Scalp Hunter [Scalping-Algo]═══════════════════════════════════════════════════════════════════════════════
🎯 SCALP HUNTER
Precision ATR Momentum System for Fast Timeframes
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📌 OVERVIEW
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Scalp Hunter is a high-accuracy scalping indicator designed specifically for
low timeframe trading (3M, 4M, 5M). It combines ATR-based trailing stops with
multiple confirmation filters to deliver clean, actionable signals.
✅ No Repaint
✅ No Delay
✅ Confirmed Signals Only
✅ Multi-Filter Validation
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⚙️ HOW IT WORKS
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The indicator uses an ATR Trailing Stop as its core engine. When price crosses
the trail line, a potential signal is generated. But here's what makes it
accurate — signals must pass through 4 additional filters:
│
├─ 📊 PRICE ACTION FILTER
│ • Candle must close in signal direction
│ • Body size > 50% of full candle range
│ • Confirms strong momentum, not weak wicks
│
├─ 📈 VOLUME FILTER
│ • Volume must exceed 1.1x of 10-period average
│ • Filters out low-conviction moves
│ • Toggle on/off in settings
│
├─ 📉 EMA TREND FILTER
│ • Long signals: price must be above 21 EMA
│ • Short signals: price must be below 21 EMA
│ • Keeps you trading with the trend
│
└─ 🔥 MOMENTUM FILTER (RSI)
• RSI must confirm direction (>50 for longs, <50 for shorts)
• Avoids overbought/oversold extremes
• Fast 7-period RSI tuned for scalping
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🎨 VISUAL GUIDE
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🟢 GREEN TRIANGLE (▲) = Long Entry Signal
🔴 RED TRIANGLE (▼) = Short Entry Signal
━━ GREEN LINE = Bullish Trail Stop (support)
━━ RED LINE = Bearish Trail Stop (resistance)
🟢 GREEN BARS = Bullish Trend Active
🔴 RED BARS = Bearish Trend Active
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📖 HOW TO USE
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STEP 1: Add to Chart
• Apply indicator to 3M, 4M, or 5M chart
• Works on any liquid market (crypto, forex, stocks, futures)
STEP 2: Wait for Signal
• 🟢 Triangle appears below bar = LONG opportunity
• 🔴 Triangle appears above bar = SHORT opportunity
• Signal fires at bar OPEN (no repaint, you can act immediately)
STEP 3: Entry
• Enter at market or use limit order near signal bar close
• Trail stop line shows your initial stop level
STEP 4: Stop Loss
• Place stop just beyond the trail line
• Long: stop below green trail line
• Short: stop above red trail line
STEP 5: Take Profit
• Option A: Fixed R:R (1:1.5 or 1:2 recommended)
• Option B: Trail your stop using the indicator line
• Option C: Exit when opposite signal appears
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⚡ RECOMMENDED SETTINGS
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For 3M / 4M / 5M (Default - Aggressive Scalping):
• ATR Sensitivity: 0.8
• ATR Length: 8
• RSI Length: 7
• EMA Length: 21
• All filters: ON
For 15M / 30M (Slower Scalps):
• ATR Sensitivity: 1.0
• ATR Length: 10
• RSI Length: 10
• EMA Length: 34
• All filters: ON
For Volatile Markets (Crypto/News Events):
• ATR Sensitivity: 1.2
• ATR Length: 12
• Volume Filter: ON (important!)
• Other filters: ON
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🔔 ALERTS
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Three alert conditions available:
📲 "Scalp Long" → Fires on long entry signal
📲 "Scalp Short" → Fires on short entry signal
📲 "Any Signal" → Fires on both
To set up:
1. Click "Alert" button (clock icon)
2. Select "Scalp Hunter "
3. Choose condition
4. Set notification method (popup, email, webhook, mobile)
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⚠️ RISK DISCLAIMER
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Trading involves substantial risk. This indicator is a tool, not financial
advice. Past performance does not guarantee future results. Always:
• Use proper position sizing
• Set stop losses on every trade
• Never risk more than you can afford to lose
• Backtest before live trading
• Combine with your own analysis
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💡 TIPS FOR BEST RESULTS
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✦ Trade during high-volume sessions (London/NY open)
✦ Avoid signals during major news releases
✦ Confirm with higher timeframe trend
✦ Best results on liquid pairs/assets
✦ Keep all filters ON for highest accuracy
✦ Turn off filters only if you need more signals
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📊 WHAT MAKES THIS DIFFERENT
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Most ATR trailing indicators give too many signals. Scalp Hunter is different:
❌ Other indicators: Signal on every trail cross
✅ Scalp Hunter: Signal only when 5 conditions align
This means fewer trades, but higher probability setups.
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外汇
EDUVEST QQE Grade System - S/A/B/C Signal ClassificationEDUVEST QQE Grade System - S/A/B/C Signal Classification
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█ ORIGINALITY
This indicator introduces a unique grading system (S/A/B/C) for QQE signals, combining traditional QQE analysis with SMC (Smart Money Concepts) price zones and trading session filters. Unlike standard QQE indicators that show all signals equally, this version classifies signals by quality to help traders focus on the highest probability setups.
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█ WHAT IT DOES
- Generates BUY/SELL signals with S/A/B/C grade classification
- Automatically detects asset type and applies optimized QQE factors
- Integrates SMC price zones (support/resistance) for grade enhancement
- Filters signals by trading session time
- Displays real-time session and market status
Grade Hierarchy:
- S (Gold/Orange): Signal near SMC zone + active trading hours - Highest quality
- A (Green/Red): Score 70+ during trading hours - High quality
- B (Darker): Score 50-69 during trading hours - Medium quality
- C (Gray, small): Outside trading hours or weak signal - Low quality
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█ HOW IT WORKS
【QQE Core Calculation】
The QQE (Quantitative Qualitative Estimation) is calculated as:
1. RSI with configurable period (default: 14)
2. EMA smoothing of RSI (Smoothing Factor: 5)
3. Dynamic bands using Wilder's smoothing: RSI ± (ATR of RSI × QQE Factor)
QQE Factor is auto-adjusted per asset:
- USD/JPY: 4.238
- EUR/USD: 3.8
- Gold (XAU/USD): 8.0
- NASDAQ/US100: 9.0
【Signal Generation】
- BUY: QQE line crosses above its trailing stop (QQExlong == 1)
- SELL: QQE line crosses below its trailing stop (QQExshort == 1)
【Internal Scoring System】
Score components (0-100):
- Signal Base: +25 points when signal occurs
- QQE Strength: +10 to +20 based on RSI distance from 50
- Volatility: +15 (optimal ATR ratio 1.1-2.0), -10 (low volatility)
- Volume Confirmation: +10 (high volume), -5 (low volume)
- Session Bonus: +5 during London/NY sessions
- Base: +20 points
【Grade Assignment】
- Grade S: Signal near user-defined SMC price zone (within tolerance %) AND during trading hours
- Grade A: Internal score >= 70 AND during trading hours
- Grade B: Internal score >= 50 AND during trading hours
- Grade C: Outside trading hours OR score < 50
【SMC Price Zone Integration】
Users can set support/resistance levels for each asset. When price is within the tolerance percentage of these levels, signals are upgraded to S-grade, indicating confluence with institutional price levels.
【Trading Session Filter】
Configurable active trading hours (JST timezone):
- Default: 15:00 - 01:00 JST (London + NY overlap)
- Signals outside this window receive C-grade
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█ HOW TO USE
【Recommended Settings】
- Timeframe: 15M, 1H, 4H
- Best on: USD/JPY, EUR/USD, Gold, NASDAQ
- Focus on: S and A grade signals
【Trading Strategy】
- S-Grade (Gold/Orange): Highest conviction - consider larger position
- A-Grade (Green/Red): Strong signal - standard position
- B-Grade: Valid but use additional confirmation
- C-Grade: Avoid or use minimal size
【Setting Up SMC Zones】
1. Identify key support/resistance on higher timeframe
2. Input prices in SMC Price Settings
3. Adjust tolerance % (default: 0.15%)
4. S-grade appears when signal occurs near these levels
【Info Panel】
Top-right panel shows:
- Asset name and detection mode (Auto/Manual)
- Current session (Tokyo/London/NY)
- Trading hours status
- SMC zone proximity
【Alert Setup】
1. Enable alerts in settings
2. Create alert with "Any alert() function call"
3. Alerts include grade, price, and session info
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█ SETTINGS
Basic Settings:
- Enable Alerts: Turn on/off notifications
- Time Filter: Activate trading hour filter
- Start/End Hour: Define active trading window (JST)
QQE Settings:
- RSI Period: RSI calculation period
- RSI Smoothing: EMA smoothing factor
- Auto QQE Factor: Auto-detect optimal factor per asset
- Manual QQE Factor: Override when auto is disabled
SMC Price Settings:
- Support/Resistance levels for each asset
- Tolerance %: How close to SMC line for S-grade
Display Settings:
- Grade Only: Hide QQE lines, show only signals
- Show SMC Lines: Display support/resistance on chart
- Show Debug: Display asset detection info
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█ CREDITS
QQE concept originally developed by John Ehlers.
SMC (Smart Money Concepts) integration and grading system by EduVest.
License: Mozilla Public License 2.0
EDUVEST UTBOT ADJ - Adaptive ATR Trailing StopEDUVEST UTBOT ADJ - Adaptive ATR Trailing Stop with Session-Based Sensitivity
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█ ORIGINALITY
This indicator is an enhanced version of the classic UT Bot concept, featuring automatic session-based ATR sensitivity adjustment. Unlike the original UT Bot which uses a fixed sensitivity value, this version dynamically adapts to different trading sessions (Tokyo, London, New York) and automatically detects asset characteristics to optimize signal generation.
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█ WHAT IT DOES
- Generates BUY and SELL signals based on ATR trailing stop crossovers with a moving average
- Automatically adjusts sensitivity based on current trading session (Tokyo/London/NY)
- Auto-detects asset type and applies optimized parameters for each instrument
- Displays real-time session information and volatility status
- Provides alert functionality with customizable cooldown periods
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█ HOW IT WORKS
【Core Logic: ATR Trailing Stop】
The indicator calculates an ATR-based trailing stop using the formula:
Trailing Stop = Price ± (Sensitivity × ATR)
When price is above the trailing stop and rising, the stop trails below price.
When price is below the trailing stop and falling, the stop trails above price.
【Signal Generation】
- BUY Signal: Price crosses above the trailing stop AND Moving Average crosses above the trailing stop
- SELL Signal: Price crosses below the trailing stop AND Moving Average crosses below the trailing stop
【Session-Based Sensitivity Adjustment】
The indicator adjusts ATR sensitivity based on trading session (JST timezone):
- Tokyo (08:00-15:00): Lower sensitivity (reduced by adjustment value) - typically quieter markets
- London (15:00-23:00): Base sensitivity - moderate volatility
- New York (23:00-08:00): Higher sensitivity (increased by adjustment value) - higher volatility
【Dynamic ATR Adjustment】
When enabled, the indicator compares current ATR to its smoothed average:
- ATR Ratio = Current ATR / SMA(ATR, smoothing period)
- Volatility Multiplier = 1.0 + (Sensitivity × (2.0 - ATR Ratio))
This reduces sensitivity during high volatility (fewer false signals) and increases sensitivity during low volatility (faster response).
【Auto Asset Detection】
The indicator automatically detects the traded instrument and applies optimized parameters:
- Stable pairs (USDJPY, EURUSD, USDCHF): Base sensitivity 1.5-1.8
- Moderate pairs (AUDUSD, USDCAD, EURJPY): Base sensitivity 2.0-2.3
- Volatile pairs (GBPUSD): Base sensitivity 2.8
- Commodities (GOLD/XAUUSD): Base sensitivity 3.5
- Indices (NASDAQ/NAS100): Base sensitivity 4.0
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█ HOW TO USE
【Recommended Settings】
- Timeframe: 15 minutes or higher (15M, 1H, 4H recommended)
- Best performance on: Forex majors, Gold, NASDAQ
- Enable "Auto Asset Detection" for optimized parameters
【Entry Rules】
- BUY: Enter long when green BUY label appears
- SELL: Enter short when pink SELL label appears
【Session Panel】
The top-right panel displays:
- Current trading session (Tokyo/London/NY)
- Volatility status (High Chance/Medium Chance/Caution)
- Mode (AUTO/MANUAL)
【Alert Setup】
1. Enable "Viewer Alert Display" in settings
2. Set cooldown period (default: 15 minutes) to avoid signal spam
3. Create alert with "Any alert() function call" condition
【Important Notes】
- This indicator does not repaint - signals are confirmed at bar close
- Lower timeframes (1M, 5M) may generate excessive signals
- Always use proper risk management and confirm with other analysis
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█ SETTINGS OVERVIEW
🎯 Alert Settings
- Viewer Alert Display: Enable/disable alert labels
- Cooldown Function: Prevent rapid consecutive signals
- Cooldown Time: Minutes between alerts (5-60)
🔧 Dynamic ATR Settings
- Enable Dynamic ATR: Auto-adjust based on volatility
- ATR Period: Calculation period (default: 14)
- ATR Smoothing: Smoothing period for ratio calculation
- Volatility Sensitivity: How much to adjust (0.1-1.0)
🕐 Session ATR Adjustment
- Enable Time Adjustment: Session-based sensitivity
- Show Session Info: Display session panel
📊 Asset Settings
- Auto Asset Detection: Automatically optimize for instrument
- Manual settings available when auto-detection is disabled
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█ CREDITS
Based on the original UT Bot concept by QuantNomad.
Enhanced with session-based adaptation and auto-asset detection by EduVest.
License: Mozilla Public License 2.0
LSE Chrono-Behavior Forecast🎯 ANTICIPATE THE MOVE. TRADE THE EDGE.
The Chrono-Behavior Forecast is a revolutionary forward-looking indicator that projects future market behavior and reversal points directly onto your chart. Unlike traditional indicators that are based on lagging data, this indicator shows you what's coming next.
📊 WHAT MAKES THIS DIFFERENT
While most indicators look backward at historical price action, the Chrono-Behavior Forecast does the opposite: it plots a non-repainting forecasted line that projects market timing, behavior, and reversals for up to 24 hours into the future.
All forecasts are generated BEFORE market open - no curve fitting, no hindsight bias, no repainting. What you see is pure forward-looking analysis.
⚡ KEY FEATURES
• Non-Repainting Forecasts - The forecasted line never changes after it's plotted. What you see is what you get.
• Any Asset Class - Works on stocks, futures, forex, crypto, commodities - any tradable instrument. Place this indicator on any chart and see our forecasted line plotted right on it.
• Any Intraday Timeframe - Optimized for day trading timeframes from 1 second to 6 hours. Use shorter timeframes (1-5 min) for quick scalps, longer timeframes (15 min - 6 hr) for more deliberate entries.
• Battle-Tested - We trade these same indicators ourselves. Your success is our success.
🔬 THE METHODOLOGY
The Chrono-Behavior Forecast is the culmination of over two decades of intensive research into the hidden mechanics of market movement. We've moved beyond standard technical analysis to uncover the specific, repeatable forces that drive market behavior.
Market Energy Analysis - Our proprietary algorithm analyzes decades of historical data to decode how global exchanges influence specific asset classes over time.
Energy Forecasting - We forecast the future energy that markets are expected to exert, mapped to precise time windows throughout your trading session.
Behavioral Footprints - By mapping these "behavioral footprints" against time, we predict market impacts and reversals well before they manifest.
📈 HOW TO USE
• Identify Future Reversal Points - Use the forecasted peaks and valleys to anticipate market turning points.
• Time Your Entries & Exits - The forecast gives you the foresight to time your trades with confidence.
• Combine Multiple Markets - Layer multiple Chrono-Behavior Forecasts on a single chart to see how competing market forces converge to drive price action.
⚠️ IMPORTANT NOTES
• Best used for intraday trading on timeframes between 1 second and 6 hours.
• As with day trading in general, exercise caution during high market volatility events (e.g., NFP, FOMC announcements) and the first few minutes after US market open.
• We have forecasting indicators for 28 global exchanges including NYSE, NASDAQ, CME, LSE, TSE, SSE, and more - that can be applied to ANY chart.
🌐 CURRENTLY AVAILABLE EXCHANGES
USA: NYSE, NASDAQ, CME, ICE, CBOE
UK: LSE
Europe: Euronext, Deutsche Börse, Swiss Exchange, Nasdaq Nordic, Spanish Exchanges
Asia: TSE, SSE, SZSE, HKEX, NSE India, TWSE, KRX, SGX, SET, Bursa Malaysia, IDX
Other: TSX, TASI, ASX, JSE, ADX, B3
Custom exchange forecast development available upon request.
Directional Movement Probability (DMP Indicator) [whodatop]The Directional Movement Probability (DMP) indicator is an intraday-oriented analytical tool designed to identify probabilistic phases of directional price movement using a Z-score calculation based on the deviation of the closing price from its moving average.
The indicator is primarily intended for lower intraday timeframes , with 3-minute and 5-minute charts being the preferred operating range, where directional transitions and regime shifts are more clearly expressed.
Its primary objective is to detect the start and end of a positive Z-score zone, interpreted as a phase of dominant directional behavior.
It has demonstrated particularly consistent behavior on Forex instruments and currency futures , where mean-deviation dynamics and session-based liquidity patterns are well defined.
Core Calculation Logic
Z-score
The indicator uses a Z-score calculated from the closing price relative to its moving average.
The Lookback Length defines the calculation window for both the moving average and standard deviation.
If the standard deviation is zero, the Z-score defaults to 0.
Deadband (Hysteresis)
A symmetric deadband around zero is applied to reduce signal noise when Z fluctuates near the midpoint.
Setting Deadband = 0 disables this behavior.
Signal Filters
Filters do not alter the Z-score calculation and are applied only at the signal level.
Toxic Bar Filter
Suppresses signals on abnormally large candles by comparing bar height to recent volatility.
Session Filter
Optionally ignores signals during the Asian session (23:00–07:00 UTC) to reduce low-liquidity noise.
Limitations and Usage Notes
This is an intraday indicator, not a standalone trading system.
Best performance is typically observed on 3-minute and 5-minute charts.
Particularly well-suited for Forex markets and currency futures.
Can be applied to other asset classes and timeframes, but signal characteristics may vary.
Most effective when combined with:
- higher-timeframe directional bias,
- market structure or liquidity-based analysis,
- additional confirmation logic.
Not designed for prolonged range-bound conditions without supplementary filters.
Ultimate Major Contextual Dashboard (Multi-Asset)Overview : The Ultimate Major Dashboard is a performance-optimized market overview tool designed to provide a consolidated snapshot of the 7 major Forex pairs and Gold. It aggregates correlation, trend, momentum, and volatility data into a single, clean table, allowing users to view broader market context without switching charts.
Technical Logic & Components : This indicator utilizes a modular function to analyze EURUSD, GBPUSD, USDJPY, USDCHF, AUDUSD, USDCAD, NZDUSD, and XAUUSD across four key dimensions:
Intermarket Correlation (Pearson Coefficient): Uses ta.correlation() to compare each asset against the symbol currently on your main chart.
Logic: Values above 0.7 (Dark Green) suggest a strong positive relationship, while values below -0.7 (Dark Red) suggest inverse behavior. This is calculated over a rolling 50-period window to balance stability with current market sensitivity.
Trend Bias (EMA-200): Evaluates the long-term trend by checking price position relative to the 200-period Exponential Moving Average.
Visuals: An upward arrow (⬆) indicates price is above the EMA; a downward arrow (⬇) indicates it is below.
Momentum (RSI-14): Calculates the Relative Strength Index. The dashboard automatically highlights readings above 70 (OB) or below 30 (OS) to help identify potential momentum extremes.
Volatility (ATR-14): Displays the Average True Range as a reference for the current active range of each market, helping users compare volatility levels across the majors.
How to Interpret the Dashboard
Asset Alignment: Correlation values help identify when pairs are moving in "unison" versus when a specific currency is diverging from the group.
Directional Context: Combining the Trend (EMA) and Momentum (RSI) columns provides a quick view of whether a market is trending strongly or reaching an exhaustion point.
Volatility Benchmarking: The ATR values offer perspective on which pairs are currently the most active, assisting in market comparison based on volatility preference.
Data Handling & Customization
Multi-Symbol Sync: Data is fetched using request.security(). The calculations are synchronized with the chart's current bar state for real-time accuracy.
Dynamic TF: Users can select the analysis timeframe (60, 240, D, W) via the settings menu.
Flexibility: The dashboard position can be toggled between all four corners of the chart to avoid overlapping with price action.
Disclaimer
This tool is provided for analytical and educational purposes only. It does not generate trading signals and should not be considered financial advice.
DT Volume Profile OB [Doclad Team]DT Volume Profile OB is an advanced trading indicator designed to deliver deeper insight into market structure and price behavior. It enhances the traditional order block concept by embedding a detailed volume profile directly inside each order block, calculated using lower timeframe data.
Unlike conventional order block indicators, this tool distributes volume from lower timeframe candles across multiple segments within the order block zone. This reveals the internal volume structure of each block, allowing traders to identify where the most significant trading activity actually occurred rather than treating the zone as a single flat area.
A core feature of the indicator is its flexible order block detection logic, controlled by a single parameter called Tuning. This setting allows you to adjust the sensitivity of the algorithm:
Higher values generate fewer but more significant order blocks
Lower values produce more frequent order blocks with reduced significance
This makes the indicator adaptable to different trading styles, from short-term intraday trading to higher‑timeframe analysis.
Key Settings
Number of Segments
Defines how many segments the order block is divided into, allowing you to control the level of volume profile detail.
Tuning
Adjusts the sensitivity and frequency of order block detection to match your trading approach.
Color Settings
Fully customizable color options for all visual elements, ensuring seamless integration with any chart layout.
The example illustrates how price can react precisely to the highest-volume segment within an order block, highlighting the indicator’s ability to identify high‑impact price levels with greater accuracy.
While DT Volume Profile OB offers enhanced analytical depth, it is best used alongside other technical tools and market analysis methods. This indicator does not guarantee profitable trades; instead, it provides additional context to support more informed trading decisions.
Gain a clearer perspective on market activity with DT Volume Profile OB — a tool that goes beyond surface-level zones and reveals the volume dynamics driving price movement.
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Nexus Momentum Flow [JOAT]
Nexus Momentum Flow - ADX-Based Trend Strength Analysis
Introduction and Purpose
Nexus Momentum Flow is an open-source oscillator indicator that combines the ADX (Average Directional Index) with directional movement indicators (+DI/-DI) to create a comprehensive trend strength and direction analysis tool. The core problem this indicator solves is that ADX alone tells you trend strength but not direction, while +DI/-DI alone tells you direction but not strength. Traders need both pieces of information together.
This indicator addresses that by combining ADX strength classification with directional bias into a single confluence score, making it easy to identify when strong trends exist and which direction they favor.
Why These Components Work Together
1. ADX (Average Directional Index) - Measures trend strength regardless of direction. Values above 25 indicate trending; below 20 indicate ranging.
2. +DI (Positive Directional Indicator) - Measures upward price movement strength.
3. -DI (Negative Directional Indicator) - Measures downward price movement strength.
4. Confluence Score - Combines ADX strength with DI bias to create a single actionable metric.
The combination works because:
ADX filters out ranging markets where DI crossovers produce whipsaws
DI relationship provides direction when ADX confirms trend
Confluence score simplifies the analysis into one number
How the Calculation Works
float directionBias = diPlus - diMinus
float confluenceScore = (adx / 100) * directionBias
The confluence score is positive when +DI > -DI (bullish) and negative when -DI > +DI (bearish), with magnitude scaled by ADX strength.
Trend State Classification
EXTREME - ADX > 50 (very strong trend)
STRONG - ADX 35-50 (strong trend)
TRENDING - ADX 25-35 (moderate trend)
RANGING - ADX < 25 (no clear trend)
Dashboard Information
Status - Current trend state (EXTREME/STRONG/TRENDING/RANGING)
Direction - BULLISH or BEARISH based on DI relationship
ADX - Current ADX value
DI Bias - Difference between +DI and -DI
Confluence - Combined score with directional context
How to Use This Indicator
For Trend Following:
1. Wait for ADX to show TRENDING or higher
2. Check direction matches your trade bias
3. Enter on pullbacks when confluence remains positive/negative
4. Exit when ADX drops to RANGING
For Avoiding Whipsaws:
1. Do not trade DI crossovers when ADX shows RANGING
2. Only trust directional signals when ADX confirms trend
3. Use RANGING periods for mean-reversion strategies instead
For Trend Exhaustion:
1. Watch for EXTREME ADX readings
2. Extreme trends often precede reversals
3. Consider taking profits when ADX reaches extreme levels
Input Parameters
ADX Length (14) - Period for ADX calculation
DI Length (14) - Period for directional indicators
ADX Smoothing (14) - Smoothing period for ADX
Trend Threshold (25) - ADX level for trend confirmation
Strong Threshold (35) - ADX level for strong trend
Extreme Threshold (50) - ADX level for extreme trend
Timeframe Recommendations
Daily/4H: Best for swing trading trend analysis
1H: Good for intraday trend following
15m: More signals but requires faster reaction
Limitations
ADX is a lagging indicator - trends are confirmed after they start
DI crossovers can whipsaw even with ADX filter
Works best in markets that trend clearly
May miss early trend entries due to confirmation requirement
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes.
This indicator does not constitute financial advice. Trend analysis does not guarantee profitable trades. Always use proper risk management.
- Made with passion by officialjackofalltrades
Anchored VWAP PercentageINDICATOR: ANCHORED VWAP PERCENTAGE (AVWAP)
1. Overview
The Anchored VWAP Percentage (AVWAP) is a quantitative momentum and mean-reversion tool. It measures the percentage distance between the current price and a Volume Weighted Average Price (VWAP) that resets automatically based on specific time cycles. It allows traders to identify overextended market conditions relative to institutional value.
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2. Core Logic & Calculation
The script tracks the relationship between price and volume starting from a specific Anchor Point .
* Volume-Weighted Foundation: Unlike simple moving averages, this indicator uses the VWAP formula: sum(Volume * Price) / sum(Volume) .
* Automatic Anchoring: The starting point (Anchor) resets automatically depending on the chart timeframe (e.g., resets weekly on a 15m chart, or yearly on a Daily chart).
* Percentage Deviation: It calculates the precise gap between the price and the VWAP, plotted as an oscillator: ((Price - VWAP) / VWAP) * 100 .
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3. Adaptive Intelligence (Multi-Asset & Multi-TF)
The AVWAP is built with an internal database of 85th Percentile (P85) volatility thresholds. It recognizes that different assets have different "stretching" limits:
1. Asset-Specific Calibration: It includes optimized data for Bitcoin, Ethereum, Altcoins, Forex, and Indices .
2. Dynamic Timeframe Mapping: The anchor period and the exhaustion thresholds adjust automatically. For example:
* Intraday (1m-5m): Anchors to an 8-hour (480 min) cycle.
* Mid-Term (15m-60m): Anchors to a Weekly (W) cycle.
* Swing (Daily): Anchors to a Yearly (12M) cycle.
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4. Visual Anatomy
The indicator is designed for high-speed decision-making:
* The Histogram:
* Green: Price is trading above the VWAP (Bullish premium).
* Red: Price is trading below the VWAP (Bearish discount).
* P85 Threshold Lines:
* These lines represent the 85th percentile of historical deviations . Historically, the price stays within these boundaries 85% of the time.
* Background Highlighting: When the histogram crosses the P85 line, the background glows, signaling a Statistical Exhaustion Zone where a retracement to the mean is highly probable.
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5. How to Trade with AVWAP
* Mean Reversion: When the histogram reaches the P85 Zone , the price is "statistically overextended." This is a prime area to look for reversals or to take profits on existing trends.
* Trend Strength: If the histogram stays near the Zero Line while the price moves, the trend is supported by healthy volume.
* Value Area: The Zero Line represents the Fair Value . Buying near the Zero Line during a bullish histogram (Green) offers a high-probability entry with low risk.
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6. Technical Parameters
* Asset Selection: A dropdown to switch between Crypto, Forex, and Indices.
* Color Customization: User-defined colors for bullish and bearish sentiment.
* Precision Control: 4-decimal precision for accurate tracking of thin-margin assets like Forex.
Fractal Wave Hunter [JOAT]
Fractal Wave Hunter - Multi-Method Fractal Detection System
Introduction and Purpose
Fractal Wave Hunter is an open-source overlay indicator that identifies key reversal patterns using multiple fractal detection methods. The core problem this indicator solves is that different fractal methods catch different types of reversals. Williams' classic 5-bar fractal is reliable but slow; Hougaard's 4-bar method is faster but noisier. Using only one method means missing valid signals that the other would catch.
This indicator addresses that by combining both methods plus HOLP/LOHP detection, giving traders a comprehensive view of potential reversal points.
Why These Methods Work Together
Each fractal method has different characteristics:
1. 4-Bar Fractal (Hougaard Method) - Faster detection, identifies momentum shifts when close exceeds recent highs/lows. Best for catching early reversals.
2. Classic 5-Bar Fractal (Williams) - Traditional pivot detection requiring the middle bar to be the highest/lowest of 5 bars. Best for identifying significant swing points.
3. HOLP/LOHP - High of Low Period and Low of High Period signals identify when price makes a new extreme within a defined lookback. Best for trend exhaustion detection.
By combining these methods, traders can:
Use 4-bar fractals for early entry signals
Use 5-bar fractals for confirmation and stop placement
Use HOLP/LOHP for trend exhaustion warnings
How the Detection Works
4-Bar Fractal (Hougaard):
bool fractal4BuyBase = close > high and close > high
bool fractal4SellBase = close < low and close < low
Classic 5-Bar Fractal:
bool fractalHigh = high > high and high > high and high > high and high > high
bool fractalLow = low < low and low < low and low < low and low < low
Signal Types
4B (4-Bar Buy) - Close exceeds high and high - early bullish signal
4S (4-Bar Sell) - Close below low and low - early bearish signal
FH (Fractal High) - Classic 5-bar swing high - confirmed resistance
FL (Fractal Low) - Classic 5-bar swing low - confirmed support
HOLP - High of low period - potential bullish exhaustion
LOHP - Low of high period - potential bearish exhaustion
Dashboard Information
4-Bar Fractal - Count of bullish/bearish 4-bar fractals
Classic Fractal - Count of 5-bar fractal highs/lows
HOLP/LOHP - Reversal signal counts
Total Signals - Combined pattern count
How to Use This Indicator
For Counter-Trend Entries:
1. Wait for 4-bar fractal signal at key support/resistance
2. Confirm with 5-bar fractal forming nearby
3. Enter with stop beyond the fractal point
For Stop Placement:
1. Use 5-bar fractal highs/lows as stop-loss references
2. These represent confirmed swing points that should hold if trend continues
For Trend Analysis:
1. Track swing structure using fractal highs and lows
2. Higher fractal lows = uptrend structure
3. Lower fractal highs = downtrend structure
Input Parameters
Show 4-Bar Fractals (true) - Toggle Hougaard method signals
Show Classic Fractals (true) - Toggle Williams method signals
Show HOLP/LOHP (true) - Toggle exhaustion signals
ATR Filter (false) - Only show signals during volatile conditions
Swing Lines (true) - Connect significant swing points
Timeframe Recommendations
1H-Daily: Best for reliable fractal detection
15m-30m: More signals but higher noise
Weekly: Fewer but more significant fractals
Limitations
5-bar fractals have inherent 2-bar lag (need confirmation)
4-bar fractals can produce false signals in choppy markets
HOLP/LOHP signals work best at trend extremes
Not all fractals lead to significant reversals
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes.
This indicator does not constitute financial advice. Fractal detection does not guarantee reversals. Always use proper risk management.
- Made with passion by officialjackofalltrades
Aurora Volatility Bands [JOAT]Aurora Volatility Bands - Dynamic ATR-Based Envelope System
Introduction and Purpose
Aurora Volatility Bands is an open-source overlay indicator that creates multi-layered volatility envelopes around price using ATR (Average True Range) calculations. The core problem this indicator solves is that static bands (like fixed percentage envelopes) fail to adapt to changing market conditions. During high volatility, static bands are too tight; during low volatility, they're too wide.
This indicator addresses that by using ATR-based dynamic bands that automatically expand during volatile periods and contract during quiet periods, providing contextually appropriate support/resistance levels at all times.
Why These Components Work Together
The indicator combines three analytical approaches:
1. Triple-Layer Band System - Inner (1x ATR), Outer (2x ATR), and Extreme (3x ATR) bands provide graduated levels of significance
2. Volatility State Detection - Compares current ATR to historical average to classify market regime
3. Multiple MA Types - Allows customization of the center line calculation method
These components complement each other:
The triple-layer system gives traders multiple reference points - inner bands for normal moves, outer for significant moves, extreme for rare events
Volatility state detection tells you WHEN bands are expanding or contracting, helping anticipate breakouts or mean-reversion
MA type selection lets you match the indicator to your trading style (faster EMA vs smoother SMA)
How the Calculation Works
The bands are calculated using ATR multiplied by configurable factors:
float atr = ta.atr(atrPeriod)
float innerUpper = centerMA + (atr * innerMult)
float outerUpper = centerMA + (atr * outerMult)
float extremeUpper = centerMA + (atr * extremeMult)
Volatility state is determined by comparing current ATR percentage to its historical average:
float atrPercent = (atr / close) * 100
float avgAtrPercent = ta.sma(atrPercent, volatilityLookback)
float volatilityRatio = atrPercent / avgAtrPercent
bool isExpanding = volatilityRatio > 1.2 // 20%+ above average
bool isContracting = volatilityRatio < 0.8 // 20%+ below average
Signal Types
Band Touch - Price reaches inner, outer, or extreme bands
Mean Reversion - Price returns to center after touching outer/extreme bands
Breakout - Sustained move beyond outer bands during volatility expansion
Dashboard Information
Volatility - Current state (EXPANDING/CONTRACTING/NORMAL)
Vol Ratio - Current volatility vs average (e.g., 1.5x = 50% above average)
ATR - Current ATR value
ATR % - ATR as percentage of price
Zone - Current price position (EXTREME HIGH/UPPER ZONE/CENTER ZONE/etc.)
Position - Price position as percentage within band structure
Width - Total band width as percentage of price
Using SMA in settings:
How to Use This Indicator
For Mean-Reversion Trading:
1. Wait for price to touch outer or extreme bands
2. Check that volatility state is NORMAL or CONTRACTING (not expanding)
3. Look for reversal candlestick patterns at the band
4. Enter toward center MA with stop beyond the band
For Breakout Trading:
1. Wait for volatility state to show EXPANDING
2. Look for price closing beyond outer bands
3. Enter in direction of breakout
4. Use the band as trailing stop reference
For Volatility Analysis:
1. Monitor volatility ratio for regime changes
2. CONTRACTING often precedes large moves (squeeze)
3. EXPANDING confirms trend strength
Using VWMA and Mean Reversion Signal/MR:
Input Parameters
ATR Period (14) - Period for ATR calculation
Inner/Outer/Extreme Multipliers (1.0/2.0/3.0) - Band distance from center
MA Type (EMA) - Center line calculation method
MA Period (20) - Period for center line
Volatility Comparison Period (20) - Lookback for volatility state
Timeframe Recommendations
15m-1H: Good for intraday mean-reversion
4H-Daily: Best for swing trading and breakout identification
Weekly: Useful for position trading and major level identification
Limitations
ATR-based bands lag during sudden volatility spikes
Mean-reversion signals can fail in strong trends
Breakout signals may whipsaw in ranging markets
Works best on liquid instruments with consistent volatility patterns
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. The source code is fully visible and can be studied to understand how each component works.
This indicator does not constitute financial advice. Band touches do not guarantee reversals. Past performance does not guarantee future results. Always use proper risk management, position sizing, and stop-losses.
- Made with passion by officialjackofalltrades
Quantum Reversal Detector [JOAT]
Quantum Reversal Detector - Multi-Factor Reversal Probability Analysis
Introduction and Purpose
Quantum Reversal Detector is an open-source overlay indicator that combines multiple reversal detection methods into a unified probability-based framework. The core problem this indicator addresses is the unreliability of single-factor reversal signals. A price touching support means nothing without momentum confirmation; an RSI oversold reading means nothing without price structure context.
This indicator solves that by requiring multiple independent factors to align before generating reversal signals, then expressing the result as a probability score rather than a binary signal.
Why These Components Work Together
The indicator combines five analytical approaches, each addressing a different aspect of reversal detection:
1. RSI Extremes - Identifies momentum exhaustion (overbought/oversold)
2. MACD Crossovers - Confirms momentum direction change
3. Support/Resistance Proximity - Ensures price is at a significant level
4. Multi-Depth Momentum - Analyzes momentum across multiple timeframes
5. Statistical Probability - Quantifies reversal likelihood using Bayesian updating
These components are not randomly combined. Each filter catches reversals that others miss:
RSI catches momentum exhaustion but misses structural reversals
MACD catches momentum shifts but lags price action
S/R proximity catches structural levels but ignores momentum
Multi-depth momentum catches divergences across timeframes
Probability scoring combines all factors into actionable confidence levels
How the Detection System Works
Step 1: Pattern Detection
The indicator first identifies potential reversal conditions:
// Check if price is at support/resistance
float lowestLow = ta.lowest(low, period)
float highestHigh = ta.highest(high, period)
bool atSupport = low <= lowestLow * 1.002
bool atResistance = high >= highestHigh * 0.998
// Check RSI conditions
float rsi = ta.rsi(close, 14)
bool oversold = rsi < 30
bool overbought = rsi > 70
// Check MACD crossover
float macd = ta.ema(close, 12) - ta.ema(close, 26)
float signal = ta.ema(macd, 9)
bool macdBullish = ta.crossover(macd, signal)
bool macdBearish = ta.crossunder(macd, signal)
// Combine for reversal detection
if atSupport and oversold and macdBullish
bullishReversal := true
Step 2: Multi-Depth Momentum Analysis
The indicator calculates momentum across multiple periods to detect divergences:
calculateQuantumMomentum(series float price, simple int period, simple int depth) =>
float totalMomentum = 0.0
for i = 0 to depth - 1
int currentPeriod = period * (i + 1)
float momentum = ta.roc(price, currentPeriod)
totalMomentum += momentum
totalMomentum / depth
This creates a composite momentum reading that smooths out noise while preserving genuine momentum shifts.
Step 3: Bayesian Probability Calculation
The indicator uses Bayesian updating to calculate reversal probability:
bayesianProbability(series float priorProb, series float likelihood, series float evidence) =>
float posterior = evidence > 0 ? (likelihood * priorProb) / evidence : priorProb
math.min(math.max(posterior, 0.0), 1.0)
The prior probability starts at 50% and updates based on:
RSI extreme readings increase likelihood
MACD crossovers increase likelihood
S/R proximity increases likelihood
Momentum divergence increases likelihood
Step 4: Confidence Intervals
Using Monte Carlo simulation concepts, the indicator estimates price distribution:
monteCarloSimulation(series float price, series float volatility, simple int iterations) =>
float sumPrice = 0.0
float sumSqDiff = 0.0
for i = 0 to iterations - 1
float randomFactor = (i % 10 - 5) / 10.0
float simulatedPrice = price + volatility * randomFactor
sumPrice += simulatedPrice
float avgPrice = sumPrice / iterations
// Calculate standard deviation for confidence intervals
This provides 95% and 99% confidence bands around the current price.
Signal Classification
Signals are classified by confirmation level:
Confirmed Reversal : Pattern detected for N consecutive bars (default 3)
High Probability : Confirmed + Bayesian probability > 70%
Ultra High Probability : High probability + PDF above average
Dashboard Information
The dashboard displays:
Bayesian Probability - Updated reversal probability (0-100%)
Quantum Momentum - Multi-depth momentum average
RSI - Current RSI value with overbought/oversold status
Volatility - Current ATR as percentage of price
Reversal Signal - BULLISH, BEARISH, or NONE
Divergence - Momentum divergence detection
MACD - Current MACD histogram value
S/R Zone - AT SUPPORT, AT RESISTANCE, or NEUTRAL
95% Confidence - Price range with 95% probability
Bull/Bear Targets - ATR-based reversal targets
Visual Elements
Quantum Bands - ATR-based upper and lower channels
Probability Field - Circle layers showing probability distribution
Confidence Bands - 95% and 99% confidence interval circles
Reversal Labels - REV markers at confirmed reversals
High Probability Markers - Star diamonds at high probability setups
Reversal Zones - Boxes around confirmed reversal areas
Divergence Markers - Triangles at momentum divergences
How to Use This Indicator
For Reversal Trading:
1. Wait for Bayesian Probability to exceed 70%
2. Confirm price is at S/R zone (dashboard shows AT SUPPORT or AT RESISTANCE)
3. Check that RSI is in extreme territory (oversold for longs, overbought for shorts)
4. Enter when REV label appears with high probability marker
For Risk Management:
1. Use the 95% confidence band as a stop-loss reference
2. Use Bull/Bear Targets for take-profit levels
3. Higher probability readings warrant larger position sizes
For Filtering False Signals:
1. Increase Confirmation Bars to require more consecutive signals
2. Only trade when probability exceeds 70%
3. Require divergence confirmation for highest conviction
Input Parameters
Reversal Period (21) - Lookback for S/R and momentum calculations
Quantum Depth (5) - Number of momentum layers for multi-depth analysis
Confirmation Bars (3) - Consecutive bars required for confirmation
Detection Sensitivity (1.2) - Band width and target multiplier
Bayesian Probability (true) - Enable probability calculation
Monte Carlo Simulation (true) - Enable confidence interval calculation
Normal Distribution (true) - Enable PDF calculation
Confidence Intervals (true) - Enable confidence bands
Timeframe Recommendations
1H-4H: Best for swing trading reversals
Daily: Fewer but more significant reversal signals
15m-30m: More signals, requires higher probability threshold
Limitations
Statistical concepts are simplified implementations for Pine Script
Monte Carlo uses deterministic pseudo-random factors, not true randomness
Bayesian probability uses simplified prior/likelihood model
Reversal detection does not guarantee actual reversals will occur
Confirmation bars add lag to signal generation
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. The source code is fully visible and can be studied to understand how each component works.
This indicator does not constitute financial advice. Reversal detection is probabilistic, not predictive. The probability scores represent statistical likelihood based on historical patterns, not guaranteed outcomes. Past performance does not guarantee future results. Always use proper risk management, position sizing, and stop-losses.
- Made with passion by officialjackofalltrades
Photon Price Action Scanner [JOAT]Photon Price Action Scanner - Multi-Pattern Recognition with Adaptive Filtering
Introduction and Purpose
Photon Price Action Scanner is an open-source overlay indicator that automates the detection of 15+ candlestick patterns while filtering them through multiple confirmation layers. The core problem this indicator solves is pattern noise: raw candlestick pattern detection produces too many signals, most of which fail because they lack context. This indicator addresses that by combining pattern recognition with trend alignment, volume-weighted strength scoring, velocity confirmation, and an adaptive neural bias filter.
The combination of these components is not arbitrary. Each filter addresses a specific weakness in standalone pattern detection:
Trend alignment ensures patterns appear in favorable market structure
Volume-weighted strength filters out weak patterns with low conviction
Velocity confirmation identifies momentum behind the pattern
Neural bias filter adapts to recent price behavior to avoid counter-trend signals
What Makes This Indicator Original
While candlestick pattern scanners exist, this indicator's originality comes from:
1. Multi-Layer Filtering System - Patterns must pass through trend, strength, velocity, and neural bias filters before generating signals. This dramatically reduces false positives compared to simple pattern detection.
2. Adaptive Neural Bias Filter - A custom momentum-adjusted EMA that learns from recent price action using a configurable learning rate. This is not a standard moving average but an adaptive filter that accelerates during trends and smooths during consolidation.
3. Pattern Strength Scoring - Each pattern receives a strength score based on volume ratio and body size, allowing traders to focus on high-conviction setups rather than every pattern occurrence.
4. Smart Cooldown System - Prevents signal overlap by enforcing minimum bar spacing between pattern labels, keeping charts clean even when "Show All Patterns" is enabled.
How the Components Work Together
Step 1: Pattern Detection
The indicator scans for 15 candlestick patterns using precise mathematical definitions:
// Example: Bullish Engulfing requires the current bullish candle to completely
// engulf the previous bearish candle with a larger body
isBullishEngulfing() =>
bool pattern = close < open and close > open and
open <= close and close >= open and
close - open > open - close
pattern
// Example: Three White Soldiers requires three consecutive bullish candles
// with each opening within the previous body and closing higher
isThreeWhiteSoldiers() =>
bool pattern = close > open and close > open and close > open and
close < close and close < close and
open > open and open < close and
open > open and open < close
pattern
Step 2: Strength Calculation
Each detected pattern receives a strength score combining volume and body size:
float volRatio = avgVolume > 0 ? volume / avgVolume : 1.0
float bodySize = math.abs(close - open) / close
float baseStrength = (volRatio + bodySize * 100) / 2
This ensures patterns with above-average volume and large bodies score higher than weak patterns on low volume.
Step 3: Trend Alignment
Patterns are checked against the trend direction using an EMA:
float trendEMA = ta.ema(close, i_trendPeriod)
int trendDir = close > trendEMA ? 1 : close < trendEMA ? -1 : 0
Bullish patterns in uptrends and bearish patterns in downtrends receive priority.
Step 4: Neural Bias Filter
The adaptive filter uses a momentum-adjusted EMA that responds to price changes:
neuralEMA(series float src, simple int period, simple float lr) =>
var float neuralValue = na
var float momentum = 0.0
if na(neuralValue)
neuralValue := src
float error = src - neuralValue
float adjustment = error * lr
momentum := momentum * 0.9 + adjustment * 0.1
neuralValue := neuralValue + adjustment + momentum
neuralValue
The learning rate (lr) controls how quickly the filter adapts. Higher values make it more responsive; lower values make it smoother.
Step 5: Velocity Confirmation
Price velocity (rate of change) must exceed the average velocity for strong signals:
float velocity = ta.roc(close, i_trendPeriod)
float avgVelocity = ta.sma(velocity, i_trendPeriod)
bool velocityBull = velocity > avgVelocity * 1.5
Step 6: Signal Classification
Signals are classified based on how many filters they pass:
Strong Pattern : Pattern + strength threshold + trend alignment + neural bias + velocity
Ultra Pattern : Strong pattern + gap in same direction + velocity confirmation
Watch Pattern : Pattern detected but not all filters passed
Detected Patterns
Classic Reversal Patterns:
Bullish/Bearish Engulfing - Complete body engulfment with larger body
Hammer - Long lower wick (2x body), small upper wick, bullish context
Shooting Star - Long upper wick (2x body), small lower wick, bearish context
Morning Star - Three-bar bullish reversal with small middle body
Evening Star - Three-bar bearish reversal with small middle body
Piercing Line - Bullish candle closing above midpoint of previous bearish candle
Dark Cloud Cover - Bearish candle closing below midpoint of previous bullish candle
Bullish/Bearish Harami - Small body contained within previous larger body
Doji - Body less than 10% of total range (indecision)
Advanced Patterns (Optional):
Three White Soldiers - Three consecutive bullish candles with rising closes
Three Black Crows - Three consecutive bearish candles with falling closes
Tweezer Top - Equal highs with reversal candle structure
Tweezer Bottom - Equal lows with reversal candle structure
Island Reversal - Gap isolation creating reversal structure
Dashboard Information
The dashboard displays real-time analysis:
Pattern - Current detected pattern name or "SCANNING..."
Bull/Bear Strength - Volume-weighted strength scores
Trend - UPTREND, DOWNTREND, or SIDEWAYS based on EMA
RSI - 14-period RSI for momentum context
Momentum - 10-period momentum reading
Volatility - ATR as percentage of price
Neural Bias - BULLISH, BEARISH, or NEUTRAL from adaptive filter
Action - ULTRA BUY/SELL, BUY/SELL, WATCH BUY/SELL, or WAIT
Visual Elements
Pattern Labels - Abbreviated codes (BE=Engulfing, H=Hammer, MS=Morning Star, etc.)
Neural Bias Line - Adaptive trend line showing filter direction
Gap Boxes - Cyan boxes highlighting price gaps
Action Zones - Dashed boxes around strong pattern areas
Velocity Markers - Small circles when velocity confirms direction
Ultra Signals - Large labels for highest conviction setups
How to Use This Indicator
For Reversal Trading:
1. Wait for a pattern to appear at a key support/resistance level
2. Check that the Action shows "BUY" or "SELL" (not just "WATCH")
3. Confirm the Neural Bias aligns with your trade direction
4. Use the strength score to gauge conviction (higher is better)
For Trend Continuation:
1. Identify the trend using the Trend row in the dashboard
2. Look for patterns that align with the trend (bullish patterns in uptrends)
3. Ultra signals indicate the strongest continuation setups
For Filtering Noise:
1. Keep "Show All Patterns" disabled to see only filtered signals
2. Increase "Pattern Strength Filter" to see fewer, higher-quality patterns
3. Enable "Velocity Confirmation" to require momentum behind patterns
Input Parameters
Scan Sensitivity (1.0) - Overall detection sensitivity multiplier
Pattern Strength Filter (3) - Minimum strength score for strong signals
Trend Period (20) - EMA period for trend determination
Show All Patterns (false) - Display all patterns regardless of filters
Advanced Patterns (true) - Enable soldiers/crows/tweezer detection
Gap Analysis (true) - Enable gap detection and boxes
Velocity Confirmation (true) - Require velocity for strong signals
Neural Bias Filter (true) - Enable adaptive trend filter
Neural Period (50) - Lookback for neural bias calculation
Neural Learning Rate (0.12) - Adaptation speed (0.01-0.5)
Timeframe Recommendations
1H-4H: Best balance of signal frequency and reliability
Daily: Fewer but more significant patterns
15m-30m: More signals, requires tighter filtering (increase strength threshold)
Limitations
Pattern detection is mechanical and does not consider fundamental context
Neural bias filter may lag during rapid trend reversals
Gap detection requires clean price data without after-hours gaps
Strength scoring favors high-volume patterns, which may miss valid low-volume setups
- Made with passion by officialjackofalltrades
Key Time Window & Kill Zones
📌 Key Time Window & Kill Zones
This indicator highlights important global trading sessions and high-probability execution windows using fixed UTC (GMT+0) timings, which align correctly with IST and all other time zones through TradingView’s internal time conversion.
It is designed to help traders focus on institutional activity periods, avoid low-probability hours, and execute trades only during statistically active market windows for Crypto, Forex And US markets.
________________________________________
⏱️ Session Timings (All in UTC / GMT+0)
Asia Range — 22:00 – 05:00 (Red) ( NO TRADING ZONE)
• Marks the Asian session consolidation range
• Useful for identifying liquidity highs and lows
• Acts as reference for London and New York liquidity sweeps
________________________________________
Frankfurt Trap Time — 07:00 – 08:00 (Grey) ( NO TRADING ZONE)
• Commonly produces false breakouts and stop-hunts
• No-trade zone
• Used only to observe potential liquidity traps before London open
________________________________________
London Kill Zone — 08:00 – 09:00 (Blue) (TRADING ZONE)
• High-volatility window at London open
• Trades are valid only after Frankfurt liquidity is swept
• Suitable for smart-money entries following manipulation
________________________________________
New York Range — 13:00 – 17:00 (Purple)
• Defines the broader New York session range
• Tradeable only when market structure is trending
• Provides context for NY session price development
________________________________________
New York Kill Zone (Key Time Window) — 14:00 – 15:00 (Deep Purple) ( KEY TIME WINDOW- TRADING WINDOW)
• Primary execution window
• Best setups form after London or NY open inducement
• Suitable for both reversals and continuations
________________________________________
NYSE Cash Open — 14:30 – 14:45 (Dark Purple) ( AVOID NEW ENTRIES IN THIS ZONE)
• Exact US cash market opening window
• Increased volatility and decisive price moves
• One of the most important intraday execution periods
________________________________________
🧠 How to Use
• Use session zones as time-based confirmation, not standalone signals
• Combine with:
o Market structure
o Liquidity sweeps
o Inducement
o Order blocks / supply & demand
• Avoid trading outside the highlighted sessions
• Best suited for intraday and scalping strategies
________________________________________
⚠️ Important Notes
• All sessions are plotted in UTC (GMT+0)
• Automatically adjust to the user’s chart time zone (including IST)
• This indicator does not generate buy or sell signals
• Intended for educational and analytical purposes only
________________________________________
BONUS
Two Extra Options To mark your Special Time Zones If you Want.
Entropy Balance Oscillator [JOAT]
Entropy Balance Oscillator - Chaos Theory Edition
Overview
Entropy Balance Oscillator is an open-source oscillator indicator that applies chaos theory concepts to market analysis. It calculates market entropy (disorder/randomness), balance (price position within range), and various chaos metrics to identify whether the market is in an ordered, chaotic, or balanced state. This helps traders understand market regime and adjust their strategies accordingly.
What This Indicator Does
The indicator calculates and displays:
Entropy - Measures market disorder using return distribution analysis
Balance - Price position within the high-low range, normalized to -1 to +1
Lyapunov Exponent - Estimates sensitivity to initial conditions (chaos indicator)
Hurst Exponent - Measures long-term memory in price series (trend persistence)
Strange Attractor - Simulated attractor points for visualization
Bifurcation Detection - Identifies potential regime change points
Chaos Index - Combined entropy and volatility score
Market Phase - Classification as CHAOS, ORDER, or BALANCED
How It Works
Entropy is calculated using return distribution:
calculateEntropy(series float price, simple int period) =>
// Calculate returns and their absolute values
// Sum absolute returns for normalization
// Apply Shannon entropy formula: -sum(p * log(p))
float entropy = 0.0
for i = 0 to array.size(returns) - 1
float prob = math.abs(array.get(returns, i)) / sumAbs
if prob > 0
entropy -= prob * math.log(prob)
entropy
Balance measures price position within range:
calculateBalance(series float high, series float low, series float close, simple int period) =>
float range = high - low
float position = (close - low) / (range > 0 ? range : 1)
float balance = ta.ema(position, period)
(balance - 0.5) * 2 // Normalize to -1 to +1
Lyapunov Exponent estimates chaos sensitivity:
lyapunovExponent(series float price, simple int period) =>
float sumLog = 0.0
for i = 1 to period
float ratio = price > 0 ? math.abs(price / price ) : 1.0
if ratio > 0
sumLog += math.log(ratio)
lyapunov := sumLog / period
Hurst Exponent measures trend persistence:
H > 0.5: Trending/persistent behavior
H = 0.5: Random walk
H < 0.5: Mean-reverting behavior
Signal Generation
Phase changes and extreme conditions generate signals:
Chaos Phase: Normalized entropy exceeds chaos threshold (default 0.7)
Order Phase: Normalized entropy falls below order threshold (default 0.3)
Extreme Chaos: Entropy exceeds 1.5x chaos threshold
Extreme Order: Entropy falls below 0.5x order threshold
Bifurcation: Variance exceeds 2x average variance
Dashboard Panel (Top-Right)
Market Phase - Current phase (CHAOS/ORDER/BALANCED)
Entropy Level - Normalized entropy value
Balance - Current balance reading (-1 to +1)
Chaos Index - Combined chaos score percentage
Volatility - Current price volatility
Lyapunov Exp - Lyapunov exponent value
Hurst Exponent - Hurst exponent value
Chaos Score - Overall chaos assessment
Status - Current market status
Visual Elements
Entropy Line - Main oscillator showing normalized entropy
Entropy EMA - Smoothed entropy for trend reference
Balance Area - Filled area showing balance direction
Chaos/Order Thresholds - Horizontal dashed lines
Lyapunov Line - Step line showing Lyapunov exponent
Strange Attractor - Circle plots showing attractor points
Phase Space - Line showing phase space reconstruction
Phase Background - Background color based on current phase
Extreme Markers - X-cross for extreme chaos, diamond for extreme order
Bifurcation Markers - Circles at potential regime changes
Input Parameters
Entropy Period (default: 20) - Period for entropy calculation
Balance Period (default: 14) - Period for balance calculation
Chaos Threshold (default: 0.7) - Threshold for chaos phase
Order Threshold (default: 0.3) - Threshold for order phase
Lyapunov Exponent (default: true) - Enable Lyapunov calculation
Hurst Exponent (default: true) - Enable Hurst calculation
Strange Attractor (default: true) - Enable attractor visualization
Bifurcation Detection (default: true) - Enable bifurcation detection
Suggested Use Cases
Identify market regime for strategy selection (trend-following vs mean-reversion)
Watch for phase changes as potential trading environment shifts
Use Hurst exponent to assess trend persistence
Monitor chaos index for volatility regime awareness
Avoid trading during extreme chaos phases
Timeframe Recommendations
Best on 1H to Daily charts. Chaos metrics require sufficient data for meaningful calculations.
Limitations
Chaos theory concepts are applied as analogies, not rigorous mathematical implementations
Lyapunov and Hurst calculations are simplified approximations
Strange attractor visualization is conceptual
Bifurcation detection uses variance as proxy
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always use proper risk management.
- Made with passion by officialjackofalltrades
Velocity Divergence Radar [JOAT]
Velocity Divergence Radar - Momentum Physics Edition
Overview
Velocity Divergence Radar is an open-source oscillator indicator that applies physics concepts to market analysis. It calculates price velocity (rate of change), acceleration (rate of velocity change), and jerk (rate of acceleration change) to provide a multi-dimensional view of momentum. The indicator also includes divergence detection and force vector analysis.
What This Indicator Does
The indicator calculates and displays:
Velocity - Rate of price change over a configurable period, smoothed with EMA
Acceleration - Rate of velocity change, showing momentum shifts
Jerk (3rd Derivative) - Rate of acceleration change, indicating momentum stability
Force Vectors - Volume-weighted acceleration representing market force
Kinetic Energy - Calculated as 0.5 * mass (volume ratio) * velocity squared
Momentum Conservation - Tracks momentum relative to historical average
Divergence Detection - Identifies when price and velocity diverge at pivots
How It Works
Velocity is calculated as smoothed rate of change:
calculateVelocity(series float price, simple int period) =>
float roc = ta.roc(price, period)
float velocity = ta.ema(roc, period / 2)
velocity
Acceleration is the change in velocity:
calculateAcceleration(series float velocity, simple int period) =>
float accel = ta.change(velocity, period)
float smoothAccel = ta.ema(accel, period / 2)
smoothAccel
Jerk is the change in acceleration:
calculateJerk(series float acceleration, simple int period) =>
float jerk = ta.change(acceleration, period)
float smoothJerk = ta.ema(jerk, period / 2)
smoothJerk
Force is calculated using F = m * a (mass approximated by volume ratio):
calculateForceVector(series float mass, series float acceleration) =>
float force = mass * acceleration
float forceDirection = math.sign(force)
float forceMagnitude = math.abs(force)
Signal Generation
Signals are generated based on velocity behavior:
Bullish Divergence: Price makes lower low while velocity makes higher low
Bearish Divergence: Price makes higher high while velocity makes lower high
Velocity Cross: Velocity crosses above/below zero line
Extreme Velocity: Velocity exceeds 1.5x the upper/lower zone threshold
Jerk Extreme: Jerk exceeds 2x standard deviation
Force Extreme: Force magnitude exceeds 2x average
Dashboard Panel (Top-Right)
Velocity - Current velocity value
Acceleration - Current acceleration value
Momentum Strength - Combined velocity and acceleration strength
Radar Score - Composite score based on velocity and acceleration
Direction - STRONG UP/SLOWING UP/STRONG DOWN/SLOWING DOWN/FLAT
Jerk - Current jerk value
Force Vector - Current force magnitude
Kinetic Energy - Current kinetic energy value
Physics Score - Overall physics-based momentum score
Signal - Current actionable status
Visual Elements
Velocity Line - Main oscillator line with color based on direction
Velocity EMA - Smoothed velocity for trend reference
Acceleration Histogram - Bar chart showing acceleration direction
Jerk Area - Filled area showing jerk magnitude
Vector Magnitude - Line showing combined vector strength
Radar Scan - Oscillating pattern for visual effect
Zone Lines - Upper and lower threshold lines
Divergence Labels - BULL DIV / BEAR DIV markers
Extreme Markers - Triangles at velocity extremes
Input Parameters
Velocity Period (default: 14) - Period for velocity calculation
Acceleration Period (default: 7) - Period for acceleration calculation
Divergence Lookback (default: 10) - Bars to scan for divergence
Radar Sensitivity (default: 1.0) - Zone threshold multiplier
Jerk Analysis (default: true) - Enable 3rd derivative calculation
Force Vectors (default: true) - Enable force analysis
Kinetic Energy (default: true) - Enable energy calculation
Momentum Conservation (default: true) - Enable momentum tracking
Suggested Use Cases
Identify momentum direction using velocity sign and magnitude
Watch for divergences as potential reversal warnings
Use acceleration to detect momentum shifts before price confirms
Monitor jerk for momentum stability assessment
Combine force and kinetic energy for conviction analysis
Timeframe Recommendations
Works on all timeframes. Higher timeframes provide smoother readings; lower timeframes show more granular momentum changes.
Limitations
Physics analogies are conceptual and not literal market physics
Divergence detection uses pivot-based lookback and may lag
Force calculation uses volume ratio as mass proxy
Kinetic energy is a derived metric, not actual energy
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always use proper risk management.
- Made with passion by officialjackofalltrades
Fractal Market Geometry [JOAT]
Fractal Market Geometry
Overview
Fractal Market Geometry is an open-source overlay indicator that combines fractal analysis with harmonic pattern detection, Fibonacci retracements and extensions, Elliott Wave concepts, and Wyckoff phase identification. It provides traders with a geometric framework for understanding market structure and identifying potential reversal patterns with multi-factor signal confirmation.
What This Indicator Does
The indicator calculates and displays:
Fractal Detection - Identifies fractal highs and lows using Williams-style pivot analysis with configurable period
Fractal Dimension - Calculates market complexity using range-based dimension estimation
Harmonic Patterns - Detects Gartley, Butterfly, Bat, Crab, Shark, Cypher, and ABCD patterns using Fibonacci ratios
Fibonacci Retracements - Key levels at 38.2%, 50%, and 61.8%
Fibonacci Extensions - Projection level at 161.8%
Elliott Wave Count - Simplified wave counting based on pivot detection (1-5)
Wyckoff Phase - Volume-based phase identification (Accumulation, Markup, Distribution, Neutral)
Golden Spiral Levels - ATR-based support and resistance levels using phi (1.618) ratio
Trend Detection - EMA crossover trend identification (20/50 EMA)
How It Works
Fractal detection uses a configurable period to identify swing points:
detectFractalHigh(simple int period) =>
bool result = true
float centerVal = high
for i = 0 to period - 1
if high >= centerVal or high >= centerVal
result := false
break
Harmonic pattern detection uses Fibonacci ratio analysis between swing points. Each pattern has specific ratio requirements:
Gartley: AB 0.382-0.618, BC 0.382-0.886, CD 1.27-1.618
Butterfly: AB 0.382-0.5, BC 0.382-0.886, CD 1.618-2.24
Bat: AB 0.5-0.618, BC 1.13-1.618, CD 1.618-2.24
Crab: AB 0.382-0.618, BC 0.382-0.886, CD 2.24-3.618
Shark: AB 0.382-0.618, BC 1.13-1.618, CD 1.618-2.24
Cypher: AB 0.382-0.618, BC 1.13-1.414, CD 0.786-0.886
Wyckoff phase detection analyzes volume relative to price movement:
wyckoffPhase(simple int period) =>
float avgVol = ta.sma(volume, period)
float priceChg = ta.change(close, period)
string phase = "NEUTRAL"
if volume > avgVol * 1.5 and math.abs(priceChg) < close * 0.02
phase := "ACCUMULATION"
else if volume > avgVol * 1.5 and math.abs(priceChg) > close * 0.05
phase := "MARKUP"
else if volume < avgVol * 0.7
phase := "DISTRIBUTION"
phase
Signal Generation
Signals use multi-factor confirmation for accuracy:
BUY Signal: Fractal low + Uptrend (EMA20 > EMA50) + RSI 30-55 + Bullish candle + Volume confirmation
SELL Signal: Fractal high + Downtrend (EMA20 < EMA50) + RSI 45-70 + Bearish candle + Volume confirmation
Pattern Detection: Label appears when harmonic pattern completes at current bar
Dashboard Panel (Top-Right)
Dimension - Fractal dimension value (market complexity measure)
Last High - Most recent fractal high price
Last Low - Most recent fractal low price
Pattern - Current harmonic pattern name or NONE
Elliott Wave - Current wave count (Wave 1-5) or OFF
Wyckoff - Current market phase or OFF
Trend - BULLISH, BEARISH, or NEUTRAL based on EMA crossover
Signal - BUY, SELL, or WAIT status
Visual Elements
Fractal Markers - Small triangles at fractal highs (down arrow) and lows (up arrow)
Geometry Lines - Dashed lines connecting the most recent fractal high and low
Fibonacci Levels - Clean horizontal lines at 38.2%, 50%, and 61.8% retracement levels
Fibonacci Extension - Horizontal line at 161.8% extension level
Golden Spiral Levels - Support and resistance lines based on ATR x 1.618
3D Fractal Field - Optional depth layers around swing levels (OFF by default)
Harmonic Pattern Markers - Small diamond shapes when Crab, Shark, or Cypher patterns detected
Pattern Labels - Text label showing pattern name when detected
Signal Labels - BUY/SELL labels on confirmed multi-factor signals
Input Parameters
Fractal Period (default: 5) - Bars on each side for fractal detection
Geometry Depth (default: 3) - Complexity of geometric calculations
Pattern Sensitivity (default: 0.8) - Tolerance for pattern ratio matching
Show Fibonacci Levels (default: true) - Display retracement levels
Show Fibonacci Extensions (default: true) - Display extension level
Elliott Wave Detection (default: true) - Enable wave counting
Wyckoff Analysis (default: true) - Enable phase detection
Golden Spiral Levels (default: true) - Display spiral support/resistance
Show Fractal Points (default: true) - Display fractal markers
Show Geometry Lines (default: true) - Display connecting lines
Show Pattern Labels (default: true) - Display pattern name labels
Show 3D Fractal Field (default: false) - Display depth layers
Show Harmonic Patterns (default: true) - Display pattern markers
Show Buy/Sell Signals (default: true) - Display signal labels
Suggested Use Cases
Identify potential reversal zones using harmonic pattern completion
Use Fibonacci levels for entry, stop-loss, and target planning
Monitor Wyckoff phases for accumulation/distribution awareness
Track Elliott Wave counts for trend structure analysis
Use fractal dimension to gauge market complexity
Wait for multi-factor signal confirmation before entering trades
Timeframe Recommendations
Best on 1H to Daily charts. Lower timeframes produce more fractals but with less significance. Higher timeframes provide stronger levels and more reliable signals.
Limitations
Harmonic pattern detection uses simplified ratio ranges and may not match all textbook definitions
Elliott Wave counting is basic and does not include all wave rules
Wyckoff phase detection is volume-based approximation
Fractal dimension calculation is simplified
Signals require fractal confirmation which has inherent lag equal to the fractal period
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always use proper risk management.
- Made with passion by officialjackofalltrades
Dimensional Support ResistanceDimensional Support Resistance
Overview
Dimensional Support Resistance is an open-source overlay indicator that automatically detects and displays clean, non-overlapping support and resistance levels using pivot-based analysis with intelligent filtering. It identifies significant swing highs and lows, filters them by minimum distance to prevent visual clutter, and provides volume-confirmed bounce signals.
What This Indicator Does
The indicator calculates and displays:
Dynamic Pivot Levels - Automatically detected swing highs and lows based on configurable pivot strength
Distance Filtering - Ensures levels are spaced apart by a minimum percentage to prevent overlap
S/R Zones - Visual zones around each level showing the price area of significance
Bounce Detection - Identifies when price reverses at support or resistance levels
Volume Confirmation - Strong signals require above-average volume for confirmation
How It Works
Pivot detection scans for swing highs and lows using a configurable strength parameter. A pivot low requires the low to be lower than all surrounding bars within the strength period.
Signal Generation
The indicator generates bounce signals using TradingView's built-in pivot detection combined with candle reversal confirmation:
Support Bounce: Pivot low forms with bullish close (close > open)
Resistance Bounce: Pivot high forms with bearish close (close < open)
Strong Bounce: Bounce occurs with volume 1.5x above 20-period average
A cooldown period of 15 bars prevents signal spam.
Dashboard Panel
A compact dashboard displays:
Support - Count of active support levels
Resistance - Count of active resistance levels
Dashboard position is configurable (Top Left, Top Right, Bottom Left, Bottom Right).
Visual Elements
Support Lines - Green horizontal lines at support levels
Resistance Lines - Red horizontal lines at resistance levels
S/R Zones - Semi-transparent boxes around levels showing zone width
Price Labels - S: and R: labels showing exact price of nearest levels
BOUNCE Markers - Triangle shapes with text when price bounces at a level
STRONG Markers - Label shapes when bounce occurs with high volume
Input Parameters
Lookback Period (default: 100) - Historical bars to scan for pivots
Pivot Strength (default: 8) - Bars on each side required for valid pivot (higher = fewer but stronger levels)
Max Levels Each Side (default: 2) - Maximum support and resistance levels displayed
Zone Width % (default: 0.15) - Width of zones around each level as percentage of price
Min Distance Between Levels % (default: 1.0) - Minimum spacing between levels to prevent overlap
Show S/R Zones (default: true) - Toggle zone visualization
Show Bounce Signals (default: true) - Toggle signal markers
Support Color (default: #00ff88) - Color for support elements
Resistance Color (default: #ff3366) - Color for resistance elements
Suggested Use Cases
Identify key support and resistance levels for entry and exit planning
Use bounce signals as potential reversal confirmation
Combine with other indicators for confluence-based trading decisions
Monitor strong signals for high-probability setups with volume confirmation
Timeframe Recommendations
Works on all timeframes. Higher timeframes (4H, Daily) provide more significant levels with fewer signals. Lower timeframes show more granular structure but may produce more noise.
Limitations
Pivot detection requires lookback bars, so very recent pivots may not be immediately visible
Bounce signals are based on pivot formation and may lag by the pivot strength period
Levels are recalculated on each bar, so they may shift as new pivots form
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always use proper risk management and conduct your own analysis before trading.
- Made with passion by officialjackofalltrades
G Trade SessionsWe built this indicator because we was tired of guessing when major markets open and close. It draws simple boxes around each trading session so you can instantly see where the action is.
What it does:
Shows you the four key sessions — Asia, Frankfurt, London, and New York — as transparent boxes right on your chart. Each box marks the high and low of that session, which is super useful for spotting support/resistance levels.
Why I like it:
No clutter — boxes are subtle and don't get in the way
Labels switch from black to white automatically depending on your chart theme (dark or light)
Sessions don't overlap, so the chart stays clean
You can turn off any session you don't care about
Hope you find it useful!
Quantum Flow [JOAT]Quantum Flow Nexus - Advanced Multi-Dimensional Flow Analysis
Overview
Quantum Flow Nexus is an open-source overlay indicator that combines custom EMA-based flow calculations with order flow analysis, multi-timeframe correlation, and liquidity zone detection. It provides traders with a structured framework for analyzing market momentum and identifying potential entry points based on multiple confirming factors.
What This Indicator Does
The indicator calculates several analytical components:
Quantum Flow Oscillator - A custom oscillator built from multiple EMA layers at different depths
Flow Momentum - Rate of change of the flow oscillator
Order Flow Delta - Buy vs sell volume pressure estimation
Smart Money Index - Volume-weighted directional bias metric
Multi-Timeframe Entanglement - Price correlation across 15m and 60m timeframes
Liquidity Zones - Historical swing high/low levels with volume significance
Wave Function State - Momentum-based decisiveness detection
How It Works
The core quantum oscillator uses a custom EMA calculation with depth layering:
quantumOscillator(series float src, simple int len, simple int depth) =>
float osc = 0.0
for i = 1 to depth
int fastLen = len / i
int slowLen = len * i
float emaFast = quantumEMA(src, fastLen)
float emaSlow = quantumEMA(src, slowLen)
osc += (emaFast - emaSlow) / depth
osc
This creates a multi-layered view of momentum by comparing EMAs at progressively different speeds.
Signal Generation
Basic signals occur when:
Bullish: Flow crosses above lower band + positive momentum + positive order flow delta
Bearish: Flow crosses below upper band + negative momentum + negative order flow delta
Strong signals require additional confirmation:
Smart Money Index above/below threshold (50/-50)
Entanglement score above 50%
Wave function in collapsed state (decisive momentum)
Confluence Score Calculation
The indicator combines multiple factors into a single confluence percentage:
float confluenceScore = (flowStrength * 20 + entanglementScore * 0.3 + math.abs(orderFlowDelta) * 0.5) / 3
Dashboard Panel (Top-Right)
Flow Strength - Distance from center line normalized by standard deviation
Momentum - Current rate of change of flow
Trend - BULLISH/BEARISH/NEUTRAL based on flow vs EMA
Confluence Score - Combined factor percentage
Order Flow Delta - Buy/sell pressure percentage
Entanglement - Multi-timeframe correlation score
Wave State - COLLAPSED or SUPERPOSITION
Signal - Current actionable status
Visual Elements
Flow Lines - Center flow line with upper/lower bands
Quantum Zones - Filled areas between bands showing bullish/bearish zones
3D Quantum Field - Five oscillating layers creating depth visualization
Order Flow Blocks - Boxes highlighting significant order flow imbalances
Liquidity Heatmap - Dashed lines at significant historical levels
Signal Markers - Triangles for basic signals, labels for strong signals
Input Parameters
Flow Period (default: 21) - Base period for flow calculations
Quantum Depth (default: 3) - Number of EMA layers
Sensitivity (default: 1.5) - Band width multiplier
Liquidity Max Levels (default: 8) - Maximum liquidity zones displayed
Liquidity Min Strength Ratio (default: 0.10) - Minimum volume significance
Suggested Use Cases
Identify momentum direction using flow oscillator position
Confirm entries with order flow and smart money readings
Use liquidity zones as potential support/resistance areas
Wait for strong signals with multiple factor confirmation
Timeframe Recommendations
Effective on 15m to Daily charts. Lower timeframes may produce more signals with higher noise levels.
Limitations
Order flow is estimated from candle structure, not actual order book data
Multi-timeframe requests add processing time
Liquidity zones are based on historical pivots and may not reflect current market structure
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always use proper risk management.
- Made with passion by officialjackofalltrades
Ocean Master [JOAT]Ocean Master QE - Advanced Oceanic Market Analysis with Quantum Flow Dynamics
Overview
Ocean Master QE is an open-source overlay indicator that combines multiple analytical techniques into a unified market analysis framework. It uses ATR-based dynamic channels, volume-weighted order flow analysis, multi-timeframe correlation (quantum entanglement concept), and harmonic oscillator calculations to provide traders with a comprehensive view of market conditions.
What This Indicator Does
The indicator calculates and displays several key components:
Dynamic Price Channels - ATR-adjusted upper, middle, and lower channels that adapt to current volatility conditions
Order Flow Analysis - Separates buying and selling volume pressure to calculate a directional delta
Smart Money Index - Volume-weighted order flow metric that highlights potential institutional activity
Harmonic Oscillator - Weighted combination of 10 Fibonacci-period EMAs (5, 8, 13, 21, 34, 55, 89, 144, 233, 377) to identify trend direction
Multi-Timeframe Correlation - Measures price correlation across 1H, 4H, and Daily timeframes
Wave Function Analysis - Momentum-based state detection that identifies when price action becomes decisive
How It Works
The core channel calculation uses ATR with a configurable quantum sensitivity factor:
float atr = ta.atr(i_atrLength)
float quantumFactor = 1.0 + (i_quantumSensitivity * 0.1)
float quantumATR = atr * quantumFactor
upperChannel := ta.highest(high, i_length) - (quantumATR * 0.5)
lowerChannel := ta.lowest(low, i_length) + (quantumATR * 0.5)
midChannel := (upperChannel + lowerChannel) * 0.5
Order flow is calculated by separating volume into buy and sell components based on candle direction:
The harmonic oscillator weights shorter EMAs more heavily using inverse weighting (1/1, 1/2, 1/3... 1/10), creating a responsive yet smooth trend indicator.
Signal Generation
Confluence signals require multiple conditions to align:
Bullish: Harmonic oscillator crosses above zero + positive Smart Money Index + positive Order Flow Delta
Bearish: Harmonic oscillator crosses below zero + negative Smart Money Index + negative Order Flow Delta
Dashboard Panel (Top-Right)
Bias - Current market direction based on price vs mid-channel
Entanglement - Multi-timeframe correlation score (0-100%)
Wave State - COLLAPSED (decisive) or SUPERPOSITION (uncertain)
Volume - Current volume relative to 20-period average
Volatility - ATR as percentage of price
Smart Money - Volume-weighted order flow reading
Visual Elements
Ocean Depth Layers - Gradient fills between channel levels representing different price zones
Channel Lines - Upper (surface), middle, and lower (seabed) dynamic levels
Divergence Markers - Triangle shapes when harmonic oscillator crosses zero
Confluence Labels - BULL/BEAR labels when multiple factors align
Suggested Use Cases
Identify trend direction using the harmonic oscillator and channel position
Monitor order flow for potential institutional activity
Use multi-timeframe correlation to confirm trade direction across timeframes
Watch for confluence signals where multiple factors align
Input Parameters
Length (default: 14) - Base period for channel and indicator calculations
ATR Length (default: 14) - Period for ATR calculation
Quantum Depth (default: 3) - Complexity factor for calculations
Quantum Sensitivity (default: 1.5) - Channel width multiplier
Timeframe Recommendations
Works on all timeframes. Higher timeframes (4H, Daily) provide smoother signals; lower timeframes require faster reaction times and may produce more noise.
Limitations
Multi-timeframe requests add processing overhead
Order flow estimation is based on candle direction, not actual order book data
Correlation calculations require sufficient historical data
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always use proper risk management and conduct your own analysis before trading.
- Made with passion by officialjackofalltrades
