NR4 & NR7 with Breakouts [LuxAlgo]NR4 & NR7 with Breakouts is a simple indicator that utilizes the NR4 and NR7 candle patterns to display candle ranges and signals from range breakouts.
🔶 USAGE
The Narrow Range Patterns are candle formations determined by the last candle having a narrower (high-low) range than the previous number. This indicator showcases the 2 most recognized Narrow Range Patterns, which are the 4 and 7 bar variants (NR4 and NR7).
These patterns, introduced by Toby Crabel, are thought to provide insight for potential market breakouts by identifying periods of low volatility indicated by a candle with a small range. This is due to the idea that markets often move from periods of low volatility (contraction) to high volatility (expansion), and the NR4 and NR7 patterns help spot these transitions.
By utilizing these patterns, traders are better able to anticipate and respond to market shifts for better decision-making and risk management.
NOTE: These patterns have traditionally been studied on the Daily Timeframe Chart. This indicator allows the user to select a timeframe to generate these patterns from. It is suggested to be mindful of this when considering these patterns.
In this indicator, on the bar after the pattern is detected, the Narrow Range Bar will be highlighted with a zone, and lines displaying the range will extend from it. These ranges are helpful for providing levels to set limit orders and for managing risk.
Users are able to adjust which pattern they want visualized on their chart, please note;
All NR7s are NR4s but not all NR4s are NR7s.
Because of this, you will notice that when selecting "NR4" to display, the colors will change, but the detected ranges will not change.
🔹 Signals
When a Narrow Range Bar is detected, the script will wait for the price to close outside of the Range, then a signal will fire indicating the direction of exit. The signals are produced from the last NR4 or NR7 and will have the potential to fire from that range until a new NR4 or NR7 is detected.
After a signal fires, the logic goes into a "reset" period where it will wait for the price to reach the Range Mean before firing another signal.
These signals can be anticipated by considering the underlying logic and watching price approach the range extremities, and can be improved by utilizing other market information for confluence.
🔶 SETTINGS
Timeframe: Choose which timeframe to identify the NR4 and NR7 Pattern on. This must be Higher than the chart timeframe.
Pattern Type: Choose which (or all) patterns to display.
Indicators and strategies
OA - PowerZones Support And ResistancePowerZones - Dynamic Support/Resistance Identifier
Overview
PowerZones is an advanced technical analysis tool that automatically detects significant support and resistance zones using volume data and pivot points. This indicator pulls data from higher timeframes (weekly by default) to help you identify strong and meaningful levels that are filtered from short-term "noise."
Features
Multi-Timeframe Analysis: Create support/resistance levels from daily, weekly, or monthly data
Volume Filtering: Detect high-volume pivot points to identify more reliable levels
Dynamic Threshold: Volume filter that automatically adjusts to market conditions
Visual Clarity: Support/resistance zones are displayed as boxes with adjustable transparency
Optimal Level Selection: Filter out close levels to focus on the most significant support/resistance points
Use Cases
Entry/Exit Points: Identify trading opportunities at important support and resistance levels
Stop-Loss Placement: Use natural support levels to set more effective stop-losses
Target Setting: Use potential resistance levels as profit-taking targets
Understanding Market Structure: Detect long-term support/resistance zones to better interpret price movement
Input Parameters
Lookback Period: The period used to determine pivot points
Box Width : Adjusts the width of support/resistance zones
Relative Volume Period: The period used for relative volume calculation
Maximum Number of Boxes: Maximum number of support/resistance zones to display on the chart
Box Transparency: Transparency value for the boxes
Timeframe: Timeframe to use for support/resistance detection (Daily, Weekly, Monthly)
How It Works
PowerZones identifies pivot highs and lows in the selected timeframe. It filters these points using volume data to show only meaningful and strong levels. The indicator also consolidates nearby levels, allowing you to focus only on the most important zones on the chart.
Best Practices
Weekly timeframe setting is ideal for identifying long-term important support/resistance levels
Working with weekly levels on a daily chart allows you to combine long-term levels with short-term trades
ATR-based box width creates support/resistance zones that adapt to market volatility
Use the indicator along with other technical indicators such as RSI, MACD, or moving averages to confirm trading signals
Note: Like all technical indicators, this indicator does not guarantee 100% accuracy. Always apply risk management principles and use it in conjunction with other analysis methods to achieve the best results.
If you like the PowerZones indicator, please show your support by giving it a star and leaving a comment!
Dual-Phase Trend Regime Oscillator (Zeiierman)█ Overview
Trend Regime: Dual-Phase Oscillator (Zeiierman) is a volatility-sensitive trend classification tool that dynamically switches between two oscillators, one optimized for low volatility, the other for high volatility.
By analyzing standard deviation-based volatility states and applying correlation-derived oscillators, this indicator reveals not only whether the market is trending but also what kind of trend regime it is in —Bullish or Bearish —and how that regime reacts to market volatility.
█ Its Uniqueness
Most trend indicators assume a static market environment; they don't adjust their logic when the underlying volatility shifts. That often leads to false signals in choppy conditions or late entries in trending phases.
Trend Regime: Dual-Phase Oscillator solves this by introducing volatility-aware adaptability. It switches between a slow, stable oscillator in calm markets and a fast, reactive oscillator in volatile ones, ensuring the right sensitivity at the right time.
█ How It Works
⚪ Volatility State Engine
Calculates returns-based volatility using standard deviation of price change
Smooths the current volatility with a moving average
Builds a volatility history window and performs median clustering to determine typical "Low" and "High" volatility zones
Dynamically assigns the chart to one of two internal volatility regimes: Low or High
⚪ Dual Oscillators
In Low Volatility, it uses a Slow Trend Oscillator (longer lookback, smoother)
In High Volatility, it switches to a Fast Trend Oscillator (shorter lookback, responsive)
Both oscillators use price-time correlation as a measure of directional strength
The output is normalized between 0 and 1, allowing for consistent interpretation
⚪ Trend Regime Classification
The active oscillator is compared to a neutral threshold (0.5)
If above: Bullish Regime, if below: Bearish Regime, else: Neutral
The background and markers update to reflect regime changes visually
Triangle markers highlight bullish/bearish regime shifts
█ How to Use
⚪ Identify Current Trend Regime
Use the background color and chart table to immediately recognize whether the market is trending up or down.
⚪ Trade Regime Shifts
Use triangle markers (▲ / ▼) to spot fresh regime entries, which are ideal for confirming breakouts within trends.
⚪ Pullback Trading
Look for pullbacks when the trend is in a stable condition and the slow oscillator remains consistently near the upper or lower threshold. Watch for moments when the fast oscillator retraces back toward the midline, or slightly above/below it — this often signals a potential pullback entry in the direction of the prevailing trend.
█ Settings Explained
Length (Slow Trend Oscillator) – Used in calm conditions. Longer = smoother signals
Length (Fast Trend Oscillator) – Used in volatile conditions. Shorter = more responsive
Volatility Refit Interval – Controls how often the system recalculates Low/High volatility levels
Current Volatility Period – Lookback used for immediate volatility measurement
Volatility Smoothing Length – Applies an SMA to the raw volatility to reduce noise
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Premium Lux AlgoCombining multiple indicators to receive buy and sell signals and create support and resistance levels and cloud space
3 Candle Rules -PJThis script is to identify the change in trend by simply applying 3 rules on candle sticks. These three rules are applied by comparing HLC of current candle with previous candle.
Scalp Cloud Signal🟢 Scalp Cloud Signal
📉📈 A custom indicator specially designed for scalping in lower timeframes (M5 to H1 max)
🧠 Concept:
Scalp Cloud Signal uses two Exponential Moving Averages (EMAs) to detect short-term trend shifts:
⚡ Fast EMA: period 5
🐢 Slow EMA: period 13
🎯 How it works:
✅ Bullish crossover (fast EMA crosses above slow EMA) →
🌿 Displays a green cloud = Bullish trend
🔼 A small bull triangle appears below the candle
❌ Bearish crossover (fast EMA crosses below slow EMA) →
🍁 Displays a red cloud = Bearish trend
🔽 A small bear triangle appears above the candle
📌 Good to know:
📍This indicator does not provide automated buy/sell signals — it is intended to enhance trend
readability
📍Can be used in confluence with other tools (e.g. RSI, price action…) for better entries
📍Visual signals are plotted exactly at the crossover moment
ETF Builder & Backtest System [TradeDots]Create, analyze, and monitor your own custom “ETF-like” portfolio directly on TradingView. This script merges up to 10 different assets with user-defined weightings into a single composite chart, allowing you to see how your personalized portfolio would have performed historically. It is an original tool designed to help traders and investors quickly gauge risk and return profiles without leaving the TradingView platform.
📝 HOW IT WORKS
1. Custom Portfolio Construction
Multiple Assets : Combine up to 10 different stocks, ETFs, cryptocurrencies, or other symbols.
User-Defined Weights : Allocate each asset a percentage weight (e.g., 15% in AAPL, 10% in MSFT, etc.).
Single Composite Value : The script calculates a weighted “ETF-style” price, effectively simulating a merged portfolio curve on your chart.
2. Performance Tracking & Return Analysis
Automatic History Capture : The indicator records each asset’s starting price when it first appears in your chosen date range.
Rolling Updates : As time progresses, all asset prices are continually evaluated and the portfolio value is updated in real time.
Buy & Hold Returns : See how each asset—and the overall portfolio—performed from the “start” date to the most recent bar.
Annualized Return : Automatically calculates CAGR (Compound Annual Growth Rate) to help visualize performance over varying timescales.
3. Table & Visual Output
Performance Table : A comprehensive table displays individual asset returns, annualized returns, and portfolio totals.
Normalized Chart Plot : The composite ETF value is scaled to 100 at the start date, making it easy to compare relative growth or decline.
Optional Time Filter : You can define a specific date range (Start/End Dates) to focus on a particular period or to limit historical data.
⚙️ KEY FEATURES
1. Flexible Asset Selection
Choose any symbols from multiple asset classes. The script will only run calculations when data is available—no need to worry about missing quotes.
2. Dynamic Table Reporting
Start Price for each asset
Percentage Weight in the portfolio
Total Return (%) and Annualized Return (%)
3. Simple Backtesting Logic
This script takes a straightforward Buy & Hold perspective. Once the start date is reached, the portfolio remains static until the end date, so you can quickly assess hypothetical growth.
4. Plot Customization
Toggle the main “ETF” plot on/off.
Alter the visual style for tables and text.
Adjust the time filter to limit or extend your performance measurement window.
🚀 HOW TO USE IT
1. Add the Script
Search for “ETF Builder & Backtest System ” in the Indicators & Strategies tab or manually add it to your chart after saving it in your Pine Editor.
2. Configure Inputs
Enable Time Filter : Choose whether to restrict the analysis to a particular date range.
Start & End Date : Define the period you want to measure performance over (e.g., from 2019-12-31 to 2025-01-01).
Assets & Weights : Enter each symbol and specify a percentage weight (up to 10 assets).
Display Options : Pick where you want the Table to appear and choose background/text colors.
3. Interpret the Table & Plots
Asset Rows : Each asset’s ticker, weighting, start price, and performance metrics.
ETF Total Row : Summarizes total weighting, composite starting value, and overall returns.
Normalized Plot : Tracks growth/decline of the combined portfolio, starting at 100 on the chart.
4. Refine Your Strategy
Compare how different weights or a new mix of assets would have performed over the same period.
Assess if certain assets contribute disproportionately to your returns or volatility.
Use the results to guide allocations in your real trading or paper trading accounts.
❗️LIMITATIONS
1. Buy & Hold Only
This script does not handle rebalancing or partial divestments. Once the portfolio starts, weights remain fixed throughout the chosen timeframe.
2. No Reinvestment Tracking
Dividends or other distributions are not factored into performance.
3. Data Availability
If historical data for a particular asset is unavailable on TradingView, related results may display as “N/A.”
4. Market Regimes & Volatility
Past performance does not guarantee similar future behavior. Markets can change rapidly, which may render historical backtests less predictive over time.
⚠️ RISK DISCLAIMER
Trading and investing carry significant risk and can result in financial loss. The “ETF Builder & Backtest System ” is provided for informational and educational purposes only. It does not constitute financial advice.
Always conduct your own research.
Use proper risk management and position sizing.
Past performance does not guarantee future results.
This script is an original creation by TradeDots, published under the Mozilla Public License 2.0.
Use this indicator as part of a broader trading or investment approach—consider fundamental and technical factors, overall market context, and personal risk tolerance. No trading tool can assure profits; exercise caution and responsibility in all financial decisions.
Tremor Tracker [theUltimator5]Tremor Tracker is a volatility monitoring tool that visualizes the "tremors" of price action by measuring and analyzing the average volatility of the current trading range, working on any timeframe. This indicator is designed to help traders detect when the market is calm, when volatility is building, and when it enters a potentially unstable or explosive state by using a lookback period to determine the average volatility and highlights outliers.
🔍 What It Does
Calculates bar-level volatility as the percentage difference between the high and low of each candle.
Applies a user-selected moving average (SMA, EMA, or WMA) to smooth out short-term noise and highlight trends in volatility.
Compares current volatility to its long-term average over a configurable lookback period.
Dynamically colors each volatility bar based on how extreme it is relative to historical behavior:
🟢 Lime — Low volatility (subdued, ranging conditions)
🟡 Yellow — Moderate or building volatility
🟣 Fuchsia — Elevated or explosive volatility
⚙️ Customizable Settings
Low Volatility Limit and High Volatility Limit: Define the thresholds for color changes based on volatility's ratio to its average.
Volatility MA Length: Adjust the smoothing period for the volatility moving average.
Average Volatility Lookback: Set how many bars are used to calculate the long-term average.
MA Type: Choose between SMA, EMA, or WMA for smoothing.
Show Volatility MA Line?: Toggle the display of the smoothed volatility trendline.
Show Raw Volatility Bars?: Toggle the display of raw per-bar volatility with dynamic coloring.
🧠 Use Cases
Identify breakout conditions: When volatility spikes above average, it may signal the onset of a new trend or a news-driven breakout.
Avoid chop zones: Prolonged periods of low volatility often precede sharp moves — a classic “calm before the storm” setup.
Timing reversion trades: Detect overextended conditions when volatility is well above historical norms.
Adapt strategies by volatility regime: Use color feedback to adjust risk, position sizing, or strategy selection based on real-time conditions.
📌 Notes
Volatility is expressed as a percentage, making this indicator suitable for use across different timeframes and asset classes.
The tool is designed to be visually intuitive, so traders can quickly spot evolving volatility states without diving into raw numbers.
Smarter Money Concepts - MTF IFVGs [PhenLabs]📊 Smarter Money Concepts - MTF IFVG
Version: PineScript™ v6
📌 Description
This multi-timeframe indicator identifies Inverse Fair Value Gaps (IFVGs) and their inversions across simultaneous chart intervals, helping traders spot liquidity voids and potential reversal zones. By analyzing price action through the lens of institutional order flow patterns, it solves the problem of manual gap tracking across timeframes while incorporating volatility-adjusted parameters and psychological level analysis for higher-probability setups.
🚀 Points of Innovation
• Multi-Timeframe Engine - Simultaneous analysis of 3 higher timeframes
• Adaptive Parameters - Auto-adjusts to market volatility conditions
• Quality Scoring System - Ranks gaps using RVI strength and size metrics
• Inversion Tracking - Monitors failed gaps for counter-trend signals
• Render Optimization - Prevents chart clutter with smart gap management
🔧 Core Components
FVG Detection Logic: Identifies gaps using customizable price source (Close/Wick)
Inversion Tracker: Manages failed gaps and generates counter signals
Multi-Timeframe Engine: Processes 3 independent higher timeframe analyses
Dashboard System: Real-time display of active gaps across all timeframes
🔥 Key Features
• Volatility-adjusted gap size filters (ATR-based)
• Customizable timeframe confluence analysis
• Color-coded quality scoring
• Non-repainting inversion signals
• Mobile-optimized visual rendering
🎨 Visualization
• Colored Boxes: Translucent zones show active gaps (green/bullish, red/bearish)
• Midline Plot: Dashed gray line marks gap midpoint for price targets
• Inversion Markers: Intense colors show failed gaps (dark red/bullish failure, bright green/bearish failure)
• HTF Differentiation: Higher timeframe gaps shown in blue/teal hues
📖 Usage Guidelines
Multi-Timeframe Settings
• Higher Timeframe 1
Default: 30 | Range: Any > Chart TF | Controls primary confluence timeframe
• Show All Timeframes
Default: True | Toggles multi-TF gap displays
Gap Settings
• Source
Default: Close | Options: | Determines gap measurement method
• RVI Period
Default: 14 | Range: 1-50 | Sets momentum confirmation sensitivity
• RVI Value
Default 0.1 | 0 to see all IFVGs | Increase min RVI to see the most powerful IFVGs
✅ Best Use Cases
• Identifying confluence across timeframes
• Spotting institutional order blocks
• High-probability reversal trading
• Trend continuation confirmation
• Volatility breakout setups
⚠️ Limitations
• Repaints historical gap zones
• Requires understanding of FVG concepts
• Higher timeframe data latency
• Quality scores rely on RVI/ATR settings
💡 What Makes This Unique
First FVG indicator with true multi-timeframe processing
Adaptive parameters that auto-adjust to volatility
Quantifiable quality scoring system
Professional-grade dashboard with HTF tracking
🔬 How It Works
Gap Detection: Identifies FVGs using price relationships and RVI confirmation
Inversion Tracking: Monitors price breaches to flag failed gaps
Quality Assessment: Scores gaps based on size, momentum, and location
Adaptive Filtering: Adjusts parameters using ATR-based volatility analysis
Multi-TF Synthesis: Correlates gaps across user-selected timeframes
Visual Rendering: Displays only relevant, active gaps to prevent clutter
💡 Note:
Start with default settings and gradually adjust parameters after observing market interactions. Focus on gaps with quality scores above 7 that align with higher timeframe trends. Combine with price action at psychological levels for highest-probability setups. Remember that higher timeframe gaps generally carry more significance than current chart gaps.
1-Candle Order Block DetectorThis simple indicator is based on the 1-Candle rule. During an impulsive move toward the upside or downside, an order block is plotted based on a single down-closed or up-closed candle.
Inputs can be easily customized based on preferences or strength of trend filtering.
[blackcat] L3 Squeeze DynamicsOVERVIEW
📈 The L3 Squeeze Dynamics indicator integrates three powerful analytical components:
🌈 Squishy Momento Indicator (SMI): Detects periods when volatility contracts/expands
🔄 Converging Band Patterns: Combines Bollinger Bands & Keltner Channel overlays
🎯 Parabolic SAR: Identifies potential reversal zones through dynamic reference lines
The system produces actionable trade alerts during critical turning points where traditional trends become compressed/squeezed.
KEY CONCEPTS EXPLAINED
Market Compression Theory
When prices consolidate within tight ranges across multiple timeframe dimensions, they're said to be experiencing a 'squeeze'. These moments often precede explosive breakout moves that follow.
Bollinger-Band Analysis
: Defines how far back we look to calculate averages
: Controls band width relative to standard deviation
→ Helps identify overextended vs contracted states
Keltner Channel Integration
: Measures average range movement
: Determines channel boundaries from True Range data
→ Provides context about trending pressure
SAR Implementation Details
: Initial push factor
: Rate of change adjustment
: Ceiling point cap
→ Tracks trend progression dynamically
TRADING STRATEGY OUTLINE
🔵 LONG ENTRY CONDITIONS:
✓ Rising squeeze dynamics reading
✓ Above centerline crossing
✓ Below VW-RSI resistance level
✓ SAR below current price zone
🔴 SHORT ENTRY REQUIREMENTS:
✗ Falling squeeze metrics
✗ Below midline penetration
✗ Through VW-RSI support barrier
✗ SAR above present rate area
🔄 EXIT MECHANISMS:
⚡ Immediate stops triggered by opposite direction breaks
♻️ Trail stops activated after initial profit targets hit
💪 Multi-bar conformation filters reduce false alarms
PRACTICAL USAGE GUIDE
INITIAL SETUP
Chart Selection: Daily minimum recommended
Timeframe Alignment: Ensure consistent intervals
Risk Parameters: Define max loss per trade upfront
DYNAMIC ADJUSTMENT
Parameter Optimization: Test various length/mult combinations
Confirmation Rules: Add secondary validations if needed
Label Management: Customize appearance as preferred
MONITORING PROCEDURES
Regularly review recent signals validity
Track win-rate statistics
Adapt thresholds based on changing market regimes
ADVANCED FEATURES BREAKDOWN
🔍 Visualization Layering:
Base Bars: Colored yellow/orange/fuchsia/purple depending on strength/direction
Reference Lines: SAR plotted as cross markers
Alert Labels: Explicitly marked positions with specific codes
⚙️ Calculation Framework:
Linear Regression Application: Smooths raw price action input
Cumulative Trend Filtering: Reduces noise via sequential logic blocks
Conditional State Machines: Handles complex state transitions between phases
🧮 Mathematical Foundation:
Standard Deviation Calculations: Quantify typical price dispersion
Weighted Average Processing: Incorporates volume influence into RSI variant
Boolean Logic Gates: Precisely define trigger scenarios
TROUBLESHOOTING TIPS
Common Issues Solutions
Frequent False Alerts Tighten parameter constraints
Delayed Entries Increase lag tolerance thresholds
Inconsistent Results Review asset-specific adjustments required
RISK MANAGEMENT RECOMMENDATIONS
📋 Essential Practices:
Position Size Control: Never exceed predetermined limits
Proper Stop Placement: Use logical breach points rather than arbitrary distances
Profit Target Planning: Set realistic objectives aligned with reward/risk ratios
Money Management Protocols: Adhere strictly to portfolio allocation guidelines
EXTENSION POTENTIALITY
Future Enhancements Could Include:
Additional Filter Layers: MACD, Stochastic integration options
Machine Learning Components: Pattern recognition improvements
Adaptive Algorithm Tuning: Self-adjusting parameters based on historical success rates
Advanced Order Execution Strategies: Bracket orders implementation possibilities
TECHNICAL DETAILS
Performance Metrics:
Computationally Efficient: Optimized for real-time processing
Memory Friendly: Minimal overhead impact on resources
Scalable Architecture: Easily modifiable core structure
Code Structure Principles:
Modular Design Approach: Separate functions handle distinct responsibilities
Clear Variable Naming Convention: Improves maintainability/readability
Comprehensive Documentation Strategy: Inline explanations guide modifications
FINAL REMARKS
This sophisticated algorithm represents years of refinement combining both fundamental principles and practical experience. While highly effective under appropriate circumstances, it's crucial to remember no single indicator guarantees profits consistently. Successful application requires disciplined execution alongside robust money management practices.
Always test thoroughly before committing capital using any automated strategies!
🌟 Happy Trading! ✅
[blackcat] L3 Ichimoku FusionCOMPREHENSIVE ANALYSIS OF THE L3 ICHIMOKU FUSION INDICATOR
🌐 Overview:
The L3 Ichimoku Fusion is a sophisticated multi-layered technical analysis tool integrating classic Japanese market forecasting techniques with enhanced dynamic elements designed specifically for identifying potential turning points in financial instruments' pricing action.
Key Purpose:
To provide traders with an intuitive yet powerful framework combining established ichimoku principles while incorporating additional validation checkpoints derived from cross-timeframe convergence studies.
THEORETICAL FOUNDATION EXPLAINED
🎓 Conceptual Background:
:
• Conversion & Base Lines tracking intermediate term averages
• Lagging Span providing delayed feedback mechanism
• Lead Spans projecting future equilibrium states
:
• Adaptive parameter scaling options
• Automated labeling system for critical junctures
• Real-time alert infrastructure enabling immediate response capability
PARAMETER CONFIGURATION GUIDE
⚙️ Input Parameters Explained In Detail:
Regional Setting Selection:**
→ Oriental Configuration: Standardized approach emphasizing slower oscillation cycles
→ Occidental Variation: Optimized settings reducing lag characteristics typical of original methodology
Multiplier Adjustment Functionality:**
↔ Allows fine-graining oscillator responsiveness without altering core relationship dynamics
↕ Enables adaptation to various instrument volatility profiles efficiently
Displacement Value Control:**
↓ Controls lead/lag offset positioning relative to current prices
↑ Provides flexibility in adjusting visual representation alignment preferences
DYNAMIC CALCULATION PROCESSES
💻 Algorithmic Foundation:
:
Utilizes highest/lowest extremes over specified lookback windows
Produces more responsive conversions compared to simple MAs
:
→ Confirms directional bias across multiple independent criteria
← Ensures higher probability outcomes reduce random noise influence
:
♾ Creates persistent annotations documenting significant events
🔄 Handles complex state transitions maintaining historical record integrity
VISUALIZATION COMPONENTS OVERVIEW
🎨 Display Architecture Details:
:
→ Solid colored trendlines representing conversion/base relationships
↑ Fill effect overlay differentiating expansion/compression phases
↔ Offset spans positioned according to calculated displacement values
:
→ Green shading indicates positive configuration scenarios
↘ Red filling highlights negative arrangement situations
⟳ Orange transition areas mark transitional periods requiring caution
:
✔️ LE: Long Entry opportunity confirmed
❌ SE: Short Setup validated
☑ XL/XS: Position closure triggers active
✓ RL/RS: Potential re-entry chances emerging
STRATEGIC APPLICATION FRAMEWORK
📋 Practical Deployment Guidelines:
Initial Integration Phase:
Select appropriate timeframe matching trading horizon preference
Configure input parameters aligning with target asset behavior traits
Test thoroughly under simulated conditions prior to live usage
Active Monitoring Procedures:
• Regular observation of cloud formation evolution
• Tracking label placements against actual price movements
• Noting pattern development leading up to signaled entry/exit moments
Decision Making Process Flowchart:
→ Identify clear breakout/crossover events exceeding confirmation thresholds
← Evaluate contextual factors supporting/rejecting indicated direction
↑ Execute trades only after achieving required number of confirming inputs
PERFORMANCE OPTIMIZATION TECHNIQUES
🚀 Refinement Strategies:
Calibration Optimization Approach:
→ Start testing with default suggested configurations
↓ Gradually adjust individual components observing outcome changes
↑ Document findings systematically building personalized version profile
Context Adaptability Methods:
➕ Add supplementary indicators enhancing overall reliability
➖ Remove unnecessary complexity layers if causing confusion
✨ Incorporate custom rules adapting to specific security behaviors
Efficiency Improvement Tactics:
🔧 Streamline redundant processing routines where possible
♻️ Leverage shared data streams whenever feasible
⚡ Optimize refresh frequencies balancing update speed vs computational load
RISK MITIGATION PROTOCOLS
🛡️ Safety Measures Implementation Guide:
Position Sizing Principles:
∅ Never exceed preset maximum exposure limits defined by risk tolerance
± Scale positions proportionally per account size/market capitalization
× Include slippage allowances within planning stages accounting for liquidity variations
Validation Requirements Hierarchy:
☐ Verify signals meet minimum number of concurrent validations
⛔ Ignore isolated occurrences lacking adequate evidence backing
▶ Look for convergent evidence strengthening conviction level
Emergency Response Planning:
↩ Establish predefined exit strategies including trailing stops mechanisms
🌀 Plan worst-case scenario responses ahead avoiding panic reactions
⇄ Maintain contingency plans addressing unexpected adverse developments
USER EXPERIENCE ENHANCEMENT FEATURES
🌟 Additional Utility Functions:
Alert System Infrastructure:
→ Automatic notifications delivered directly to user devices
↑ Message content customized explaining triggered condition specifics
↔ Timing optimization ensuring minimal missed opportunities due to latency issues
Historical Review Capability:
→ Ability to analyze past performance retrospectively
↓ Assess effectiveness across varying market regimes objectively
↗ Generate statistics measuring success/failure rates quantitatively
Community Collaboration Support:
↪ Share personal optimizations benefiting wider trader community
↔ Exchange experiences improving collective understanding base
✍️ Provide constructive feedback aiding ongoing refinement process
CONCLUSION AND NEXT STEPS
This comprehensive guide serves as your roadmap toward mastering the capabilities offered by the L3 Ichimoku Fusion indicator effectively. Success relies heavily on disciplined application combined with continuous learning and adjustment processes throughout implementation journey.
Wishing you prosperous trading endeavors! 👋💰
PowerHouse SwiftEdge AI v2.10 StrategyOverview
The PowerHouse SwiftEdge AI v2.10 Strategy is a sophisticated trading system designed to identify high-probability trade setups in forex, stocks, and cryptocurrencies. By combining multi-timeframe trend analysis, momentum signals, volume confirmation, and smart money concepts (Change of Character and Break of Structure ), this strategy offers traders a robust tool to capitalize on market trends while minimizing false signals. The strategy’s unique “AI” component analyzes trends across multiple timeframes to provide a clear, actionable dashboard, making it accessible for both novice and experienced traders. The strategy is fully customizable, allowing users to tailor its filters to their trading style.
What It Does
This strategy generates Buy and Sell signals based on a confluence of technical indicators and smart money concepts. It uses:
Multi-Timeframe Trend Analysis: Confirms the market’s direction by analyzing trends on the 1-hour (60M), 4-hour (240M), and daily (D) timeframes.
Momentum Filter: Ensures trades align with strong price movements to avoid choppy markets.
Volume Filter: Validates signals with above-average volume to confirm market participation.
Breakout Filter: Requires price to break key levels for added confirmation.
Smart Money Signals (CHoCH/BOS): Identifies reversals (CHoCH) and trend continuations (BOS) based on pivot points.
AI Trend Dashboard: Summarizes trend strength, confidence, and predictions across timeframes, helping traders make informed decisions without needing to analyze complex data manually.
The strategy also plots dynamic support and resistance trendlines, take-profit (TP) levels, and “Get Ready” signals to alert users of potential setups before they fully develop. Trades are executed with predefined take-profit and stop-loss levels for disciplined risk management.
How It Works
The strategy integrates multiple components to create a cohesive trading system:
Multi-Timeframe Trend Analysis:
The strategy evaluates trends on three timeframes (1H, 4H, Daily) using Exponential Moving Averages (EMA) and Volume-Weighted Average Price (VWAP). A trend is considered bullish if the price is above both the EMA and VWAP, bearish if below, or neutral otherwise.
Signals are only generated when the trend on the user-selected higher timeframe aligns with the trade direction (e.g., Buy signals require a bullish higher timeframe trend). This reduces noise and ensures trades follow the broader market context.
Momentum Filter:
Measures the percentage price change between consecutive bars and compares it to a volatility-adjusted threshold (based on the Average True Range ). This ensures trades are taken only during significant price movements, filtering out low-momentum conditions.
Volume Filter (Optional):
Checks if the current volume exceeds a long-term average and shows positive short-term volume change. This confirms strong market participation, reducing the risk of false breakouts.
Breakout Filter (Optional):
Requires the price to break above (for Buy) or below (for Sell) recent highs/lows, ensuring the signal aligns with a structural shift in the market.
Smart Money Concepts (CHoCH/BOS):
Change of Character (CHoCH): Detects potential reversals when the price crosses under a recent pivot high (for Sell) or over a recent pivot low (for Buy) with a bearish or bullish candle, respectively.
Break of Structure (BOS): Confirms trend continuations when the price breaks below a recent pivot low (for Sell) or above a recent pivot high (for Buy) with strong momentum.
These signals are plotted as horizontal lines with labels, making it easy to visualize key levels.
AI Trend Dashboard:
Combines trend direction, momentum, and volatility (ATR) across timeframes to calculate a trend score. Scores above 0.5 indicate an “Up” trend, below -0.5 indicate a “Down” trend, and otherwise “Neutral.”
Displays a table summarizing trend strength (as a percentage), AI confidence (based on trend alignment), and Cumulative Volume Delta (CVD) for market context.
A second table (optional) shows trend predictions for 1H, 4H, and Daily timeframes, helping traders anticipate future market direction.
Dynamic Trendlines:
Plots support and resistance lines based on recent swing lows and highs within user-defined periods (shortTrendPeriod, longTrendPeriod). These lines adapt to market conditions and are colored based on trend strength.
Why This Combination?
The PowerHouse SwiftEdge AI v2.10 Strategy is original because it seamlessly integrates traditional technical analysis (EMA, VWAP, ATR, volume) with smart money concepts (CHoCH, BOS) and a proprietary AI-driven trend analysis. Unlike standalone indicators, this strategy:
Reduces False Signals: By requiring confluence across trend, momentum, volume, and breakout filters, it minimizes trades in choppy or low-conviction markets.
Adapts to Market Context: The ATR-based momentum threshold adjusts dynamically to volatility, ensuring signals remain relevant in both trending and ranging markets.
Simplifies Decision-Making: The AI dashboard distills complex multi-timeframe data into a user-friendly table, eliminating the need for manual analysis.
Leverages Smart Money: CHoCH and BOS signals capture institutional price action patterns, giving traders an edge in identifying reversals and continuations.
The combination of these components creates a balanced system that aligns short-term trade entries with longer-term market trends, offering a unique blend of precision, adaptability, and clarity.
How to Use
Add to Chart:
Apply the strategy to your TradingView chart on a liquid symbol (e.g., EURUSD, BTCUSD, AAPL) with a timeframe of 60 minutes or lower (e.g., 15M, 60M).
Configure Inputs:
Pivot Length: Adjust the number of bars (default: 5) to detect pivot highs/lows for CHoCH/BOS signals. Higher values reduce noise but may delay signals.
Momentum Threshold: Set the base percentage (default: 0.01%) for momentum confirmation. Increase for stricter signals.
Take Profit/Stop Loss: Define TP and SL in points (default: 10 each) for risk management.
Higher/Lower Timeframe: Choose timeframes (60M, 240M, D) for trend filtering. Ensure the chart timeframe is lower than or equal to the higher timeframe.
Filters: Enable/disable momentum, volume, or breakout filters to suit your trading style.
Trend Periods: Set shortTrendPeriod (default: 30) and longTrendPeriod (default: 100) for trendline plotting. Keep below 2000 to avoid buffer errors.
AI Dashboard: Toggle Enable AI Market Analysis to show/hide the prediction table and adjust its position.
Interpret Signals:
Buy/Sell Labels: Green "Buy" or red "Sell" labels indicate trade entries with predefined TP/SL levels plotted.
Get Ready Signals: Yellow "Get Ready BUY" or orange "Get Ready SELL" labels warn of potential setups.
CHoCH/BOS Lines: Aqua (CHoCH Sell), lime (CHoCH Buy), fuchsia (BOS Sell), or teal (BOS Buy) lines mark key levels.
Trendlines: Green/lime (support) or fuchsia/purple (resistance) dashed lines show dynamic support/resistance.
AI Dashboard: Check the top-right table for trend strength, confidence, and CVD. The optional bottom table shows trend predictions (Up, Down, Neutral).
Backtest and Trade:
Use TradingView’s Strategy Tester to evaluate performance. Adjust TP/SL and filters based on results.
Trade manually based on signals or automate with TradingView alerts (set alerts for Buy/Sell labels).
Originality and Value
The PowerHouse SwiftEdge AI v2.10 Strategy stands out by combining multi-timeframe analysis, smart money concepts, and an AI-driven dashboard into a single, user-friendly system. Its adaptive momentum threshold, robust filtering, and clear visualizations empower traders to make confident decisions without needing advanced technical knowledge. Whether you’re a day trader or swing trader, this strategy provides a versatile, data-driven approach to navigating dynamic markets.
Important Notes:
Risk Management: Always use appropriate position sizing and risk management, as the strategy’s TP/SL levels are customizable.
Symbol Compatibility: Test on liquid symbols with sufficient historical data (at least 2000 bars) to avoid buffer errors.
Performance: Backtest thoroughly to optimize settings for your market and timeframe.
Golden Setup V1Golden Setup V1 is an overlay indicator that automates Tony Rago’s “Golden Setup” price-level framework. It divides the chart into fixed “blockSize” intervals (default 100 points) and plots a series of key horizontal levels within each block—levels at 00, 12, 26, 33, 50, 62, 77 and 88 offsets. These levels act as dynamic support and resistance grids that roll up or down as price moves between blocks.
Key Features
Customizable Offsets
Define eight offset levels corresponding to Rago’s Golden Setup:
00 (Round Number)
12 (Target 12)
26 (First “Golden” level)
33 (Target 33)
50 (Mid-block pivot)
62 (Target 62)
77 (Second “Golden” level)
88 (Target 88)
Multi-Block Coverage
Choose how many blocks above and below the current 100-point block you wish to display, so you always have levels drawn for the surrounding price range.
Golden-Only Filter
A handy toggle lets you show only the two “Golden” offsets (26 & 77), which many traders prioritize for high-probability bounce or breakout areas.
Dynamic Nearest-Level Label
Highlights the closest Golden Setup level (to the right edge of the chart) with a movable label, so you always know which level price is approaching.
Full Styling Control
Customize line colors, widths, block size, label fonts and opacity to suit your charting style.
How It Works
Block Calculation
On each bar, the indicator computes the “current block” by flooring (close / blockSize) and multiplying back by blockSize.
Level Offsets
It adds each of the eight user-defined offsets to that block base (and, if price has moved below the lowest offset, shifts the block down one interval).
Drawing
Each level is drawn as a horizontal line extending across the chart for as many blocks above/below as you select.
Nearest-Level Detection
Within the present block, it calculates which of the plotted levels is closest to price and displays that value on the right edge.
Usage Tips
Use the Golden-Only filter to declutter and focus solely on the 26 & 77 levels, which often act as strong intra-block pivot points.
Combine with volume or momentum indicators to confirm bounces at these levels.
Adjust blockSize (e.g. 50 or 200) if you wish to work in smaller or larger price increments.
⚠️ Disclaimer: This script is for educational and illustrative purposes only. Trading involves risk—always back-test and validate any strategy on a demo account before going live.
Clarity Strategy: UT Bot + HMA + JCFBV (v6 fixed)The Clarity Strategy filters UT Bot signals with trend, volatility, and candle strength for high-accuracy entries, using dynamic or fixed TP/SL.
Merged: Range Filter & Smart Envelope//@version=5
indicator("Merged: Range Filter & Smart Envelope", overlay=true, max_lines_count=500, max_labels_count=500)
// ==================== Range Filter Settings ====================
// Color variables
upColor = color.white
midColor = #90bff9
downColor = color.blue
// Source
src = input(defval=close, title="Source")
// Sampling Period
per = input.int(defval=100, minval=1, title="Sampling Period")
// Range Multiplier
mult = input.float(defval=3.0, minval=0.1, title="Range Multiplier")
// Smooth Average Range
smoothrng(x, t, m) =>
wper = t * 2 - 1
avrng = ta.ema(math.abs(x - x ), t)
smoothrng = ta.ema(avrng, wper) * m
smoothrng
smrng = smoothrng(src, per, mult)
// Range Filter
rngfilt(x, r) =>
rngfilt = x
rngfilt := x > nz(rngfilt ) ? x - r < nz(rngfilt ) ? nz(rngfilt ) : x - r :
x + r > nz(rngfilt ) ? nz(rngfilt ) : x + r
rngfilt
filt = rngfilt(src, smrng)
// Filter Direction
upward = 0.0
upward := filt > filt ? nz(upward ) + 1 : filt < filt ? 0 : nz(upward )
downward = 0.0
downward := filt < filt ? nz(downward ) + 1 : filt > filt ? 0 : nz(downward )
// Target Bands
hband = filt + smrng
lband = filt - smrng
// Colors
filtcolor = upward > 0 ? upColor : downward > 0 ? downColor : midColor
barcolor = src > filt and src > src and upward > 0 ? upColor :
src > filt and src < src and upward > 0 ? upColor :
src < filt and src < src and downward > 0 ? downColor :
src < filt and src > src and downward > 0 ? downColor : midColor
filtplot = plot(filt, color=filtcolor, linewidth=2, title="Range Filter")
// Target
hbandplot = plot(hband, color=color.new(upColor, 70), title="High Target")
lbandplot = plot(lband, color=color.new(downColor, 70), title="Low Target")
// Fills
fill(hbandplot, filtplot, color=color.new(upColor, 90), title="High Target Range")
fill(lbandplot, filtplot, color=color.new(downColor, 90), title="Low Target Range")
// Bar Color
barcolor(barcolor)
// Break Outs
longCond = bool(na)
shortCond = bool(na)
longCond := src > filt and src > src and upward > 0 or
src > filt and src < src and upward > 0
shortCond := src < filt and src < src and downward > 0 or
src < filt and src > src and downward > 0
CondIni = 0
CondIni := longCond ? 1 : shortCond ? -1 : CondIni
longCondition = longCond and CondIni == -1
shortCondition = shortCond and CondIni == 1
// ==================== Smart Envelope with Stochastic RSI ====================
h_env = input.float(8., 'Bandwidth', minval = 0)
mult_env = input.float(3., minval = 0)
repaint = input(true, 'Repainting Smoothing')
// Stochastic RSI Settings
smoothK = input.int(3, "K", minval=1)
smoothD = input.int(3, "D", minval=1)
lengthRSI = input.int(14, "RSI Length", minval=1)
lengthStoch = input.int(14, "Stochastic Length", minval=1)
rsi1 = ta.rsi(src, lengthRSI)
k = ta.sma(ta.stoch(rsi1, rsi1, rsi1, lengthStoch), smoothK)
d = ta.sma(k, smoothD)
// Nadaraya-Watson Envelope Functions
gauss(x, h) => math.exp(-(math.pow(x, 2)/(h * h * 2)))
var coefs = array.new_float(0)
var den = 0.
if barstate.isfirst and not repaint
for i = 0 to 499
w = gauss(i, h_env)
coefs.push(w)
den := coefs.sum()
out = 0.
if not repaint
for i = 0 to 499
out += src * coefs.get(i)
out /= den
mae = ta.sma(math.abs(src - out), 499) * mult_env
upper_env = out + mae
lower_env = out - mae
// Compute and display NWE
n = bar_index
var float y2 = na
var float y1 = na
nwe = array.new(0)
if barstate.islast and repaint
sae = 0.
for i = 0 to math.min(499,n - 1)
sum = 0.
sumw = 0.
for j = 0 to math.min(499,n - 1)
w = gauss(i - j, h_env)
sum += src * w
sumw += w
y2 := sum / sumw
sae += math.abs(src - y2)
nwe.push(y2)
sae := sae / math.min(499,n - 1) * mult_env
for i = 0 to math.min(499,n - 1)
if i % 2
line.new(n-i+1, y1 + sae, n-i, nwe.get(i) + sae, color=color.teal)
line.new(n-i+1, y1 - sae, n-i, nwe.get(i) - sae, color=color.red)
y1 := nwe.get(i)
// Plot Nadaraya-Watson Envelope
plot(repaint ? na : out + mae, 'Upper Envelope', color=color.teal)
plot(repaint ? na : out - mae, 'Lower Envelope', color=color.red)
// Stochastic RSI Plot
plot(k, "Stochastic RSI K", color=color.blue)
plot(d, "Stochastic RSI D", color=color.orange)
h0 = hline(80, "Upper Band", color=color.gray)
hline(50, "Middle Band", color=color.new(color.gray, 50))
h1 = hline(20, "Lower Band", color=color.gray)
fill(h0, h1, color=color.rgb(33, 150, 243, 90), title="Stochastic RSI Background")
// ==================== Combined Signal Logic ====================
// Enhanced Signal Confirmation
ma_length = input.int(20, "Filter Moving Average Length", minval=1)
ma = ta.sma(close, ma_length)
// Combined Buy Signal: Range Filter + Stochastic RSI + Envelope
combined_buy = (longCondition or (ta.crossover(k, d) and close > upper_env)) and close > ma
combined_sell = (shortCondition or (ta.crossunder(k, d) and close < lower_env)) and close < ma
// Plot combined signals with higher priority
plotshape(combined_buy, "Combined Buy", shape.labelup, location.belowbar, color=color.green, size=size.normal, text="STRONG BUY")
plotshape(combined_sell, "Combined Sell", shape.labeldown, location.abovebar, color=color.red, size=size.normal, text="STRONG SELL")
// Original signals (lower priority)
plotshape(longCondition and not combined_buy, "Buy Signal", shape.labelup, location.belowbar, color=color.lime, size=size.small, text="BUY")
plotshape(shortCondition and not combined_sell, "Sell Signal", shape.labeldown, location.abovebar, color=color.maroon, size=size.small, text="SELL")
// Plot the moving average filter line
plot(ma, "Filter MA", color=color.purple, linewidth=2)
// Alerts
alertcondition(combined_buy, title="Strong Buy Alert", message="Strong Buy Signal")
alertcondition(combined_sell, title="Strong Sell Alert", message="Strong Sell Signal")
Accurate Swing Trading System - Strategy//@version=5
strategy("Accurate Swing Trading System - Strategy", overlay=true)
// Inputs
no = input.int(3, title="Swing")
Barcolor = input.bool(true, title="Barcolor")
Bgcolor = input.bool(false, title="Bgcolor")
// Logic
res = ta.highest(high, no)
sup = ta.lowest(low, no)
avd = close > res ? 1 : close < sup ? -1 : 0
avn = ta.valuewhen(avd != 0, avd, 0)
tsl = avn == 1 ? sup : res
Buy = ta.crossover(close, tsl)
Sell = ta.crossunder(close, tsl)
// Plotting
plotshape(Buy, title="BUY", style=shape.labelup, location=location.belowbar, color=color.green, text="BUY", textcolor=color.black)
plotshape(Sell, title="SELL", style=shape.labeldown, location=location.abovebar, color=color.red, text="SELL", textcolor=color.black)
colr = close >= tsl ? color.green : close <= tsl ? color.red : na
plot(tsl, color=colr, linewidth=3, title="TSL")
barcolor(Barcolor ? colr : na)
bgcolor(Bgcolor ? colr : na)
// Alerts
alertcondition(Buy, title="Buy Signal", message="Buy")
alertcondition(Sell, title="Sell Signal", message="Sell")
// Strategy Orders
if Buy
strategy.entry("Buy", strategy.long)
if Sell
strategy.close("Buy")
Median Price RSI DeviationThis indicator is a smoothed RSI-based trend filter that combines median price smoothing, customizable moving averages, and standard deviation bands to identify bullish or bearish conditions:
=> It first smooths price using a median filter.
=> Then it calculates RSI on that smoothed price.
=> The RSI is further smoothed using a selectable moving average (e.g., DEMA, EMA).
=> Standard deviation bands are applied around this smoothed RSI.
Signals:
=> A bullish signal is triggered when the upper band exceeds a long threshold (default 50).
=> A bearish signal occurs when the smoothed RSI drops below a short threshold (default 40).
Time-Based Fair Value Gaps (FVG) with Inversions (iFVG)The Time-Based Fair Value Gaps (FVG) with Inversions (iFVG) (ICT/SMT) is a specialized tool for ICT traders, pinpointing Fair Value Gaps (FVGs) within customizable 10-minute windows each hour (:00–:10, :10–:20, :20–:30, :30–:40, :40–:50, :50–:60).
Optimized for 10 minute charts or lower, this indicator identifies bullish and bearish FVGs, tracks their mitigation to form inverted FVGs (iFVGs) as key support/resistance zones, and generates retest signals with "Close" or "Wick" options.
With toggleable ATR filtering, optional FVG labels, mitigation removal, and alerts for new FVGs and signals, this indicator delivers precision for ICT strategies.
A timeframe warning ensures users stay on lower timeframes (<1 hour) for accurate filtering, making it ideal for targeting macro timeframes and hourly transitions.
Settings Description:
Show Last (disp_num): Sets the number of recent inverted FVGs (iFVGs) to display (1–100, default: 5). Lower values reduce chart clutter, while higher values show more historical zones.
Time Window Checkboxes (enable_00_10, enable_10_20, etc.): Six toggles to enable/disable FVG detection in each 10-minute window (:00–:10, :10–:20, :20–:30, :30–:40, :40–:50, :50–:60). All default to enabled, allowing FVGs across the hour. Disable specific windows to focus on key ICT periods (e.g., :00–:10 for hourly opens).
Signal Preference (signal_pref): Choose "Close" (default) or "Wick" for iFVG retest signals. "Close" requires the candle body to confirm the retest, while "Wick" uses highs/lows, offering earlier but potentially noisier signals.
Use ATR Filter (use_atr): Enables/disables ATR-based size filtering for FVGs (default: true). When enabled, only FVGs larger than ATR × Multiplier are shown, reducing noise.
ATR Multiplier (atr_multi): Sets the ATR threshold for FVG size (0–∞, default: 0.25). Higher values filter for larger gaps; setting to 0 uses the average bar range, making the filter very permissive.
Remove Mitigated FVGs (remove_mitigated): Removes FVGs and iFVGs when price fully closes through them (default: true), aligning with ICT’s principle that mitigated gaps lose relevance.
Show FVG Labels (show_labels): Displays “Bull FVG” or “Bear FVG” labels above/below gaps (default: true). Disable to reduce chart clutter.
Colors (bull_color, bear_color, midline_color): Customize colors for bullish FVGs (green), bearish FVGs (red), and midlines (gray). Adjust transparency for visibility.
Recommendations for ICT Traders
To maximize the indicator’s effectiveness within ICT concepts, use it on 1–5 minute charts during macro timeframes like the New York Kill Zone (7:00–11:00 AM EST) or London Kill Zone (2:00–5:00 AM EST), where institutional order flow often creates significant FVGs. Focus on the :00–:10 and :50–:60 windows by enabling only these checkboxes , as they capture hourly opens and closes, key for ICT setups like Judas swings or liquidity grabs.
Keep ATR filtering enabled with a multiplier of 0.25–0.5 to prioritize impactful gaps, but disable it on lower timeframes (e.g., 1-minute) for more FVGs during high-volatility periods.
Enable mitigation removal to declutter the chart, reflecting ICT’s view that filled FVGs are less relevant unless inverted.
Use "Close" signal preference for conservative retest confirmation, switching to "Wick" for faster entries in aggressive setups.
Set alerts for “Bullish FVG Detected,” “Bearish FVG Detected,” “Bullish Signal,” and “Bearish Signal” to catch real-time opportunities.
Avoid timeframes ≥1 hour, as the minute-based filter may be unreliable, and heed the warning label to stay on lower timeframes for precision.
Market Mafia Sniper Strategy - XOTWODThe Market Mafia Sniper is a professional-grade, multi-timeframe precision trading system designed for scalping, intraday, swing, and position trading across any Forex, Crypto, Indices, and Metals market.
🚀 Core Features:
Entry Bias Detection: Trades only in the direction of major trend bias using EMA 200 and VWAP confluence.
Advanced Confirmation: Confirms entries with MACD crossovers and RSI momentum filtering.
Multi-Timeframe Power: Simultaneously scans 15 minutes, 1 hour, 4 hours, and Daily timeframes for sniper signals.
Dynamic Take Profit: Adjusts Risk:Reward dynamically based on timeframe-specific ATR measurements.
DECODE M2 Global Liquidity IndexThe most comprehensive M2 indicator on Trading View.
- Custom lead setting (days)
- Data sources for the 20 largest economies
- Only selected sources are loaded for efficiency
- Automatic multi-timeframe recalculation
Entropy Bands (TechnoBlooms)Entropy Bands — A New Era of Volatility and Trend Analysis
Entropy Bands is our next indicator as a part of the Quantum Price Theory (QPT) Series of indicators.
🧠 Overview
Entropy Bands are an advanced volatility-based indicator that reimagines traditional banded systems like Bollinger Bands.
Built on entropy theory, adaptive moving averages, and dynamic volatility measurement, Entropy Bands provide deeper insights into market randomness, trend strength, and breakout potential.
Instead of only relying on price deviation (like Bollinger Bands), Entropy Bands integrate chaos theory principles to create smarter, more responsive dynamic bands that adapt to real market behavior.
🚀Why is Entropy Bands Different — and Better
Dynamic Band Width : Adjusts using both entropy and ATR, creating smarter expansion/contraction.
Multi-Moving Average Core : Choose between SMA, EMA, or WMA for optimal centerline behavior.
Noise and Breakout Filtering : Filters fake breakouts by analyzing candle body size and entropy conditions.
Visual Clarity : Background and candle coloring highlight chaotic/noisy zones, trend zones, and breakout moments.
Entropy Bands don't just react to price — they analyze the underlying market behavior, offering superior decision-making signals.
📚 Watch Band Behavior:
Bands expand during volatility spikes or chaotic conditions.
Bands contract during low volatility or tight consolidation zones.
📚 Analyze Candle Coloring:
Green = Bullish breakout (closing above upper band).
Pink = Bearish breakout (closing below lower band).
Gray = Inside bands (neutral/random noise).
✨ Key Features of Entropy Bands:
Entropy-Based Band Width Calculation: A scientific edge over pure price deviation methods.
Dynamic Background Coloring: Highlights high entropy areas where randomness dominates.
Candle Breakout Coloring: Easy-to-spot trend breakouts and strength moves.
Multi-MA Flexibility: Adapt the bands’ core to trending, ranging, or volatile markets.
Body Size Filter: Protects against fake breakouts by requiring meaningful candle body moves.
CYCLE BY RiotWolftradingDescription of the "CYCLE" Indicator
The "CYCLE" indicator is a custom Pine Script v5 script for TradingView that visualizes cyclic patterns in price action, dividing the trading day into specific sessions and 90-minute quarters (Q1-Q4). It is designed to identify and display market phases (Accumulation, Manipulation, Distribution, and Continuation/Reversal) along with key support and resistance levels within those sessions. Additionally, it allows customization of boxes, lines, labels, and colors to suit user preferences.
Main Features
Cycle Phases:
Accumulation (1900-0100): Represents the phase where large operators accumulate positions.
Manipulation (0100-0700): Identifies potential manipulative moves to mislead retail traders.
Distribution (0700-1300): The phase where large operators distribute their positions.
Continuation/Reversal (1300-1900): Indicates whether the price continues the trend or reverses.
90-Minute Quarters (Q1-Q4):
Divides each 6-hour cycle (360 minutes) into four 90-minute quarters (Q1: 00:00-01:30, Q2: 01:30-03:00, Q3: 03:00-04:30, Q4: 04:30-06:00 UTC).
Each quarter is displayed with a colored box (Q1: light purple, Q2: light blue, Q3: light gray, Q4: light pink) and labels (defaulted to black).
Support and Resistance Visualization:
Draws boxes or lines (based on settings) showing the high and low levels of each session.
Optionally displays accumulated volume at the highs and lows within the boxes.
Daily Lines and Last 3 Boxes:
How to Use the Indicator
Step 1: Add the Indicator to TradingView
Open TradingView and select the chart where you want to apply the indicator (e.g., UMG9OOR on a 5-minute timeframe, as shown in the screenshot).
Go to the Pine Editor (at the bottom of the TradingView interface).
Copy and paste the provided code.
Click Compile and then Add to Chart.
Step 2: Configure the Indicator
Click on the indicator name on the chart ("CYCLE") and select Settings (or double-click the name).
Adjust the options based on your needs:
Cycle Phases: Enable/disable phases (Accumulation, Manipulation, Distribution, Continuation/Reversal) and adjust their time slots if needed.
90-Minute Quarters: Enable/disable quarters (Q1-Q4).
Step 3: Interpret the Indicator
Identify Cycle Phases:
Observe the red boxes indicating the phases (Accumulation, Manipulation, etc.).
The high and low levels within each phase are potential support/resistance zones.
If volume is enabled, pay attention to the accumulated volume at highs and lows, as it may indicate the strength of those levels.
Use the 90-Minute Quarters (Q1-Q4):
The colored boxes (Q1-Q4) divide the day into 90-minute segments.
Each quarter shows the price range (high and low) during that period.
Use these boxes to identify price patterns within each quarter, such as breakouts or consolidations.
The labels (Q1, Q2, etc.) help you track time and anticipate potential moves in the next quarter.
Analyze Support and Resistance:
The high and low levels of each phase/quarter act as support and resistance.
Daily lines (if enabled) show key levels from the previous day, useful for planning entries/exits.
The "last 3 boxes below price" (if enabled) highlight potential support levels the price might target.
Avoid Manipulation:
During the Manipulation phase (0100-0700), be cautious of sharp moves or false breakouts.
Use the high/low levels of this phase to identify potential traps (as explained in your first question about manipulation candles).
Step 4: Trading Strategy
Entries and Exits:
Support/Resistance: Use the high/low levels of phases and quarters to set entry or exit points.
For example, if the price bounces off a Q1 support level, consider a buy.
Breakouts: If the price breaks a high/low of a quarter (e.g., Q2), wait for confirmation to enter in the direction of the breakout.
Volume: If accumulated volume is high near a key level, that level may be more significant.
Risk Management:
Place stop-loss orders below lows (for buys) or above highs (for sells) identified by the indicator.
Avoid trading during the Manipulation phase unless you have a specific strategy to handle false breakouts.
Time Context:
Use the quarters (Q1-Q4) to plan your trades based on time. For example, if Q3 is typically volatile in your market, prepare for larger moves between 03:00-04:30 UTC.
Step 5: Adjustments and Testing
Test on Different Timeframes: The indicator is set for a 5-minute timeframe (as in the screenshot), but you can test it on other timeframes (e.g., 1-minute, 15-minute) by adjusting the time slots if needed.
Adjust Colors and Styles: If the default colors are not visible on your chart, change them for better clarity.
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📌 1. **Accumulation: Strong Institutional Activity**
- During the **accumulation phase, we see **high volume: 82.773K, which suggests strong buying interest**, likely from institutional players.
- This sets the base for the following upward move in price.
---
📌 2. **Manipulation: False Breakout with Lower Volume**
- Later, there's a manipulation phase where price breaks above previous highs, but the volume (71.814K) is **lower than during accumulation**.
- This implies that buyers are not as aggressive as before—no real demandbehind the breakout.
- It’s likely a bull trap, where smart money is selling into the breakout to exit their positions.
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### 📌 3. Distribution: Weakness and Lack of Demand
- The market enters a distribution phase, and volume drops even further (only 7.914K).
- Price struggles to go higher, and you start seeing rejections at the top.
- This shows that demand is drying up, and smart money is offloading positions**—not accumulating anymore.
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### 💡 Why Take the Short Here?
- Volume is not increasing with new highs—showing weak demand**.
- The manipulation volume is weaker than the accumulation volume, confirming the breakout was likely false.
- Structure starts to break down (Q levels falling), which confirms weakness.
- This creates a high-probability short setup:
- **Entry:** after confirmation of distribution and structural breakdown.
- **Stop loss:** above the manipulation high.
- **Target:** down toward previous lows or value zones.
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### ✅ Conclusion
Since the manipulation volume failed to exceed the accumulation volume, the breakout lacked real strength. Combined with decreasing volume in the distribution phase, this indicates fading demand and supply taking control—which justifies entering a short position.
