequence == 1, bar_index, 0))
sequenceQuality = totalMoves > 0 ? perfectMoves / totalMoves : 1.0
First, it tracks price extension from the sequence starting point:
priceExtension = (close - sequenceStartPrice) / sequenceStartPrice * 100
Then, pattern exhaustion is identified when sequences become overextended:
isExhausted = math.abs(currentSequence) >= maxSequence or
math.abs(priceExtension) > resetThreshold * math.abs(currentSequence)
Finally, the pattern strength combines sequence length, quality, and price movement with momentum enhancement:
patternStrength = currentSequence * sequenceQuality * (1 + math.abs(priceExtension) / 10)
enhancedSignal = patternStrength + momentum * 10
signal = ta.ema(enhancedSignal, smooth)
This creates a sequence-based momentum indicator that combines consecutive movement analysis with pattern sustainability assessment, providing traders with both directional signals and exhaustion insights for entry/exit timing.
🟢 Signal Interpretation
Positive Values (Above Zero): Sequential pattern strength indicating bullish momentum with consecutive upward price movements and sustained buying pressure = Long/Buy opportunities
Negative Values (Below Zero): Sequential pattern strength indicating bearish momentum with consecutive downward price movements and sustained selling pressure = Short/Sell opportunities
Zero Line Crosses: Pattern transitions between bullish and bearish regimes, indicating potential trend changes or momentum shifts when sequences break
Upper Threshold Zone: Area above maximum sequence threshold (2x maxSequence) indicating extremely strong bullish patterns approaching exhaustion levels
Lower Threshold Zone: Area below negative threshold (-2x maxSequence) indicating extremely strong bearish patterns approaching exhaustion levels
Mean Reversion Channel [QuantAlgo]🟢 Overview
The Mean Reversion Channel indicator is a range-bound trading system that combines dynamic price channels with momentum-weighted analysis to identify optimal mean reversion opportunities. It creates adaptive upper and lower reversion zones based on recent price action and volatility, while incorporating a momentum-biased equilibrium line that shifts based on volume-weighted price momentum. This creates a three-tier system where traders and investors can identify overbought and oversold conditions within established ranges, detect momentum exhaustion points, and anticipate channel breakouts or breakdowns. This indicator is particularly valuable for strategic dollar cost averaging (DCA) strategies, as it helps identify optimal accumulation zones during oversold conditions and provides tactical risk management levels for systematic investment approaches across different market conditions and asset classes.
🟢 How It Works
The indicator employs a four-stage calculation process that transforms raw price and volume data into actionable mean reversion signals. First, it establishes the base channel by calculating the highest high and lowest low over a user-defined lookback period, creating the foundational price range for mean reversion analysis. This channel adapts continuously as new price data becomes available, ensuring the system remains relevant to current market conditions.
In the second stage, the system calculates volume-weighted momentum by combining price momentum with volume activity. The momentum calculation takes the price change over a specified period and multiplies it by the volume ratio (current volume versus 20-period average volume, for instance) and a volume factor multiplier. This creates momentum readings that are more significant during high-volume periods and less influential during low-volume conditions.
The third stage creates the dynamic reversion zones using Average True Range (ATR) calculations. The upper reversion zone is positioned below the channel high by an ATR-based distance, while the lower reversion zone is positioned above the channel low. These zones contract when momentum is negative (upper zone) or positive (lower zone), creating asymmetric reversion bands that adapt to momentum conditions.
The final stage establishes the momentum-biased equilibrium line by calculating the midpoint between the reversion zones and adjusting it based on momentum bias. When momentum is positive, the equilibrium shifts upward; when negative, it shifts downward. This creates a dynamic reference level that helps identify when price action is moving against the prevailing momentum trend, signaling potential mean reversion opportunities.
🟢 How to Use
1. Mean Reversion Signal Identification
Lower Reversion Zone Signals: When price reaches or falls below the lower reversion zone with bearish momentum, the system generates potential long/buy entry signals indicating oversold conditions within the established range.
Upper Reversion Zone Signals: When price reaches or exceeds the upper reversion zone with bullish momentum, the system generates potential short/sell entry signals indicating overbought conditions.
2. Equilibrium Line Analysis and Momentum Exhaustion
Equilibrium Breaks: The dynamic equilibrium line serves as a momentum bias indicator within the channel. Price crossing above equilibrium suggests shifting to bullish bias, while breaks below indicate bearish bias development within the mean reversion framework.
Momentum Exhaustion Signals: The system identifies momentum exhaustion when price breaks through the equilibrium line opposite to the prevailing momentum direction. Bullish exhaustion occurs when price falls below equilibrium despite positive momentum, while bearish exhaustion happens when price rises above equilibrium during negative momentum periods.
3. Channel Expansion and Breakout Detection
Channel Boundary Breaks: When price breaks above the upper reversion zone or below the lower reversion zone, it signals potential channel expansion or false breakout conditions. These events often precede significant trend changes or range expansion phases.
Range Expansion Alerts: Breaks above the channel high or below the channel low indicate potential breakout from the mean reversion range, suggesting trend continuation or new directional movement beyond the established boundaries.
🟢 Pro Tips for Trading and Investing
→ Strategic DCA Optimization: Use the lower reversion zone as primary accumulation levels for dollar cost averaging strategies. When price reaches oversold conditions with bearish momentum exhaustion signals, it often represents optimal entry points for systematic investment programs, allowing investors to accumulate positions at statistically favorable price levels within the established range.
→ DCA Pause and Acceleration Signals : Monitor equilibrium line breaks to adjust DCA frequency and amounts. When price consistently trades below equilibrium with momentum exhaustion signals, consider accelerating DCA intervals or increasing investment amounts. Conversely, when price reaches upper reversion zones, consider pausing or reducing DCA activity until more favorable conditions return.
→ Momentum Divergence Detection: Watch for divergences between price action and momentum readings within the channel. When price makes new lows but momentum shows improvement, or price makes new highs with deteriorating momentum, these signal high-probability mean reversion setups ideal for contrarian investment approaches.
→ Alert-Based Systematic Investing/Trading: Utilize the comprehensive alert system for automated DCA triggers. Set up alerts for lower reversion zone touches combined with momentum exhaustion signals to create systematic entry points that remove emotional decision-making from long-term investment strategies, particularly effective for volatile assets where timing improvements can significantly impact overall returns.
