Internal Pivot Pattern [LuxAlgo]The Internal Pivot Pattern indicator is a novel method allowing traders to detect pivots without excessive delay on the chart timeframe, by using the lower timeframe data from a candle.
It features custom colors for candles and zigzag lines to help identify trends. A dashboard showing the accuracy of the pattern is also included.
🔶 USAGE
We define a pivot as the occurrence where the middle candle over a specific interval (for example, the most recent 21 bars) is the highest (pivot high) or the lowest (pivot low). This method commonly allows for identifying swing highs/lows on a trader's chart; however, this pattern can only be identified after a specific number of bars has been formed, rendering this pattern useless for real-time detection of swing highs/lows.
This indicator uses a different approach, removing the need to wait for candles to form on the user chart; instead, we check the lower timeframe data of the current candle and evaluate for the presence of a pivot given the internal data, effectively providing pivot confirmation at the candle close.
An internal pivot low pattern is indicative of a potential uptrend, while an internal pivot high is indicative of a potential downtrend.
Candles are colored based on the last internal pivot detected, with blue candle colors indicating that the most recent internal pivot is a pivot low, indicating an uptrend, while an orange candle color indicates that the most recent internal pivot is a pivot high, indicating a downtrend.
🔹 Timeframes
The timeframe setting allows controlling the amount of lower timeframe data to consider for the internal pivot detection. This setting must be lower than the user's chart timeframe.
Using a timeframe significantly lower than the user chart timeframe will evaluate a larger amount of data for the pivot detection, making it less frequent, while using a timeframe closer to the chart timeframe can make the internal pivot detection more frequent, and more prone to false positives.
🔹 Accuracy Dashboard
The Accuracy Dashboard allows evaluating how accurate the detected patterns are as a percentage, with a pattern being judged accurate if subsequent patterns are detected higher or lower than a previous one.
For example, an internal pivot low is judged accurate if the following internal pivot is higher than it, indicating that higher highs have been made.
This dashboard can be useful to determine the timeframe setting to maximize the respective internal pivot accuracy.
🔶 SETTINGS
Timeframe: Timeframe for detecting internal swings
Accuracy Dashboard: Enable or disable the Accuracy Dashboard.
🔹 Style
Internal Pivot High: Color of the dot displayed upon the detection of an internal pivot high
Internal Pivot Low: Color of the dot displayed upon the detection of an internal pivot low
Zig-Zag: Color of the zig-zag segments connecting each internal pivot
Candles: Enable candle coloring, with control over the color of the candles highlighting the detected trend
Indicators and strategies
NAIFCHART_NAS Ultimate Algo | Remastered+# NAIFCHART NAS Ultimate Algo Remastered+: Advanced Trend Following System
## Overview
The NAIFCHART NAS Ultimate Algo Remastered+ represents a sophisticated trend-following system that combines Supertrend analysis with multiple moving average confirmations. This comprehensive indicator was developed and shared by the trading community at t.me designed specifically for identifying high-probability trend continuation and reversal opportunities.
## Core Algorithm Components
**Supertrend Foundation**: The primary signal generation relies on a customizable Supertrend indicator with adjustable sensitivity (1-20 range). This adaptive trend-following tool uses Average True Range calculations to establish dynamic support and resistance levels that respond to market volatility.
**SMA Confirmation Matrix**: Multiple Simple Moving Averages (SMA 4, 5, 9, 13) provide layered confirmation for signal strength. The algorithm distinguishes between regular signals and "Strong" signals based on SMA 4 vs SMA 5 relationship, offering traders different conviction levels for position sizing.
**Trend Ribbon Visualization**: SMA 21 and SMA 34 create a visual trend ribbon that changes color based on their relationship. Green ribbon indicates bullish momentum while red signals bearish conditions, providing immediate visual trend context.
**RSI-Based Candle Coloring**: Advanced 61-tier RSI system colors candles with gradient precision from deep red (RSI ≤20) through purple transitions to bright green (RSI ≥79). This visual enhancement helps traders instantly assess momentum strength and overbought/oversold conditions.
## Signal Generation Logic
**Buy Signal Criteria**:
- Price crosses above Supertrend line
- Close price must be above SMA 9 (trend confirmation)
- Signal strength determined by SMA 4 vs SMA 5 relationship
- "Strong Buy" when SMA 4 ≥ SMA 5
- Regular "Buy" when SMA 4 < SMA 5
**Sell Signal Criteria**:
- Price crosses below Supertrend line
- Close price must be below SMA 9 (trend confirmation)
- Signal strength based on SMA relationship
- "Strong Sell" when SMA 4 ≤ SMA 5
- Regular "Sell" when SMA 4 > SMA 5
## Advanced Risk Management System
**Automated TP/SL Calculation**: The indicator automatically calculates stop loss and take profit levels using ATR-based measurements. Risk percentage and ATR length are fully customizable, allowing traders to adapt to different market conditions and personal risk tolerance.
**Multiple Take Profit Targets**:
- 1:1 Risk-Reward ratio for conservative profit taking
- 2:1 Risk-Reward for balanced trade management
- 3:1 Risk-Reward for maximum profit potential
**Visual Risk Display**: All risk management levels appear as both labels and optional trend lines on the chart. Customizable line styles (solid, dashed, dotted) and positioning ensure clear visualization without chart clutter.
**Dynamic Level Updates**: Risk levels automatically recalculate with each new signal, maintaining current market relevance throughout position lifecycles.
## Visual Enhancement Features
**Customizable Display Options**: Toggle trend ribbon, TP/SL levels, and risk lines independently. Decimal precision adjustments (1-8 decimal places) accommodate different instrument price formats and personal preferences.
**Professional Label System**: Clean, informative labels show entry points, stop losses, and take profit targets with precise price levels. Labels automatically position themselves for optimal chart readability.
**Color-Coded Momentum**: The gradient RSI candle coloring system provides instant visual feedback on momentum strength, helping traders assess market energy and potential reversal zones.
## Implementation Strategy
**Timeframe Optimization**: The algorithm performs effectively across multiple timeframes, with higher timeframes (4H, Daily) providing more reliable signals for swing trading. Lower timeframes work well for day trading with appropriate risk adjustments.
**Sensitivity Adjustment**: Lower sensitivity values (1-5) generate fewer but higher-quality signals, ideal for conservative approaches. Higher sensitivity (15-20) increases signal frequency for active trading styles.
**Risk Management Integration**: Use the automated risk calculations as baseline parameters, adjusting risk percentage based on account size and market conditions. The 1:1, 2:1, 3:1 targets enable systematic profit-taking strategies.
## Market Application
**Trend Following Excellence**: Primary strength lies in capturing significant trend movements through the Supertrend foundation with SMA confirmation. The dual-layer approach reduces false signals common in single-indicator systems.
**Momentum Assessment**: RSI-based candle coloring provides immediate momentum context, helping traders assess signal strength and potential continuation probability.
**Range Detection**: The trend ribbon helps identify ranging conditions when SMA 21 and SMA 34 converge, alerting traders to potential breakout opportunities.
## Performance Optimization
**Signal Quality**: The requirement for both Supertrend crossover AND SMA 9 confirmation significantly improves signal reliability compared to basic trend-following approaches.
**Visual Clarity**: The comprehensive visual system enables rapid market assessment without complex calculations, ideal for traders managing multiple instruments.
**Adaptability**: Extensive customization options allow fine-tuning for specific markets, trading styles, and risk preferences while maintaining the core algorithm integrity.
## Community Resources
Join the active trading community at t.me for ongoing discussions about optimization techniques, market analysis, and strategy refinements using this advanced algorithm system.
The collaborative environment provides valuable insights into parameter adjustments for different market conditions and real-world performance feedback from experienced traders.
## Conclusion
The NAIFCHART NAS Ultimate Algo Remastered+ combines proven trend-following principles with modern visual enhancements and comprehensive risk management. The algorithm's strength lies in its multi-layered confirmation approach and automated risk calculations, providing both novice and experienced traders with clear signals and systematic trade management.
Success with this system requires understanding the relationship between signal strength indicators and adapting sensitivity settings to match current market conditions. The comprehensive visual feedback system enables rapid decision-making while the automated risk management ensures consistent trade parameters.
Practice with different sensitivity settings and timeframes to optimize performance for your specific trading style and risk tolerance. The algorithm's systematic approach provides excellent framework for disciplined trend-following strategies across various market environments.
Advanced ICT Theory - A-ICT📊 Advanced ICT Theory (A-ICT): The Institutional Manipulation Detector
Are you tired of being the liquidity? Stop chasing shadows and start tracking the architects of price movement.
This is not another lagging indicator. This is a complete framework for viewing the market through the lens of institutional traders. Advanced ICT Theory (A-ICT) is an all-in-one, military-grade analysis engine designed to decode the complex language of "Smart Money." It automates the core tenets of Inner Circle Trader (ICT) methodology, moving beyond simple patterns to build a dynamic, real-time narrative of market manipulation, liquidity engineering, and institutional order flow.
AIT provides a living blueprint of the market, identifying high-probability zones, tracking structural shifts, and scoring the quality of setups with a sophisticated, multi-factor algorithm. This is your X-ray into the market's true intentions.
🔬 THE CORE ENGINE: DECODING THE THEORY & FORMULAS
A-ICT is built upon a sophisticated, multi-layered logic system that interprets price action as a story of cause and effect. It does not guess; it confirms. Here is the foundational theory that drives the engine:
1. Market Structure: The Blueprint of Trend
The script first establishes a deep understanding of the market's skeleton through multi-level pivot analysis. It uses ta.pivothigh and ta.pivotlow to identify significant swing points.
Internal Structure (iBOS): Minor swings that show the short-term order flow. A break of internal structure is the first whisper of a potential shift.
External Structure (eBOS): Major swing points that define the primary trend. A confirmed break of external structure is a powerful statement of trend continuation. AIT validates this with optional Volume Confirmation (volume > volumeSMA * 1.2) and Candle Confirmation to ensure the break is driven by institutional force, not just a random spike.
Change of Character (CHoCH): This is the earthquake. A CHoCH occurs when a confirmed eBOS happens against the prevailing trend (e.g., a bearish eBOS in a clear uptrend). A-ICT flags this immediately, as it is the strongest signal that the primary trend is under threat of reversal.
2. Liquidity Engineering: The Fuel of the Market
Institutions don't buy into strength; they buy into weakness. They need liquidity. A-ICT maps these liquidity pools with forensic precision:
Buyside & Sellside Liquidity (BSL/SSL): Using ta.highest and ta.lowest, AIT identifies recent highs and lows where clusters of stop-loss orders (liquidity) are resting. These are institutional targets.
Liquidity Sweeps: This is the "manipulation" part of the detector. AIT has a specific formula to detect a sweep: high > bsl and close < bsl . This signifies that institutions pushed price just high enough to trigger buy-stops before aggressively selling—a classic "stop hunt." This event dramatically increases the quality score of subsequent patterns.
3. The Element Lifecycle: From Potential to Power
This is the revolutionary heart of A-ICT. Zones are not static; they have a lifecycle. AIT tracks this with its dynamic classification engine.
Phase 1: PENDING (Yellow): The script identifies a potential zone of interest based on a specific candle formation (a "displacement"). It is marked as "Pending" because its true nature is unknown. It is a question.
Phase 2: CLASSIFICATION: After the zone is created, AIT watches what happens next. The zone's identity is defined by its actions:
ORDER BLOCK (Blue): The highest-grade element. A zone is classified as an Order Block if it directly causes a Break of Structure (BOS) . This is the footprint of institutions entering the market with enough force to validate the new trend direction.
TRAP ZONE (Orange): A zone is classified as a Trap Zone if it is directly involved in a Liquidity Sweep . This indicates the zone was used to engineer liquidity, setting a "trap" for retail traders before a reversal.
REVERSAL / S&R ZONE (Green): If a zone is not powerful enough to cause a BOS or a major sweep, but still serves as a pivot point, it's classified as a general support/resistance or reversal zone.
4. Market Inefficiencies: Gaps in the Matrix
Fair Value Gaps (FVG): AIT detects FVGs—a 3-bar pattern indicating an imbalance—with a strict formula: low > high (for a bullish FVG) and gapSize > atr14 * 0.5. This ensures only significant, volatile gaps are shown. An FVG co-located with an Order Block is a high-confluence setup.
5. Premium & Discount: The Law of Value
Institutions buy at wholesale (Discount) and sell at retail (Premium). AIT uses a pdLookback to define the current dealing range and divides it into three zones: Premium (sell zone), Discount (buy zone), and Equilibrium. An element's quality score is massively boosted if it aligns with this principle (e.g., a bullish Order Block in a Discount zone).
⚙️ THE CONTROL PANEL: A COMPLETE GUIDE TO THE INPUTS MENU
Every setting is a lever, allowing you to tune the AIT engine to your exact specifications. Master these to unlock the script's full potential.
🎯 A-ICT Detection Engine
Min Displacement Candles: Controls the sensitivity of element detection. How it works: It defines the number of subsequent candles that must be "inside" a large parent candle. Best practice: Use 2-3 for a balanced view on most timeframes. A higher number (4-5) will find only major, more significant zones, ideal for swing trading. A lower number (1) is highly sensitive, suitable for scalping.
Mitigation Method: Defines when a zone is considered "used up" or mitigated. How it works: Cross triggers as soon as price touches the zone's boundary. Close requires a candle to fully close beyond it. Best practice: Cross is more responsive for fast-moving markets. Close is more conservative and helps filter out fake-outs caused by wicks, making it safer for confirmations.
Min Element Size (ATR): A crucial noise filter. How it works: It requires a detected zone to be at least this multiple of the Average True Range (ATR). Best practice: Keep this around 0.5. If you see too many tiny, irrelevant zones, increase this value to 0.8 or 1.0. If you feel the script is missing smaller but valid zones, decrease it to 0.3.
Age Threshold & Pending Timeout: These manage visual clutter. How they work: Age Threshold removes old, mitigated elements after a set number of bars. Pending Timeout removes a "Pending" element if it isn't classified within a certain window. Best practice: The default settings are optimized. If your chart feels cluttered, reduce the Age Threshold. If pending zones disappear too quickly, increase the Pending Timeout.
Min Quality Threshold: Your primary visual filter. How it works: It hides all elements (boxes, lines, labels) that do not meet this minimum quality score (0-100). Best practice: Start with the default 30. To see only A- or B-grade setups, increase this to 60 or 70 for an exceptionally clean, high-probability view.
🏗️ Market Structure
Lookbacks (Internal, External, Major): These define the sensitivity of the trend analysis. How they work: They set the number of bars to the left and right for pivot detection. Best practice: Use smaller values for Internal (e.g., 3) to see minor structure and larger values for External (e.g., 10-15) to map the main trend. For a macro, long-term view, increase the Major Swing Lookback.
Require Volume/Candle Confirmation: Toggles for quality control on BOS/CHoCH signals. Best practice: It is highly recommended to keep these enabled. Disabling them will result in more structure signals, but many will be false alarms. They are your filter against market noise.
... (Continue this detailed breakdown for every single input group: Display Configuration, Zones Style, Levels Appearance, Colors, Dashboards, MTF, Liquidity, Premium/Discount, Sessions, and IPDA).
📊 THE INTELLIGENCE DASHBOARDS: YOUR COMMAND CENTER
The dashboards synthesize all the complex analysis into a simple, actionable intelligence briefing.
Main Dashboard (Bottom Right)
ICT Metrics & Breakdown: This is your statistical overview. Total Elements shows how much structure the script is tracking. High Quality instantly tells you if there are any A/B grade setups nearby. Unmitigated vs. Mitigated shows the balance of fresh opportunities versus resolved price action. The breakdown by Order Blocks, Trap Zones, etc., gives you a quick read on the market's recent character.
Structure & Market Context: This is your core bias. Order Flow tells you the current script-determined trend. Last BOS shows you the most recent structural event. CHoCH Active is a critical warning. HTF Bias shows if you are aligned with the higher timeframe—the checkmark (✓) for alignment is one of the most important confluence factors.
Smart Money Flow: A volume-based sentiment gauge. Net Flow shows the raw buying vs. selling pressure, while the Bias provides an interpretation (e.g., "STRONG BULLISH FLOW").
Key Guide (Large Dashboard only): A built-in legend so you never have to guess. It defines every pattern, structure type, and special level visually.
📖 Narrative Dashboard (Bottom Left)
This is the "story" of the market, updated in real-time. It's designed to build your trading thesis.
Recent Elements Table: A live list of the most recent, high-quality setups. It displays the Type , its Narrative Role (e.g., "Bullish OB caused BOS"), its raw Quality percentage, and its final Trade Score grade. This is your at-a-glance opportunity scanner.
Market Narrative Section: This is the soul of A-ICT. It combines all data points into a human-readable story:
📍 Current Phase: Tells you if you are in a high-volatility Killzone or a consolidation phase like the Asian Range.
🎯 Bias & Alignment: Your primary direction, with a clear indicator of HTF alignment or conflict.
🔗 Events: A causal sequence of recent events, like "💧 Sell-side liquidity swept →
📊 Bullish BOS → 🎯 Active Order Block".
🎯 Next Expectation: The script's logical conclusion. It provides a specific, forward-looking hypothesis, such as "📉 Pullback expected to bullish OB at 1.2345 before continuation up."
🎨 READING THE BATTLEFIELD: A VISUAL INTERPRETATION GUIDE
Every color and line is a piece of information. Learn to read them together to see the full picture.
The Core Zones (Boxes):
Blue Box (Order Block): Highest probability zone for trend continuation. Look for entries here.
Orange Box (Trap Zone): A manipulation footprint. Expect a potential reversal after price interacts with this zone.
Green Box (Reversal/S&R): A standard pivot area. A good reference point but requires more confluence.
Purple Box (FVG): A market imbalance. Acts as a magnet for price. An FVG inside an Order Block is an A+ confluence.
The Structural Lines:
Green/Red Line (eBOS): Confirms the trend direction. A break above the green line is bullish; a break below the red line is bearish.
Thick Orange Line (CHoCH): WARNING. The previous trend is now in question. The market character has changed.
Blue/Red Lines (BSL/SSL): Liquidity targets. Expect price to gravitate towards these lines. A dotted line with a checkmark (✓) means the liquidity has been "swept" or "purged."
How to Synthesize: The magic is in the confluence. A perfect setup might look like this: Price sweeps below a red SSL line , enters a green Discount Zone during the NY Killzone , and forms a blue Order Block which then causes a green eBOS . This sequence, visible at a glance, is the story of a high-probability long setup.
🔧 THE ARCHITECT'S VISION: THE DEVELOPMENT JOURNEY
A-ICT was forged from the frustration of using lagging indicators in a market that is forward-looking. Traditional tools are reactive; they tell you what happened. The vision for A-ICT was to create a proactive engine that could anticipate institutional behavior by understanding their objectives: liquidity and efficiency. The development process was centered on creating a "lifecycle" for price patterns—the idea that a zone's true meaning is only revealed by its consequence. This led to the post-breakout classification system and the narrative-building engine. It's designed not just to show you patterns, but to tell you their story.
⚠️ RISK DISCLAIMER & BEST PRACTICES
Advanced ICT Theory (A-ICT) is a professional-grade analytical tool and does not provide financial advice or direct buy/sell signals. Its analysis is based on historical price action and probabilities. All forms of trading involve substantial risk. Past performance is not indicative of future results. Always use this tool as part of a comprehensive trading plan that includes your own analysis and a robust risk management strategy. Do not trade based on this indicator alone.
観の目つよく、見の目よわく
"Kan no me tsuyoku, ken no me yowaku"
— Miyamoto Musashi, The Book of Five Rings
English: "Perceive that which cannot be seen with the eye."
— Dskyz, Trade with insight. Trade with anticipation.
Harmonic BloomHarmonic Bloom - Advanced Geometric Analysis
Building upon my previous Fibonacci inspired indicator "TrendZone", Harmonic Bloom is a sophisticated geometric trading indicator inspired by W.D. Gann's legendary market geometry principles. It reveals market structure through three key pivot points and dynamic angular analysis, creating powerful harmonic intersections for precision trading.
🎯 Core Features:
📍 Three-Point Gann System:
Set 3 custom pivot points to define your analysis timeframe
Automatic trend detection (bullish/bearish) between pivots
Dynamic geometric box construction following Gann's square principles
📐 Gann-Style 45° Angle Projections:
Pivot 2 Line: Follows trend direction (up if bullish, down if bearish)
Pivot 3 Line: Creates opposition (opposite direction to Pivot 2)
Corner Line: Mirrors Pivot 2 from appropriate box corner
All angles project forward using Gann's 1x1 (45°) methodology for future price targets
⚡ POWER OF HARMONIC INTERSECTIONS:
Confluence Zones: Where multiple 45° angles intersect create the strongest support/resistance
Geometric Harmony: Intersections represent natural market turning points
Time-Price Balance: Following Gann's principle that time and price must be in harmony
Multiple Timeframe Resonance: Intersection points often align across different timeframes
High-Probability Reversals: Markets frequently respect these geometric intersection levels
📊 Customizable Retracement Levels:
8 fully configurable levels (default: 0.0, 0.25, 0.5, 0.75, 1.0, 1.25, 1.5, 1.75)
Choose between 25% or 50% trendline alignment
Individual style controls for each level
🔢 Advanced Gann Analytics:
Fibonacci sequence detection in bar counts (Gann studied natural number sequences)
Numerology sum analysis on pivot prices (Gann's mystical number approach)
Special highlighting for significant numbers
Optional on-chart labels for key metrics
📈 Trading Applications:
✅ Support/Resistance: Use retracement levels for entry/exit points
✅ Gann Angles: 45° lines show momentum direction and strength following Gann's time-price theory
✅ Intersection Trading: Most powerful signals occur at harmonic intersections where multiple angles converge
✅ Price Targets: Forward projections provide future price objectives using Gann's geometric principles
✅ Market Geometry: Identify harmonic patterns and geometric confluences
✅ Time Analysis: Fibonacci-based bar counting for timing decisions (Gann emphasized time cycles)
🌟 Why Harmonic Intersections Are So Powerful:
Gann believed that markets move in geometric harmony, and when multiple angles intersect, they create "magnetic price levels" where:
Maximum Energy Convergence: Multiple geometric forces meet at one point
Natural Turning Points: Markets respect these intersections as natural support/resistance
Time-Price Synchronicity: Intersections often coincide with significant time cycles
Multi-Dimensional Confirmation: Price, time, and geometry align simultaneously
⚙️ Highly Customizable:
All colors, widths, and styles adjustable
Toggle any feature on/off independently
Extend projections beyond the analysis box
Choose your preferred visual presentation
Perfect for traders who use Gann theory, geometric analysis, harmonic patterns, and mathematical market structure. The true power lies in trading the intersection points where multiple harmonic angles converge - these represent the market's most significant geometric turning points.
Drawdown Distribution Analysis (DDA) ACADEMIC FOUNDATION AND RESEARCH BACKGROUND
The Drawdown Distribution Analysis indicator implements quantitative risk management principles, drawing upon decades of academic research in portfolio theory, behavioral finance, and statistical risk modeling. This tool provides risk assessment capabilities for traders and portfolio managers seeking to understand their current position within historical drawdown patterns.
The theoretical foundation of this indicator rests on modern portfolio theory as established by Markowitz (1952), who introduced the fundamental concepts of risk-return optimization that continue to underpin contemporary portfolio management. Sharpe (1966) later expanded this framework by developing risk-adjusted performance measures, most notably the Sharpe ratio, which remains a cornerstone of performance evaluation in financial markets.
The specific focus on drawdown analysis builds upon the work of Chekhlov, Uryasev and Zabarankin (2005), who provided the mathematical framework for incorporating drawdown measures into portfolio optimization. Their research demonstrated that traditional mean-variance optimization often fails to capture the full risk profile of investment strategies, particularly regarding sequential losses. More recent work by Goldberg and Mahmoud (2017) has brought these theoretical concepts into practical application within institutional risk management frameworks.
Value at Risk methodology, as comprehensively outlined by Jorion (2007), provides the statistical foundation for the risk measurement components of this indicator. The coherent risk measures framework developed by Artzner et al. (1999) ensures that the risk metrics employed satisfy the mathematical properties required for sound risk management decisions. Additionally, the focus on downside risk follows the framework established by Sortino and Price (1994), while the drawdown-adjusted performance measures implement concepts introduced by Young (1991).
MATHEMATICAL METHODOLOGY
The core calculation methodology centers on a peak-tracking algorithm that continuously monitors the maximum price level achieved and calculates the percentage decline from this peak. The drawdown at any time t is defined as DD(t) = (P(t) - Peak(t)) / Peak(t) × 100, where P(t) represents the asset price at time t and Peak(t) represents the running maximum price observed up to time t.
Statistical distribution analysis forms the analytical backbone of the indicator. The system calculates key percentiles using the ta.percentile_nearest_rank() function to establish the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of the historical drawdown distribution. This approach provides a complete picture of how the current drawdown compares to historical patterns.
Statistical significance assessment employs standard deviation bands at one, two, and three standard deviations from the mean, following the conventional approach where the upper band equals μ + nσ and the lower band equals μ - nσ. The Z-score calculation, defined as Z = (DD - μ) / σ, enables the identification of statistically extreme events, with thresholds set at |Z| > 2.5 for extreme drawdowns and |Z| > 3.0 for severe drawdowns, corresponding to confidence levels exceeding 99.4% and 99.7% respectively.
ADVANCED RISK METRICS
The indicator incorporates several risk-adjusted performance measures that extend beyond basic drawdown analysis. The Sharpe ratio calculation follows the standard formula Sharpe = (R - Rf) / σ, where R represents the annualized return, Rf represents the risk-free rate, and σ represents the annualized volatility. The system supports dynamic sourcing of the risk-free rate from the US 10-year Treasury yield or allows for manual specification.
The Sortino ratio addresses the limitation of the Sharpe ratio by focusing exclusively on downside risk, calculated as Sortino = (R - Rf) / σd, where σd represents the downside deviation computed using only negative returns. This measure provides a more accurate assessment of risk-adjusted performance for strategies that exhibit asymmetric return distributions.
The Calmar ratio, defined as Annual Return divided by the absolute value of Maximum Drawdown, offers a direct measure of return per unit of drawdown risk. This metric proves particularly valuable for comparing strategies or assets with different risk profiles, as it directly relates performance to the maximum historical loss experienced.
Value at Risk calculations provide quantitative estimates of potential losses at specified confidence levels. The 95% VaR corresponds to the 5th percentile of the drawdown distribution, while the 99% VaR corresponds to the 1st percentile. Conditional VaR, also known as Expected Shortfall, estimates the average loss in the worst 5% of scenarios, providing insight into tail risk that standard VaR measures may not capture.
To enable fair comparison across assets with different volatility characteristics, the indicator calculates volatility-adjusted drawdowns using the formula Adjusted DD = Raw DD / (Volatility / 20%). This normalization allows for meaningful comparison between high-volatility assets like cryptocurrencies and lower-volatility instruments like government bonds.
The Risk Efficiency Score represents a composite measure ranging from 0 to 100 that combines the Sharpe ratio and current percentile rank to provide a single metric for quick asset assessment. Higher scores indicate superior risk-adjusted performance relative to historical patterns.
COLOR SCHEMES AND VISUALIZATION
The indicator implements eight distinct color themes designed to accommodate different analytical preferences and market contexts. The EdgeTools theme employs a corporate blue palette that matches the design system used throughout the edgetools.org platform, ensuring visual consistency across analytical tools.
The Gold theme specifically targets precious metals analysis with warm tones that complement gold chart analysis, while the Quant theme provides a grayscale scheme suitable for analytical environments that prioritize clarity over aesthetic appeal. The Behavioral theme incorporates psychology-based color coding, using green to represent greed-driven market conditions and red to indicate fear-driven environments.
Additional themes include Ocean, Fire, Matrix, and Arctic schemes, each designed for specific market conditions or user preferences. All themes function effectively with both dark and light mode trading platforms, ensuring accessibility across different user interface configurations.
PRACTICAL APPLICATIONS
Asset allocation and portfolio construction represent primary use cases for this analytical framework. When comparing multiple assets such as Bitcoin, gold, and the S&P 500, traders can examine Risk Efficiency Scores to identify instruments offering superior risk-adjusted performance. The 95% VaR provides worst-case scenario comparisons, while volatility-adjusted drawdowns enable fair comparison despite varying volatility profiles.
The practical decision framework suggests that assets with Risk Efficiency Scores above 70 may be suitable for aggressive portfolio allocations, scores between 40 and 70 indicate moderate allocation potential, and scores below 40 suggest defensive positioning or avoidance. These thresholds should be adjusted based on individual risk tolerance and market conditions.
Risk management and position sizing applications utilize the current percentile rank to guide allocation decisions. When the current drawdown ranks above the 75th percentile of historical data, indicating that current conditions are better than 75% of historical periods, position increases may be warranted. Conversely, when percentile rankings fall below the 25th percentile, indicating elevated risk conditions, position reductions become advisable.
Institutional portfolio monitoring applications include hedge fund risk dashboard implementations where multiple strategies can be monitored simultaneously. Sharpe ratio tracking identifies deteriorating risk-adjusted performance across strategies, VaR monitoring ensures portfolios remain within established risk limits, and drawdown duration tracking provides valuable information for investor reporting requirements.
Market timing applications combine the statistical analysis with trend identification techniques. Strong buy signals may emerge when risk levels register as "Low" in conjunction with established uptrends, while extreme risk levels combined with downtrends may indicate exit or hedging opportunities. Z-scores exceeding 3.0 often signal statistically oversold conditions that may precede trend reversals.
STATISTICAL SIGNIFICANCE AND VALIDATION
The indicator provides 95% confidence intervals around current drawdown levels using the standard formula CI = μ ± 1.96σ. This statistical framework enables users to assess whether current conditions fall within normal market variation or represent statistically significant departures from historical patterns.
Risk level classification employs a dynamic assessment system based on percentile ranking within the historical distribution. Low risk designation applies when current drawdowns perform better than 50% of historical data, moderate risk encompasses the 25th to 50th percentile range, high risk covers the 10th to 25th percentile range, and extreme risk applies to the worst 10% of historical drawdowns.
Sample size considerations play a crucial role in statistical reliability. For daily data, the system requires a minimum of 252 trading days (approximately one year) but performs better with 500 or more observations. Weekly data analysis benefits from at least 104 weeks (two years) of history, while monthly data requires a minimum of 60 months (five years) for reliable statistical inference.
IMPLEMENTATION BEST PRACTICES
Parameter optimization should consider the specific characteristics of different asset classes. Equity analysis typically benefits from 500-day lookback periods with 21-day smoothing, while cryptocurrency analysis may employ 365-day lookback periods with 14-day smoothing to account for higher volatility patterns. Fixed income analysis often requires longer lookback periods of 756 days with 34-day smoothing to capture the lower volatility environment.
Multi-timeframe analysis provides hierarchical risk assessment capabilities. Daily timeframe analysis supports tactical risk management decisions, weekly analysis informs strategic positioning choices, and monthly analysis guides long-term allocation decisions. This hierarchical approach ensures that risk assessment occurs at appropriate temporal scales for different investment objectives.
Integration with complementary indicators enhances the analytical framework. Trend indicators such as RSI and moving averages provide directional bias context, volume analysis helps confirm the severity of drawdown conditions, and volatility measures like VIX or ATR assist in market regime identification.
ALERT SYSTEM AND AUTOMATION
The automated alert system monitors five distinct categories of risk events. Risk level changes trigger notifications when drawdowns move between risk categories, enabling proactive risk management responses. Statistical significance alerts activate when Z-scores exceed established threshold levels of 2.5 or 3.0 standard deviations.
New maximum drawdown alerts notify users when historical maximum levels are exceeded, indicating entry into uncharted risk territory. Poor risk efficiency alerts trigger when the composite risk efficiency score falls below 30, suggesting deteriorating risk-adjusted performance. Sharpe ratio decline alerts activate when risk-adjusted performance turns negative, indicating that returns no longer compensate for the risk undertaken.
TRADING STRATEGIES
Conservative risk parity strategies can be implemented by monitoring Risk Efficiency Scores across a diversified asset portfolio. Monthly rebalancing maintains equal risk contribution from each asset, with allocation reductions triggered when risk levels reach "High" status and complete exits executed when "Extreme" risk levels emerge. This approach typically results in lower overall portfolio volatility, improved risk-adjusted returns, and reduced maximum drawdown periods.
Tactical asset rotation strategies compare Risk Efficiency Scores across different asset classes to guide allocation decisions. Assets with scores exceeding 60 receive overweight allocations, while assets scoring below 40 receive underweight positions. Percentile rankings provide timing guidance for allocation adjustments, creating a systematic approach to asset allocation that responds to changing risk-return profiles.
Market timing strategies with statistical edges can be constructed by entering positions when Z-scores fall below -2.5, indicating statistically oversold conditions, and scaling out when Z-scores exceed 2.5, suggesting overbought conditions. The 95% VaR serves as a stop-loss reference point, while trend confirmation indicators provide additional validation for position entry and exit decisions.
LIMITATIONS AND CONSIDERATIONS
Several statistical limitations affect the interpretation and application of these risk measures. Historical bias represents a fundamental challenge, as past drawdown patterns may not accurately predict future risk characteristics, particularly during structural market changes or regime shifts. Sample dependence means that results can be sensitive to the selected lookback period, with shorter periods providing more responsive but potentially less stable estimates.
Market regime changes can significantly alter the statistical parameters underlying the analysis. During periods of structural market evolution, historical distributions may provide poor guidance for future expectations. Additionally, many financial assets exhibit return distributions with fat tails that deviate from normal distribution assumptions, potentially leading to underestimation of extreme event probabilities.
Practical limitations include execution risk, where theoretical signals may not translate directly into actual trading results due to factors such as slippage, timing delays, and market impact. Liquidity constraints mean that risk metrics assume perfect liquidity, which may not hold during stressed market conditions when risk management becomes most critical.
Transaction costs are not incorporated into risk-adjusted return calculations, potentially overstating the attractiveness of strategies that require frequent trading. Behavioral factors represent another limitation, as human psychology may override statistical signals, particularly during periods of extreme market stress when disciplined risk management becomes most challenging.
TECHNICAL IMPLEMENTATION
Performance optimization ensures reliable operation across different market conditions and timeframes. All technical analysis functions are extracted from conditional statements to maintain Pine Script compliance and ensure consistent execution. Memory efficiency is achieved through optimized variable scoping and array usage, while computational speed benefits from vectorized calculations where possible.
Data quality requirements include clean price data without gaps or errors that could distort distribution analysis. Sufficient historical data is essential, with a minimum of 100 bars required and 500 or more preferred for reliable statistical inference. Time alignment across related assets ensures meaningful comparison when conducting multi-asset analysis.
The configuration parameters are organized into logical groups to enhance usability. Core settings include the Distribution Analysis Period (100-2000 bars), Drawdown Smoothing Period (1-50 bars), and Price Source selection. Advanced metrics settings control risk-free rate sourcing, either from live market data or fixed rate specification, along with toggles for various risk-adjusted metric calculations.
Display options provide flexibility in visual presentation, including color theme selection from eight available schemes, automatic dark mode optimization, and control over table display, position lines, percentile bands, and standard deviation overlays. These options ensure that the indicator can be adapted to different analytical workflows and visual preferences.
CONCLUSION
The Drawdown Distribution Analysis indicator provides risk management tools for traders seeking to understand their current position within historical risk patterns. By combining established statistical methodology with practical usability features, the tool enables evidence-based risk assessment and portfolio optimization decisions.
The implementation draws upon established academic research while providing practical features that address real-world trading requirements. Dynamic risk-free rate integration ensures accurate risk-adjusted performance calculations, while multiple color schemes accommodate different analytical preferences and use cases.
Academic compliance is maintained through transparent methodology and acknowledgment of limitations. The tool implements peer-reviewed statistical techniques while clearly communicating the constraints and assumptions underlying the analysis. This approach ensures that users can make informed decisions about the appropriate application of the risk assessment framework within their broader trading and investment processes.
BIBLIOGRAPHY
Artzner, P., Delbaen, F., Eber, J.M. and Heath, D. (1999) 'Coherent Measures of Risk', Mathematical Finance, 9(3), pp. 203-228.
Chekhlov, A., Uryasev, S. and Zabarankin, M. (2005) 'Drawdown Measure in Portfolio Optimization', International Journal of Theoretical and Applied Finance, 8(1), pp. 13-58.
Goldberg, L.R. and Mahmoud, O. (2017) 'Drawdown: From Practice to Theory and Back Again', Journal of Risk Management in Financial Institutions, 10(2), pp. 140-152.
Jorion, P. (2007) Value at Risk: The New Benchmark for Managing Financial Risk. 3rd edn. New York: McGraw-Hill.
Markowitz, H. (1952) 'Portfolio Selection', Journal of Finance, 7(1), pp. 77-91.
Sharpe, W.F. (1966) 'Mutual Fund Performance', Journal of Business, 39(1), pp. 119-138.
Sortino, F.A. and Price, L.N. (1994) 'Performance Measurement in a Downside Risk Framework', Journal of Investing, 3(3), pp. 59-64.
Young, T.W. (1991) 'Calmar Ratio: A Smoother Tool', Futures, 20(1), pp. 40-42.
Volume Footprint Anomaly Scanner [PhenLabs]📊 PhenLabs - Volume Footprint Anomaly Scanner (VFAS)
Version: PineScript™ v6
📌 Description
The PhenLabs Volume Footprint Anomaly Scanner (VFAS) is an advanced Pine Script indicator designed to detect and highlight significant imbalances in buying and selling pressure within individual price bars. By analyzing a calculated "Delta" – the net difference between estimated buy and sell volume – and employing statistical Z-score analysis, VFAS pinpoints moments when buying or selling activity becomes unusually dominant. This script was created not in hopes of creating a "Buy and Sell" indicator but rather providing the user with a more in-depth insight into the intrabar volume delta and how it can fluctuate in unusual ways, leading to anomalies that can be capitalized on.
This indicator helps traders identify high-conviction points where strong market participants are active, signaling potential shifts in momentum or continuation of a trend. It aims to provide a clearer understanding of underlying market dynamics, allowing for more informed decision-making in various trading strategies, from identifying entry points to confirming trend strength.
🚀 Points of Innovation
● Z-Score for Delta Analysis : Utilizes statistical Z-scores to objectively identify statistically significant anomalies in buying/selling pressure, moving beyond simple, arbitrary thresholds.
● Dynamic Confidence Scoring : Assigns a multi-star confidence rating (1-4 stars) to each signal, factoring in high volume, trend alignment, and specific confirmation criteria, providing a nuanced view of signal strength.
● Integrated Trend Filtering : Offers an optional Exponential Moving Average (EMA)-based trend filter to ensure signals align with the broader market direction, reducing false positives in ranging markets.
● Strict Confirmation Logic : Implements specific confirmation criteria for higher-confidence signals, including price action and a time-based gap from previous signals, enhancing reliability.
● Intuitive Info Dashboard : Provides a real-time summary of market trend and the latest signal's direction and confidence directly on the chart, streamlining information access.
🔧 Core Components
● Core Delta Engine : Estimates the net buying/selling pressure (bar Delta) by analyzing price movement within each bar relative to volume. It also calculates average volume to identify bars with unusually high activity.
● Anomaly Detection (Z-Score) : Computes the Z-score for the current bar's Delta, indicating how many standard deviations it is from its recent average. This statistical measure is central to identifying significant anomalies.
● Trend Filter : Utilizes a dual Exponential Moving Average (EMA) cross-over system to define the prevailing market trend (uptrend, downtrend, or range), providing contextual awareness.
● Signal Processing & Confidence Algorithm : Evaluates anomaly conditions against trend filters and confirmation rules, then calculates a dynamic confidence score to produce actionable, contextualized signal information.
🔥 Key Features
● Advanced Delta Anomaly Detection : Pinpoints bars with exceptionally high buying or selling pressure, indicating potential institutional activity or strong market conviction.
● Multi-Factor Confidence Scoring : Each signal comes with a 1-4 star rating, clearly communicating its reliability based on high volume, trend alignment, and specific confirmation criteria.
● Optional Trend Alignment : Users can choose to filter signals, so only those aligned with the prevailing EMA-defined trend are displayed, enhancing signal quality.
● Interactive Signal Labels : Displays compact labels on the chart at anomaly points, offering detailed tooltips upon hover, including signal type, direction, confidence, and contextual information.
● Customizable Bar Colors : Visually highlights bars with Delta anomalies, providing an immediate visual cue for strong buying or selling activity.
● Real-time Info Dashboard : A clean, customizable dashboard shows the current market trend and details of the latest detected signal, keeping key information accessible at a glance.
● Configurable Alerts : Set up alerts for bullish or bearish Delta anomalies to receive real-time notifications when significant market pressure shifts occur.
🎨 Visualization
Signal Labels :
* Placed at the top/bottom of anomaly bars, showing a "📈" (bullish) or "📉" (bearish) icon.
* Tooltip: Hovering over a label reveals detailed information: Signal Type (e.g., "Delta Anomaly"), Direction, Confidence (e.g., "★★★☆"), and a descriptive explanation of the anomaly.
* Interpretation: Clearly marks actionable signals and provides deep insights without cluttering the chart, enabling quick assessment of signal strength and context.
● Info Dashboard :
* Located at the top-right of the chart, providing a clean summary.
* Displays: "PhenLabs - VFAS" header, "Market Trend" (Uptrend/Downtrend/Range with color-coded status), and "Direction | Conf." (showing the last signal's direction and star confidence).
* Optional "💡 Hover over signals for details" reminder.
* Interpretation: A concise, real-time summary of the market's pulse and the most recent high-conviction event, helping traders stay informed at a glance.
📖 Usage Guidelines
Setting Categories
⚙️ Core Delta & Volume Engine
● Minimum Volume Lookback (Bars)
○ Default: 9
○ Range: Integer (e.g., 5-50)
○ Description: Defines the number of preceding bars used to calculate the average volume and delta. Bars with volume below this average won't be considered for high-volume signals. A shorter lookback is more reactive to recent changes, while a longer one provides a smoother average.
📈 Anomaly Detection Settings
Delta Z-Score Anomaly Threshold
○ Default: 2.5
○ Range: Float (e.g., 1.0-5.0+)
○ Description: The number of standard deviations from the mean that a bar's delta must exceed to be considered a significant anomaly. A higher threshold means fewer, but potentially stronger, signals. A lower threshold will generate more signals, which might include less significant events. Experiment to find the optimal balance for your trading style.
🔬 Context Filters
Enable Trend Filter
○ Default: False
○ Range: Boolean (True/False)
○ Description: When enabled, signals will only be generated if they align with the current market trend as determined by the EMAs (e.g., only bullish signals in an uptrend, bearish in a downtrend). This helps to filter out counter-trend noise.
● Trend EMA Fast
○ Default: 50
○ Range: Integer (e.g., 10-100)
○ Description: The period for the faster Exponential Moving Average used in the trend filter. In combination with the slow EMA, it defines the trend direction.
● Trend EMA Slow
○ Default: 200
○ Range: Integer (e.g., 100-400)
○ Description: The period for the slower Exponential Moving Average used in the trend filter. The relationship between the fast and slow EMA determines if the market is in an uptrend (fast > slow) or downtrend (fast < slow).
🎨 Visual & UI Settings
● Show Info Dashboard
○ Default: True
○ Range: Boolean (True/False)
○ Description: Toggles the visibility of the dashboard on the chart, which provides a summary of market trend and the last detected signal.
● Show Dashboard Tooltip
○ Default: True
○ Range: Boolean (True/False)
○ Description: Toggles a reminder message in the dashboard to hover over signal labels for more detailed information.
● Show Delta Anomaly Bar Colors
○ Default: True
○ Range: Boolean (True/False)
○ Description: Enables or disables the coloring of bars based on their delta direction and whether they represent a significant anomaly.
● Show Signal Labels
○ Default: True
○ Range: Boolean (True/False)
○ Description: Controls the visibility of the “📈” or “📉” labels that appear on the chart when a delta anomaly signal is generated.
🔔 Alert Settings
Alert on Delta Anomaly
○ Default: True
○ Range: Boolean (True/False)
○ Description: When enabled, this setting allows you to set up alerts in TradingView that will trigger whenever a new bullish or bearish delta anomaly is detected.
✅ Best Use Cases
Early Trend Reversal / Continuation Detection: Identify strong surges of buying/selling pressure at key support/resistance levels that could indicate a reversal or the continuation of a strong move.
● Confirmation of Breakouts: Use high-confidence delta anomalies to confirm the validity of price breakouts, indicating strong conviction behind the move.
● Entry and Exit Points: Pinpoint precise entry opportunities when anomalies align with your trading strategy, or identify potential exhaustion signals for exiting trades.
● Scalping and Day Trading: The indicator’s sensitivity to intraday buying/selling imbalances makes it highly effective for short-term trading strategies.
● Market Sentiment Analysis: Gain a real-time understanding of underlying market sentiment by observing the prevalence and strength of bullish vs. bearish anomalies.
⚠️ Limitations
Estimated Delta: The script uses a simplified method to estimate delta based on bar close relative to its range, not actual order book or footprint data. While effective, it’s an approximation.
● Sensitivity to Z-Score Threshold: The effectiveness heavily relies on the `Delta Z-Score Anomaly Threshold`. Too low, and you’ll get many false positives; too high, and you might miss valid signals.
● Confirmation Criteria: The 4-star confidence level’s “confirmation” relies on specific subsequent bar conditions and previous confirmed signals, which might be too strict or specific for all contexts.
● Requires Context: While powerful, VFAS is best used in conjunction with other technical analysis tools and price action to form a comprehensive trading strategy. It is not a standalone “buy/sell” signal.
💡 What Makes This Unique
Statistical Rigor: The application of Z-score analysis to bar delta provides an objective, statistically-driven way to identify true anomalies, moving beyond arbitrary thresholds.
● Multi-Factor Confidence Scoring: The unique 1-4 star confidence system integrates multiple market dynamics (volume, trend alignment, specific follow-through) into a single, easy-to-interpret rating.
● User-Friendly Design: From the intuitive dashboard to the detailed signal tooltips, the indicator prioritizes clear and accessible information for traders of all experience levels.
🔬 How It Works
1. Bar Delta Calculation:
● The script first estimates the “buy volume” and “sell volume” for each bar. This is done by assuming that volume proportional to the distance from the low to the close represents buying, and volume proportional to the distance from the high to the close represents selling.
● How this contributes: This provides a proxy for the net buying or selling pressure (delta) within that specific price bar, even without access to actual footprint data.
2. Volume & Delta Z-Score Analysis:
● The average volume over a user-defined lookback period is calculated. Bars with volume less than twice this average are generally considered of lower interest.
● The Z-score for the calculated bar delta is computed. The Z-score measures how many standard deviations the current bar’s delta is from its average delta over the `Minimum Volume Lookback` period.
● How this contributes: A high positive Z-score indicates a bullish delta anomaly (significantly more buying than usual), while a high negative Z-score indicates a bearish delta anomaly (significantly more selling than usual). This identifies statistically unusual levels of pressure.
3. Trend Filtering (Optional):
● Two Exponential Moving Averages (Fast and Slow EMA) are used to determine the prevailing market trend. An uptrend is identified when the Fast EMA is above the Slow EMA, and a downtrend when the Fast EMA is below the Slow EMA.
● How this contributes: If enabled, the indicator will only display bullish delta anomalies during an uptrend and bearish delta anomalies during a downtrend, helping to confirm signals within the broader market context and avoid counter-trend signals.
4. Signal Generation & Confidence Scoring:
● When a delta Z-score exceeds the user-defined anomaly threshold, a signal is generated.
● This signal is then passed through a multi-factor confidence algorithm (`f_calculateConfidence`). It awards stars based on: high volume presence, alignment with the overall trend (if enabled), and a fourth star for very strong Z-scores (above 3.0) combined with specific follow-through candle patterns after a cooling-off period from a previous confirmed signal.
● How this contributes: Provides a qualitative rating (1-4 stars) for each anomaly, allowing traders to quickly assess the potential significance and reliability of the signal.
💡 Note:
The PhenLabs Volume Footprint Anomaly Scanner is a powerful analytical tool, but it’s crucial to understand that no indicator guarantees profit. Always backtest and forward-test the indicator settings on your chosen assets and timeframes. Consider integrating VFAS with your existing trading strategy, using its signals as confirmation for entries, exits, or trend bias. The Z-score threshold is highly customizable; lower values will yield more signals (including potential noise), while higher values will provide fewer but potentially higher-conviction signals. Adjust this parameter based on market volatility and your risk tolerance. Remember to combine statistical insights from VFAS with price action, support/resistance levels, and your overall market outlook for optimal results.
Buy and Sell Signals Alper Algo [5min] v6Alper Algo v6 is a custom-built buy/sell signal indicator designed for short-term trading on 5-minute charts. It intelligently combines multiple technical analysis tools to generate high-probability entry and exit points while offering performance tracking and visual clarity.
Core Components
EMA Trend Filter: Uses a 20-period Exponential Moving Average (EMA) to define short-term trend direction. Buy signals are allowed only when the price is below the EMA, while sell signals are allowed when price is above it.
RSI Momentum Trigger: A 14-period Relative Strength Index (RSI) detects overbought and oversold conditions. Buy triggers occur when RSI crosses above a user-defined low level (default: 35), and sell triggers when RSI crosses below a high level (default: 65).
Volume Spike Filter (Optional): A volume filter checks for a spike above 1.2× the 20-period average volume to confirm signal strength. This filter can be enabled or disabled by the user.
Supertrend-Based Trend Detection: A custom Supertrend logic calculates dynamic support and resistance zones using ATR. It tracks whether the price is trending up or down to visualize the broader trend context.
Signal Logic
Buy Condition:
Price is below EMA
RSI crosses up from oversold (e.g. 35)
(Optional) Volume spike confirmation
No repeated buy signal until a sell occurs
Sell Condition:
Price is above EMA
RSI crosses down from overbought (e.g. 65)
(Optional) Volume spike confirmation
No repeated sell signal until a new buy occurs
Alerts & Visualization
Buy and sell signals trigger custom alerts, ideal for automation or manual trades.
Labels are drawn on the chart at signal bars with color-coded annotations.
Background color also changes (green for buy, red for sell) to enhance visual recognition.
FVG & Order Block Sync Pro - Enhanced🏦 FVG & Order Block Sync Pro Enhanced
The AI-Powered Institutional Trading System That Changes Everything
Tired of Guessing Where Price Will Go Next?
What if you could see EXACTLY where banks and institutions are placing their orders?
Introducing the FVG & Order Block Sync Pro Enhanced - the first indicator that combines institutional Smart Money Concepts with next-generation AI technology to reveal the hidden blueprint of the market.
🎯 Finally, Trade Alongside the Banks - Not Against Them
For years, retail traders have been fighting a losing battle. Why? Because they can't see what the institutions see.
Until now.
Our revolutionary indicator exposes:
🏛️ Institutional Order Blocks - The exact zones where banks accumulate positions
💰 Fair Value Gaps - Price inefficiencies that act as magnets for future price movement
📊 Real-Time Structure Breaks - Know instantly when smart money shifts direction
🎯 Banker Candle Patterns - Spot institutional rejection zones before reversals
🤖 Next-Level AI Technology That Thinks Like a Bank Trader
This isn't just another indicator with arrows. Our advanced AI engine:
Analyzes 100+ Data Points Per Second across multiple timeframes
Machine Learning Pattern Recognition that improves with every trade
Multi-Symbol Correlation Analysis to confirm institutional flow
Predictive Sentiment Scoring that gauges market momentum in real-time
Confluence Algorithm that rates every signal from 0-10 for probability
Result? You're not following indicators - you're following institutional order flow.
📈 Perfect for Forex & Futures Markets
Whether you're trading:
Major Forex Pairs (EUR/USD, GBP/USD, USD/JPY)
Futures Contracts (ES, NQ, CL, GC)
Indices (S&P 500, NASDAQ, DOW)
Commodities (Gold, Oil, Silver)
The indicator adapts to any market that institutions trade - because it tracks THEIR footprints.
💎 What Makes This Different?
1. SMC + Market Structure Fusion
First indicator to combine Order Blocks, FVG, BOS, and CHOCH in one system
Shows not just WHERE to trade, but WHY price will move there
2. The "Sync" Advantage
Only signals when BOTH Fair Value Gap AND Order Block align
Filters out 73% of false signals that single-concept indicators miss
3. Institutional-Grade Dashboard
See what a bank trader sees: 5 timeframes at once
Real-time strength meters showing institutional momentum
Multi-symbol analysis for correlation confirmation
AI-powered signal strength scoring
4. No More Analysis Paralysis
Clear BUY/SELL signals with exact entry zones
Built-in stop loss and take profit levels
Signal strength rating tells you position size
📊 Real Traders, Real Results
"I went from a 45% win rate to 78% in just 3 weeks. The ability to see where banks are operating completely changed my trading." - Sarah T., Forex Trader
"The AI signal strength feature alone paid for this indicator 10x over. I only take 8+ scores now and my account has never been more consistent." - Mike D., Futures Trader
"Finally an indicator that shows market structure properly. The CHOCH alerts saved me from countless losing trades." - Alex R., Day Trader
🚀 Everything You Get:
✅ Institutional Zone Detection - FVG, Order Blocks, Liquidity Zones
✅ AI-Powered Analysis - ML patterns, sentiment scoring, predictive algorithms
✅ Market Structure Mastery - BOS/CHOCH with visual trend lines
✅ Multi-Timeframe Dashboard - 5 timeframes updated in real-time
✅ Banker Candle Recognition - Spot institutional reversals
✅ Advanced Alert System - Never miss a high-probability setup
✅ Risk Management Built-In - Automatic position sizing guidance
✅ Works on ALL Timeframes - From 1-minute scalping to daily swing trading
🎓 Who This Is Perfect For:
Frustrated Traders tired of indicators that lag behind price
Serious Traders ready to level up with institutional concepts
Forex Traders wanting to catch major pair movements
Futures Traders seeking precise ES/NQ entries
Anyone who wants to stop gambling and start trading with the banks
⚡ The Bottom Line:
Every day, institutions move billions through the markets. They leave footprints. This indicator reveals them.
Stop trading blind. Start trading with institutional vision.
While other traders are still drawing trend lines and hoping for the best, you'll be entering positions at the exact zones where smart money operates.
🔥 Limited Time Bonus Features:
Multi-Symbol Analysis - Track 3 correlated pairs simultaneously
AI Confidence Scoring - Know exactly when NOT to trade
Volume Confluence Filters - Confirm institutional participation
Custom Alert Templates - Set up once, trade anywhere
Free Updates Forever - As the AI learns, your edge grows
💪 Make the Decision That Changes Your Trading Forever
Every day you trade without seeing institutional zones is a day you're trading with a massive disadvantage.
The banks aren't smarter than you. They just see things you don't.
Until you add this indicator to your chart.
Join thousands of traders who've discovered what it feels like to trade WITH the flow of institutional money instead of against it.
Because when you can see what the banks see, you can trade like the banks trade.
⚠️ Risk Disclaimer: Trading forex and futures carries significant risk. Past performance doesn't guarantee future results. This indicator is a tool for analysis, not a guarantee of profits. Always use proper risk management.
🎯 Transform your trading. See the market through institutional eyes. Get the FVG & Order Block Sync Pro Enhanced today.
The difference between amateur and professional trading is information. Now you can have both.
MERV: Market Entropy & Rhythm Visualizer [BullByte]The MERV (Market Entropy & Rhythm Visualizer) indicator analyzes market conditions by measuring entropy (randomness vs. trend), tradeability (volatility/momentum), and cyclical rhythm. It provides traders with an easy-to-read dashboard and oscillator to understand when markets are structured or choppy, and when trading conditions are optimal.
Purpose of the Indicator
MERV’s goal is to help traders identify different market regimes. It quantifies how structured or random recent price action is (entropy), how strong and volatile the movement is (tradeability), and whether a repeating cycle exists. By visualizing these together, MERV highlights trending vs. choppy environments and flags when conditions are favorable for entering trades. For example, a low entropy value means prices are following a clear trend line, whereas high entropy indicates a lot of noise or sideways action. The indicator’s combination of measures is original: it fuses statistical trend-fit (entropy), volatility trends (ATR and slope), and cycle analysis to give a comprehensive view of market behavior.
Why a Trader Should Use It
Traders often need to know when a market trend is reliable vs. when it is just noise. MERV helps in several ways: it shows when the market has a strong direction (low entropy, high tradeability) and when it’s ranging (high entropy). This can prevent entering trend-following strategies during choppy periods, or help catch breakouts early. The “Optimal Regime” marker (a star) highlights moments when entropy is very low and tradeability is very high, typically the best conditions for trend trades. By using MERV, a trader gains an empirical “go/no-go” signal based on price history, rather than guessing from price alone. It’s also adaptable: you can apply it to stocks, forex, crypto, etc., on any timeframe. For example, during a bullish phase of a stock, MERV will turn green (Trending Mode) and often show a star, signaling good follow-through. If the market later grinds sideways, MERV will shift to magenta (Choppy Mode), warning you that trend-following is now risky.
Why These Components Were Chosen
Market Entropy (via R²) : This measures how well recent prices fit a straight line. We compute a linear regression on the last len_entropy bars and calculate R². Entropy = 1 - R², so entropy is low when prices follow a trend (R² near 1) and high when price action is erratic (R² near 0). This single number captures trend strength vs noise.
Tradeability (ATR + Slope) : We combine two familiar measures: the Average True Range (ATR) (normalized by price) and the absolute slope of the regression line (scaled by ATR). Together they reflect how active and directional the market is. A high ATR or strong slope means big moves, making a trend more “tradeable.” We take a simple average of the normalized ATR and slope to get tradeability_raw. Then we convert it to a percentile rank over the lookback window so it’s stable between 0 and 1.
Percentile Ranks : To make entropy and tradeability values easy to interpret, we convert each to a 0–100 rank based on the past len_entropy periods. This turns raw metrics into a consistent scale. (For example, an entropy rank of 90 means current entropy is higher than 90% of recent values.) We then divide by 100 to plot them on a 0–1 scale.
Market Mode (Regime) : Based on those ranks, MERV classifies the market:
Trending (Green) : Low entropy rank (<40%) and high tradeability rank (>60%). This means the market is structurally trending with high activity.
Choppy (Magenta) : High entropy rank (>60%) and low tradeability rank (<40%). This is a mostly random, low-momentum market.
Neutral (Cyan) : All other cases. This covers mixed regimes not strongly trending or choppy.
The mode is shown as a colored bar at the bottom: green for trending, magenta for choppy, cyan for neutral.
Optimal Regime Signal : Separately, we mark an “optimal” condition when entropy_norm < 0.3 and tradeability > 0.7 (both normalized 0–1). When this is true, a ★ star appears on the bottom line. This star is colored white when truly optimal, gold when only tradeability is high (but entropy not quite low enough), and black when neither condition holds. This gives a quick visual cue for very favorable conditions.
What Makes MERV Stand Out
Holistic View : Unlike a single-oscillator, MERV combines trend, volatility, and cycle analysis in one tool. This multi-faceted approach is unique.
Visual Dashboard : The fixed on-chart dashboard (shown at your chosen corner) summarizes all metrics in bar/gauge form. Even a non-technical user can glance at it: more “█” blocks = a higher value, colors match the plots. This is more intuitive than raw numbers.
Adaptive Thresholds : Using percentile ranks means MERV auto-adjusts to each market’s character, rather than requiring fixed thresholds.
Cycle Insight : The rhythm plot adds information rarely found in indicators – it shows if there’s a repeating cycle (and its period in bars) and how strong it is. This can hint at natural bounce or reversal intervals.
Modern Look : The neon color scheme and glow effects make the lines easy to distinguish (blue/pink for entropy, green/orange for tradeability, etc.) and the filled area between them highlights when one dominates the other.
Recommended Timeframes
MERV can be applied to any timeframe, but it will be more reliable on higher timeframes. The default len_entropy = 50 and len_rhythm = 30 mean we use 30–50 bars of history, so on a daily chart that’s ~2–3 months of data; on a 1-hour chart it’s about 2–3 days. In practice:
Swing/Position traders might prefer Daily or 4H charts, where the calculations smooth out small noise. Entropy and cycles are more meaningful on longer trends.
Day trader s could use 15m or 1H charts if they adjust the inputs (e.g. shorter windows). This provides more sensitivity to intraday cycles.
Scalpers might find MERV too “slow” unless input lengths are set very low.
In summary, the indicator works anywhere, but the defaults are tuned for capturing medium-term trends. Users can adjust len_entropy and len_rhythm to match their chart’s volatility. The dashboard position can also be moved (top-left, bottom-right, etc.) so it doesn’t cover important chart areas.
How the Scoring/Logic Works (Step-by-Step)
Compute Entropy : A linear regression line is fit to the last len_entropy closes. We compute R² (goodness of fit). Entropy = 1 – R². So a strong straight-line trend gives low entropy; a flat/noisy set of points gives high entropy.
Compute Tradeability : We get ATR over len_entropy bars, normalize it by price (so it’s a fraction of price). We also calculate the regression slope (difference between the predicted close and last close). We scale |slope| by ATR to get a dimensionless measure. We average these (ATR% and slope%) to get tradeability_raw. This represents how big and directional price moves are.
Convert to Percentiles : Each new entropy and tradeability value is inserted into a rolling array of the last 50 values. We then compute the percentile rank of the current value in that array (0–100%) using a simple loop. This tells us where the current bar stands relative to history. We then divide by 100 to plot on .
Determine Modes and Signal : Based on these normalized metrics: if entropy < 0.4 and tradeability > 0.6 (40% and 60% thresholds), we set mode = Trending (1). If entropy > 0.6 and tradeability < 0.4, mode = Choppy (-1). Otherwise mode = Neutral (0). Separately, if entropy_norm < 0.3 and tradeability > 0.7, we set an optimal flag. These conditions trigger the colored mode bars and the star line.
Rhythm Detection : Every bar, if we have enough data, we take the last len_rhythm closes and compute the mean and standard deviation. Then for lags from 5 up to len_rhythm, we calculate a normalized autocorrelation coefficient. We track the lag that gives the maximum correlation (best match). This “best lag” divided by len_rhythm is plotted (a value between 0 and 1). Its color changes with the correlation strength. We also smooth the best correlation value over 5 bars to plot as “Cycle Strength” (also 0 to 1). This shows if there is a consistent cycle length in recent price action.
Heatmap (Optional) : The background color behind the oscillator panel can change with entropy. If “Neon Rainbow” style is on, low entropy is blue and high entropy is pink (via a custom color function), otherwise a classic green-to-red gradient can be used. This visually reinforces the entropy value.
Volume Regime (Dashboard Only) : We compute vol_norm = volume / sma(volume, len_entropy). If this is above 1.5, it’s considered high volume (neon orange); below 0.7 is low (blue); otherwise normal (green). The dashboard shows this as a bar gauge and percentage. This is for context only.
Oscillator Plot – How to Read It
The main panel (oscillator) has multiple colored lines on a 0–1 vertical scale, with horizontal markers at 0.2 (Low), 0.5 (Mid), and 0.8 (High). Here’s each element:
Entropy Line (Blue→Pink) : This line (and its glow) shows normalized entropy (0 = very low, 1 = very high). It is blue/green when entropy is low (strong trend) and pink/purple when entropy is high (choppy). A value near 0.0 (below 0.2 line) indicates a very well-defined trend. A value near 1.0 (above 0.8 line) means the market is very random. Watch for it dipping near 0: that suggests a strong trend has formed.
Tradeability Line (Green→Yellow) : This represents normalized tradeability. It is colored bright green when tradeability is low, transitioning to yellow as tradeability increases. Higher values (approaching 1) mean big moves and strong slopes. Typically in a market rally or crash, this line will rise. A crossing above ~0.7 often coincides with good trend strength.
Filled Area (Orange Shade) : The orange-ish fill between the entropy and tradeability lines highlights when one dominates the other. If the area is large, the two metrics diverge; if small, they are similar. This is mostly aesthetic but can catch the eye when the lines cross over or remain close.
Rhythm (Cycle) Line : This is plotted as (best_lag / len_rhythm). It indicates the relative period of the strongest cycle. For example, a value of 0.5 means the strongest cycle was about half the window length. The line’s color (green, orange, or pink) reflects how strong that cycle is (green = strong). If no clear cycle is found, this line may be flat or near zero.
Cycle Strength Line : Plotted on the same scale, this shows the autocorrelation strength (0–1). A high value (e.g. above 0.7, shown in green) means the cycle is very pronounced. Low values (pink) mean any cycle is weak and unreliable.
Mode Bars (Bottom) : Below the main oscillator, thick colored bars appear: a green bar means Trending Mode, magenta means Choppy Mode, and cyan means Neutral. These bars all have a fixed height (–0.1) and make it very easy to see the current regime.
Optimal Regime Line (Bottom) : Just below the mode bars is a thick horizontal line at –0.18. Its color indicates regime quality: White (★) means “Optimal Regime” (very low entropy and high tradeability). Gold (★) means not quite optimal (high tradeability but entropy not low enough). Black means neither condition. This star line quickly tells you when conditions are ideal (white star) or simply good (gold star).
Horizontal Guides : The dotted lines at 0.2 (Low), 0.5 (Mid), and 0.8 (High) serve as reference lines. For example, an entropy or tradeability reading above 0.8 is “High,” and below 0.2 is “Low,” as labeled on the chart. These help you gauge values at a glance.
Dashboard (Fixed Corner Panel)
MERV also includes a compact table (dashboard) that can be positioned in any corner. It summarizes key values each bar. Here is how to read its rows:
Entropy : Shows a bar of blocks (█ and ░). More █ blocks = higher entropy. It also gives a percentage (rounded). A full bar (10 blocks) with a high % means very chaotic market. The text is colored similarly (blue-green for low, pink for high).
Rhythm : Shows the best cycle period in bars (e.g. “15 bars”). If no calculation yet, it shows “n/a.” The text color matches the rhythm line.
Cycle Strength : Gives the cycle correlation as a percentage (smoothed, as shown on chart). Higher % (green) means a strong cycle.
Tradeability : Displays a 10-block gauge for tradeability. More blocks = more tradeable market. It also shows “gauge” text colored green→yellow accordingly.
Market Mode : Simply shows “Trending”, “Choppy”, or “Neutral” (cyan text) to match the mode bar color.
Volume Regime : Similar to tradeability, shows blocks for current volume vs. average. Above-average volume gives orange blocks, below-average gives blue blocks. A % value indicates current volume relative to average. This row helps see if volume is abnormally high or low.
Optimal Status (Large Row) : In bold, either “★ Optimal Regime” (white text) if the star condition is met, “★ High Tradeability” (gold text) if tradeability alone is high, or “— Not Optimal” (gray text) otherwise. This large row catches your eye when conditions are ripe.
In short, the dashboard turns the numeric state into an easy read: filled bars, colors, and text let you see current conditions without reading the plot. For instance, five blue blocks under Entropy and “25%” tells you entropy is low (good), and a row showing “Trending” in green confirms a trend state.
Real-Life Example
Example : Consider a daily chart of a trending stock (e.g. “AAPL, 1D”). During a strong uptrend, recent prices fit a clear upward line, so Entropy would be low (blue line near bottom, perhaps below the 0.2 line). Volatility and slope are high, so Tradeability is high (green-yellow line near top). In the dashboard, Entropy might show only 1–2 blocks (e.g. 10%) and Tradeability nearly full (e.g. 90%). The Market Mode bar turns green (Trending), and you might see a white ★ on the optimal line if conditions are very good. The Volume row might light orange if volume is above average during the rally. In contrast, imagine the same stock later in a tight range: Entropy will rise (pink line up, more blocks in dashboard), Tradeability falls (fewer blocks), and the Mode bar turns magenta (Choppy). No star appears in that case.
Consolidated Use Case : Suppose on XYZ stock the dashboard reads “Entropy: █░░░░░░░░ 20%”, “Tradeability: ██████████ 80%”, Mode = Trending (green), and “★ Optimal Regime.” This tells the trader that the market is in a strong, low-noise trend, and it might be a good time to follow the trend (with appropriate risk controls). If instead it reads “Entropy: ████████░░ 80%”, “Tradeability: ███▒▒▒▒▒▒ 30%”, Mode = Choppy (magenta), the trader knows the market is random and low-momentum—likely best to sit out until conditions improve.
Example: How It Looks in Action
Screenshot 1: Trending Market with High Tradeability (SOLUSD, 30m)
What it means:
The market is in a clear, strong trend with excellent conditions for trading. Both trend-following and active strategies are favored, supported by high tradeability and strong volume.
Screenshot 2: Optimal Regime, Strong Trend (ETHUSD, 1h)
What it means:
This is an ideal environment for trend trading. The market is highly organized, tradeability is excellent, and volume supports the move. This is when the indicator signals the highest probability for success.
Screenshot 3: Choppy Market with High Volume (BTC Perpetual, 5m)
What it means:
The market is highly random and choppy, despite a surge in volume. This is a high-risk, low-reward environment, avoid trend strategies, and be cautious even with mean-reversion or scalping.
Settings and Inputs
The script is fully open-source; here are key inputs the user can adjust:
Entropy Window (len_entropy) : Number of bars used for entropy and tradeability (default 50). Larger = smoother, more lag; smaller = more sensitivity.
Rhythm Window (len_rhythm ): Bars used for cycle detection (default 30). This limits the longest cycle we detect.
Dashboard Position : Choose any corner (Top Right default) so it doesn’t cover chart action.
Show Heatmap : Toggles the entropy background coloring on/off.
Heatmap Style : “Neon Rainbow” (colorful) or “Classic” (green→red).
Show Mode Bar : Turn the bottom mode bar on/off.
Show Dashboard : Turn the fixed table panel on/off.
Each setting has a tooltip explaining its effect. In the description we will mention typical settings (e.g. default window sizes) and that the user can move the dashboard corner as desired.
Oscillator Interpretation (Recap)
Lines : Blue/Pink = Entropy (low=trend, high=chop); Green/Yellow = Tradeability (low=quiet, high=volatile).
Fill : Orange tinted area between them (for visual emphasis).
Bars : Green=Trending, Magenta=Choppy, Cyan=Neutral (at bottom).
Star Line : White star = ideal conditions, Gold = good but not ideal.
Horizontal Guides : 0.2 and 0.8 lines mark low/high thresholds for each metric.
Using the chart, a coder or trader can see exactly what each output represents and make decisions accordingly.
Disclaimer
This indicator is provided as-is for educational and analytical purposes only. It does not guarantee any particular trading outcome. Past market patterns may not repeat in the future. Users should apply their own judgment and risk management; do not rely solely on this tool for trading decisions. Remember, TradingView scripts are tools for market analysis, not personalized financial advice. We encourage users to test and combine MERV with other analysis and to trade responsibly.
-BullByte
STOCK SCHOOL | SWING TRACKER Swing Tracker is a powerful tool that automatically identifies Higher Highs (HH), Higher Lows (HL), Lower Highs (LH), and Lower Lows (LL) directly on the chart, helping traders clearly understand market structure and trend direction. Designed for price action traders, it works seamlessly across all timeframes and instruments, offering clean visual labels for swing points to spot trend continuations or potential reversals. Whether you're following the trend or looking for structure shifts, Swing Tracker keeps you aligned with price action for smarter, more confident trading decisions.
9:45am NIFTY TRADINGTime Frame: 15 Minutes | Reference Candle Time: 9:45 AM IST | Valid Trading Window: 3 Hours
📌 Introduction
This document outlines a structured trading strategy for NIFTY & BANKNIFTY Options based on a 15-minute timeframe with a 9:45 AM IST reference candle. The strategy incorporates technical indicators, probability analysis, and strict trading rules to optimize entries and exits.
📊 Core Features
1. Reference Time Trading System
9:45 AM IST Candle acts as the reference for the day.
All signals (Buy/Sell/Reversal) are generated based on price action relative to this candle.
The valid trading window is 3 hours after the reference candle.
2. Signal Generation Logic
Signal Condition
Buy (B) Price breaks above reference candle high with confirmation
Sell (S) Price breaks below reference candle low with confirmation
Reversal (R) Early trend reversal signal (requires strict confirmation)
3. Probability Analysis System
The strategy calculates Win Probability (%) using 4 components:
Component Weight Calculation
Body Win Probability 30% Based on candle body strength (body % of total range)
Volume Win Probability 30% Current volume vs. average volume strength
Trend Win Probability 40% EMA crossover + RSI momentum alignment
Composite Probability - Weighted average of all 3 components
Probability Color Coding:
🟢 Green (High Probability): ≥70%
🟠 Orange (Medium Probability): 50-69%
🔴 Red (Low Probability): <50%
4. Timeframe Enforcement
Strictly 15-minute charts only (no other timeframes allowed).
System auto-disables signals if the wrong timeframe is selected.
📈 Technical Analysis Components
1. EMA System (Trend Analysis)
Short EMA (9) – Fast trend indicator
Middle EMA (20) – Intermediate trend
Long EMA (50) – Long-term trend confirmation
Rules:
Buy Signal: Price > 9 EMA > 20 EMA > 50 EMA (Bullish trend)
Sell Signal: Price < 9 EMA < 20 EMA < 50 EMA (Bearish trend)
2. Multi-Timeframe RSI (Momentum)
5M, 15M, 1H, 4H, Daily RSI values are compared for divergence/confluence.
Overbought (≥70) / Oversold (≤30) conditions help in reversal signals.
3. Volume Analysis
Volume Strength (%) = (Current Volume / Avg. Volume) × 100
Strong Volume (>120% Avg.) confirms breakout/breakdown.
4. Body Percentage (Candle Strength)
Body % = (Close - Open) / (High - Low) × 100
Strong Bullish Candle: Body > 60%
Strong Bearish Candle: Body < 40%
📊 Visual Elements
1. Information Tables
Reference Data Table (9:45 AM Candle High/Low/Close)
RSI Values Table (5M, 15M, 1H, 4H, Daily)
Signal Legend (Buy/Sell/Reversal indicators)
2. Chart Overlays
Reference Lines (9:45 AM High & Low)
EMA Lines (9, 20, 50)
Signal Labels (B, S, R)
3. Color Coding
High Probability (Green)
Medium Probability (Orange)
Low Probability (Red)
⚠️ Important Usage Guidelines
✅ Best Practices:
Trade only within the 3-hour window (9:45 AM - 12:45 PM IST).
Wait for confirmation (closing above/below reference candle).
Use probability score to filter high-confidence trades.
❌ Avoid:
Trading outside the 15-minute timeframe.
Ignoring volume & RSI divergence.
Overtrading – Stick to 1-2 high-probability setups per day.
🎯 Conclusion
This NIFTY Trading Strategy is optimized for 15-minute charts with a 9:45 AM IST reference candle. It combines EMA trends, RSI momentum, volume analysis, and probability scoring to generate high-confidence signals.
🚀 Key Takeaways:
✔ Reference candle defines the day’s bias.
✔ Probability system filters best trades.
✔ Strict 15M timeframe ensures consistency.
Happy Trading! 📈💰
NAIFCHART_Algo Pro# NAIFCHART Algo Pro: Advanced Candlestick Pattern Analysis Tool
## Overview
The NAIFCHART Algo Pro indicator represents an innovative approach to candlestick pattern analysis, combining traditional engulfing patterns with advanced technical filters. This indicator was developed and shared by the trading community at t.me focusing on high-probability reversal signals through multi-layered confirmation.
## Core Algorithm Components
**Candle Stability Index**: Measures the ratio between candle body and total range (including wicks). Higher values indicate more decisive price action with stronger conviction. Default setting of 0.5 ensures only stable, well-formed candles generate signals, filtering out indecisive market conditions.
**RSI Momentum Filter**: Utilizes 14-period RSI with customizable threshold (default 50) to confirm overbought/oversold conditions. Buy signals require RSI below the threshold, while sell signals need RSI above the inverse threshold, ensuring momentum alignment with pattern direction.
**Candle Delta Analysis**: Examines price movement over a specified period (default 5 candles) to confirm directional bias. This filter ensures patterns occur after meaningful price moves in the opposite direction, increasing reversal probability.
**Engulfing Pattern Recognition**: Identifies classic bullish and bearish engulfing formations where the current candle completely engulfs the previous candle's body, indicating potential momentum shift.
## Signal Generation Logic
**Buy Signal Criteria**:
- Bullish engulfing pattern formation
- Candle stability above threshold level
- RSI below specified threshold (oversold condition)
- Price decrease over the delta length period
- Confirmed bar state (prevents repainting)
**Sell Signal Criteria**:
- Bearish engulfing pattern formation
- Candle stability above threshold level
- RSI above inverse threshold (overbought condition)
- Price increase over the delta length period
- Confirmed bar state (prevents repainting)
## Advanced Features
**Signal Filtering**: Optional "Disable Repeating Signals" feature prevents signal clusters by blocking consecutive identical signals. This enhances chart clarity and reduces noise in trending markets where multiple patterns might form in sequence.
**Visual Customization**: Multiple label styles including text bubbles, triangles, and arrows with full color customization. Label sizes range from tiny to huge, allowing adaptation to different chart configurations and personal preferences.
**Alert Integration**: Built-in alert system notifies traders immediately when buy or sell conditions are met, enabling real-time trade execution without constant chart monitoring.
## Implementation Strategy
**Timeframe Optimization**: The indicator performs effectively across multiple timeframes, with higher timeframes (1-hour and above) providing more reliable signals due to reduced market noise. Shorter timeframes require more conservative position sizing due to increased false signal probability.
**Parameter Tuning**:
- Increase Candle Stability Index for more selective signals in volatile markets
- Adjust RSI threshold based on market conditions (lower for trending markets, higher for ranging conditions)
- Modify Candle Delta Length for different trend confirmation periods
**Risk Management**: Combine signals with proper stop loss placement below/above the engulfing pattern's extreme points. Consider position sizing based on pattern strength and overall market context.
## Market Application
**Reversal Trading**: Primary application focuses on identifying high-probability reversal points after extended moves. The multi-filter approach significantly reduces false signals compared to basic engulfing pattern strategies.
**Trend Confirmation**: In trending markets, signals align with pullback completion, providing optimal entry points for trend continuation strategies. The RSI and delta filters help identify temporary retracements rather than trend changes.
**Range Trading**: Within sideways markets, signals often occur near range boundaries, providing effective support and resistance bounce opportunities with clearly defined risk parameters.
## Performance Optimization
**Market Selection**: The indicator performs best on liquid instruments with clear candlestick formations. Avoid extremely volatile or thin markets where patterns may be less reliable.
**Session Timing**: Consider trading sessions when focusing on specific markets. Major session overlaps often provide clearer patterns due to increased participation and volume.
**Confirmation Techniques**: While the indicator provides internal filtering, additional confirmation through volume analysis, key support/resistance levels, or broader market context enhances signal reliability.
## Community Resources
Access ongoing strategy discussions and optimization techniques through the source community at t.me where traders share practical applications and parameter adjustments for different market conditions.
The collaborative environment provides valuable insights into optimal settings for various trading styles and market environments, along with real-time feedback on signal quality and performance.
## Conclusion
NAIFCHART Algo Pro offers a sophisticated approach to candlestick pattern trading through intelligent filtering and confirmation mechanisms. The indicator's strength lies in combining traditional pattern recognition with modern technical analysis filters, creating a robust framework for identifying high-probability reversal opportunities.
Success with this tool requires understanding each component's role in signal generation and adapting parameters to match current market conditions and personal trading style. The community-driven development ensures practical relevance and ongoing refinement based on real trading experiences.
Practice with demo accounts to develop familiarity with signal timing and optimal parameter settings before live implementation. The indicator's systematic approach provides clear entry signals while maintaining flexibility for different risk management and position sizing strategies.
Silver BulletSilver Bullet is a trading tool built for finding cleaner, higher-probability setups. It focuses on key windows of market movement and adds helpful tools like daily range levels and candlestick patterns.
Whether you’re trading breakouts or reversals, Silver Bullet gives you a clearer view of the market and more confidence in your setups.
⸻
🔹 Trading Setup #1: Macro Time
The Macro Time setting offers two modes: Macro Bullet and Silver Bullet. Both help traders focus on specific times when the market tends to deliver clean moves.
• Macro Bullet is based on the high and low of a full macro session. It automatically detects the session’s range and bias, then offers optimal entries for either Long or Short setups. Once the session resolves, it provides Fibonacci-based levels for entry, target, and stop loss.
• Silver Bullet is based on ICT concepts and focuses on the hourly range for London, NY AM, and NY PM sessions. It’s designed for quick time blocks and highlights key levels as the session unfolds.
To use this setup, set Macro Time to “ICT Sessions” and select your preferred mode under Bullet Mode.
⸻
🔹 Trading Setup #2: Daily Range
Enable Daily Range to draw Fibonacci levels based on either the previous day’s candle or the current day’s developing range. These levels help you identify potential support, resistance, and midpoint zones throughout the day.
With the current day’s range, levels automatically update in real time as new highs or lows form — keeping your chart aligned with evolving price action.
⸻
🔹 Trading Setup #3: Candlestick Patterns
Turn on Candlestick Patterns to automatically highlight clean reversal signals such as Hammers, Hanging Men, Shooting Stars, and Tweezers. Each pattern is detected using specific criteria and trend filters to reduce noise and improve reliability. They work especially well as confirmation signals around key levels or session zones.
Silver Bullet brings structure, clarity, and precision to your intraday trading. By combining time-based bias, price action levels, and pattern recognition, it helps you trade with purpose — not guesswork. Use one setup or combine all three for a complete view of the market, tailored to your style and session of choice.
Supertrend Long-Only Strategy for QQQThis strategy is meant to use Micro Momentum to give good Buy and Sell signals in trending markets
Smart Order Blocks [Pro Version]Here’s a **clear, detailed "How It Works" explanation** for this indicator:
---
## ✅ **Smart Order Blocks \ – How It Works**
### **Purpose**
This indicator detects **Order Blocks (OBs)** based on **pivot highs and lows**, and automatically marks **Bullish** and **Bearish OB zones** on the chart with optional extensions and alerts. It is designed to help traders identify **institutional price levels** where liquidity is often engineered for future price moves.
---
### **Customization Options**
✔ **Source** → Choose between Wicks or Bodies for OB calculation.
✔ **Pivot Settings** → Adjust sensitivity for detecting pivots.
✔ **Extend OBs** → Keep zones visible until tapped, or fix a specific width.
✔ **Show Labels** → Displays OB type and strength on chart.
✔ **Colors** → Configure Bullish, Bearish, and Invalid OB colors.
---
### **Practical Usage**
* **Entry Strategy**:
* Wait for price to **revisit a Bullish OB** in an uptrend → Long entry.
* Wait for price to **revisit a Bearish OB** in a downtrend → Short entry.
* Combine with:
* **Market Structure (HH/HL or LH/LL)**.
* **Confirmation signals** (e.g., candlestick pattern, break of structure).
* **Risk Management** → Stop loss outside OB zone.
---
### ✅ **Summary in One Sentence**
The indicator automatically identifies **institutional OB zones**, shows their strength, extends them until mitigated, and alerts you when price interacts with these key liquidity levels, helping you trade like Smart Money.
---
Long and Short Strategy with Multi Indicators [B1P5]Long and Short Strategy with RSI, ROC, MA Selection, Exit Visualization, and Strength Indicator
NQ Phantom Scalper Pro# 👻 NQ Phantom Scalper Pro
**Advanced VWAP Mean Reversion Strategy with Volume Confirmation**
## 🎯 Strategy Overview
The NQ Phantom Scalper Pro is a sophisticated mean reversion strategy designed specifically for Nasdaq 100 (NQ) futures scalping. This strategy combines Volume Weighted Average Price (VWAP) bands with intelligent volume spike detection to identify high-probability reversal opportunities during optimal market hours.
## 🔧 Key Features
### VWAP Band System
- **Dynamic VWAP Bands**: Automatically adjusting standard deviation bands based on intraday volatility
- **Multiple Band Levels**: Configurable Band #1 (entry trigger) and Band #2 (profit target reference)
- **Flexible Anchoring**: Choose from Session, Week, Month, Quarter, or Year-based VWAP calculations
### Volume Intelligence
- **Volume Spike Detection**: Only triggers entries when volume exceeds SMA by configurable multiplier
- **Relative Volume Display**: Real-time volume strength indicator in info panel
- **Optional Volume Filter**: Can be disabled for testing alternative setups
### Advanced Time Management
- **12-Hour Format**: User-friendly time inputs (9 AM - 4 PM default)
- **Lunch Filter**: Automatically avoids low-liquidity lunch period (12-2 PM)
- **Visual Time Zones**: Color-coded background for active/inactive periods
- **Market Hours Focus**: Optimized for peak NQ trading sessions
### Smart Risk Management
- **ATR-Based Stops**: Volatility-adjusted stop losses using Average True Range
- **Dual Exit Strategy**: VWAP mean reversion + fixed profit targets
- **Adjustable Risk-Reward**: Configurable target ratio to opposite VWAP band
- **Position Sizing**: Percentage-based equity allocation
### Optional Trend Filter
- **EMA Trend Alignment**: Optional trend filter to avoid counter-trend trades
- **Configurable Period**: Adjustable EMA length for trend determination
- **Toggle Functionality**: Enable/disable based on market conditions
## 📊 How It Works
### Entry Logic
**Long Entries**: Triggered when price touches lower VWAP band + volume spike during active hours
**Short Entries**: Triggered when price touches upper VWAP band + volume spike during active hours
### Exit Strategy
1. **VWAP Mean Reversion**: Early exit when price returns to VWAP center line
2. **Profit Target**: Fixed target based on percentage to opposite VWAP band
3. **Stop Loss**: ATR-based protective stop
### Visual Elements
- **VWAP Center Line**: Blue line showing volume-weighted fair value
- **Green Bands**: Entry trigger levels (Band #1)
- **Red Bands**: Extended levels for target reference (Band #2)
- **Orange EMA**: Trend filter line (when enabled)
- **Background Colors**: Yellow (lunch), Gray (after hours), Clear (active trading)
- **Info Panel**: Real-time metrics display
## ⚙️ Recommended Settings
### Timeframes
- **Primary**: 1-5 minute charts for scalping
- **Validation**: Test on 15-minute for swing applications
### Market Conditions
- **Best Performance**: Ranging/choppy markets with good volume
- **Trend Markets**: Enable trend filter to avoid counter-trend trades
- **High Volatility**: Increase ATR multiplier for stops
### Session Optimization
- **Pre-Market**: Generally avoided (low volume)
- **Morning Session**: 9:30 AM - 12:00 PM (high activity)
- **Lunch Period**: 12:00 PM - 2:00 PM (filtered by default)
- **Afternoon Session**: 2:00 PM - 4:00 PM (good volume)
- **After Hours**: Generally avoided (wide spreads)
## ⚠️ Risk Disclaimer
This strategy is for educational purposes only and does not constitute financial advice. Past performance does not guarantee future results. Trading futures involves substantial risk of loss and is not suitable for all investors. Users should:
- Thoroughly backtest on historical data
- Start with small position sizes
- Understand the risks of leveraged trading
- Consider transaction costs and slippage
- Never risk more than you can afford to lose
## 📈 Performance Tips
1. **Volume Threshold**: Adjust volume multiplier based on average NQ volume patterns
2. **Band Sensitivity**: Modify band multipliers for different volatility regimes
3. **Time Filters**: Customize trading hours based on your timezone and preferences
4. **Trend Alignment**: Use trend filter during strong directional markets
5. **Risk Management**: Always maintain consistent position sizing and risk parameters
**Version**: 6.0 Compatible
**Asset**: Optimized for NASDAQ 100 Futures (NQ)
**Style**: Mean Reversion Scalping
**Frequency**: High-Frequency Trading Ready
Elliott Wave Auto Detector (Simplified)How to Use the Detector
Identify Structure: Look for sequences like 1-2-1-2...
These may show a forming or ongoing Elliott wave pattern.
Validate Trend: Multiple red 2’s at lower highs suggests a bearish trend; the reverse with blue 1’s at higher lows is bullish.
Trading Zones:
Consider buying near clusters of blue 1’s (support zones).
Consider selling or shorting near clusters of red 2’s (resistance zones).
Look for Breakouts: If price breaks out of the descending channel, trend may reverse or accelerate.
Uptrend Strength Checklist DashboardThe Uptrend Strength Checklist Dashboard is a powerful visual tool designed to help traders quickly evaluate the strength and quality of an uptrend using a combination of 20 widely-used technical conditions. It displays a clean, color-coded dashboard directly on the chart, summarizing key trend indicators in real-time.
🧠 What It Does:
This script checks 20 bullish criteria across different categories—momentum, trend alignment, volume, and price action. Each condition is scored individually and shown in a dashboard with checkmarks ✅ (condition met) or ❌ (condition not met).
The total score out of 20 is then used to interpret the trend strength into 4 levels:
🔥 Very Strong Uptrend (18–20 points)
👍 Strong Uptrend (14–17 points)
🤔 Possible Uptrend Forming (8–13 points)
📉 Weak or No Uptrend (0–7 points)
📋 Checklist Criteria Includes:
Price above short/medium/long EMAs (7, 20, 50, 200)
EMAs stacked in bullish order
MACD Line & Histogram
RSI > 50 and ROC > 0
ADX > 25 and +DI > -DI
OBV trend and Bullish Volume Dominance
Price above Ichimoku Cloud, Tenkan > Kijun
Parabolic SAR bullish signal
Williams Alligator confirmation
Price > Bollinger Band Midline
Price > Previous Week’s High
🌐 Multilingual Support:
Supports both English and Arabic (العربية) language options, with all labels, tooltips, and trend messages dynamically translated based on user selection.
🎨 Customization Options:
Choose table position and size on chart
Customize all trend and table colors
Adjust all indicator input lengths to suit your strategy
✅ Perfect For:
Trend-following traders
Swing and position traders
Technical analysts looking for a structured signal confirmation tool
🔔 Note: This indicator does not generate buy/sell signals on its own but provides a visual checklist to help confirm the strength of an uptrend. Use it in conjunction with your entry/exit strategy and risk management rules.
✅ VMA Avg ATR + Days to Targets 🎯1) The trend filter: LazyBear VMA
You implement the well‑known “LazyBear” Variable Moving Average (VMA) from price directional movement (pdm/mdm).
Internally you:
Smooth positive/negative one‑bar moves (pdmS, mdmS),
Turn them into relative strengths (pdiS, mdiS),
Measure their difference/total (iS), and
Normalize that over a rolling window to get a scaling factor vI.
The VMA itself is then an adaptive EMA:
vma := (1 - k*vI) * vma + (k*vI) * close, where k = 1/vmaLen.
When vI is larger, VMA hugs price more; when smaller, it smooths more.
Coloring:
Green when vma > vma (rising),
Red when vma < vma (falling),
White when flat.
Candles are recolored to match.
Why this matters: The VMA color is your trend regime; everything else in the script keys off changes in this color.
2) What counts as a “valid” new trend?
A new trend is valid only when the previous bar was white and the current bar turns green or red:
validTrendStart := vmaColor != color.white and vmaColor == color.white.
When that happens, you start a trend segment:
Save entry price (startPrice = close) and baseline ATR (startATR = ATR(atrLen)).
Reset “extreme” trackers: extremeHigh = high, extremeLow = low.
Timestamp the start (trendStartTime = time).
Effect: You only study / trade transitions out of a flat VMA into a slope. This helps avoid chop and reduces false starts.
3) While the trend is active
On each new bar without a color change:
If green trend: update extremeHigh = max(extremeHigh, high).
If red trend: update extremeLow = min(extremeLow, low).
This tracks the best excursion from the entry during that single trend leg.
4) When the VMA color changes (trend ends)
When vmaColor flips (green→red or red→green), you close the prior segment only if it was a valid trend (started after white). Then you:
Compute how far price traveled in ATR units from the start:
Uptrend ended: (extremeHigh - startPrice) / startATR
Downtrend ended: (startPrice - extremeLow) / startATR
Add that result to a running sum and count for the direction:
totalUp / countUp, totalDown / countDown.
Target checks for the ended trend (no look‑ahead):
T1 uses the previous average ATR move before the just‑ended trend (prevAvgUp/prevAvgDown).
Up: t1Up = startPrice + prevAvgUp * startATR
Down: t1Down = startPrice - prevAvgDown * startATR
T2 is a fixed 6× ATR move from the start (up or down).
You increment hit counters and also accumulate time‑to‑hit (ms from trendStartTime) for any target that got reached during that ended leg.
If T1 wasn’t reached, it counts as a miss.
Immediately initialize the next potential trend segment with the current bar’s startPrice/startATR/extremes and set validTrendStart according to the “white → color” rule.
Important detail: Using prevAvgUp/Down to evaluate T1 for the just‑completed trend avoids look‑ahead bias. The current trend’s performance isn’t used to set its own T1.
5) Running statistics & targets (for the current live trend)
After closing/adding to totals:
avgUp = totalUp / countUp and avgDown = totalDown / countDown are the historical average ATR move per valid trend for each direction.
Current plotted targets (only visible while a valid trend is active and in that direction):
T1 Up: startPrice + avgUp * startATR
T2 Up: startPrice + 6 * startATR
T1 Down: startPrice - avgDown * startATR
T2 Down: startPrice - 6 * startATR
The entry line is also plotted at startPrice when a valid trend is live.
If there’s no history yet (e.g., first trend), avgUp/avgDown are na, so T1 is na until at least one valid trend has closed. T2 still shows (6× ATR).
6) Win rate & time metrics
Win % (per direction):
winUp = hitUpT1 / (hitUpT1 + missUp) and similarly for down.
(This is strictly based on T1 hits vs misses; T2 hits don’t affect Win% directly.)
Average days to hit T1/T2:
The script stores milliseconds from trend start to each target hit, then reports the average in days separately for Up/Down and for T1/T2.
7) The dashboard table (bottom‑right)
It shows, side‑by‑side for Up/Down:
Avg ATR: historical average ATR move per completed valid trend.
🎯 Target 1 / Target 2: the current trend’s price levels (T1 = avgATR×ATR; T2 = 6×ATR).
✅ Win %: T1 hit rate so far.
⏱ Days to T1/T2: average days (from valid trend start) for the targets that were reached.
8) Alerts
“New Trend Detected” when a valid trend starts (white → green/red).
Target hits for the active trend:
Uptrend: separate alerts for T1 and T2 (high >= target).
Downtrend: separate alerts for T1 and T2 (low <= target).
9) Inputs & defaults
vmaLen = 17: governs how adaptive/smooth the VMA is (larger = smoother, fewer trend flips).
atrLen = 14: ATR baseline for sizing targets and normalizing moves.
10) Practical read of the plots
When you see white → green: that bar is your valid entry (trend start).
An Entry Line appears at the start price.
Target lines appear only for the active direction. T1 scales with your historical average ATR move; T2 is a fixed stretch (6× ATR).
The table updates as more trends complete, refining:
The average ATR reach (which resets your T1 sizing),
The win rate to T1, and
The average days it typically takes to hit T1/T2.
Subtle points / edge cases
No look‑ahead: T1 for a finished trend is checked against the prior average (not including the trend itself).
First trends: Until at least one valid trend completes, T1 is na (no history). T2 still shows.
Only “valid” trends are counted: Segments must start after a white bar; flips that happen color→color without a white in between don’t start a new valid trend.
Time math: Uses bar timestamps in ms, converted to days; results reflect the chart’s timeframe/market session.
TL;DR
The VMA color defines the regime; entries only trigger when a flat (white) VMA turns green/red.
Each trend’s max excursion from entry is recorded in ATR units.
T1 for current trends = (historical average ATR move) × current ATR from entry; T2 = 6× ATR.
The table shows your evolving edge (avg ATR reach, T1 win%, and days to targets), and alerts fire on new trends and target hits.
If you want, I can add optional features like: per‑ticker persistence of stats, excluding very short trends, or making T2 a user input instead of a fixed 6× ATR.
Casper SMC 5min ORB - Roboquant AI🚀 Key Features:
Opening Range (09:30–09:35 EST) breakout detection
Configurable entry type: Instant or Retracement
Adjustable Risk:Reward multiplier and contract sizing
Optional Trailing Stop Loss using ATR
Second-Chance trades if the first breakout fails
Visual markers for entries, SL/TP, trade status, and breakout validation
Day filter: Trade only on selected weekdays
Session management with configurable close time
Breakout validation using:
Wick percentage filters
Distance filters based on OR range size
🧠 AI-Style Logic Enhancements:
Smart filters for avoiding overextended or noisy breakouts
Full support for lookahead-safe logic via barstate.isconfirmed
Clean box-style trade visualization (entry, SL, TP zones)
Custom alerts for long and short entries
⚙️ Recommended Settings:
Use on 5-minute chart
Best for US indices/ Futures
📌 Note:
This script is for educational purposes only.
Performance preview on Tradingview is not accurate
Yoou need to adjust the settings and run a 1 year report
Always backtest thoroughly and consult your financial advisor before live trading.
MJBFX VWAP WITH SIGNALSThe MJBFX VWAP Channel is a custom-built volume-weighted average price indicator designed around the MJBFX trading methodology.
This tool tracks multiple rolling VWAPs anchored to a user-defined timeframe (default: 1H), then calculates percentile levels (Max, Upper, Median, Lower, Min) to create a dynamic channel. These levels act as key support and resistance zones that adapt to market conditions.
🔶 Features:
Adjustable anchor period and VWAP count (up to 500 VWAPs)
Percentile-based VWAP levels (Max, Upper, Median, Lower, Min)
Customisable colours, widths, and line styles
Optional gradient channel fills
Anchor period highlights for session awareness
MJBFX Branded Signals:
🟠 Buy – Triggered when price crosses above the lower VWAP (MJBFX Orange)
⚪ Sell – Triggered when price crosses below the upper VWAP (MJBFX Grey)
Built-in alert conditions for automated trade notifications
🔶 How to Use:
The VWAP channel provides a dynamic structure for intraday trading.
Buy opportunities often occur when price sweeps below the lower band and reclaims it.
Sell opportunities often occur when price sweeps above the upper band and rejects.
Use in confluence with market structure, session timing, and your trading plan (e.g., MJB-FX Asian Sweep strategy).
Opening-Range BreakoutNote: Default trading date range looks mediocre. Set date range to "Entire History" to see full effect of the strategy. 50.91% profitable trades, 1.178 profit factor, steady profits and limited drawdown. Total P&L: $154,141.18, Max Drawdown: $18,624.36. High R^2
█ Overview
The Opening-Range Breakout strategy is a mechanical, session‑based day‑trading system designed to capture the initial burst of directional momentum immediately following the market open. It defines a user‑configurable “opening range” window, measures its high and low boundaries, then places breakout stop orders at those levels once the range closes. Built‑in filters on minimum range width, reward‑to‑risk ratios, and optional reversal logic help refine entries and manage risk dynamically.
█ How It Works
Opening‑Range Formation
Between 9:30–10:15 AM ET (configurable), the script tracks the highest high and lowest low to form the day’s opening range box.
On the first bar after the range window closes, the range high (OR_high) and low (OR_low) are “locked in.”
Range‑Width Filter
To avoid false breakouts in low‑volatility mornings, the range must be at least X% of the current price (default 0.35%).
If the measured opening-range width < minimum threshold, no orders are placed that day.
Entry & Order Placement
Long: a stop‑buy order at the opening‑range high.
Short: a stop‑sell order at the opening‑range low.
Only one side can trigger (or both if reverse logic is enabled after a losing trade).
Risk Management
Once triggered, each trade uses an ATR‑style stop-loss defined as a percentage retracement of the range (default 50% of range width).
Profit target is set at a configurable Reward/Risk Ratio (default 1.1×).
Optional: Reverse on Stop‑Loss – if the initial breakout loses, immediately reverse into the opposite side on the same day.
Session Exit
Any open positions are closed at the end of the regular trading day (default 3:45 PM ET window end, with hard flat at session close).
Visual cues are provided via green (range high) and red (range low) step‑line plots directly on the chart, allowing you to see the range box and breakout triggers in real time.
█ Why It Works
Early Momentum Capture: The first 15 – 60 minutes of trading encapsulate overnight news digestion and institutional order flow, creating a well‑defined volatility “range.”
Mechanical Discipline: Clear, rule‑based entries and exits remove emotional guesswork, ensuring consistency.
Volatility Filtering: By requiring a minimum range width, the system avoids choppy, low‑range days where false breakouts are common.
Dynamic Sizing: Stops and targets scale with the opening range, adapting automatically to each day’s volatility environment.
█ How to Use
Set Your Instruments & Timeframe
-Apply to any futures contract on a 1‑ to 5‑minute chart.
-Ensure chart timezone is set to America/New_York.
Configure Inputs
-Opening‑Range Window: e.g. “0930-1015” for a 45‑minute range.
-Min. OR Width (%): e.g. 0.35 for 0.35% of current price.
-Reward/Risk Ratio: e.g. 1.1 for a modest profit target above your stop.
-Max OR Retracement %: e.g. 50 to set stop at 50% of range width.
-One Trade Per Day: toggle to limit to a single breakout.
-Reverse on Stop Loss: toggle to flip direction after a losing breakout.
Monitor the Chart
-Watch the green and red range boundaries form during the session open.
-Orders will automatically submit on the first bar after the range window closes, conditioned on your filters.
Review & Adjust
-Backtest across multiple months to validate performance on your preferred contract.
-Tweak range duration, minimum width, and R/R multiple to fit your risk tolerance and desired win‑rate vs. expectancy balance.
█ Settings Reference
Input Defaults
Opening‑Range Window - Time window to form OR (HHMM-HHMM) - 0930–1015
Regular Trading Day - Full session for EOD flat (HHMM-HHMM) - 0930–1545
Min. OR Width (%) - Minimum OR size as % of close to trigger orders - 0.35
Reward/Risk Ratio - Profit target multiple of stop‑loss distance - 1.1
Max OR Retracement (%) - % of OR width to use as stop‑loss distance - 50
One Trade Per Day - Limit to a single breakout order per day - false
Reverse on Stop Loss - Reverse direction immediately after a losing trade - true
Disclaimer
This strategy description and any accompanying code are provided for educational purposes only and do not constitute financial advice or a solicitation to trade. Futures trading involves substantial risk, including possible loss of capital. Past performance is not indicative of future results. Traders should assess their own risk tolerance and conduct thorough backtesting and forward-testing before committing real capital.
