HUNT_line [Dr.Forexy]HUNT_line Indicator
📊 **Category:** Price Action & Market Structure
⏰ **Recommended Timeframe:** 5-minute and higher
🎯 **Purpose:** Advanced market structure visualization for professional traders
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⚡ **Key Features:**
• Break of Structure (BOS) and Change of Character (CHOCH) detection
• Internal & Swing Market Structure analysis
• Order Blocks identification with smart filtering
• Fair Value Gaps (FVG) visualization
• Premium/Discount Zones
• Multi-timeframe support
• Real-time structure alerts
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🛠 **How to Use:**
1. Apply on 5M or higher timeframes for best results
2. Monitor BOS/CHOCH for trend direction changes
3. Use Order Blocks as potential support/resistance areas
4. Watch for FVG fills as price inefficiency zones
5. Combine multiple confluences for higher probability setups
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⚠️ **Risk Disclaimer:**
This indicator is for educational purposes only.
Not financial advice. Always conduct your own research.
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🔹 **Credits:**
Inspired by LuxAlgo's "Smart Money Concepts" with custom improvements
Cerca negli script per "gaps"
Predicted Funding RatesOverview
The Predicted Funding Rates indicator calculates real-time funding rate estimates for perpetual futures contracts on Binance. It uses triangular weighting algorithms on multiple different timeframes to ensure an accurate prediction.
Funding rates are periodic payments between long and short position holders in perpetual futures markets
If positive, longs pay shorts (usually bullish)
If negative, shorts pay longs (usually bearish)
This is a prediction. Actual funding rates depend on the instantaneous premium index, derived from bid/ask impacts of futures. So whilst it may imitate it similarly, it won't be completely accurate.
This only applies currently to Binance funding rates, as HyperLiquid premium data isn't available. Other Exchanges may be added if their premium data is uploaded.
Methods
Method 1: Collects premium 1-minunute data using triangular weighing over 8 hours. This granular method fills in predicted funding for 4h and less recent data
Method 2: Multi-time frame approach. Daily uses 1 hour data in the calculation, 4h + timeframes use 15M data. This dynamic method fills in higher timeframes and parts where there's unavailable premium data on the 1min.
How it works
1) Premium data is collected across multiple timeframes (depending on the timeframe)
2) Triangular weighing is applied to emphasize recent data points linearly
Tri_Weighing = (data *1 + data *2 + data *3 + data *4) / (1+2+3+4)
3) Finally, the funding rate is calculated
FundingRate = Premium + clamp(interest rate - Premium, -0.05, 0.05)
where the interest rate is 0.01% as per Binance
Triangular weighting is calculated on collected premium data, where recent data receives progressively higher weight (1, 2, 3, 4...). This linear weighting scheme provides responsiveness to recent market conditions while maintaining stability, similar to an exponential moving average but with predictable, linear characteristics
A visual representation:
Data points: ──────────────>
Weights: 1 2 3 4 5
Importance: ▂ ▃ ▅ ▆ █
How to use it
For futures traders:
If funding is trending up, the market can be interpreted as being in a bull market
If trending down, the market can be interpreted as being in a bear market
Even used simply, it allows you to gauge roughly how well the market is performing per funding. It can basically be gauged as a sentiment indicator too
For funding rate traders:
If funding is up, it can indicate a long on implied APR values
If funding is down, it can indicate a short on implied APR values
It also includes an underlying APR, which is the annualized funding rate. For Binance, it is current funding * (24/8) * 365
For Position Traders: Monitor predicted funding rates before entering large positions. Extremely high positive rates (>0.05% for 8-hour periods) suggest overleveraged longs and potential reversal risk. Conversely, extreme negative rates indicate shorts dominance
Table:
Funding rate: Gives the predicted funding rate as a percentage
Current premium: Displays the current premium (difference between perpetual futures price and the underlying spot) as a percentage
Funding period: You can choose between 1 hour funding (HyperLiquid usually) and 8 hour funding (Binance)
APR: Underlying annualized funding rate
What makes it original
Whilst some predicted funding scripts exist, some aren't as accurate or have gaps in data. And seeing as funding values are generally missing from TV tickers, this gives traders accessibility to the script when they would have to use other platforms
Notes
Currently only compatible with symbols that have Binance USDT premium indices
Optimal accuracy is found on timeframes that are 4H or less. On higher timeframes, the accuracy drops off
Actual funding rates may differ
Inputs
Funding Period: Choose between "8 Hour" (standard Binance cycle) or "1 Hour" (divides the 8-hour rate by 8 for granular comparison)
Plot Type: Display as "Funding Rate" (percentage per interval) or "APR" (annualized rate calculated as 8-hour rate × 3 × 365)
Table: Toggle the information table showing current funding rate, premium, funding period, and APR in the top-right corner
Positive Colour: Sets the colour for positive funding rates where longs pay shorts (default: #00ffbb turquoise)
Negative Colour: Sets the colour for negative funding rates where shorts pay longs (default: red)
Table Background: Controls the background colour and transparency of the information table (default: transparent dark blue)
Table Text Colour: Sets the colour for all text labels in the information table (default: white)
Table Text Size: Controls font size with options from Tiny to Huge, with Small as the default balance of readability and space
Dynamic Volume Trace Profile [ChartPrime]⯁ OVERVIEW
Dynamic Volume Trace Profile is a reimagined take on volume profile analysis. Instead of plotting a static horizontal histogram on the side of your chart, this indicator projects dynamic volume trace lines directly onto the price action. Each bin is color-graded according to its relative strength, creating a living “volume skeleton” of the market. The orange trace highlights the current Point of Control (POC)—the price level with maximum historical traded volume within the lookback window. On the right side, the tool builds a mini profile, showing absolute volume per bin alongside its percentage share, where the POC always represents 100% strength .
⯁ KEY FEATURES
Dynamic On-Chart Bins:
The range between highest high and lowest low is split into 25 bins. Each bin is drawn as a horizontal trace line across the lookback chart period.
Gradient Color Encoding:
Trace lines fade from transparent to teal depending on relative volume size. The more intense the teal, the stronger the historical traded activity at that level.
Automatic POC Highlight:
The bin with the highest aggregated volume is flagged with an orange line . This POC adapts bar-by-bar as volume distribution shifts.
Right-Side Volume Profile:
At the chart’s right edge, the script prints a box-style profile. Each bin shows:
• Total volume (absolute units).
• Percentage of max volume, in parentheses (POC bin = 100%).
This gives both raw and normalized context at a glance.
Adjustable Lookback Window:
The lookback defines how many bars feed the profile. Increase for stable HTF zones or decrease for responsive intraday distributions.
POC Toggle & Styling:
Optionally toggle POC highlighting on/off, adjust colors, and set line thickness for better integration with your chart theme.
⯁ HOW IT WORKS (UNDER THE HOOD)
Step Sizing:
over last 100 bars is divided by to calculate bin height.
Volume Aggregation:
For each bar in the , the script checks which bin the close falls into, then adds that bar’s volume to the bin’s counter.
Gradient Mapping:
Bin volume is normalized against the max volume across all bins. That value is mapped onto a gradient from transparent → teal.
POC Logic:
The bin with highest volume is colored orange both on the dynamic trace and in the right-side profile.
Right-Hand Profile:
Boxes are drawn for each bin proportional to volume / maxVolume × 50 units, with text labels showing both absolute volume and normalized %.
⯁ USAGE
Use the orange trace as the dominant “magnet” level—price often gravitates to the POC.
Watch for clusters of strong teal traces as areas of high acceptance; thin or faint zones mark low-liquidity gaps prone to fast moves.
On intraday charts, tighten lookback to reveal session-based distributions . For swing or position trading, expand lookback to surface more durable volume shelves.
Compare the right-side profile % to judge how “top-heavy” or “bottom-heavy” the current distribution is.
Use bright, intense color traces as context for confluence with structure, OBs, or liquidity hunts.
⯁ CONCLUSION
Dynamic Volume Trace Profile takes the traditional volume profile and fuses it into the body of price itself. Instead of a fixed sidebar, you see gradient traces layered directly on the chart, giving real-time context of where volume concentrated and where price may be drawn. With built-in POC highlighting, normalized % readouts, and an adaptive right-side profile, it offers both precision levels and market structure awareness in a cleaner, more intuitive form.
Volume Profile 3D (Zeiierman)█ Overview
Volume Profile 3D (Zeiierman) is a next-generation volume profile that renders market participation as a 3D-style profile directly on your chart. Instead of flat histograms, you get a depth-aware profile with parallax, gradient transparency, and bull/bear separation, so you can see where liquidity stacked up and how it shifted during the move.
Highlights:
3D visual effect with perspective and depth shading for clarity.
Bull/Bear separation to see whether up bars or down bars created the volume.
Flexible colors and gradients that highlight where the most significant trading activity took place.
This is a state-of-the-art volume profile — visually powerful, highly flexible, and unlike anything else available.
█ How It Works
⚪ Profile Construction
The price range (from highest to lowest) is divided into a number of levels (buckets). Each bar’s volume is added to the correct level, based on its average price. This builds a map of where trading volume was concentrated.
You can choose to:
Aggregate all volume at each level, or
Split bullish vs. bearish volume , slightly offset for clarity.
This creates a clear view of which price zones matter most to the market.
⚪ 3D Effect Creation
The unique part of this indicator is how the 3D projection is built. Each volume block’s width is scaled to its relative size, then tilted with a slope factor to create a depth effect.
maxVol = bins.bu.max() + bins.be.max()
width = math.max(1, math.floor(bucketVol / maxVol * ((bar_index - start) * mult)))
slope = -(step * dev) / ((bar_index - start) * (mult/2))
factor = math.pow(math.min(1.0, math.abs(slope) / step), .5)
width → determines how far the volume extends, based on relative strength.
slope → creates the angled projection for the 3D look.
factor → adjusts perspective to make deeper areas shrink naturally.
The result is a 3D-style volume profile where large areas pop forward and smaller areas fade back, giving you immediate visual context.
█ How to Use
⚪ Support & Resistance Zones (HVNs and Value Area)
Regions where a lot of volume traded tend to act like walls:
If price approaches a high-volume area from above, it may act as support.
From below, it may act as resistance.
Traders often enter or exit near these zones because they represent strong agreement among market participants.
⚪ POC Rejections & Mean Reversions
The Point of Control (POC) is the single price level with the highest volume in the profile.
When price returns to the POC and rejects it, that’s often a signal for reversal trades.
In ranging markets, price may bounce between edges of the Value Area and revert to POC.
⚪ Breakouts via Low-Volume Zones (LVNs)
Low volume areas (gaps in the profile) offer path of least resistance:
Price often moves quickly through these thin zones when momentum builds.
Use them to spot breakouts or continuation trades.
⚪ Directional Insight
Use the bull/bear separation to see whether buyers or sellers dominated at key levels.
█ Settings
Use Active Chart – Profile updates with visible candles.
Custom Period – Fixed number of bars.
Up/Down – Adjust tilt for the 3D angle.
Left/Right – Scale width of the profile.
Aggregated – Merge bull/bear volume.
Bull/Bear Shift – Separate bullish and bearish volume.
Buckets – Number of price levels.
Choose from templates or set custom colors.
POC Gradient option makes high volume bolder, low volume lighter.
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
RXTrend█ OVERVIEW
The "RXTrend" indicator is a technical analysis tool based on a unique approach to trend identification using RSI values from overbought and oversold zones. Designed for traders seeking a precise tool to identify key market levels and trend direction, the indicator offers flexible settings, dynamic trend lines, candlestick coloring, and buy/sell signals, supported by alerts for key events.
█ CONCEPTS
"RXTrend" leverages the Relative Strength Index (RSI) to identify overbought and oversold zones, which are often significant areas on the chart due to potentially higher volume, increased volatility, or acting as pivot points. To address this, I created an indicator that uses RSI values from these zones, mapping them to price levels to determine the trend. Additionally, for a clearer market picture, boxes are added to highlight overbought and oversold zones on the chart, and candlestick coloring is based on the direction of the RSI moving average. This provides further confirmation of the trend direction and identifies potential correction or reversal points. The indicator is universal and works across all markets (stocks, forex, cryptocurrencies) and timeframes.
█ FEATURES
- RSI Calculation: Calculates RSI based on the closing price over a specified period, with a default length of 14.
- Trend Line: A smoothed trend line based on mapping RSI values from overbought (for downtrends) or oversold (for uptrends) zones to price levels. RSI values are transformed into prices using the price range from a selected period (default: 50 bars) and then smoothed to form the trend line. The line changes color based on the trend direction (blue for uptrend, orange for downtrend).
- Candlestick Coloring: Option to color candles based on the direction of the RSI moving average (RSI MA). Candle colors align with the trend and box colors (blue for uptrend, orange for downtrend, gray for neutral).
- Overbought and Oversold Zones: Identifies overbought (RSI > OB) and oversold (RSI < OS) levels, drawing dynamic boxes on the price chart to reflect these zones. Boxes update in real-time, adjusting to new highs and lows.
- Buy and Sell Signals: Generates buy signals (blue "Buy" labels) when the price crosses above the smoothed oversold line and sell signals (orange "Sell" labels) when the price crosses below the smoothed overbought line.
- Shadow Fill: Option to fill the space between the trend line and price (HL2) with adjustable transparency, aiding visual trend assessment.
Alerts: Built-in alerts for:
- Buy and sell signals.
- Appearance of new overbought/oversold boxes.
- RSI MA direction change (candle color change to uptrend or downtrend).
Customization: Allows adjustment of RSI length, overbought/oversold levels, smoothing period, colors, box and label transparency, and the option to keep boxes after RSI returns to normal.
█ HOW TO USE
Add to Chart: Apply the indicator to your TradingView chart via the Pine Editor or Indicators menu.
Configure Settings:
RSI Settings:
- RSI Length: Sets the RSI calculation period (default: 14).
- Overbought Level (OB): Sets the overbought threshold (default: 70).
- Oversold Level (OS): Sets the oversold threshold (default: 30).
Price Settings:
- Price Range Lookback: Defines the period for calculating the price range (default: 50).
Candle Coloring:
- Color Candles: Enables/disables candle coloring based on RSI MA direction.
- RSI MA Length: Sets the RSI moving average period (default: 21).
Smoothing Settings:
- Smoothing Length: Degree of trend line smoothing (default: 5).
Colors:
- Trend Colors: Customize colors for uptrend (default: blue), downtrend (default: orange), and shadow fill.
Box Settings:
- Box Transparency: Adjusts box transparency (0-100).
- Box Colors: Sets colors for overbought (orange) and oversold (blue) zones.
- Keep Boxes: Determines if boxes remain after RSI returns to normal.
Signals:
- Show Buy/Sell Signals: Enables/disables signal label display.
- Label Transparency: Adjusts signal label transparency.
Interpreting Signals:
- Trend Line: Shows market direction (blue for uptrend, orange for downtrend).
- Buy Signals: Blue "Buy" label appears when the price crosses above the smoothed oversold line, signaling a potential uptrend.
- Sell Signals: Orange "Sell" label appears when the price crosses below the smoothed overbought line, signaling a potential downtrend.
- Overbought/Oversold Boxes: Orange boxes indicate overbought zones (RSI > OB), blue boxes indicate oversold zones (RSI < OS). Boxes expand dynamically in real-time.
- Candlestick Coloring: Candle colors align with the trend and box colors, reflecting RSI MA direction.
- Alerts: Set up alerts in TradingView for buy/sell signals, new overbought/oversold boxes, or RSI MA direction changes.
- Combining with Other Tools: Use the indicator alongside support/resistance levels, Fair Value Gaps (FVG), or other indicators to confirm signals.
█ APPLICATIONS
The "RXTrend" indicator is designed to identify key market zones and trend direction, making it useful for trend-following and reversal strategies. It enables:
- Trend Confirmation: Candlestick coloring and the trend line help assess the dominant market direction, supporting entry or exit decisions. The trend line can act as a significant support/resistance level, and a price bounce from it may provide a good entry point, especially when confirmed by Fibonacci levels. Additionally, the appearance of overbought/oversold boxes combined with a change in candle color (RSI MA direction) may indicate an impending correction. This allows analysis of potential market overextension and correction endings, enabling multiple entries within a trend.
- Overbought and Oversold Zone Identification: Boxes highlight potential reversal or correction points, especially when combined with support/resistance levels or FVG.
- Signal-Based Strategies: Buy and sell signals can be used as entry points in a trend or as warnings of potential reversals.
█ NOTES
- The indicator is universal and works across all markets and timeframes due to its RSI-based and price-mapping logic.
- Adjust settings (e.g., RSI length, OB/OS levels, smoothing) to suit your trading style and timeframe.
- Use in conjunction with other technical analysis tools to enhance signal accuracy.
MAMA [DCAUT]█ MAMA (MESA Adaptive Moving Average)
📊 OVERVIEW
The MESA Adaptive Moving Average (MAMA) represents an advanced implementation of John F. Ehlers' adaptive moving average system using the Hilbert Transform Discriminator. This indicator automatically adjusts to market cycles, providing superior responsiveness compared to traditional fixed-period moving averages while maintaining smoothness.
MAMA dynamically calculates two lines: the fast-adapting MAMA line and the following FAMA (Following Adaptive Moving Average) line. The system's core strength lies in its ability to automatically detect and adapt to the dominant market cycle, reducing lag during trending periods while providing stability during consolidation phases.
🎯 CORE CONCEPTS
Signal Interpretation:
• MAMA above FAMA: Indicates bullish trend momentum with the fast line leading upward movement
• MAMA below FAMA: Suggests bearish trend momentum with the fast line leading downward movement
• Golden Cross: MAMA crossing above FAMA signals potential upward momentum shift
• Death Cross: MAMA crossing below FAMA indicates potential downward momentum shift
• Line Convergence: MAMA and FAMA approaching each other suggests trend consolidation or potential reversal
Primary Applications:
• Trend Following: Enhanced responsiveness to trend changes compared to traditional moving averages
• Crossover Signals: MAMA/FAMA crossovers for identifying potential entry and exit points
• Cycle Analysis: Automatic adaptation to market's dominant cycle characteristics
• Reduced Lag: Minimized delay in trend detection while maintaining signal smoothness
📐 MATHEMATICAL FOUNDATION
Hilbert Transform Discriminator Technology:
The MAMA system employs John F. Ehlers' Hilbert Transform Discriminator, a sophisticated signal processing technique borrowed from telecommunications engineering. The Hilbert Transform creates a complex representation of the price series by generating a 90-degree phase-shifted version of the original signal, enabling precise cycle measurement.
The discriminator analyzes the instantaneous phase relationships between the original price series and its Hilbert Transform counterpart. This mathematical relationship reveals the dominant cycle period present in the market data at each point in time, forming the foundation for adaptive smoothing.
Instantaneous Period Calculation:
The algorithm computes the instantaneous period using the arctangent of the ratio between the Hilbert Transform and the original price series. This calculation produces a real-time measurement of the market's dominant cycle, typically ranging from short-term noise cycles to longer-term trend cycles.
The instantaneous period measurement undergoes additional smoothing to prevent erratic behavior from single-bar anomalies. This smoothed period value becomes the basis for calculating the adaptive alpha coefficient that controls the moving average's responsiveness.
Dynamic Alpha Coefficient System:
The adaptive alpha calculation represents the core mathematical innovation of MAMA. The alpha coefficient is derived from the instantaneous period measurement and constrained within the user-defined fast and slow limits.
The mathematical relationship converts the measured cycle period into an appropriate smoothing factor: shorter detected cycles result in higher alpha values (increased responsiveness), while longer cycles produce lower alpha values (increased stability). This creates an automatic adaptation mechanism that responds to changing market conditions.
MAMA/FAMA Calculation Process:
The MAMA line applies the dynamically calculated alpha coefficient to an exponential moving average formula: MAMA = alpha × Price + (1 - alpha) × MAMA . The FAMA line then applies a secondary smoothing operation to the MAMA line, creating a following average that provides confirmation signals.
This dual-line approach ensures that the fast-adapting MAMA line captures trend changes quickly, while the FAMA line offers a smoother confirmation signal, reducing the likelihood of acting on temporary price fluctuations.
Cycle Detection Mechanism:
The underlying cycle detection employs quadrature components derived from the Hilbert Transform to measure both amplitude and phase characteristics of price movements. This allows the system to distinguish between genuine trend changes and temporary price noise, automatically adjusting the smoothing intensity accordingly.
The mathematical framework ensures that during strong trending periods with clear directional movement, the algorithm reduces smoothing to minimize lag. Conversely, during consolidation phases with mixed signals, increased smoothing helps filter out false breakouts and whipsaws.
📋 PARAMETER CONFIGURATION
Source Selection Strategy:
• HL2 (High+Low)/2 (Default): Recommended for cycle analysis as it represents the midpoint of each period's trading range, reducing impact of opening gaps and closing spikes
• Close Price: Traditional choice reflecting final market sentiment, suitable for end-of-day analysis
• HLC3 (High+Low+Close)/3: Balanced approach incorporating range information with closing emphasis
• OHLC4 (Open+High+Low+Close)/4: Most comprehensive price representation for complete market view
Fast Limit Configuration (Default 0.5):
Controls the maximum responsiveness of the adaptive system. Higher values increase sensitivity to recent price changes but may introduce more noise. This parameter sets the upper bound for the dynamic alpha calculation.
Slow Limit Configuration (Default 0.05):
Determines the minimum responsiveness, providing stability during uncertain market conditions. Lower values increase smoothing but may cause delayed signals. This parameter sets the lower bound for the dynamic alpha calculation.
Parameter Relationship Considerations:
The fast and slow limits work together to define the adaptive range. The wider the range between these limits, the more dramatic the adaptation between trending and consolidating market conditions. Different market characteristics may benefit from different parameter configurations, requiring individual testing and validation.
📊 COLOR CODING SYSTEM
Line Visualization:
• Green Line (MAMA): The fast-adapting moving average that responds quickly to price changes
• Red Line (FAMA): The following adaptive moving average that provides confirmation signals
The fixed color scheme provides consistent visual identification of each line, enabling clear differentiation between the fast-adapting MAMA and the following FAMA throughout all market conditions.
💡 CORE VALUE PROPOSITION
Advantages Over Traditional Moving Averages:
• Cycle Adaptation: Automatically adjusts to market's dominant cycle rather than using fixed periods
• Reduced Lag: Faster response to genuine trend changes while filtering market noise
• Mathematical Foundation: Based on advanced signal processing techniques from telecommunications engineering
• Dual-Line System: Provides both fast adaptation (MAMA) and confirmation (FAMA) in one indicator
Comparative Performance Characteristics:
Unlike fixed-period moving averages that apply the same smoothing regardless of market conditions, MAMA adapts its behavior based on current market cycle characteristics. This may help reduce whipsaws during consolidation periods while maintaining responsiveness during trending phases.
Usage Considerations:
This indicator is designed for technical analysis purposes. The adaptive nature means that parameter optimization should consider the specific characteristics of the asset and timeframe being analyzed. Like all technical indicators, MAMA should be used as part of a comprehensive analysis approach rather than as a standalone signal generator.
Alert Functionality:
The indicator includes alert conditions for MAMA/FAMA crossovers, enabling automated notification of potential momentum shifts. These alerts can assist in timing analysis but should be combined with other forms of market analysis for decision-making purposes.
ICT SMC — OB & FVG (Enhanced v6)This indicator is a comprehensive implementation of ICT Smart Money Concepts (SMC), focusing on Order Blocks (OB) and Fair Value Gaps (FVG) with enhanced detection logic and session-based filtering.
🔍 Key Features
Impulse-Based OB Detection: Identifies bullish and bearish order blocks using configurable impulse bar logic and ATR-based movement thresholds.
Fair Value Gap Detection: Highlights FVGs based on price displacement logic, helping traders spot potential inefficiencies in price action.
Session Filtering: Allows users to filter signals based on major trading sessions (Sydney, Tokyo, London, New York).
Trend & Volume Confirmation: Integrates EMA slope, market structure breaks, and volume analysis to score trade signals.
Visual Zones: Displays OB and FVG zones using colored boxes with customizable transparency and color settings.
Signal Alerts: Generates long/short trade signals based on a scoring system and session validation, with built-in alert conditions.
⚙️ Customization
Adjustable EMA and ATR lengths
Configurable impulse bar count and movement thresholds
Toggleable session filters
Custom colors for OB and FVG zones
📈 Use Cases
This tool is ideal for traders who follow ICT concepts and want a visual, automated way to identify high-probability zones and trade setups based on smart money principles.
SCTI - D14SCTI - D14 Comprehensive Technical Analysis Suite
English Description
SCTI D14 is an advanced multi-component technical analysis indicator designed for professional traders and analysts. This comprehensive suite combines multiple analytical tools into a single, powerful indicator that provides deep market insights across various timeframes and methodologies.
Core Components:
1. EMA System (Exponential Moving Averages)
13 customizable EMA lines with periods ranging from 8 to 2584
Fibonacci-based periods (8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584)
Color-coded visualization for easy trend identification
Individual toggle controls for each EMA line
2. TFMA (Multi-Timeframe Moving Averages)
Cross-timeframe analysis with 3 independent EMA calculations
Real-time labels showing trend direction and price relationships
Customizable timeframes for each moving average
Percentage deviation display from current price
3. PMA (Precision Moving Average Cloud)
7-layer moving average system with customizable periods
Fill areas between moving averages for trend visualization
Support and resistance zone identification
Dynamic color-coded trend clouds
4. VWAP (Volume Weighted Average Price)
Multiple anchor points (Session, Week, Month, Quarter, Year, Earnings, Dividends, Splits)
Standard deviation bands for volatility analysis
Automatic session detection and anchoring
Statistical price level identification
5. Advanced Divergence Detector
12 technical indicators for divergence analysis (MACD, RSI, Stochastic, CCI, Williams %R, Bias, Momentum, OBV, VW-MACD, CMF, MFI, External)
Regular and hidden divergences detection
Bullish and bearish signals with visual confirmation
Customizable sensitivity and filtering options
Real-time alerts for divergence formations
6. Volume Profile & Node Analysis
Comprehensive volume distribution analysis
Point of Control (POC) identification
Value Area High/Low (VAH/VAL) calculations
Volume peaks and troughs detection
Support and resistance levels based on volume
7. Smart Money Concepts
Market structure analysis with Break of Structure (BOS) and Change of Character (CHoCH)
Internal and swing structure detection
Equal highs and lows identification
Fair Value Gaps (FVG) detection and visualization
Liquidity zones and institutional flow analysis
8. Trading Sessions
9 major trading sessions (Asia, Sydney, Tokyo, Shanghai, Hong Kong, Europe, London, New York, NYSE)
Real-time session status and countdown timers
Session volume and performance tracking
Customizable session boxes and labels
Statistical session analysis table
Key Features:
Modular Design: Enable/disable any component independently
Real-time Analysis: Live updates with market data
Multi-timeframe Support: Works across all chart timeframes
Customizable Alerts: Set alerts for any detected pattern or signal
Professional Visualization: Clean, organized display with customizable colors
Performance Optimized: Efficient code for smooth chart performance
Use Cases:
Trend Analysis: Identify market direction using multiple EMA systems
Entry/Exit Points: Use divergences and structure breaks for timing
Risk Management: Utilize volume profiles and session analysis for better positioning
Multi-timeframe Analysis: Confirm signals across different timeframes
Institutional Analysis: Track smart money flows and market structure
Perfect For:
Day traders seeking comprehensive market analysis
Swing traders needing multi-timeframe confirmation
Professional analysts requiring detailed market structure insights
Algorithmic traders looking for systematic signal generation
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中文描述
SCTI - D14是一个先进的多组件技术分析指标，专为专业交易者和分析师设计。这个综合套件将多种分析工具整合到一个强大的指标中，在各种时间框架和方法论中提供深度市场洞察。
核心组件：
1. EMA系统（指数移动平均线）
13条可定制EMA线，周期从8到2584
基于斐波那契的周期（8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584）
颜色编码可视化，便于趋势识别
每条EMA线的独立切换控制
2. TFMA（多时间框架移动平均线）
跨时间框架分析，包含3个独立的EMA计算
实时标签显示趋势方向和价格关系
每个移动平均线的可定制时间框架
显示与当前价格的百分比偏差
3. PMA（精密移动平均云）
7层移动平均系统，周期可定制
移动平均线间填充区域用于趋势可视化
支撑阻力区域识别
动态颜色编码趋势云
4. VWAP（成交量加权平均价格）
多个锚点（交易时段、周、月、季、年、财报、分红、拆股）
标准差带用于波动性分析
自动时段检测和锚定
统计价格水平识别
5. 高级背离检测器
12个技术指标用于背离分析（MACD、RSI、随机指标、CCI、威廉姆斯%R、Bias、动量、OBV、VW-MACD、CMF、MFI、外部指标）
常规和隐藏背离检测
看涨看跌信号配视觉确认
可定制敏感度和过滤选项
背离形成的实时警报
6. 成交量分布与节点分析
全面的成交量分布分析
控制点（POC）识别
价值区域高/低点（VAH/VAL）计算
成交量峰值和低谷检测
基于成交量的支撑阻力水平
7. 聪明钱概念
市场结构分析，包括结构突破（BOS）和结构转变（CHoCH）
内部和摆动结构检测
等高等低识别
公允价值缺口（FVG）检测和可视化
流动性区域和机构资金流分析
8. 交易时区
9个主要交易时段（亚洲、悉尼、东京、上海、香港、欧洲、伦敦、纽约、纽交所）
实时时段状态和倒计时器
时段成交量和表现跟踪
可定制时段框和标签
统计时段分析表格
主要特性：
模块化设计：可独立启用/禁用任何组件
实时分析：随市场数据实时更新
多时间框架支持：适用于所有图表时间框架
可定制警报：为任何检测到的模式或信号设置警报
专业可视化：清洁、有序的显示界面，颜色可定制
性能优化：高效代码确保图表流畅运行
使用场景：
趋势分析：使用多重EMA系统识别市场方向
入场/出场点：利用背离和结构突破进行时机选择
风险管理：利用成交量分布和时段分析进行更好定位
多时间框架分析：在不同时间框架间确认信号
机构分析：跟踪聪明钱流向和市场结构
适用于：
寻求全面市场分析的日内交易者
需要多时间框架确认的摆动交易者
需要详细市场结构洞察的专业分析师
寻求系统化信号生成的算法交易者
FVG Diamond📊 Overview
FVG Diamond is an advanced indicator that detects three specific price action patterns: Inside Bar, Outside Bar, and Diamond Formation. Unlike basic FVG tools, it focuses on these higher-level setups for more precise analysis.
✨ Key Features
🎯 Detection of 3 Advanced FVG Pattern Types
Independent on/off toggle for each pattern
Inside FVG (Inside Bar / Harami): The body of the 3rd candle forms an inside bar relative to the 2nd candle
Outside FVG (Outside Bar / Engulfing): The body of the 1st candle forms an outside bar relative to the 2nd candle
Diamond FVG (Diamond Formation): A unique pattern that satisfies both Inside and Outside conditions
🎯 Mitigation Feature
ON: FVG boxes are automatically removed once price fully fills the FVG zone (keeps the chart clean by showing only active FVGs)
OFF: FVG boxes remain on the chart indefinitely (allows full historical review of all FVGs)
🎨 Visual Features
Color Coding: Assign unique colors to each pattern type
Transparency Control: Default 70% transparency for optimal readability
Extension Display: Extend the right edge of FVG boxes for any number of bars
⚙️ Advanced Configuration
Threshold Settings
Manual Threshold: Define a minimum gap size by percentage
Auto Threshold: Dynamically adjusts based on market volatility
Mitigation Tools
Real-Time Mitigation: Automatic removal when price fills an FVG zone
Mitigation Levels: Display filled FVG levels with dashed lines
🔔 Alerts
Notification on new Bullish/Bearish FVG detection
Notification when an FVG is mitigated (filled)
Works with all FVG types
📈 How to Use
Add the indicator to your chart
The three advanced FVG patterns will be detected and displayed automatically
Set your preferred threshold (0% = detect all gaps)
⚠️ Note: This indicator is designed as an analysis support tool. Trading decisions should be made in combination with other methods of technical and fundamental analysis.
Author: omochi_
Version: 1.0
Last Updated: September 28, 2025
ATR Regime Study [CHE] ATR Regime Study — ATR percentile regimes with clear bands, table and live label
Summary
This study classifies volatility into five regimes by converting ATR into a percentile rank over a rolling window, plotted on a standardized scale between zero and one hundred. Colored bands mark regime thresholds, while a compact table and an optional label report the current percentile and regime. The standardized scale makes symbols and timeframes easier to compare than raw ATR values. Implemented in Pine v6 as a separate pane (overlay set to false), it is a context tool to adapt tactics and risk handling to the prevailing volatility environment.
Motivation: Why this design?
Raw ATR varies with price scale and asset characteristics, which makes regime comparison inconsistent and leads to poor transfer of settings across symbols and timeframes. The core idea is to transform ATR into a percentile rank within a user-defined lookback, then map it into discrete regimes. This yields a stable, interpretable context signal that shifts slower than raw ATR while still responding to genuine volatility changes.
What’s different vs. standard approaches?
Reference baseline: Traditional ATR plots or ATR bands using fixed multipliers.
Architecture differences:
Percentile ranking of ATR within a rolling window.
Five discrete regimes with fixed thresholds at ninety, seventy, thirty, and ten.
Visual fills between thresholds plus a live table and a last-bar label.
Practical effect: You read a single normalized line between zero and one hundred with consistent thresholds. This improves cross-asset comparison and makes regime shifts obvious at a glance.
How it works (technical)
The script computes ATR over a configurable length, then converts that series to a percentile rank over a configurable number of bars. The percentile is naturally scaled and limited between zero and one hundred. That value is mapped to one of five regimes: above ninety (Extreme), between seventy and ninety (Elevated), between thirty and seventy (Normal), between ten and thirty (Calm), and below ten (Squeeze). Horizontal guide lines mark the thresholds, and fills shade the regions. A table is created once and updated on each bar to show regime definitions and highlight the current row. An optional label on the last bar displays the current percentile and regime. No higher-timeframe requests are used, so repaint risk is limited to normal live-bar fluctuation until the bar closes.
Parameter Guide
ATR length — Effect: Controls how fast ATR reacts to new ranges. Default: fourteen. Trade-offs/Tips: Increase to reduce noise in choppy markets; decrease to react faster during regime changes.
Percentile window (bars) — Effect: Number of bars used for the percentile ranking. Default: two hundred fifty-two. Trade-offs/Tips: Larger windows stabilize the percentile but slow adaptation after structural regime shifts; smaller windows adapt faster but may flip more often.
Table › Show — Effect: Toggles the regime overview table. Default: enabled. Trade-offs/Tips: Disable on constrained layouts to reduce visual clutter.
Table › Position — Effect: Anchors the table in a chart corner. Default: Top Right. Trade-offs/Tips: Choose a corner that avoids overlapping other panels or drawings.
Label › Show — Effect: Toggles a last-bar label with current percentile and regime. Default: enabled. Trade-offs/Tips: Useful for quick reads; disable if it obscures other annotations.
Reading & Interpretation
The white line shows ATR percentile between zero and one hundred. Crossing above seventy signals an elevated volatility environment; above ninety indicates event-driven extremes. Between thirty and seventy represents typical conditions. Between ten and thirty indicates calm conditions that often suit mean reversion. Below ten reflects compression, where breakout probability often increases. The colored bands visually reinforce these ranges. The table summarizes regime definitions and highlights the current state. The last-bar label mirrors the current percentile and regime for quick inspection.
Practical Workflows & Combinations
Trend following: Prefer continuation tactics when the percentile holds in the Normal or Elevated bands and structure confirms higher highs and higher lows. Consider wider stops and partial position sizing as percentile rises.
Mean reversion: Favor fades in Calm regimes within defined ranges; use structure filters and time-of-day constraints to avoid low-liquidity whipsaws.
Breakout preparation: Track compressions below ten; plan entries only with structure confirmation and risk caps, since compressions can persist.
Multi-asset/Multi-TF: Defaults travel well on daily charts. For intraday, reduce the percentile window to align with session dynamics. Combine with trend or market structure tools for confirmation.
Behavior, Constraints & Performance
Repaint/confirmation: The percentile updates during live bars and stabilizes on close; closed bars do not repaint.
security/HTF: Not used. If you add higher-timeframe aggregation externally, account for standard repaint caveats.
Resources: Declared maximum bars back is two thousand; limits for lines and labels are five hundred each. A short loop updates the table rows; arrays are used for table content only.
Known limits: Regime boundaries are fixed; assets with persistent volatility shifts may require window retuning. Low-liquidity periods and gaps can produce abrupt percentile changes. ATR is direction-agnostic and should be paired with trend or structure context.
Sensible Defaults & Quick Tuning
Start with ATR length fourteen and percentile window two hundred fifty-two on daily charts.
Too many flips: Increase ATR length or increase the percentile window.
Too sluggish: Decrease the percentile window or reduce ATR length.
Intraday noise: Keep ATR length moderate and reduce the window to a session-appropriate size; optionally hide the label to declutter.
Compressed markets: Maintain defaults but rely more on structure and volume filters before acting.
What this indicator is—and isn’t
This is a volatility regime context layer that standardizes ATR into interpretable regimes. It is not a complete trading system, not predictive, and not a stand-alone entry signal. Use it alongside structure analysis, confirmation tools, and disciplined risk management.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Best regards and happy trading
Chervolino
ICT 369 Sniper MSS Indicator (HTF Bias) - H2LThis script is an ICT (Inner Circle Trader) concept-based trading indicator designed to identify high-probability reversal or continuation setups, primarily focusing on intraday trading using a Higher Timeframe (HTF) directional bias.
Here are the four core components of the indicator:
Higher Timeframe (HTF) Bias Filter (Market Structure Shift - MSS): It determines the overall trend by checking if the current price has broken the most recent high or low swing point of a larger timeframe (e.g., 4H). This establishes a Bullish or Bearish bias, ensuring trades align with the dominant trend.
Fair Value Gap (FVG) and OTE: It identifies price imbalances (FVGs) and calculates the Optimal Trade Entry (OTE) levels (50%, 62%, 70.5%, etc.) within those gaps, looking for price to retrace into these specific areas.
Kill Zones (Timing): It incorporates specific time windows (London and New York Kill Zones, based on NY Time) where institutional trading activity is high, only allowing entry signals during these defined periods.
Signal and Targets: It triggers a Long or Short signal when all criteria are met (HTF Bias, FVG, OTE retracement, and Kill Zone timing). It then calculates and plots suggested trade levels, including a Stop Loss (SL) and three Take Profit targets (TP1, TP2, and a dynamic Runner Target based on the weekly Average True Range or ATR).
In summary, it's a comprehensive tool for traders following ICT principles, automating the confluence check across trend, structure, liquidity, and timing.
Mystic Pulse V2.0 [CHE] Mystic Pulse V2.0 — Adaptive DI streaks with gradient intensity for clearer trend persistence
Summary
Mystic Pulse V2.0 measures directional persistence by counting how often the positive or negative directional index strengthens and dominates. These counts drive gradient colors for bars, wicks, and helper plots, so intensity reflects local momentum rather than absolute values. A windowed normalization and gamma control adapt the visuals to recent conditions, preventing one regime from overpowering the next. The result is an immediate, at-a-glance read of trend direction and stamina without relying on crossovers alone.
Motivation: Why this design?
Classical DI and ADX signals can flip during choppy phases or feel sluggish in calm regimes. This script focuses on persistence: it increments a positive or negative streak only when the corresponding directional pressure both strengthens compared with the prior bar and dominates the other side. Simple OHLC pre-smoothing reduces micro-noise, and local normalization keeps the scale relevant to the last segment of data, not a distant past.
What’s different vs. standard approaches?
Reference baseline: Traditional DI and ADX lines with crossovers and fixed-scale thresholds.
Architecture differences:
Wilder-style recursive smoothing on true range and directional movement.
Streak counters for positive and negative pressure that advance only on strengthening and dominance.
Windowed normalization and gamma shaping for visual intensity.
Wick coloring via `plotcandle` with forced overlay from a pane indicator.
Practical effect: Bars and wicks grow more vivid during sustained pressure and fade during indecision. The column plots show streak depth directly, which helps filter one-bar flips.
How it works (technical)
1. Pre-smoothing: Open, high, low, and close are averaged over a short simple moving window to dampen micro-ticks.
2. Directional inputs: True range and directional movement are formed from the smoothed prices, then recursively smoothed using a Wilder-style update that carries prior state forward.
3. DI comparison: The script derives positive and negative directional ratios relative to smoothed range. A side advances its streak when it increases compared with the previous bar and exceeds the opposite side. The other streak resets.
4. Trend score and color base: The difference between positive and negative streaks defines the active side.
5. Normalization and gamma: The absolute streak magnitude and each side’s streak are normalized within a rolling window. Gamma parameters reshape intensity so mid-range values are either compressed or emphasized.
6. Rendering:
Two column plots show positive and negative streak counts in the pane with gradient colors.
A square marker at the bottom uses the global gradient as a compact heat cue.
Bar colors on the main chart use either the gradient, neutral trend colors, or no paint depending on toggles.
Wick, border, and candle overlays are colored via `plotcandle` with forced overlay.
7. State handling: Smoothed values and counters persist across bars; initialization uses first available values without lookahead. No higher-timeframe requests are used, so repaint risk is limited to normal live-bar evolution.
Parameter Guide
Show neutral candles (fallback) — Paints main-chart bars in plain up or down colors when gradients are disabled — Default false — Use when you prefer simple up/down coloring.
Show last N shapes — Limits bottom square markers — Default 333 — Reduce if your chart gets cluttered.
ADX smoothing length — Controls the Wilder smoothing window for range and directional movement — Default 9 — Larger values increase stability but respond later.
OHLC SMA length — Pre-smoothing for inputs — Default 1 — Increase slightly on noisy assets to reduce flip risk.
Gradient barcolor — Enables gradient bar paint on the main chart — Default true — Turn off to use wicks only or neutral bars.
Wick coloring — Colors wicks, borders, and bodies via overlay — Default true — Disable if it conflicts with other overlays.
Gradient window — Lookback for local normalization — Default 100 — Shorter windows adapt faster; longer windows provide steadier intensity.
Gradient transparency — Overall transparency for gradient paints — Default 0 — Increase to make gradients subtler.
Gamma bars/shapes — Contrast for bar and shape intensity — Default 0.70 — Lower values brighten mid-tones; higher values compress them.
Gamma plots — Contrast for the column plots — Default 0.80 — Tune separately from bar intensity.
Wick transparency — Transparency for wick coloring — Default 0 — Raise to let price action show through.
Up/Down colors (dark and neon) — Base and accent colors for both directions — Defaults as provided — Adjust to match your chart theme.
Reading & Interpretation
Pane columns: The green column represents the positive streak count; the red column represents the negative streak count. Taller columns signal stronger persistence.
Gradient marker: The bottom square indicates the active side and persistence strength at a glance.
Main-chart bars and wicks: Color direction shows the dominant side; intensity reflects the normalized and gamma-shaped streak magnitude. Faded tones suggest weak or fading pressure.
Practical Workflows & Combinations
Trend following: Enter in the direction of the active side when the corresponding column expands over several bars. Confirm with structure such as higher highs and higher lows or lower highs and lower lows.
Exits and stops: Consider scaling out when intensity fades toward mid-range while structure stalls. Tighten stops after extended streaks or when wicks lose intensity.
Multi-asset/Multi-TF: Use defaults for liquid assets on intraday to swing timeframes. For highly volatile instruments, raise smoothing and the normalization window. For calm markets, lower them to regain sensitivity.
Behavior, Constraints & Performance
Repaint/confirmation: Values update during the live bar and stabilize after bar close. No historical repaint beyond normal live-bar updates.
security()/HTF: Not used; cross-timeframe repaint paths do not apply.
Resources: Declared `max_bars_back` two thousand; no explicit loops or arrays; plot and label limits are generous.
Known limits: Streak counters can remain elevated during slow reversals. Very short normalization windows can cause rapid intensity swings. Gaps or extreme spikes may temporarily distort intensity until the window adapts.
Sensible Defaults & Quick Tuning
Start with: ADX smoothing nine, OHLC SMA one, normalization window one hundred, gradient and wick coloring enabled, gamma around zero point seven to zero point eight.
Too many flips: Increase ADX smoothing and the normalization window; consider a small bump in OHLC SMA.
Too sluggish: Decrease ADX smoothing and the normalization window.
Colors overpower chart: Increase gradient and wick transparency or raise gamma to compress mid-tones.
What this indicator is—and isn’t
This is a visualization and signal layer that represents directional persistence and intensity. It does not issue trade entries or exits on its own and is not predictive. Use it alongside market structure, volume, and risk controls.
Disclaimer
The content, including any code, is for educational and informational purposes only and does not constitute financial advice or a recommendation to buy or sell any instrument. Trading involves substantial risk, including the possible loss of principal. Past performance is not indicative of future results. Always do your own research and consider consulting a qualified professional.
Adaptive Heikin Ashi [CHE]Adaptive Heikin Ashi — volatility-aware HA with fewer fake flips
Summary
Adaptive Heikin Ashi is a volatility-aware reinterpretation of classic Heikin Ashi that continuously adjusts its internal smoothing based on the current ATR regime, which means that in quiet markets the indicator reacts more quickly to genuine directional changes, while in turbulent phases it deliberately increases its smoothing to suppress jitter and color whipsaws, thereby reducing “noise” and cutting down on fake flips without resorting to heavy fixed smoothing that would lag everywhere.
Motivation: why adapt at all?
Classic Heikin Ashi replaces raw OHLC candles with a smoothed construction that averages price and blends each new candle with the previous HA state, which typically cleans up trends and improves visual coherence, yet its fixed smoothing amount treats calm and violent markets the same, leading to the usual dilemma where a setting that looks crisp in a narrow range becomes too nervous in a spike, and a setting that tames high volatility feels unnecessarily sluggish as soon as conditions normalize; by allowing the smoothing weight to expand and contract with volatility, Adaptive HA aims to keep candles readable across shifting regimes without constant manual retuning.
What is different from normal Heikin Ashi?
Fixed vs. adaptive blend:
Classic HA implicitly uses a fixed 50/50 blend for the open update (`HA_open_t = 0.5 HA_open_{t-1} + 0.5 HA_close_{t-1}`), while this script replaces the constant 0.5 with a dynamic weight `w_t` that oscillates around 0.5 as a function of observed volatility, which turns the open update into an EMA-like filter whose “alpha” automatically changes with market conditions.
Volatility as the steering signal:
The script measures volatility via ATR and compares it to a rolling baseline (SMA of ATR over the same length), producing a normalized deviation that is scaled by sensitivity, clamped to ±1 for stability, and then mapped to a bounded weight interval ` `, so the adaptation is strong enough to matter but never runs away.
Outcome that matters to traders:
In high volatility, the weight shifts upward toward the prior HA open, which strengthens smoothing exactly where classic HA tends to “chatter,” while in low volatility the weight shifts downward toward the most recent HA close, which speeds up reaction so quiet trends do not feel artificially delayed; this is the practical mechanism by which noise and fake signals are reduced without accepting blanket lag.
How it works
1. HA close matches classic HA:
`HA_close_t = (Open_t + High_t + Low_t + Close_t) / 4`
2. Volatility normalization:
`ATR_t` is computed over `atr_length`, its baseline is `ATR_SMA_t = SMA(ATR, atr_length)`, and the raw deviation is `(ATR_t / ATR_SMA_t − 1)`, which is then scaled by `adapt_sensitivity` and clamped to ` ` to obtain `v_t`, ensuring that pathological spikes cannot destabilize the weighting.
3. Adaptive weight around 0.5:
`w_t = 0.5 + oscillation_range v_t`, giving `w_t ∈ `, so with a default `range = 0.20` the weight stays between 0.30 and 0.70, which is wide enough to matter but narrow enough to preserve HA identity.
4. EMA-like open update:
On the very first bar the open is seeded from a stable combination of the raw open and close, and thereafter the update is
`HA_open_t = w_t HA_open_{t−1} + (1 − w_t) HA_close_{t−1}`,
which is equivalent to an EMA where higher `w_t` means heavier inertia (more smoothing) and lower `w_t` means stronger pull to the latest price information (more responsiveness).
5. High and low follow classic HA composition:
`HA_high_t = max(High_t, max(HA_open_t, HA_close_t))`,
`HA_low_t = min(Low_t, min(HA_open_t, HA_close_t))`,
thereby keeping visual semantics consistent with standard HA so that your existing reading of bodies, wicks, and transitions still applies.
Why this reduces noise and fake signals in practice
Fake flips in HA typically occur when a fixed blending rule is forced to process candles during a volatility surge, producing rapid alternations around pivots or within wide intrabar ranges; by increasing smoothing exactly when ATR jumps relative to its baseline, the adaptive open stabilizes the candle body progression and suppresses transient color changes, while in the opposite scenario of compressed ranges, the reduced smoothing allows small but persistent directional pressure to reflect in candle color earlier, which reduces the tendency to enter late after multiple slow transitions.
Parameter guide (what each input really does)
ATR Length (default 14): controls both the ATR and its baseline window, where longer values dampen the adaptation by making the baseline slower and the deviation smaller, which is helpful for noisy lower timeframes, while shorter values make the regime detector more reactive.
Oscillation Range (default 0.20): sets the maximum distance from 0.5 that the weight may travel, so increasing it towards 0.25–0.30 yields stronger smoothing in turbulence and faster response in calm periods, whereas decreasing it to 0.10–0.15 keeps the behavior closer to classical HA and is useful if your strategy already includes heavy downstream smoothing.
Adapt Sensitivity (default 6.0): multiplies the normalized ATR deviation before clamping, such that higher sensitivity accelerates adaptation to regime shifts, while lower sensitivity produces gradual transitions; negative values intentionally invert the mapping (higher vol → less smoothing) and are generally not recommended unless you are testing a counter-intuitive hypothesis.
Reading the candles and the optional diagnostic
You interpret colors and bodies just like with normal HA, but you can additionally enable the Adaptive Weight diagnostic plot to see the regime in real time, where values drifting up toward the upper bound indicate a turbulent context that is being deliberately smoothed, and values gliding down toward the lower bound indicate a calm environment in which the indicator chooses to move faster, which can be valuable for discretionary confirmation when deciding whether a fresh color shift is likely to stick.
Practical workflows and combinations
Trend-following entries: use color continuity and body expansion as usual, but expect fewer spurious alternations around news spikes or into liquidity gaps; pairing with structure (swing highs/lows, breaks of internal ranges) keeps entries disciplined.
Exit management: when the diagnostic weight remains elevated for an extended period, you can be stricter with exit triggers because flips are less likely to be accidental noise; conversely, when the weight is depressed, consider earlier partials since the indicator is intentionally more nimble.
Multi-asset, multi-TF: the adaptation is especially helpful if you rotate instruments with very different vol profiles or hop across timeframes, since you will not need to retune a fixed smoothing parameter every time conditions change.
Behavior, constraints, and performance
The script does not repaint historical bars and uses only past information on closed candles, yet just like any candle-based visualization the current live bar will update until it closes, so you should avoid acting on mid-bar flips without a rule that accounts for bar close; there are no `security()` calls or higher-timeframe lookups, which keeps performance light and execution deterministic, and the clamping of the volatility signal ensures numerical stability even during extreme ATR spikes.
Sensible defaults and quick tuning
Start with the defaults (`ATR 14`, `Range 0.20`, `Sensitivity 6.0`) and observe the weight plot across a few volatile events; if you still see too many flips in turbulence, either raise `Range` to 0.25 or trim `Sensitivity` to 4–5 so that the weight can move high but does not overreact, and if the indicator feels too slow in quiet markets, lower `Range` toward 0.15 or raise `Sensitivity` to 7–8 to bias the weight a bit more aggressively downward when conditions compress.
What this indicator is—and is not
Adaptive Heikin Ashi is a context-aware visualization layer that improves the signal-to-noise ratio and reduces fake flips by modulating smoothing with volatility, but it is not a complete trading system, it does not predict the future, and it should be combined with structure, risk controls, and position management that fit your market and timeframe; always forward-test on your instruments, and remember that even adaptive smoothing can delay recognition at sharp turning points when volatility remains elevated.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Best regards and happy trading
Chervolino
BOCS AdaptiveBOCS Adaptive Strategy - Automated Volatility Breakout System
WHAT THIS STRATEGY DOES:
This is an automated trading strategy that detects consolidation patterns through volatility analysis and executes trades when price breaks out of these channels. Take-profit and stop-loss levels are calculated dynamically using Average True Range (ATR) to adapt to current market volatility. The strategy closes positions partially at the first profit target and exits the remainder at the second target or stop loss.
TECHNICAL METHODOLOGY:
Price Normalization Process:
The strategy begins by normalizing price to create a consistent measurement scale. It calculates the highest high and lowest low over a user-defined lookback period (default 100 bars). The current close price is then normalized using the formula: (close - lowest_low) / (highest_high - lowest_low). This produces values between 0 and 1, allowing volatility analysis to work consistently across different instruments and price levels.
Volatility Detection:
A 14-period standard deviation is applied to the normalized price series. Standard deviation measures how much prices deviate from their average - higher values indicate volatility expansion, lower values indicate consolidation. The strategy uses ta.highestbars() and ta.lowestbars() functions to track when volatility reaches peaks and troughs over the detection length period (default 14 bars).
Channel Formation Logic:
When volatility crosses from a high level to a low level, this signals the beginning of a consolidation phase. The strategy records this moment using ta.crossover(upper, lower) and begins tracking the highest and lowest prices during the consolidation. These become the channel boundaries. The duration between the crossover and current bar must exceed 10 bars minimum to avoid false channels from brief volatility spikes. Channels are drawn using box objects with the recorded high/low boundaries.
Breakout Signal Generation:
Two detection modes are available:
Strong Closes Mode (default): Breakout occurs when the candle body midpoint math.avg(close, open) exceeds the channel boundary. This filters out wick-only breaks.
Any Touch Mode: Breakout occurs when the close price exceeds the boundary.
When price closes above the upper channel boundary, a bullish breakout signal generates. When price closes below the lower boundary, a bearish breakout signal generates. The channel is then removed from the chart.
ATR-Based Risk Management:
The strategy uses request.security() to fetch ATR values from a specified timeframe, which can differ from the chart timeframe. For example, on a 5-minute chart, you can use 1-minute ATR for more responsive calculations. The ATR is calculated using ta.atr(length) with a user-defined period (default 14).
Exit levels are calculated at the moment of breakout:
Long Entry Price = Upper channel boundary
Long TP1 = Entry + (ATR × TP1 Multiplier)
Long TP2 = Entry + (ATR × TP2 Multiplier)
Long SL = Entry - (ATR × SL Multiplier)
For short trades, the calculation inverts:
Short Entry Price = Lower channel boundary
Short TP1 = Entry - (ATR × TP1 Multiplier)
Short TP2 = Entry - (ATR × TP2 Multiplier)
Short SL = Entry + (ATR × SL Multiplier)
Trade Execution Logic:
When a breakout occurs, the strategy checks if trading hours filter is satisfied (if enabled) and if position size equals zero (no existing position). If volume confirmation is enabled, it also verifies that current volume exceeds 1.2 times the 20-period simple moving average.
If all conditions are met:
strategy.entry() opens a position using the user-defined number of contracts
strategy.exit() immediately places a stop loss order
The code monitors price against TP1 and TP2 levels on each bar
When price reaches TP1, strategy.close() closes the specified number of contracts (e.g., if you enter with 3 contracts and set TP1 close to 1, it closes 1 contract). When price reaches TP2, it closes all remaining contracts. If stop loss is hit first, the entire position exits via the strategy.exit() order.
Volume Analysis System:
The strategy uses ta.requestUpAndDownVolume(timeframe) to fetch up volume, down volume, and volume delta from a specified timeframe. Three display modes are available:
Volume Mode: Shows total volume as bars scaled relative to the 20-period average
Comparison Mode: Shows up volume and down volume as separate bars above/below the channel midline
Delta Mode: Shows net volume delta (up volume - down volume) as bars, positive values above midline, negative below
The volume confirmation logic compares breakout bar volume to the 20-period SMA. If volume ÷ average > 1.2, the breakout is classified as "confirmed." When volume confirmation is enabled in settings, only confirmed breakouts generate trades.
INPUT PARAMETERS:
Strategy Settings:
Number of Contracts: Fixed quantity to trade per signal (1-1000)
Require Volume Confirmation: Toggle to only trade signals with volume >120% of average
TP1 Close Contracts: Exact number of contracts to close at first target (1-1000)
Use Trading Hours Filter: Toggle to restrict trading to specified session
Trading Hours: Session input in HHMM-HHMM format (e.g., "0930-1600")
Main Settings:
Normalization Length: Lookback bars for high/low calculation (1-500, default 100)
Box Detection Length: Period for volatility peak/trough detection (1-100, default 14)
Strong Closes Only: Toggle between body midpoint vs close price for breakout detection
Nested Channels: Allow multiple overlapping channels vs single channel at a time
ATR TP/SL Settings:
ATR Timeframe: Source timeframe for ATR calculation (1, 5, 15, 60, etc.)
ATR Length: Smoothing period for ATR (1-100, default 14)
Take Profit 1 Multiplier: Distance from entry as multiple of ATR (0.1-10.0, default 2.0)
Take Profit 2 Multiplier: Distance from entry as multiple of ATR (0.1-10.0, default 3.0)
Stop Loss Multiplier: Distance from entry as multiple of ATR (0.1-10.0, default 1.0)
Enable Take Profit 2: Toggle second profit target on/off
VISUAL INDICATORS:
Channel boxes with semi-transparent fill showing consolidation zones
Green/red colored zones at channel boundaries indicating breakout areas
Volume bars displayed within channels using selected mode
TP/SL lines with labels showing both price level and distance in points
Entry signals marked with up/down triangles at breakout price
Strategy status table showing position, contracts, P&L, ATR values, and volume confirmation status
HOW TO USE:
For 2-Minute Scalping:
Set ATR Timeframe to "1" (1-minute), ATR Length to 12, TP1 Multiplier to 2.0, TP2 Multiplier to 3.0, SL Multiplier to 1.5. Enable volume confirmation and strong closes only. Use trading hours filter to avoid low-volume periods.
For 5-15 Minute Day Trading:
Set ATR Timeframe to match chart or use 5-minute, ATR Length to 14, TP1 Multiplier to 2.0, TP2 Multiplier to 3.5, SL Multiplier to 1.2. Volume confirmation recommended but optional.
For Hourly+ Swing Trading:
Set ATR Timeframe to 15-30 minute, ATR Length to 14-21, TP1 Multiplier to 2.5, TP2 Multiplier to 4.0, SL Multiplier to 1.5. Volume confirmation optional, nested channels can be enabled for multiple setups.
BACKTEST CONSIDERATIONS:
Strategy performs best during trending or volatility expansion phases
Consolidation-heavy or choppy markets produce more false signals
Shorter timeframes require wider stop loss multipliers due to noise
Commission and slippage significantly impact performance on sub-5-minute charts
Volume confirmation generally improves win rate but reduces trade frequency
ATR multipliers should be optimized for specific instrument characteristics
COMPATIBLE MARKETS:
Works on any instrument with price and volume data including forex pairs, stock indices, individual stocks, cryptocurrency, commodities, and futures contracts. Requires TradingView data feed that includes volume for volume confirmation features to function.
KNOWN LIMITATIONS:
Stop losses execute via strategy.exit() and may not fill at exact levels during gaps or extreme volatility
request.security() on lower timeframes requires higher-tier TradingView subscription
False breakouts inherent to breakout strategies cannot be completely eliminated
Performance varies significantly based on market regime (trending vs ranging)
Partial closing logic requires sufficient position size relative to TP1 close contracts setting
RISK DISCLOSURE:
Trading involves substantial risk of loss. Past performance of this or any strategy does not guarantee future results. This strategy is provided for educational purposes and automated backtesting. Thoroughly test on historical data and paper trade before risking real capital. Market conditions change and strategies that worked historically may fail in the future. Use appropriate position sizing and never risk more than you can afford to lose. Consider consulting a licensed financial advisor before making trading decisions.
ACKNOWLEDGMENT & CREDITS:
This strategy is built upon the channel detection methodology created by AlgoAlpha in the "Smart Money Breakout Channels" indicator. Full credit and appreciation to AlgoAlpha for pioneering the normalized volatility approach to identifying consolidation patterns and sharing this innovative technique with the TradingView community. The enhancements added to the original concept include automated trade execution, multi-timeframe ATR-based risk management, partial position closing by contract count, volume confirmation filtering, and real-time position monitoring.
X VIBVolume Imbalance Zones
X VIB highlights price-levels where buying or selling pressure overwhelmed the opposing side within a single bar transition, leaving a void that the market often revisits. The script paints those voids as boxes so you can quickly see where liquidity may rest, where price may pause or react, and which imbalances persist across sessions.
What it plots
For each completed calculation bar (your chart’s timeframe or a higher timeframe you choose), the indicator draws a box that spans the prior bar’s close to the current bar’s open—only when that bar-to-bar transition exhibits a valid volume imbalance (VIB) by the selected rules. Boxes are time-anchored from the previous bar’s time to the current bar’s time close, and they are capped to a configurable count so the chart remains readable.
Two ways to define “Volume Imbalance”
X VIB calculates imbalances in two complementary ways. Both techniques isolate bar-to-bar displacement that reflects one-sided pressure, but they differ in strictness and how much confirmation they require.
Continuity VIB (Bar-to-Bar Displacement)
A strict definition that requires aligned progress and overlap between consecutive bars. In practical terms, a bullish continuity VIB demands that the new bar advances beyond the prior bar’s close, opens above it, and maintains upward progress without erasing the displacement; the bearish case mirrors this to the downside.
Use when: you want the cleanest, most structurally reliable voids that reflect decisive initiative flow.
Effect on boxes: typically fewer, higher-quality zones that mark locations of strong one-sided intent.
Gap-Qualified VIB (Displacement with Gap Confirmation)
A confirmatory definition that treats the bar-to-bar displacement as an imbalance only if the transition also observes a protective “gap-like” relationship with surrounding prices. This extra condition filters out many borderline transitions and emphasizes voids that were less likely to be traded through on their formation.
Use when: you want additional confirmation that the void had genuine follow-through pressure at birth.
Effect on boxes: often slightly fewer but “stickier” zones that can attract price on retests.
Both modes are drawn identically on the chart (as boxes spanning the displacement). Their difference is purely in the qualification of what counts as a VIB. You can display either set independently or together to compare how each mode surfaces structure.
Multi-Timeframe (MTF) logic
You can compute imbalances on a higher timeframe (e.g., 15-minute) while viewing a lower timeframe chart. When MTF is active, X VIB:
Samples open, high, low, close, time, and time_close from the selected HTF in a single, synchronized request (no gaps, no lookahead).
Only evaluates and draws boxes once per HTF bar close, ensuring clean, stable zones that don’t repaint intra-bar.
How traders use these zones
Reversion into voids: Price often returns to “fill” part of a void before deciding on continuation or reversal.
Context for entries/exits: VIB boxes provide precise, mechanically derived levels for limit entries, scale-outs, and invalidation points.
Confluence: Combine with session opens, HTF levels, or volatility bands to grade setups. Continuity VIBs can mark impulse anchors; Gap-Qualified VIBs often mark stickier pockets.
Inputs & controls
Calculate on higher timeframe? Toggle MTF computation; choose your Calc timeframe (e.g., 15).
Show VIBs: Master toggle for drawing imbalance boxes.
Color & Opacity: Pick the box fill and border intensity that suits your theme.
# Instances: Cap how many historical boxes remain on the chart to avoid clutter.
Notes & best practices
Signal density: Continuity VIBs tend to be more frequent on fast charts; Gap-Qualified VIBs are more selective. Try both and keep what aligns with your trade plan.
MTF discipline: When using a higher calc timeframe, analyze reactions primarily at that timeframe’s pace to avoid over-fitting to noise.
Lifecycle awareness: Not all voids fill. Track which boxes persist; durable voids often define the map of the session.
Foresight Cone (HoltxF1xVWAP) [KedArc Quant]Description:
This is a time-series forecasting indicator that estimates the next bar (F1) and projects a path a few bars ahead. It also draws a confidence cone based on how accurate the recent forecasts have been. You can optionally color the projection only when price agrees with VWAP.
Why it’s different
* One clear model: Everything comes from Holt’s trend-aware forecasting method—no mix of unrelated indicators.
* Transparent visuals: You see the next-bar estimate (F1), the forward projection, and a cone that widens or narrows based on recent forecast error.
* Context, not signals: The VWAP option only changes colors. It doesn’t add trade rules.
* No look-ahead: Accuracy is measured using the forecast made on the previous bar versus the current bar.
Inputs (what they mean)
* Source: Price series to forecast (default: Close).
* Preset: Quick profiles for fast, smooth, or momentum markets (see below).
* Alpha (Level): How fast the model reacts to new prices. Higher = faster, twitchier.
* Beta (Trend): How fast the model updates the slope. Higher = faster pivots, more flips in chop.
* Horizon: How many bars ahead to project. Bigger = wider cone.
* Residual Window: How many bars to judge recent accuracy. Bigger = steadier cone.
* Confidence Z: How wide the cone should be (typical setting ≈ “95% style” width).
* Show Bands / Draw Forward Path: Turn the cone and forward lines on/off.
* Color only when aligned with VWAP: Highlights projections only when price agrees with the trend side of VWAP.
* Colors / Show Panel: Styling plus a small panel with RMSE, MAPE, and trend slope.
Presets (when to pick which)
* Scalp / Fast (1-min): Very responsive; best for quick moves. More twitch in chop.
* Smooth Intraday (1–5 min): Calmer and steadier; a good default most days.
* Momentum / Breakout: Quicker slope tracking during strong pushes; may over-react in ranges.
* Custom: Set your own values if you know exactly what you want.
What is F1 here?
F1 is the model’s next-bar fair value. Crosses of price versus F1 can hint at short-term momentum shifts or mean-reversion, especially when viewed with VWAP or the cone.
How this helps
* Gives a baseline path of where price may drift and a cone that shows normal wiggle room.
* Helps you tell routine noise (inside cone) from information (edges or breaks outside the cone).
* Keeps you aware of short-term bias via the trend slope and F1.
How to use (step by step)
1. Add to chart → choose a Preset (start with Smooth Intraday).
2. Set Horizon around 8–15 bars for intraday.
3. (Optional) Turn on VWAP alignment to color only when price agrees with the trend side of VWAP.
4. Watch where price sits relative to the cone and F1:
* Inside = normal noise.
* At edges = stretched.
* Outside = possible regime change.
5. Check the panel: if RMSE/MAPE spike, expect a wider cone; consider a smoother preset or a higher timeframe.
6. Tweak Alpha/Beta only if needed: faster for momentum, slower for chop.
7. Combine with your own plan for entries, exits, and risk.
Accuracy Panel — what it tells you
Preset & Horizon: Shows which preset you’re using and how many bars ahead the projection goes. Longer horizons mean more uncertainty.
RMSE (error in price units): A “typical miss” measured in the chart’s currency (e.g., ₹).
Lower = tighter fit and a usually narrower cone. Rising = conditions getting noisier; the cone will widen.
MAPE (error in %): The same idea as RMSE but in percent.
Good for comparing different symbols or timeframes. Sudden spikes often hint at a regime change.
Slope T: The model’s short-term trend reading.
Positive = gentle up-bias; negative = gentle down-bias; near zero = mostly flat/drifty.
How to read it at a glance
Calm & directional: RMSE/MAPE steady or falling + Slope T positive (or negative) → trends tend to respect the cone’s mid/upper (or mid/lower) area.
Choppy/uncertain: RMSE/MAPE climbing or jumping → expect more whipsaw; rely more on the cone edges and higher-TF context.
Flat tape: Slope T near zero → mean-revert behavior is common; treat cone edges as stretch zones rather than breakout zones.
Warm-up & tweaks
Warm-up: Right after adding the indicator, the panel may be blank for a short time while it gathers enough bars.
Too twitchy? Switch to Smooth Intraday or increase the Residual Window.
Too slow? Use Scalp/Fast or Momentum/Breakout to react quicker.
Timeframe tips
* 1–3 min: Scalp/Fast or Momentum/Breakout; horizon \~8–12.
* 5–15 min: Smooth Intraday; horizon \~12–15.
* 30–60 min+: Consider a larger residual window for a steadier cone.
FAQ
Q: Is this a strategy or an indicator?
A: It’s an indicator only. It does not place orders, TP/SL, or run backtests.
Q: Does it repaint?
A: The next-bar estimate (F1) and the cone are calculated using only information available at that time. The forward path is a projection drawn on the last bar and will naturally update as new bars arrive. Historical bars aren’t revised with future data.
Q: What is F1?
A: F1 is the indicator’s best guess for the next bar.
Price crossing above/below F1 can hint at short-term momentum shifts or mean-reversion.
Q: What do “Alpha” and “Beta” do?
A: Alpha controls how fast the indicator reacts to new prices
(higher = faster, twitchier). Beta controls how fast the slope updates (higher = quicker pivots, more flips in chop).
Q: Why does the cone width change?
A: It reflects recent forecast accuracy. When the market gets noisy, the cone widens. When the tape is calm, it narrows.
Q: What does the Accuracy Panel tell me?
A:
* Preset & Horizon you’re using.
* RMSE: typical forecast miss in price units.
* MAPE: typical forecast miss in percent.
* Slope T: short-term trend reading (up, down, or flat).
If RMSE/MAPE rise, expect a wider cone and more whipsaw.
Q: The panel shows “…” or looks empty. Why?
A: It needs a short warm-up to gather enough bars. This is normal after you add the indicator or change settings/timeframes.
Q: Which timeframe is best?
A:
* 1–3 min: Scalp/Fast or Momentum/Breakout, horizon \~8–12.
* 5–15 min: Smooth Intraday, horizon \~12–15.
Higher timeframes work too; consider a larger residual window for steadier cones.
Q: Which preset should I start with?
A: Start with Smooth Intraday. If the market is trending hard, try Momentum/Breakout.
For very quick tapes, use Scalp/Fast. Switch back if things get choppy.
Q: What does the VWAP option do?
A: It only changes colors (highlights when price agrees with the trend side of VWAP).
It does not add or remove signals.
Q: Are there alerts?
A: Yes—alerts for price crossing F1 (up/down). Use “Once per bar close” to reduce noise on fast charts.
Q: Can I use this on stocks, futures, crypto, or FX?
A: Yes. It works on any symbol/timeframe. You may want to adjust Horizon and the Residual Window based on volatility.
Q: Can I use it with Heikin Ashi or other non-standard bars?
A: You can, but remember you’re forecasting the synthetic series of those bars. For pure price behavior, use regular candles.
Q: The cone feels too wide/too narrow. What do I change?
A:
* Too wide: lower Alpha/Beta a bit or increase the Residual Window.
* Too narrow (misses moves): raise Alpha/Beta slightly or try Momentum/Breakout.
Q: Why do results change when I switch timeframe or symbol?
A: Different noise levels and trends. The accuracy stats reset per chart, so the cone adapts to each context.
Q: Any limits or gotchas?
A: Extremely large Horizon may hit TradingView’s line-object limits; reduce Horizon or turn
off extra visuals if needed. Big gaps or news spikes will widen errors—expect the cone to react.
Q: Can this predict exact future prices?
A: No. It provides a baseline path and context. Always combine with your own rules and risk management.
Glossary
* TS (Time Series): Data over time (prices).
* Holt’s Method: A forecasting approach that tracks a current level and a trend to predict the next bars.
* F1: The indicator’s best guess for the next bar.
* F(h): The projected value h bars ahead.
* VWAP: Volume-Weighted Average Price—used here for optional color alignment.
* RMSE: Typical forecast miss in price units (how far off, on average).
* MAPE: Typical forecast miss in percent (scale-free, easy to compare).
Notes & limitations
* The panel needs a short warm-up; stats may be blank at first.
* The cone reflects recent conditions; sudden volatility changes will widen it.
* This is a tool for context. It does not place trades and does not promise results.
⚠️ Disclaimer
This script is provided for educational purposes only.
Past performance does not guarantee future results.
Trading involves risk, and users should exercise caution and use proper risk management when applying this strategy.
Options Max Pain Calculator [BackQuant]Options Max Pain Calculator
A visualization tool that models option expiry dynamics by calculating "max pain" levels, displaying synthetic open interest curves, gamma exposure profiles, and pin-risk zones to help identify where market makers have the least payout exposure.
What is Max Pain?
Max Pain is the theoretical expiration price where the total dollar value of outstanding options would be minimized. At this price level, option holders collectively experience maximum losses while option writers (typically market makers) have minimal payout obligations. This creates a natural gravitational pull as expiration approaches.
Core Features
Visual Analysis Components:
Max Pain Line: Horizontal line showing the calculated minimum pain level
Strike Level Grid: Major support and resistance levels at key option strikes
Pin Zone: Highlighted area around max pain where price may gravitate
Pain Heatmap: Color-coded visualization showing pain distribution across prices
Gamma Exposure Profile: Bar chart displaying net gamma at each strike level
Real-time Dashboard: Summary statistics and risk metrics
Synthetic Market Modeling**
Since Pine Script cannot access live options data, the indicator creates realistic synthetic open interest distributions based on configurable market parameters including volume patterns, put/call ratios, and market maker positioning.
How It Works
Strike Generation:
The tool creates a grid of option strikes centered around the current price. You can control the range, density, and whether strikes snap to realistic market increments.
Open Interest Modeling:
Using your inputs for average volume, put/call ratios, and market maker behavior, the indicator generates synthetic open interest that mirrors real market dynamics:
Higher volume at-the-money with decay as strikes move further out
Adjustable put/call bias to reflect current market sentiment
Market maker inventory effects and typical short-gamma positioning
Weekly options boost for near-term expirations
Pain Calculation:
For each potential expiry price, the tool calculates total option payouts:
Call options contribute pain when finishing in-the-money
Put options contribute pain when finishing in-the-money
The strike with minimum total pain becomes the Max Pain level
Gamma Analysis:
Net gamma exposure is calculated at each strike using standard option pricing models, showing where hedging flows may be most intense. Positive gamma creates price support while negative gamma can amplify moves.
Key Settings
Basic Configuration:
Number of Strikes: Controls grid density (recommended: 15-25)
Days to Expiration: Time until option expiry
Strike Range: Price range around current level (recommended: 8-15%)
Strike Increment: Spacing between strikes
Market Parameters:
Average Daily Volume: Baseline for synthetic open interest
Put/Call Volume Ratio: Market sentiment bias (>1.0 = bearish, <1.0 = bullish) It does not work if set to 1.0
Implied Volatility: Current option volatility estimate
Market Maker Factors: Dealer positioning and hedging intensity
Display Options:
Model Complexity: Simple (line only), Standard (+ zones), Advanced (+ heatmap/gamma)
Visual Elements: Toggle individual components on/off
Theme: Dark/Light mode
Update Frequency: Real-time or daily calculation
Reading the Display
Dashboard Table (Top Right):
Current Price vs Max Pain Level
Distance to Pain: Percentage gap (smaller = higher pin risk)
Pin Risk Assessment: HIGH/MEDIUM/LOW based on proximity and time
Days to Expiry and Strike Count
Model complexity level
Visual Elements:
Red Line: Max Pain level where payout is minimized
Colored Zone: Pin risk area around max pain
Dotted Lines: Major strike levels (green = support, orange = resistance)
Color Bar: Pain heatmap (blue = high pain, red = low pain/max pain zones)
Horizontal Bars: Gamma exposure (green = positive, red = negative)
Yellow Dotted Line: Gamma flip level where hedging behavior changes
Trading Applications
Expiration Pinning:
When price is near max pain with limited time remaining, there's increased probability of gravitating toward that level as market makers hedge their positions.
Support and Resistance:
High open interest strikes often act as magnets, with max pain representing the strongest gravitational pull.
Volatility Expectations:
Above gamma flip: Expect dampened volatility (long gamma environment)
Below gamma flip: Expect amplified moves (short gamma environment)
Risk Assessment:
The pin risk indicator helps gauge likelihood of price manipulation near expiry, with HIGH risk suggesting potential range-bound action.
Best Practices
Setup Recommendations
Start with Model Complexity set to "Standard"
Use realistic strike ranges (8-12% for most assets)
Set put/call ratio based on current market sentiment
Adjust implied volatility to match current levels
Interpretation Guidelines:
Small distance to pain + short time = high pin probability
Large gamma bars indicate key hedging levels to monitor
Heatmap intensity shows strength of pain concentration
Multiple nearby strikes can create wider pin zones
Update Strategy:
Use "Daily" updates for cleaner visuals during trading hours
Switch to "Every Bar" for real-time analysis near expiration
Monitor changes in max pain level as new options activity emerges
Important Disclaimers
This is a modeling tool using synthetic data, not live market information. While the calculations are mathematically sound and the modeling realistic, actual market dynamics involve numerous factors not captured in any single indicator.
Max pain represents theoretical minimum payout levels and suggests where natural market forces may create gravitational pull, but it does not guarantee price movement or predict exact expiration levels. Market gaps, news events, and changing volatility can override these dynamics.
Use this tool as additional context for your analysis, not as a standalone trading signal. The synthetic nature of the data makes it most valuable for understanding market structure and potential zones of interest rather than precise price prediction.
Technical Notes
The indicator uses established option pricing principles with simplified implementations optimized for Pine Script performance. Gamma calculations use standard financial models while pain calculations follow the industry-standard definition of minimized option payouts.
All visual elements use fixed positioning to prevent movement when scrolling charts, and the tool includes performance optimizations to handle real-time calculation without timeout errors.
Price Level Highlighter [ldlwtrades]This indicator is a minimalist and highly effective tool designed for traders who incorporate institutional concepts into their analysis. It automates the identification of key psychological price levels and adds a unique, dynamic layer of information to help you focus on the most relevant area of the market. Inspired by core principles of market structure and liquidity, it serves as a powerful visual guide for anticipating potential support and resistance.
The core idea is simple: specific price points, particularly those ending in round numbers or common increments, often act as magnets or barriers for price. While many indicators simply plot static lines, this tool goes further by intelligently highlighting the single most significant level in real-time. This dynamic feature allows you to quickly pinpoint where the market is currently engaged, offering a clear reference point for your trading decisions. It reduces chart clutter and enhances your focus on the immediate price action.
Features
Customizable Price Range: Easily define a specific Start Price and End Price to focus the indicator on the most relevant area of your chart, preventing unnecessary clutter.
Adjustable Increment: Change the interval of the lines to suit your trading style, from high-frequency increments (e.g., 10 points) for scalping to wider intervals (e.g., 50 or 100 points) for swing trading.
Intelligent Highlighting: A key feature that automatically identifies and highlights the single horizontal line closest to the current market price with a distinct color and thickness. This gives you an immediate visual cue for the most relevant price level.
Highly Customizabile: Adjust the line color, style, and width for both the main lines and the highlighted line to fit your personal chart aesthetic.
Usage
Apply the indicator to your chart.
In the settings, input your desired price range (Start Price and End Price) to match the market you are trading.
Set the Price Increment to your preferred density.
Monitor the chart for the highlighted line. This is your active price level and a key area of interest.
Combine this tool with other confirmation signals (e.g., order blocks, fair value gaps, liquidity pools) to build higher-probability trade setups.
Best Practices
Pairing: This tool is effective across all markets, including stocks, forex, indices, and crypto. It is particularly useful for volatile markets where price moves rapidly between psychological levels.
Mindful Analysis: Use the highlighted level as a reference point for your analysis, not as a standalone signal. A break above or below this level can signify a shift in market control.
Backtesting: Always backtest the indicator on your preferred market and timeframe to understand how it performs under different conditions.
1H FVG Zones Only (5m & 1h)new uses trend anaylosis. takes 15 min chart and breaks into 1hr chart fvg gaps
Harmonic Super GuppyHarmonic Super Guppy – Harmonic & Golden Ratio Trend Analysis Framework
Overview
Harmonic Super Guppy is a comprehensive trend analysis and visualization tool that evolves the classic Guppy Multiple Moving Average (GMMA) methodology, pioneered by Daryl Guppy to visualize the interaction between short-term trader behavior and long-term investor trends. into a harmonic and phase-based market framework. By combining harmonic weighting, golden ratio phasing, and multiple moving averages, it provides traders with a deep understanding of market structure, momentum, and trend alignment. Fast and slow line groups visually differentiate short-term trader activity from longer-term investor positioning, while adaptive fills and dynamic coloring clearly illustrate trend coherence, expansion, and contraction in real time.
Traditional GMMA focuses primarily on moving average convergence and divergence. Harmonic Super Guppy extends this concept, integrating frequency-aware harmonic analysis and golden ratio modulation, allowing traders to detect subtle cyclical forces and early trend shifts before conventional moving averages would react. This is particularly valuable for traders seeking to identify early trend continuation setups, preemptive breakout entries, and potential trend exhaustion zones. The indicator provides a multi-dimensional view, making it suitable for scalping, intraday trading, swing setups, and even longer-term position strategies.
The visual structure of Harmonic Super Guppy is intentionally designed to convey trend clarity without oversimplification. Fast lines reflect short-term trader sentiment, slow lines capture longer-term investor alignment, and fills highlight compression or expansion. The adaptive color coding emphasizes trend alignment: strong green for bullish alignment, strong red for bearish, and subtle gray tones for indecision. This allows traders to quickly gauge market conditions while preserving the granularity necessary for sophisticated analysis.
How It Works
Harmonic Super Guppy uses a combination of harmonic averaging, golden ratio phasing, and adaptive weighting to generate its signals.
Harmonic Weighting : Each moving average integrates three layers of harmonics:
Primary harmonic captures the dominant cyclical structure of the market.
Secondary harmonic introduces a complementary frequency for oscillatory nuance.
Tertiary harmonic smooths higher-frequency noise while retaining meaningful trend signals.
Golden Ratio Phase : Phases of each harmonic contribution are adjusted using the golden ratio (default φ = 1.618), ensuring alignment with natural market rhythms. This reduces lag and allows traders to detect trend shifts earlier than conventional moving averages.
Adaptive Trend Detection : Fast SMAs are compared against slow SMAs to identify structural trends:
UpTrend : Fast SMA exceeds slow SMA.
DownTrend : Fast SMA falls below slow SMA.
Frequency Scaling : The wave frequency setting allows traders to modulate responsiveness versus smoothing. Higher frequency emphasizes short-term moves, while lower frequency highlights structural trends. This enables adaptation across asset classes with different volatility characteristics.
Through this combination, Harmonic Super Guppy captures micro and macro market cycles, helping traders distinguish between transient noise and genuine trend development. The multi-harmonic approach amplifies meaningful price action while reducing false signals inherent in standard moving averages.
Interpretation
Harmonic Super Guppy provides a multi-dimensional perspective on market dynamics:
Trend Analysis : Alignment of fast and slow lines reveals trend direction and strength. Expanding harmonics indicate momentum building, while contraction signals weakening conditions or potential reversals.
Momentum & Volatility : Rapid expansion of fast lines versus slow lines reflects short-term bullish or bearish pressure. Compression often precedes breakout scenarios or volatility expansion. Traders can quickly gauge trend vigor and potential turning points.
Market Context : The indicator overlays harmonic and structural insights without dictating entry or exit points. It complements order blocks, liquidity zones, oscillators, and other technical frameworks, providing context for informed decision-making.
Phase Divergence Detection : Subtle divergence between harmonic layers (primary, secondary, tertiary) often signals early exhaustion in trends or hidden strength, offering preemptive insight into potential reversals or sustained continuation.
By observing both structural alignment and harmonic expansion/contraction, traders gain a clear sense of when markets are trending with conviction versus when conditions are consolidating or becoming unpredictable. This allows for proactive trade management, rather than reactive responses to lagging indicators.
Strategy Integration
Harmonic Super Guppy adapts to various trading methodologies with clear, actionable guidance.
Trend Following : Enter positions when fast and slow lines are aligned and harmonics are expanding. The broader the alignment, the stronger the confirmation of trend persistence. For example:
A fast line crossover above slow lines with expanding fills confirms momentum-driven continuation.
Traders can use harmonic amplitude as a filter to reduce entries against prevailing trends.
Breakout Trading : Periods of line compression indicate potential volatility expansion. When fast lines diverge from slow lines after compression, this often precedes breakouts. Traders can combine this visual cue with structural supports/resistances or order flow analysis to improve timing and precision.
Exhaustion and Reversals : Divergences between harmonic components, or contraction of fast lines relative to slow lines, highlight weakening trends. This can indicate liquidity exhaustion, trend fatigue, or corrective phases. For example:
A flattening fast line group above a rising slow line can hint at short-term overextension.
Traders may use these signals to tighten stops, take partial profits, or prepare for contrarian setups.
Multi-Timeframe Analysis : Overlay slow lines from higher timeframes on lower timeframe charts to filter noise and trade in alignment with larger market structures. For example:
A daily bullish alignment combined with a 15-minute breakout pattern increases probability of a successful intraday trade.
Conversely, a higher timeframe divergence can warn against taking counter-trend trades in lower timeframes.
Adaptive Trade Management : Harmonic expansion/contraction can guide dynamic risk management:
Stops may be adjusted according to slow line support/resistance or harmonic contraction zones.
Position sizing can be modulated based on harmonic amplitude and compression levels, optimizing risk-reward without rigid rules.
Technical Implementation Details
Harmonic Super Guppy is powered by a multi-layered harmonic and phase calculation engine:
Harmonic Processing : Primary, secondary, and tertiary harmonics are calculated per period to capture multiple market cycles simultaneously. This reduces noise and amplifies meaningful signals.
Golden Ratio Modulation : Phase adjustments based on φ = 1.618 align harmonic contributions with natural market rhythms, smoothing lag and improving predictive value.
Adaptive Trend Scaling : Fast line expansion reflects short-term momentum; slow lines provide structural trend context. Fills adapt dynamically based on alignment intensity and harmonic amplitude.
Multi-Factor Trend Analysis : Trend strength is determined by alignment of fast and slow lines over multiple bars, expansion/contraction of harmonic amplitudes, divergences between primary, secondary, and tertiary harmonics and phase synchronization with golden ratio cycles.
These computations allow the indicator to be highly responsive yet smooth, providing traders with actionable insights in real time without overloading visual complexity.
Optimal Application Parameters
Asset-Specific Guidance:
Forex Majors : Wave frequency 1.0–2.0, φ = 1.618–1.8
Large-Cap Equities : Wave frequency 0.8–1.5, φ = 1.5–1.618
Cryptocurrency : Wave frequency 1.2–3.0, φ = 1.618–2.0
Index Futures : Wave frequency 0.5–1.5, φ = 1.618
Timeframe Optimization:
Scalping (1–5min) : Emphasize fast lines, higher frequency for micro-move capture.
Day Trading (15min–1hr) : Balance fast/slow interactions for trend confirmation.
Swing Trading (4hr–Daily) : Focus on slow lines for structural guidance, fast lines for entry timing.
Position Trading (Daily–Weekly) : Slow lines dominate; harmonics highlight long-term cycles.
Performance Characteristics
High Effectiveness Conditions:
Clear separation between short-term and long-term trends.
Moderate-to-high volatility environments.
Assets with consistent volume and price rhythm.
Reduced Effectiveness:
Flat or extremely low volatility markets.
Erratic assets with frequent gaps or algorithmic dominance.
Ultra-short timeframes (<1min), where noise dominates.
Integration Guidelines
Signal Confirmation : Confirm alignment of fast and slow lines over multiple bars. Expansion of harmonic amplitude signals trend persistence.
Risk Management : Place stops beyond slow line support/resistance. Adjust sizing based on compression/expansion zones.
Advanced Feature Settings :
Frequency tuning for different volatility environments.
Phase analysis to track divergences across harmonics.
Use fills and amplitude patterns as a guide for dynamic trade management.
Multi-timeframe confirmation to filter noise and align with structural trends.
Disclaimer
Harmonic Super Guppy is a trend analysis and visualization tool, not a guaranteed profit system. Optimal performance requires proper wave frequency, golden ratio phase, and line visibility settings per asset and timeframe. Traders should combine the indicator with other technical frameworks and maintain disciplined risk management practices.
BSL/SSL Sweep + FVG Strategy Jobin (c) The New York ATM Model is a structured intraday strategy designed to capture algorithmic stop-hunts and reversals during the New York session open. It focuses on liquidity sweeps—either Buy-Side or Sell-Side—followed by a confirmation using Fair Value Gaps (FVGs).
FiniteStateMachine🟩 OVERVIEW
A flexible framework for creating, testing and implementing a Finite State Machine (FSM) in your script. FSMs use rules to control how states change in response to events.
This is the first Finite State Machine library on TradingView and it's quite a different way to think about your script's logic. Advantages of using this vs hardcoding all your logic include:
• Explicit logic : You can see all rules easily side-by-side.
• Validation : Tables show your rules and validation results right on the chart.
• Dual approach : Simple matrix for straightforward transitions; map implementation for concurrent scenarios. You can combine them for complex needs.
• Type safety : Shows how to use enums for robustness while maintaining string compatibility.
• Real-world examples : Includes both conceptual (traffic lights) and practical (trading strategy) demonstrations.
• Priority control : Explicit control over which rules take precedence when multiple conditions are met.
• Wildcard system : Flexible pattern matching for states and events.
The library seems complex, but it's not really. Your conditions, events, and their potential interactions are complex. The FSM makes them all explicit, which is some work. However, like all "good" pain in life, this is front-loaded, and *saves* pain later, in the form of unintended interactions and bugs that are very hard to find and fix.
🟩 SIMPLE FSM (MATRIX-BASED)
The simple FSM uses a matrix to define transition rules with the structure: state > event > state. We look up the current state, check if the event in that row matches, and if it does, output the resulting state.
Each row in the matrix defines one rule, and the first matching row, counting from the top down, is applied.
A limitation of this method is that you can supply only ONE event.
You can design layered rules using widlcards. Use an empty string "" or the special string "ANY" for any state or event wildcard.
The matrix FSM is foruse where you have clear, sequential state transitions triggered by single events. Think traffic lights, or any logic where only one thing can happen at a time.
The demo for this FSM is of traffic lights.
🟩 CONCURRENT FSM (MAP-BASED)
The map FSM uses a more complex structure where each state is a key in the map, and its value is an array of event rules. Each rule maps a named condition to an output (event or next state).
This FSM can handle multiple conditions simultaneously. Rules added first have higher priority.
Adding more rules to existing states combines the entries in the map (if you use the supplied helper function) rather than overwriting them.
This FSM is for more complex scenarios where multiple conditions can be true simultaneously, and you need to control which takes precedence. Like trading strategies, or any system with concurrent conditions.
The demo for this FSM is a trading strategy.
🟩 HOW TO USE
Pine Script libraries contain reusable code for importing into indicators. You do not need to copy any code out of here. Just import the library and call the function you want.
For example, for version 1 of this library, import it like this:
import SimpleCryptoLife/FiniteStateMachine/1
See the EXAMPLE USAGE sections within the library for examples of calling the functions.
For more information on libraries and incorporating them into your scripts, see the Libraries section of the Pine Script User Manual.
🟩 TECHNICAL IMPLEMENTATION
Both FSM implementations support wildcards using blank strings "" or the special string "ANY". Wildcards match in this priority order:
• Exact state + exact event match
• Exact state + empty event (event wildcard)
• Empty state + exact event (state wildcard)
• Empty state + empty event (full wildcard)
When multiple rules match the same state + event combination, the FIRST rule encountered takes priority. In the matrix FSM, this means row order determines priority. In the map FSM, it's the order you add rules to each state.
The library uses user-defined types for the map FSM:
• o_eventRule : Maps a condition name to an output
• o_eventRuleWrapper : Wraps an array of rules (since maps can't contain arrays directly)
Everything uses strings for maximum library compatibility, though the examples show how to use enums for type safety by converting them to strings.
Unlike normal maps where adding a duplicate key overwrites the value, this library's `m_addRuleToEventMap()` method *combines* rules, making it intuitive to build rule sets without breaking them.
🟩 VALIDATION & ERROR HANDLING
The library includes comprehensive validation functions that catch common FSM design errors:
Error detection:
• Empty next states
• Invalid states not in the states array
• Duplicate rules
• Conflicting transitions
• Unreachable states (no entry/exit rules)
Warning detection:
• Redundant wildcards
• Empty states/events (potential unintended wildcards)
• Duplicate conditions within states
You can display validation results in tables on the chart, with tooltips providing detailed explanations. The helper functions to display the tables are exported so you can call them from your own script.
🟩 PRACTICAL EXAMPLES
The library includes four comprehensive demos:
Traffic Light Demo (Simple FSM) : Uses the matrix FSM to cycle through traffic light states (red → red+amber → green → amber → red) with timer events. Includes pseudo-random "break" events and repair logic to demonstrate wildcards and priority handling.
Trading Strategy Demo (Concurrent FSM) : Implements a realistic long-only trading strategy using BOTH FSM types:
• Map FSM converts multiple technical conditions (EMA crosses, gaps, fractals, RSI) into prioritised events
• Matrix FSM handles state transitions (idle → setup → entry → position → exit → re-entry)
• Includes position management, stop losses, and re-entry logic
Error Demonstrations : Both FSM types include error demos with intentionally malformed rules to showcase the validation system's capabilities.
🟩 BRING ON THE FUNCTIONS
f_printFSMMatrix(_mat_rules, _a_states, _tablePosition)
Prints a table of states and rules to the specified position on the chart. Works only with the matrix-based FSM.
Parameters:
_mat_rules (matrix)
_a_states (array)
_tablePosition (simple string)
Returns: The table of states and rules.
method m_loadMatrixRulesFromText(_mat_rules, _rulesText)
Loads rules into a rules matrix from a multiline string where each line is of the form "current state | event | next state" (ignores empty lines and trims whitespace).
This is the most human-readable way to define rules because it's a visually aligned, table-like format.
Namespace types: matrix
Parameters:
_mat_rules (matrix)
_rulesText (string)
Returns: No explicit return. The matrix is modified as a side-effect.
method m_addRuleToMatrix(_mat_rules, _currentState, _event, _nextState)
Adds a single rule to the rules matrix. This can also be quite readble if you use short variable names and careful spacing.
Namespace types: matrix
Parameters:
_mat_rules (matrix)
_currentState (string)
_event (string)
_nextState (string)
Returns: No explicit return. The matrix is modified as a side-effect.
method m_validateRulesMatrix(_mat_rules, _a_states, _showTable, _tablePosition)
Validates a rules matrix and a states array to check that they are well formed. Works only with the matrix-based FSM.
Checks: matrix has exactly 3 columns; no empty next states; all states defined in array; no duplicate states; no duplicate rules; all states have entry/exit rules; no conflicting transitions; no redundant wildcards. To avoid slowing down the script unnecessarily, call this method once (perhaps using `barstate.isfirst`), when the rules and states are ready.
Namespace types: matrix
Parameters:
_mat_rules (matrix)
_a_states (array)
_showTable (bool)
_tablePosition (simple string)
Returns: `true` if the rules and states are valid; `false` if errors or warnings exist.
method m_getStateFromMatrix(_mat_rules, _currentState, _event, _strictInput, _strictTransitions)
Returns the next state based on the current state and event, or `na` if no matching transition is found. Empty (not na) entries are treated as wildcards if `strictInput` is false.
Priority: exact match > event wildcard > state wildcard > full wildcard.
Namespace types: matrix
Parameters:
_mat_rules (matrix)
_currentState (string)
_event (string)
_strictInput (bool)
_strictTransitions (bool)
Returns: The next state or `na`.
method m_addRuleToEventMap(_map_eventRules, _state, _condName, _output)
Adds a single event rule to the event rules map. If the state key already exists, appends the new rule to the existing array (if different). If the state key doesn't exist, creates a new entry.
Namespace types: map
Parameters:
_map_eventRules (map)
_state (string)
_condName (string)
_output (string)
Returns: No explicit return. The map is modified as a side-effect.
method m_addEventRulesToMapFromText(_map_eventRules, _configText)
Loads event rules from a multiline text string into a map structure.
Format: "state | condName > output | condName > output | ..." . Pairs are ordered by priority. You can have multiple rules on the same line for one state.
Supports wildcards: Use an empty string ("") or the special string "ANY" for state or condName to create wildcard rules.
Examples: " | condName > output" (state wildcard), "state | > output" (condition wildcard), " | > output" (full wildcard).
Splits lines by \n, extracts state as key, creates/appends to array with new o_eventRule(condName, output).
Call once, e.g., on barstate.isfirst for best performance.
Namespace types: map
Parameters:
_map_eventRules (map)
_configText (string)
Returns: No explicit return. The map is modified as a side-effect.
f_printFSMMap(_map_eventRules, _a_states, _tablePosition)
Prints a table of map-based event rules to the specified position on the chart.
Parameters:
_map_eventRules (map)
_a_states (array)
_tablePosition (simple string)
Returns: The table of map-based event rules.
method m_validateEventRulesMap(_map_eventRules, _a_states, _a_validEvents, _showTable, _tablePosition)
Validates an event rules map to check that it's well formed.
Checks: map is not empty; wrappers contain non-empty arrays; no duplicate condition names per state; no empty fields in o_eventRule objects; optionally validates outputs against matrix events.
NOTE: Both "" and "ANY" are treated identically as wildcards for both states and conditions.
To avoid slowing down the script unnecessarily, call this method once (perhaps using `barstate.isfirst`), when the map is ready.
Namespace types: map
Parameters:
_map_eventRules (map)
_a_states (array)
_a_validEvents (array)
_showTable (bool)
_tablePosition (simple string)
Returns: `true` if the event rules map is valid; `false` if errors or warnings exist.
method m_getEventFromConditionsMap(_currentState, _a_activeConditions, _map_eventRules)
Returns a single event or state string based on the current state and active conditions.
Uses a map of event rules where rules are pre-sorted by implicit priority via load order.
Supports wildcards using empty string ("") or "ANY" for flexible rule matching.
Priority: exact match > condition wildcard > state wildcard > full wildcard.
Namespace types: series string, simple string, input string, const string
Parameters:
_currentState (string)
_a_activeConditions (array)
_map_eventRules (map)
Returns: The output string (event or state) for the first matching condition, or na if no match found.
o_eventRule
o_eventRule defines a condition-to-output mapping for the concurrent FSM.
Fields:
condName (series string) : The name of the condition to check.
output (series string) : The output (event or state) when the condition is true.
o_eventRuleWrapper
o_eventRuleWrapper wraps an array of o_eventRule for use as map values (maps cannot contain collections directly).
Fields:
a_rules (array) : Array of o_eventRule objects for a specific state.
NX - ICT PD ArraysThis Pine Script indicator identifies and visualizes Fair Value Gaps (FVGs) and Order Blocks (OBs) based on refined price action logic.
FVGs are highlighted when price leaves an imbalance between candles, while Order Blocks are detected using ICT methodology—marking the last opposing candle before a displacement move.
The script dynamically tracks and updates these zones, halting box extension once price interacts with them. Customizable colors and lookback settings allow traders to tailor the display to their strategy.
