Volume Profile With HVN & LVN detectorVolume Profile Indicator
Based on the works of tradeforopp
Overview
The Volume Profile Indicator is a powerful technical analysis tool that visually represents the distribution of trading volume over price levels within a specified timeframe. It helps traders identify key support and resistance zones, high-volume trading areas, and low-volume rejection zones. The indicator includes customizable settings for Volume Point of Control (VPOC), High Volume Nodes (HVNs), and Low Volume Nodes (LVNs), making it a versatile tool for price action analysis and volume-based decision-making.
Key Features
🔹 Customizable Volume Profile
Adjustable number of rows to define the resolution of the volume profile.
Configurable timeframe aggregation for profile calculation (e.g., Daily, Weekly).
Selectable price resolution timeframe for precise profile construction.
Extendable volume profile for future sessions.
Fully customizable profile color and transparency settings.
🔹 Volume Point of Control (VPOC)
Displays the most traded price level within the selected timeframe.
Option to extend multiple VPOCs across the chart.
Adjustable VPOC line width and color customization.
Option to display VPOC labels when working with higher timeframe profiles.
🔹 High Volume Nodes (HVNs)
Identifies high-volume price levels where significant trading activity has occurred.
Configurable HVN strength to adjust detection sensitivity.
Two display modes:
Lines: Plots HVN levels as horizontal lines.
Areas: Highlights HVN regions with colored boxes.
Separate bullish and bearish HVN color settings.
🔹 Low Volume Nodes (LVNs)
Identifies low-volume price levels, which often act as rejection zones.
Configurable LVN strength to fine-tune detection.
Two display modes:
Lines: Marks LVN levels as horizontal lines.
Areas: Highlights LVN regions with shaded boxes.
Separate bullish and bearish LVN color settings.
🔹 Optimized for Performance
Efficient use of arrays for data storage and retrieval.
Global functions for HVN and LVN detection.
Uses security calls to access lower timeframe price and volume data.
Use Cases
✅ Identify Support & Resistance Levels
The indicator highlights key price levels where significant buying or selling interest exists.
✅ Detect Breakout & Reversal Zones
Low-volume areas (LVNs) often indicate price rejection zones, while high-volume areas (HVNs) suggest strong price acceptance zones.
✅ Improve Trade Entries & Exits
Traders can use the Volume Point of Control (VPOC) and volume clusters to refine entry and exit points.
✅ Enhance Price Action Strategies
By incorporating volume-based analysis, this indicator provides deeper market insights beyond traditional support/resistance and trendlines.
Customization & Settings
📌 Volume Profile Settings:
Rows: Defines the granularity of the volume profile.
Profile Timeframe: Specifies the aggregation period (e.g., Daily, Weekly).
Resolution Timeframe: Determines the price resolution for volume analysis.
Profile Extend %: Controls how much the profile extends into the next session.
📌 Volume Point of Control (VPOC):
Enable/Disable VPOC visualization.
Extend past VPOC levels to the right.
Display VPOC labels for higher timeframe profiles.
Adjustable VPOC line width and color.
📌 High Volume Nodes (HVNs):
Enable/Disable HVN detection.
Define HVN strength (volume threshold).
Choose between Line Mode or Area Mode.
Configure bullish and bearish HVN colors.
📌 Low Volume Nodes (LVNs):
Enable/Disable LVN detection.
Define LVN strength (volume threshold).
Choose between Line Mode or Area Mode.
Configure bullish and bearish LVN colors.
Cerca negli script per "horizontal line"
Multi-Timeframe Open LinesThe Multi-Timeframe Open Lines indicator is designed to help traders visualize key price levels at the open of specific time intervals. It draws horizontal lines at the open of 5-minute, 15-minute, 30-minute, and hourly candles, extending these lines to the start of the next respective interval. Traders can now control which timeframes are displayed and how many past opening lines are shown, ensuring a clean and organized chart.
Key Features:
Customizable Lines:
5-Minute Lines: Highlight the open of every 5-minute candle, ending at the start of the next 5-minute candle.
15-Minute Lines: Highlight the open of every 15-minute candle, ending at the start of the next 15-minute candle.
30-Minute Lines: Highlight the open of every 30-minute candle, ending at the start of the next 30-minute candle.
Hourly Lines: Highlight the open of every hourly candle, ending at the start of the next hourly candle.
Each timeframe's lines can be customized in terms of color, line style, and thickness.
Toggle Options:
Easily turn on or off the display of lines for each timeframe (5m, 15m, 30m, 1h) using checkboxes in the settings.
User-Defined Limits:
Control the number of past opening lines displayed for each timeframe (5m, 15m, 30m, 1h).
Prevents chart clutter by limiting the number of visible lines.
Multi-Timeframe Analysis:
Enables traders to analyze price action across multiple timeframes simultaneously, providing a clearer picture of market structure and key levels.
User-Friendly Inputs:
Easy-to-use settings for customizing line appearance and behavior, ensuring the indicator fits seamlessly into any trading strategy.
How to Use:
Apply the indicator to your chart to visualize the open price levels for 5-minute, 15-minute, 30-minute, and hourly candles.
Use the lines as dynamic support/resistance levels or to identify potential breakout/breakdown points.
Customize the colors, styles, and the number of visible lines to match your chart theme or trading preferences.
Toggle specific timeframes on or off to focus on the most relevant price levels.
Ideal For:
Traders who use multi-timeframe analysis.
Those who rely on key price levels for decision-making.
Anyone looking to enhance their chart with clear, customizable reference lines while avoiding clutter.
GANN Level (Salil Sir)GANN Level Indicator Description
This Pine Script calculates and plots Gann Levels based on a user-defined price input. It creates horizontal lines at key support and resistance levels derived from the input price, applying Gann's theory of market structure. The levels are dynamically calculated and squared for enhanced precision.
Key Features:
Manual Price Input:
The user inputs a round off of square root of base price (Manual_Input), which serves as the foundation for calculations.
Support and Resistance Levels:
Six resistance levels (R1 to R6) and six support levels (S1 to S6) are calculated by incrementing or decrementing the base price in steps of 0.25.
Squared Levels:
Each level is squared (level^2) to align with Gann's mathematical principles.
Visualization:
All levels, including the base price squared (GANN), are plotted as horizontal dotted lines:
Black Line: Base price squared (Gann Level).
Green Lines: Resistance levels.
Red Lines: Support levels.
Purpose:
The indicator helps traders identify potential support and resistance zones based on Gann's methodology, providing a mathematical framework for decision-making.
Usage:
Adjust the Manual Price in the settings to the desired value.
Observe the plotted levels for key support and resistance zones on the chart.
Use these levels to make informed trading decisions or to validate other indicators.
Support and Resistance TrendlinesStrategy:
Support: Identified as the lowest low over a specific period.
Resistance: Identified as the highest high over a specific period.
Dynamic Trendlines: We’ll use the concept of a rolling window to calculate the highest highs and lowest lows over the last n bars (you can adjust the number of bars for more sensitivity).
Explanation:
Lookback Period (length): The number of bars over which we calculate the support and resistance levels. You can adjust this value depending on the timeframe and the sensitivity you want for the trendlines.
Resistance: This is the highest high over the length of bars. We use ta.highest(high, length) to find the highest high within the specified lookback period.
Support: This is the lowest low over the length of bars. We use ta.lowest(low, length) to find the lowest low within the specified lookback period.
Plotting the Lines:
We plot the support and resistance as horizontal lines on the chart using plot().
Additionally, we create dynamic trendlines that update automatically with each new bar. The line.new function creates lines that can be modified dynamically as new price data comes in.
Line Persistence:
The line functions are used to create horizontal lines that persist across bars. The trendlines adjust their position as the bars move forward.
How It Works:
This indicator will automatically detect the highest and lowest prices over the last n bars and draw support (green line) and resistance (red line) levels on the chart.
The trendlines will adjust as the market evolves and provide visual reference points for potential areas of price reversal.
How to Use This Script:
Copy and paste the Pine Script code into the Pine Script Editor on TradingView.
Save the script, and then add it to your chart.
Adjust the Lookback Period input to suit your trading strategy and timeframe.
The support and resistance levels will be drawn dynamically, and the lines will update as new bars form.
Customizations:
You can modify the number of bars (length) used to calculate support and resistance, depending on the timeframes you're interested in.
If you need more advanced trendline drawing (such as drawing trendlines between significant high/low points or automatic adjustment to more complex patterns), you might need to implement more advanced logic using peaks and valleys or price action patterns.
Let me know if you need any further adjustments!
Sri Yantra MTF - AynetSri Yantra MTF - Aynet Script Overview
This Pine Script generates a Sri Yantra-inspired geometric pattern overlay on price charts. The pattern is dynamically updated based on multi-timeframe (MTF) inputs, utilizing high and low price ranges, and adjusting its size relative to a chosen multiplier.
The Sri Yantra is a sacred geometric figure used in various spiritual and mathematical contexts, symbolizing the interconnectedness of the universe. Here, it is applied to visualize structured price levels.
Scientific and Technical Explanation
Multi-Timeframe Integration:
Base Timeframe (baseRes): This is the primary timeframe for the analysis. The opening price and ATR (Average True Range) are calculated from this timeframe.
Pattern Timeframe (patternRes): Defines the granularity of the pattern. It ensures synchronization with price movements on specific time intervals.
Geometric Construction:
ATR-Based Scaling: The script uses ATR as a volatility measure to dynamically size the geometric pattern. The sizeMult input scales the pattern relative to price volatility.
Pattern Width (barOffset): Defines the horizontal extent of the pattern in terms of bars. This ensures the pattern is aligned with price movements and scales appropriately.
Sri Yantra-Like Geometry:
Outer Square: A bounding box is drawn around the price level.
Triangles: Multiple layers of triangles (primary, secondary, and tertiary) are calculated and drawn to mimic the structure of the Sri Yantra. These triangles converge and diverge based on price levels.
Horizontal Lines: Added at key levels to provide additional structure and aesthetic alignment.
Dynamic Updates:
The pattern recalculates and redraws itself on the last bar of the selected timeframe, ensuring it adapts to real-time price data.
A built-in check identifies new bars in the chosen timeframe (patternRes), ensuring accurate updates.
Information Table:
Displays the selected base and pattern timeframes in a table format on the top-right corner of the chart.
Allows traders to see the active settings for quick adjustments.
Key Inputs
Style Settings:
Pattern Color: Customize the color of the geometric patterns.
Size Multiplier (sizeMult): Adjusts the size of the pattern relative to price movements.
Line Width: Controls the thickness of the geometric lines.
Timeframe Settings:
Base Resolution (baseRes): Timeframe for calculating the pattern's anchor (default: daily).
Pattern Resolution (patternRes): Timeframe granularity for the pattern’s formation.
Geometric Adjustments:
Pattern Width (barOffset): Horizontal width in bars.
ATR Multiplier (rangeSize): Vertical size adjustment based on price volatility.
Scientific Concepts
Volatility Representation:
ATR (Average True Range): A standard measure of market volatility, representing the average range of price movements over a defined period. Here, ATR adjusts the vertical height of the geometric figures.
Geometric Symmetry:
The script emulates symmetry similar to the Sri Yantra, aligning with the principles of sacred geometry, which often appear in nature and mathematical constructs. Symmetry in financial data visualizations can aid in intuitive interpretation of price movements.
Multi-Timeframe Fusion:
Synchronizing patterns with multiple timeframes enhances the relevance of overlays for different trading strategies. For example, daily trends combined with hourly patterns can help traders optimize entries and exits.
Visual Features
Outer Square:
Drawn to encapsulate the geometric structure.
Represents the broader context of price levels.
Triangles:
Three layers of interlocking triangles create a fractal pattern, providing a visual alignment to price dynamics.
Horizontal Lines:
Emphasize critical levels within the pattern, offering visual cues for potential support or resistance areas.
Information Table:
Displays the active timeframe settings, helping traders quickly verify configurations.
Applications
Trend Visualization:
Patterns overlay on price movements provide a clearer view of trend direction and potential reversals.
Volatility Mapping:
ATR-based scaling ensures the pattern adjusts to varying market conditions, making it suitable for different asset classes and trading strategies.
Multi-Timeframe Analysis:
Integrates higher and lower timeframes, enabling traders to spot confluences between short-term and long-term price levels.
Potential Enhancements
Add Fibonacci Levels: Overlay Fibonacci retracements within the pattern for deeper price level insights.
Dynamic Alerts: Include alert conditions when price intersects key geometric lines.
Custom Labels: Add text descriptions for critical intersections or triangle centers.
This script is a unique blend of technical analysis and sacred geometry, providing traders with an innovative way to visualize market dynamics.
Previous Daily Candle The Previous Daily Candle indicator is a powerful tool designed to enhance your intraday trading by providing clear visual cues of the previous day's price action. By outlining the high, low, open, and close of the previous daily candle and adding a middle dividing line, this indicator offers valuable context to inform your trading decisions.
🎯 Purpose
Visual Clarity: Highlight the key levels from the previous day's price movement directly on your intraday charts.
Trend Confirmation: Quickly identify bullish or bearish sentiment based on the previous day's candle structure.
Support and Resistance: Use the outlined high and low as potential support and resistance levels for your trading strategies.
Customizable Visualization: Tailor the appearance of the outlines and middle line to fit your trading style and chart aesthetics.
🛠️ Features
Outlined Candle Structure:
High and Low Lines: Clearly mark the previous day's high and low with customizable colors and line widths.
Open and Close Representation: Visualize the previous day's open and close through the outlined structure.
Middle Dividing Line:
Average Price Level: A horizontal line divides the candle in half, representing the average of the open and close prices.
Customizable Appearance: Adjust the color and thickness to distinguish it from the high and low outlines.
Bullish and Bearish Differentiation:
Color-Coded Outlines: Automatically change the outline color based on whether the previous day's candle was bullish (green by default) or bearish (red by default).
Enhanced Visual Feedback: Quickly assess market sentiment with intuitive color cues.
Customization Options:
Outline Colors: Choose distinct colors for bullish and bearish candle outlines to match your chart's color scheme.
Middle Line Color: Select a color that stands out or blends seamlessly with your existing chart elements.
Line Width Adjustment: Modify the thickness of all lines to ensure visibility without cluttering the chart.
Transparent Candle Body:
Non-Intrusive Display: The indicator only draws the outlines and middle line, keeping the candle body transparent to maintain the visibility of your primary chart data.
⚙️ How It Works
Data Retrieval: The indicator fetches the previous day's open, high, low, and close prices using TradingView's request.security function.
Candle Analysis: Determines whether the previous day's candle was bullish or bearish by comparing the close and open prices.
Dynamic Drawing: Upon the start of a new day, the indicator deletes the previous outlines and redraws them based on the latest data.
Time Synchronization: Accurately aligns the outlines with the corresponding time periods on your intraday chart.
📈 How to Use
Add to Chart:
Open TradingView and navigate to the Pine Editor.
Paste the provided Pine Script code into the editor.
Click on Add to Chart to apply the indicator.
Customize Settings:
Access the indicator's settings by clicking the gear icon next to its name on the chart.
Adjust the Bullish Outline Color, Bearish Outline Color, Middle Line Color, and Outline Width to your preference.
Interpret the Lines:
Bullish Candle: If the previous day's close is higher than its open, the outlines will display in the bullish color (default green).
Bearish Candle: If the previous day's close is lower than its open, the outlines will display in the bearish color (default red).
Middle Line: Represents the midpoint between the open and close, providing a quick reference for potential support or resistance.
Integrate with Your Strategy:
Use the high and low outlines as potential entry or exit points.
Combine with other indicators for confirmation to strengthen your trading signals.
Cubic Bezier Curve RSI [CBCR]Overview :
Introducing the Cubic Bézier Curve RSI – an innovative approach to smoothing the traditional RSI using cubic Bézier curves. This indicator provides traders with a smoother, adaptive version of the RSI that can help filter out noise and better highlight market trends.
Key Features:
Bézier Curve : the script uses cubic Bézier curves to create a smoothed version of the RSI, offering a more visually appealing and potentially more insightful representation of market momentum.
Customizable Settings: Users can adjust the Bézier Curve Length, Impact Factor, and color modes, allowing full customization of the smoothing effect and visualization.
Color-coded Trend Indicator: The smoothed RSI is displayed with colors that indicate potential bullish or bearish trends, helping traders quickly assess market conditions.
Overbought/Oversold Lines: Option to display overbought and oversold levels for better identification of market extremes.
Parameters:
RSI Length: Set the length for the traditional RSI calculation (default is 14).
Bézier Curve Length: Adjust the length of the Bézier curve used to smooth the RSI (default is 20).
Impact Factor: Control the influence of the Bézier smoothed values versus the original RSI values (default is 0.5, ranging from 0.0 to 1.0).
Overbought/Oversold Lines: Option to show overbought (default: 70) and oversold (default: 30) lines for easier identification of extreme conditions.
Color Mode: Choose between "Trend Following" and "Overbought/Oversold" modes for line color indication.
Display Settings: Color customization for bullish and bearish phases allows better visual differentiation.
How It Works:
The CBCR uses four control points derived from historical RSI values over a user-defined length. It then applies the cubic Bezier formula to generate a sequence of points representing a smoothed version of the RSI over this range.
The Bezier curve is recalculated each time a specific number of bars (as defined by the Bezier Curve Length) have passed, helping reduce noise while retaining key trend information.
The result is a smoothed RSI that combines the adaptability of cubic Bezier curves with the familiar oscillation of the RSI, making it potentially more robust for identifying shifts in market sentiment.
Visuals:
Smoothed RSI Line: Plotted on the indicator pane, the line changes color depending on the chosen color mode:
Trend Following Mode: Color changes based on whether the smoothed RSI is above or below the 50-level.
Overbought/Oversold Mode: Color changes based on whether the smoothed RSI is above the overbought level or below the oversold level.
Bullish Color: Configurable (default: cyan).
Bearish Color: Configurable (default: red).
Overbought/Oversold Lines: Horizontal lines at user-defined levels (default: 70 for overbought, 30 for oversold) for easy identification of market extremes.
Usage:
The CBCR can be used like a traditional RSI but with a smoother output that may help traders avoid false signals generated by sudden price spikes. For instance:
Look for crossovers around the 50 level as a signal for changing momentum.
Use the overbought and oversold levels to identify potential reversal zones.
Observe the color change of the line for an immediate visual cue on current sentiment.
Daily High and Low Levels IndicatorThis Pine Script indicator displays horizontal lines representing the high and low levels of the previous trading day, extending them to the right side of the chart for better visibility. It updates automatically at the start of each new trading day.
Features:
Daily High and Low Levels: Marks the high and low levels of the previous day with horizontal lines.
Customization:
Adjust the color, style, and thickness of the lines to fit your preferences.
High Level Line Color: Customize to your preferred color (default: gray).
Low Level Line Color: Customize to your preferred color (default: white).
Line Style Options: Choose between solid, dashed, or dotted lines.
Line Thickness: Adjust the width of the lines.
Extended Lines: Extend the lines to the right side of the chart for enhanced visibility.
Labeling: Shows clear labels "Previous High" and "Previous Low" next to the lines for easy reference.
Usage :
Add this indicator to your chart to visualize the previous day's high and low levels.
Customize the appearance of the lines and labels using the input options.
The indicator will automatically update these levels at the beginning of each trading day.
This indicator is designed to help traders quickly identify significant price levels from the previous day and make informed trading decisions.
License: This script is provided under the Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) License. For more information, visit Creative Commons License.
Stochastic Momentum Channel with Volume Filter [IkkeOmar]A stochastic version of my momentum channel volume filter
The "Stochastic Momentum" indicator combines the concepts of Stochastic and Bollinger Bands to provide insights into price momentum and potential trend reversals. It can be used to identify overbought and oversold conditions, as well as potential bullish and bearish signals.
The indicator calculates a Stochastic RSI using the RSI (Relative Strength Index) of a given price source. It applies smoothing to the Stochastic RSI values using moving averages to generate two lines: the %K line and the %D line. The %K line represents the current momentum, while the %D line represents a filtered version of the momentum.
Additionally, the indicator plots Bollinger Bands around the moving average of the Stochastic RSI. The upper and lower bands represent levels where the price is considered relatively high or low compared to its recent volatility. The distance between the bands reflects the current market volatility.
Here's how the indicator can be interpreted:
Stochastic Momentum (%K and %D lines):
When the %K line crosses above the %D line, it suggests a potential upward move or bullish momentum.
When the %K line crosses below the %D line, it indicates a potential downward move or bearish momentum.
The color of the plot changes based on the relationship between the %K and %D lines. Green indicates %K > %D, while red indicates %K < %D.
Bollinger Bands (Upper and Lower Bands):
When the price crosses above the upper band, it suggests an overbought condition, indicating a potential reversal or pullback.
When the price crosses below the lower band, it suggests an oversold condition, indicating a potential reversal or bounce.
To identify potential upward moves, consider the following conditions:
If the price is not in a contraction phase (the bands are not narrowing), and the price crosses above the lower band, it may signal a potential upward move or bounce.
If the %K line crosses above the %D line while the %K line is below the upper band, it may indicate a potential upward move.
To identify potential downward moves, consider the following conditions:
If the price is not in a contraction phase (the bands are not narrowing), and the price crosses below the upper band, it may signal a potential downward move or pullback.
If the %K line crosses below the %D line while the %K line is above the lower band, it may indicate a potential downward move.
Code explanation
Input Variables:
The input function is used to create customizable input variables that can be adjusted by the user.
smoothK and smoothD are inputs for the smoothing periods of the %K and %D lines, respectively.
lengthRSI represents the length of the RSI calculation.
lengthStoch is the length parameter for the stochastic calculation.
volumeFilterLength determines the length of the volume filter used to filter the RSI.
Source Definition:
The src variable is an input that defines the price source used for the calculations.
By default, the close price is used, but the user can choose a different price source.
RSI Calculation:
The rsi1 variable calculates the RSI using the ta.rsi function.
The RSI is a popular oscillator that measures the strength and speed of price movements.
It is calculated based on the average gain and average loss over a specified period.
In this case, the RSI is calculated using the src price source and the lengthRSI parameter.
Volume Filter:
The code calculates a volume filter to filter the RSI values based on the average volume.
The volumeAvg variable calculates the simple moving average of the volume over a specified period (volumeFilterLength).
The filteredRsi variable stores the RSI values that meet the condition of having a volume greater than or equal to the average volume (volume >= volumeAvg).
Stochastic Calculation:
The k variable calculates the %K line of the Stochastic RSI using the ta.stoch function.
The ta.stoch function takes the filtered RSI values (filteredRsi) as inputs and calculates the %K line based on the length parameter (lengthStoch).
The smoothK parameter is used to smooth the %K line by applying a moving average.
The d variable represents the %D line, which is a smoothed version of the %K line obtained by applying another moving average with a period defined by smoothD.
Momentum Calculation:
The kd variable calculates the average of the %K and %D lines, representing the momentum of the Stochastic RSI.
Bollinger Bands Calculation:
The ma variable calculates the moving average of the momentum values (kd) using the ta.sma function with a period defined by bandLength.
The offs variable calculates the offset by multiplying the standard deviation of the momentum values with a factor of 1.6185.
The up and dn variables represent the upper and lower bands, respectively, by adding and subtracting the offset from the moving average.
The Bollinger Bands provide a measure of volatility and can indicate potential overbought and oversold conditions.
Color Assignments:
The colors for the plot and Bollinger Bands are assigned based on certain conditions.
If the %K line is greater than the %D line, the plotCol variable is set to green. Otherwise, it is set to red.
The upCol and dnCol variables are set to different colors based on whether the fast moving average (fastMA) is above or below the upper and lower bands, respectively.
Plotting:
The Stochastic Momentum (%K) is plotted using the plot function with the assigned color (plotCol).
The upper and lower Bollinger Bands are plotted using the plot function with the respective colors (upCol and dnCol).
The fast moving average (fastMA) is plotted in black color to distinguish it from the bands.
The hline function is used to plot horizontal lines representing the upper and lower bands of the Stochastic Momentum.
The code combines the Stochastic RSI, Bollinger Bands, and color logic to provide visual representations of momentum and potential trend reversals. It allows traders to observe the interaction between the Stochastic Momentum lines, the Bollinger Bands, and price movements, enabling them to make informed trading decisions.
Take Session High/Low Alert [MsF]Japanese below / 日本語説明は英文の後にあります。
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This indicator that displays High/Low lines for each session. The Key Levels of each session can be visually recognized, which is useful for PD Array analysis. You can display the last 3 days. Based on trinity by ICT.
The biggest feature is that the color shape of the line changes when reaching High/Low. Of course, you can also set alerts.
Unreached High/Low lines can be extended to the right. hides all timeframes over 1 hour. (alert is alive)
You can choose 4 sessions. If you only want to use 3 sessions, you can do that by setting the same session time for 2 of the 4 session settings.
About Parameter Settings
Session Time: Please set it to be a 24-hour cycle. You can also specify the time zone. The default is NY time.
Basis/Other color: The first time specified in "Session Time" in this indicator's parameter is the "Basis color". "Other color" is a line other than that.
Enable Time Lines: You can turn on/off the display of vertical lines.
High/Low color: High/Low line setting that has not been reached.
Taken color: High/Low line setting that has already been reached.
Extend Lines: Allows unreached High/Low lines to be extended to the right in the chart.
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セッションごとのHigh/Lowをライン表示するインジケーターです。
過去約３日分を表示することができます。
最大の特徴はHigh/Low到達時にラインの色形が変わることです。もちろんアラート設定も可能です。
未到達のHigh/Lowラインは右側に延長することができます。
チャート表示がビジーとなる為、1時間を超える時間足ではすべて非表示とする仕様です。（アラートは生きてます）
セッションは4つ指定できます。
もしセッションを3つのみ使用したい場合は、4つのセッション設定の内2つに同じセッション時間を設定することで実現可能です。
■パラメータ設定
Session Time：24時間周期となるように設定してください。またタイムゾーンが指定できます。デフォルトはNY timeです。
Basis/Other color：パラメータの"Session Time"にて一番最初に指定した時間が基準＝Basisとなります。Otherはそれ以外のラインとなります。
Enable Time Lines：垂直ラインの表示ON/OFFが可能です。
High/Low color：未到達のHigh/Lowライン設定となります。
Taken color：到達済みのHigh/Lowライン設定となります。
Extend Lines：未到達のHigh/Lowラインを右に延長できます。
Adaptive Market Wave TheoryAdaptive Market Wave Theory
🌊 CORE INNOVATION: PROBABILISTIC PHASE DETECTION WITH MULTI-AGENT CONSENSUS
Adaptive Market Wave Theory (AMWT) represents a fundamental paradigm shift in how traders approach market phase identification. Rather than counting waves subjectively or drawing static breakout levels, AMWT treats the market as a hidden state machine —using Hidden Markov Models, multi-agent consensus systems, and reinforcement learning algorithms to quantify what traditional methods leave to interpretation.
The Wave Analysis Problem:
Traditional wave counting methodologies (Elliott Wave, harmonic patterns, ABC corrections) share fatal weaknesses that AMWT directly addresses:
1. Non-Falsifiability : Invalid wave counts can always be "recounted" or "adjusted." If your Wave 3 fails, it becomes "Wave 3 of a larger degree" or "actually Wave C." There's no objective failure condition.
2. Observer Bias : Two expert wave analysts examining the same chart routinely reach different conclusions. This isn't a feature—it's a fundamental methodology flaw.
3. No Confidence Measure : Traditional analysis says "This IS Wave 3." But with what probability? 51%? 95%? The binary nature prevents proper position sizing and risk management.
4. Static Rules : Fixed Fibonacci ratios and wave guidelines cannot adapt to changing market regimes. What worked in 2019 may fail in 2024.
5. No Accountability : Wave methodologies rarely track their own performance. There's no feedback loop to improve.
The AMWT Solution:
AMWT addresses each limitation through rigorous mathematical frameworks borrowed from speech recognition, machine learning, and reinforcement learning:
• Non-Falsifiability → Hard Invalidation : Wave hypotheses die permanently when price violates calculated invalidation levels. No recounting allowed.
• Observer Bias → Multi-Agent Consensus : Three independent analytical agents must agree. Single-methodology bias is eliminated.
• No Confidence → Probabilistic States : Every market state has a calculated probability from Hidden Markov Model inference. "72% probability of impulse state" replaces "This is Wave 3."
• Static Rules → Adaptive Learning : Thompson Sampling multi-armed bandits learn which agents perform best in current conditions. The system adapts in real-time.
• No Accountability → Performance Tracking : Comprehensive statistics track every signal's outcome. The system knows its own performance.
The Core Insight:
"Traditional wave analysis asks 'What count is this?' AMWT asks 'What is the probability we are in an impulsive state, with what confidence, confirmed by how many independent methodologies, and anchored to what liquidity event?'"
🔬 THEORETICAL FOUNDATION: HIDDEN MARKOV MODELS
Why Hidden Markov Models?
Markets exist in hidden states that we cannot directly observe—only their effects on price are visible. When the market is in an "impulse up" state, we see rising prices, expanding volume, and trending indicators. But we don't observe the state itself—we infer it from observables.
This is precisely the problem Hidden Markov Models (HMMs) solve. Originally developed for speech recognition (inferring words from sound waves), HMMs excel at estimating hidden states from noisy observations.
HMM Components:
1. Hidden States (S) : The unobservable market conditions
2. Observations (O) : What we can measure (price, volume, indicators)
3. Transition Matrix (A) : Probability of moving between states
4. Emission Matrix (B) : Probability of observations given each state
5. Initial Distribution (π) : Starting state probabilities
AMWT's Six Market States:
State 0: IMPULSE_UP
• Definition: Strong bullish momentum with high participation
• Observable Signatures: Rising prices, expanding volume, RSI >60, price above upper Bollinger Band, MACD histogram positive and rising
• Typical Duration: 5-20 bars depending on timeframe
• What It Means: Institutional buying pressure, trend acceleration phase
State 1: IMPULSE_DN
• Definition: Strong bearish momentum with high participation
• Observable Signatures: Falling prices, expanding volume, RSI <40, price below lower Bollinger Band, MACD histogram negative and falling
• Typical Duration: 5-20 bars (often shorter than bullish impulses—markets fall faster)
• What It Means: Institutional selling pressure, panic or distribution acceleration
State 2: CORRECTION
• Definition: Counter-trend consolidation with declining momentum
• Observable Signatures: Sideways or mild counter-trend movement, contracting volume, RSI returning toward 50, Bollinger Bands narrowing
• Typical Duration: 8-30 bars
• What It Means: Profit-taking, digestion of prior move, potential accumulation for next leg
State 3: ACCUMULATION
• Definition: Base-building near lows where informed participants absorb supply
• Observable Signatures: Price near recent lows but not making new lows, volume spikes on up bars, RSI showing positive divergence, tight range
• Typical Duration: 15-50 bars
• What It Means: Smart money buying from weak hands, preparing for markup phase
State 4: DISTRIBUTION
• Definition: Top-forming near highs where informed participants distribute holdings
• Observable Signatures: Price near recent highs but struggling to advance, volume spikes on down bars, RSI showing negative divergence, widening range
• Typical Duration: 15-50 bars
• What It Means: Smart money selling to late buyers, preparing for markdown phase
State 5: TRANSITION
• Definition: Regime change period with mixed signals and elevated uncertainty
• Observable Signatures: Conflicting indicators, whipsaw price action, no clear momentum, high volatility without direction
• Typical Duration: 5-15 bars
• What It Means: Market deciding next direction, dangerous for directional trades
The Transition Matrix:
The transition matrix A captures the probability of moving from one state to another. AMWT initializes with empirically-derived values then updates online:
From/To IMP_UP IMP_DN CORR ACCUM DIST TRANS
IMP_UP 0.70 0.02 0.20 0.02 0.04 0.02
IMP_DN 0.02 0.70 0.20 0.04 0.02 0.02
CORR 0.15 0.15 0.50 0.10 0.10 0.00
ACCUM 0.30 0.05 0.15 0.40 0.05 0.05
DIST 0.05 0.30 0.15 0.05 0.40 0.05
TRANS 0.20 0.20 0.20 0.15 0.15 0.10
Key Insights from Transition Probabilities:
• Impulse states are sticky (70% self-transition): Once trending, markets tend to continue
• Corrections can transition to either impulse direction (15% each): The next move after correction is uncertain
• Accumulation strongly favors IMP_UP transition (30%): Base-building leads to rallies
• Distribution strongly favors IMP_DN transition (30%): Topping leads to declines
The Viterbi Algorithm:
Given a sequence of observations, how do we find the most likely state sequence? This is the Viterbi algorithm—dynamic programming to find the optimal path through the state space.
Mathematical Formulation:
δ_t(j) = max_i × B_j(O_t)
Where:
δ_t(j) = probability of most likely path ending in state j at time t
A_ij = transition probability from state i to state j
B_j(O_t) = emission probability of observation O_t given state j
AMWT Implementation:
AMWT runs Viterbi over a rolling window (default 50 bars), computing the most likely state sequence and extracting:
• Current state estimate
• State confidence (probability of current state vs alternatives)
• State sequence for pattern detection
Online Learning (Baum-Welch Adaptation):
Unlike static HMMs, AMWT continuously updates its transition and emission matrices based on observed market behavior:
f_onlineUpdateHMM(prev_state, curr_state, observation, decay) =>
// Update transition matrix
A *= decay
A += (1.0 - decay)
// Renormalize row
// Update emission matrix
B *= decay
B += (1.0 - decay)
// Renormalize row
The decay parameter (default 0.85) controls adaptation speed:
• Higher decay (0.95): Slower adaptation, more stable, better for consistent markets
• Lower decay (0.80): Faster adaptation, more reactive, better for regime changes
Why This Matters for Trading:
Traditional indicators give you a number (RSI = 72). AMWT gives you a probabilistic state assessment :
"There is a 78% probability we are in IMPULSE_UP state, with 15% probability of CORRECTION and 7% distributed among other states. The transition matrix suggests 70% chance of remaining in IMPULSE_UP next bar, 20% chance of transitioning to CORRECTION."
This enables:
• Position sizing by confidence : 90% confidence = full size; 60% confidence = half size
• Risk management by transition probability : High correction probability = tighten stops
• Strategy selection by state : IMPULSE = trend-follow; CORRECTION = wait; ACCUMULATION = scale in
🎰 THE 3-BANDIT CONSENSUS SYSTEM
The Multi-Agent Philosophy:
No single analytical methodology works in all market conditions. Trend-following excels in trending markets but gets chopped in ranges. Mean-reversion excels in ranges but gets crushed in trends. Structure-based analysis works when structure is clear but fails in chaotic markets.
AMWT's solution: employ three independent agents , each analyzing the market from a different perspective, then use Thompson Sampling to learn which agents perform best in current conditions.
Agent 1: TREND AGENT
Philosophy : Markets trend. Follow the trend until it ends.
Analytical Components:
• EMA Alignment: EMA8 > EMA21 > EMA50 (bullish) or inverse (bearish)
• MACD Histogram: Direction and rate of change
• Price Momentum: Close relative to ATR-normalized movement
• VWAP Position: Price above/below volume-weighted average price
Signal Generation:
Strong Bull: EMA aligned bull AND MACD histogram > 0 AND momentum > 0.3 AND close > VWAP
→ Signal: +1 (Long), Confidence: 0.75 + |momentum| × 0.4
Moderate Bull: EMA stack bull AND MACD rising AND momentum > 0.1
→ Signal: +1 (Long), Confidence: 0.65 + |momentum| × 0.3
Strong Bear: EMA aligned bear AND MACD histogram < 0 AND momentum < -0.3 AND close < VWAP
→ Signal: -1 (Short), Confidence: 0.75 + |momentum| × 0.4
Moderate Bear: EMA stack bear AND MACD falling AND momentum < -0.1
→ Signal: -1 (Short), Confidence: 0.65 + |momentum| × 0.3
When Trend Agent Excels:
• Trend days (IB extension >1.5x)
• Post-breakout continuation
• Institutional accumulation/distribution phases
When Trend Agent Fails:
• Range-bound markets (ADX <20)
• Chop zones after volatility spikes
• Reversal days at major levels
Agent 2: REVERSION AGENT
Philosophy: Markets revert to mean. Extreme readings reverse.
Analytical Components:
• Bollinger Band Position: Distance from bands, percent B
• RSI Extremes: Overbought (>70) and oversold (<30)
• Stochastic: %K/%D crossovers at extremes
• Band Squeeze: Bollinger Band width contraction
Signal Generation:
Oversold Bounce: BB %B < 0.20 AND RSI < 35 AND Stochastic < 25
→ Signal: +1 (Long), Confidence: 0.70 + (30 - RSI) × 0.01
Overbought Fade: BB %B > 0.80 AND RSI > 65 AND Stochastic > 75
→ Signal: -1 (Short), Confidence: 0.70 + (RSI - 70) × 0.01
Squeeze Fire Bull: Band squeeze ending AND close > upper band
→ Signal: +1 (Long), Confidence: 0.65
Squeeze Fire Bear: Band squeeze ending AND close < lower band
→ Signal: -1 (Short), Confidence: 0.65
When Reversion Agent Excels:
• Rotation days (price stays within IB)
• Range-bound consolidation
• After extended moves without pullback
When Reversion Agent Fails:
• Strong trend days (RSI can stay overbought for days)
• Breakout moves
• News-driven directional moves
Agent 3: STRUCTURE AGENT
Philosophy: Market structure reveals institutional intent. Follow the smart money.
Analytical Components:
• Break of Structure (BOS): Price breaks prior swing high/low
• Change of Character (CHOCH): First break against prevailing trend
• Higher Highs/Higher Lows: Bullish structure
• Lower Highs/Lower Lows: Bearish structure
• Liquidity Sweeps: Stop runs that reverse
Signal Generation:
BOS Bull: Price breaks above prior swing high with momentum
→ Signal: +1 (Long), Confidence: 0.70 + structure_strength × 0.2
CHOCH Bull: First higher low after downtrend, breaking structure
→ Signal: +1 (Long), Confidence: 0.75
BOS Bear: Price breaks below prior swing low with momentum
→ Signal: -1 (Short), Confidence: 0.70 + structure_strength × 0.2
CHOCH Bear: First lower high after uptrend, breaking structure
→ Signal: -1 (Short), Confidence: 0.75
Liquidity Sweep Long: Price sweeps below swing low then reverses strongly
→ Signal: +1 (Long), Confidence: 0.80
Liquidity Sweep Short: Price sweeps above swing high then reverses strongly
→ Signal: -1 (Short), Confidence: 0.80
When Structure Agent Excels:
• After liquidity grabs (stop runs)
• At major swing points
• During institutional accumulation/distribution
When Structure Agent Fails:
• Choppy, structureless markets
• During news events (structure becomes noise)
• Very low timeframes (noise overwhelms structure)
Thompson Sampling: The Bandit Algorithm
With three agents giving potentially different signals, how do we decide which to trust? This is the multi-armed bandit problem —balancing exploitation (using what works) with exploration (testing alternatives).
Thompson Sampling Solution:
Each agent maintains a Beta distribution representing its success/failure history:
Agent success rate modeled as Beta(α, β)
Where:
α = number of successful signals + 1
β = number of failed signals + 1
On Each Bar:
1. Sample from each agent's Beta distribution
2. Weight agent signals by sampled probabilities
3. Combine weighted signals into consensus
4. Update α/β based on trade outcomes
Mathematical Implementation:
// Beta sampling via Gamma ratio method
f_beta_sample(alpha, beta) =>
g1 = f_gamma_sample(alpha)
g2 = f_gamma_sample(beta)
g1 / (g1 + g2)
// Thompson Sampling selection
for each agent:
sampled_prob = f_beta_sample(agent.alpha, agent.beta)
weight = sampled_prob / sum(all_sampled_probs)
consensus += agent.signal × agent.confidence × weight
Why Thompson Sampling?
• Automatic Exploration : Agents with few samples get occasional chances (high variance in Beta distribution)
• Bayesian Optimal : Mathematically proven optimal solution to exploration-exploitation tradeoff
• Uncertainty-Aware : Small sample size = more exploration; large sample size = more exploitation
• Self-Correcting : Poor performers naturally get lower weights over time
Example Evolution:
Day 1 (Initial):
Trend Agent: Beta(1,1) → samples ~0.50 (high uncertainty)
Reversion Agent: Beta(1,1) → samples ~0.50 (high uncertainty)
Structure Agent: Beta(1,1) → samples ~0.50 (high uncertainty)
After 50 Signals:
Trend Agent: Beta(28,23) → samples ~0.55 (moderate confidence)
Reversion Agent: Beta(18,33) → samples ~0.35 (underperforming)
Structure Agent: Beta(32,19) → samples ~0.63 (outperforming)
Result: Structure Agent now receives highest weight in consensus
Consensus Requirements by Mode:
Aggressive Mode:
• Minimum 1/3 agents agreeing
• Consensus threshold: 45%
• Use case: More signals, higher risk tolerance
Balanced Mode:
• Minimum 2/3 agents agreeing
• Consensus threshold: 55%
• Use case: Standard trading
Conservative Mode:
• Minimum 2/3 agents agreeing
• Consensus threshold: 65%
• Use case: Higher quality, fewer signals
Institutional Mode:
• Minimum 2/3 agents agreeing
• Consensus threshold: 75%
• Additional: Session quality >0.65, mode adjustment +0.10
• Use case: Highest quality signals only
🌀 INTELLIGENT CHOP DETECTION ENGINE
The Chop Problem:
Most trading losses occur not from being wrong about direction, but from trading in conditions where direction doesn't exist . Choppy, range-bound markets generate false signals from every methodology—trend-following, mean-reversion, and structure-based alike.
AMWT's chop detection engine identifies these low-probability environments before signals fire, preventing the most damaging trades.
Five-Factor Chop Analysis:
Factor 1: ADX Component (25% weight)
ADX (Average Directional Index) measures trend strength regardless of direction.
ADX < 15: Very weak trend (high chop score)
ADX 15-20: Weak trend (moderate chop score)
ADX 20-25: Developing trend (low chop score)
ADX > 25: Strong trend (minimal chop score)
adx_chop = (i_adxThreshold - adx_val) / i_adxThreshold × 100
Why ADX Works: ADX synthesizes +DI and -DI movements. Low ADX means price is moving but not directionally—the definition of chop.
Factor 2: Choppiness Index (25% weight)
The Choppiness Index measures price efficiency using the ratio of ATR sum to price range:
CI = 100 × LOG10(SUM(ATR, n) / (Highest - Lowest)) / LOG10(n)
CI > 61.8: Choppy (range-bound, inefficient movement)
CI < 38.2: Trending (directional, efficient movement)
CI 38.2-61.8: Transitional
chop_idx_score = (ci_val - 38.2) / (61.8 - 38.2) × 100
Why Choppiness Index Works: In trending markets, price covers distance efficiently (low ATR sum relative to range). In choppy markets, price oscillates wildly but goes nowhere (high ATR sum relative to range).
Factor 3: Range Compression (20% weight)
Compares recent range to longer-term range, detecting volatility squeezes:
recent_range = Highest(20) - Lowest(20)
longer_range = Highest(50) - Lowest(50)
compression = 1 - (recent_range / longer_range)
compression > 0.5: Strong squeeze (potential breakout imminent)
compression < 0.2: No compression (normal volatility)
range_compression_score = compression × 100
Why Range Compression Matters: Compression precedes expansion. High compression = market coiling, preparing for move. Signals during compression often fail because the breakout hasn't occurred yet.
Factor 4: Channel Position (15% weight)
Tracks price position within the macro channel:
channel_position = (close - channel_low) / (channel_high - channel_low)
position 0.4-0.6: Center of channel (indecision zone)
position <0.2 or >0.8: Near extremes (potential reversal or breakout)
channel_chop = abs(0.5 - channel_position) < 0.15 ? high_score : low_score
Why Channel Position Matters: Price in the middle of a range is in "no man's land"—equally likely to go either direction. Signals in the channel center have lower probability.
Factor 5: Volume Quality (15% weight)
Assesses volume relative to average:
vol_ratio = volume / SMA(volume, 20)
vol_ratio < 0.7: Low volume (lack of conviction)
vol_ratio 0.7-1.3: Normal volume
vol_ratio > 1.3: High volume (conviction present)
volume_chop = vol_ratio < 0.8 ? (1 - vol_ratio) × 100 : 0
Why Volume Quality Matters: Low volume moves lack institutional participation. These moves are more likely to reverse or stall.
Combined Chop Intensity:
chopIntensity = (adx_chop × 0.25) + (chop_idx_score × 0.25) +
(range_compression_score × 0.20) + (channel_chop × 0.15) +
(volume_chop × i_volumeChopWeight × 0.15)
Regime Classifications:
Based on chop intensity and component analysis:
• Strong Trend (0-20%): ADX >30, clear directional momentum, trade aggressively
• Trending (20-35%): ADX >20, moderate directional bias, trade normally
• Transitioning (35-50%): Mixed signals, regime change possible, reduce size
• Mid-Range (50-60%): Price trapped in channel center, avoid new positions
• Ranging (60-70%): Low ADX, price oscillating within bounds, fade extremes only
• Compression (70-80%): Volatility squeeze, expansion imminent, wait for breakout
• Strong Chop (80-100%): Multiple chop factors aligned, avoid trading entirely
Signal Suppression:
When chop intensity exceeds the configurable threshold (default 80%), signals are suppressed entirely. The dashboard displays "⚠️ CHOP ZONE" with the current regime classification.
Chop Box Visualization:
When chop is detected, AMWT draws a semi-transparent box on the chart showing the chop zone. This visual reminder helps traders avoid entering positions during unfavorable conditions.
💧 LIQUIDITY ANCHORING SYSTEM
The Liquidity Concept:
Markets move from liquidity pool to liquidity pool. Stop losses cluster at predictable locations—below swing lows (buy stops become sell orders when triggered) and above swing highs (sell stops become buy orders when triggered). Institutions know where these clusters are and often engineer moves to trigger them before reversing.
AMWT identifies and tracks these liquidity events, using them as anchors for signal confidence.
Liquidity Event Types:
Type 1: Volume Spikes
Definition: Volume > SMA(volume, 20) × i_volThreshold (default 2.8x)
Interpretation: Sudden volume surge indicates institutional activity
• Near swing low + reversal: Likely accumulation
• Near swing high + reversal: Likely distribution
• With continuation: Institutional conviction in direction
Type 2: Stop Runs (Liquidity Sweeps)
Definition: Price briefly exceeds swing high/low then reverses within N bars
Detection:
• Price breaks above recent swing high (triggering buy stops)
• Then closes back below that high within 3 bars
• Signal: Bullish stop run complete, reversal likely
Or inverse for bearish:
• Price breaks below recent swing low (triggering sell stops)
• Then closes back above that low within 3 bars
• Signal: Bearish stop run complete, reversal likely
Type 3: Absorption Events
Definition: High volume with small candle body
Detection:
• Volume > 2x average
• Candle body < 30% of candle range
• Interpretation: Large orders being filled without moving price
• Implication: Accumulation (at lows) or distribution (at highs)
Type 4: BSL/SSL Pools (Buy-Side/Sell-Side Liquidity)
BSL (Buy-Side Liquidity):
• Cluster of swing highs within ATR proximity
• Stop losses from shorts sit above these highs
• Breaking BSL triggers short covering (fuel for rally)
SSL (Sell-Side Liquidity):
• Cluster of swing lows within ATR proximity
• Stop losses from longs sit below these lows
• Breaking SSL triggers long liquidation (fuel for decline)
Liquidity Pool Mapping:
AMWT continuously scans for and maps liquidity pools:
// Detect swing highs/lows using pivot function
swing_high = ta.pivothigh(high, 5, 5)
swing_low = ta.pivotlow(low, 5, 5)
// Track recent swing points
if not na(swing_high)
bsl_levels.push(swing_high)
if not na(swing_low)
ssl_levels.push(swing_low)
// Display on chart with labels
Confluence Scoring Integration:
When signals fire near identified liquidity events, confluence scoring increases:
• Signal near volume spike: +10% confidence
• Signal after liquidity sweep: +15% confidence
• Signal at BSL/SSL pool: +10% confidence
• Signal aligned with absorption zone: +10% confidence
Why Liquidity Anchoring Matters:
Signals "in a vacuum" have lower probability than signals anchored to institutional activity. A long signal after a liquidity sweep below swing lows has trapped shorts providing fuel. A long signal in the middle of nowhere has no such catalyst.
📊 SIGNAL GRADING SYSTEM
The Quality Problem:
Not all signals are created equal. A signal with 6/6 factors aligned is fundamentally different from a signal with 3/6 factors aligned. Traditional indicators treat them the same. AMWT grades every signal based on confluence.
Confluence Components (100 points total):
1. Bandit Consensus Strength (25 points)
consensus_str = weighted average of agent confidences
score = consensus_str × 25
Example:
Trend Agent: +1 signal, 0.80 confidence, 0.35 weight
Reversion Agent: 0 signal, 0.50 confidence, 0.25 weight
Structure Agent: +1 signal, 0.75 confidence, 0.40 weight
Weighted consensus = (0.80×0.35 + 0×0.25 + 0.75×0.40) / (0.35 + 0.40) = 0.77
Score = 0.77 × 25 = 19.25 points
2. HMM State Confidence (15 points)
score = hmm_confidence × 15
Example:
HMM reports 82% probability of IMPULSE_UP
Score = 0.82 × 15 = 12.3 points
3. Session Quality (15 points)
Session quality varies by time:
• London/NY Overlap: 1.0 (15 points)
• New York Session: 0.95 (14.25 points)
• London Session: 0.70 (10.5 points)
• Asian Session: 0.40 (6 points)
• Off-Hours: 0.30 (4.5 points)
• Weekend: 0.10 (1.5 points)
4. Energy/Participation (10 points)
energy = (realized_vol / avg_vol) × 0.4 + (range / ATR) × 0.35 + (volume / avg_volume) × 0.25
score = min(energy, 1.0) × 10
5. Volume Confirmation (10 points)
if volume > SMA(volume, 20) × 1.5:
score = 10
else if volume > SMA(volume, 20):
score = 5
else:
score = 0
6. Structure Alignment (10 points)
For long signals:
• Bullish structure (HH + HL): 10 points
• Higher low only: 6 points
• Neutral structure: 3 points
• Bearish structure: 0 points
Inverse for short signals
7. Trend Alignment (10 points)
For long signals:
• Price > EMA21 > EMA50: 10 points
• Price > EMA21: 6 points
• Neutral: 3 points
• Against trend: 0 points
8. Entry Trigger Quality (5 points)
• Strong trigger (multiple confirmations): 5 points
• Moderate trigger (single confirmation): 3 points
• Weak trigger (marginal): 1 point
Grade Scale:
Total Score → Grade
85-100 → A+ (Exceptional—all factors aligned)
70-84 → A (Strong—high probability)
55-69 → B (Acceptable—proceed with caution)
Below 55 → C (Marginal—filtered by default)
Grade-Based Signal Brightness:
Signal arrows on the chart have transparency based on grade:
• A+: Full brightness (alpha = 0)
• A: Slight fade (alpha = 15)
• B: Moderate fade (alpha = 35)
• C: Significant fade (alpha = 55)
This visual hierarchy helps traders instantly identify signal quality.
Minimum Grade Filter:
Configurable filter (default: C) sets the minimum grade for signal display:
• Set to "A" for only highest-quality signals
• Set to "B" for moderate selectivity
• Set to "C" for all signals (maximum quantity)
🕐 SESSION INTELLIGENCE
Why Sessions Matter:
Markets behave differently at different times. The London open is fundamentally different from the Asian lunch hour. AMWT incorporates session-aware logic to optimize signal quality.
Session Definitions:
Asian Session (18:00-03:00 ET)
• Characteristics: Lower volatility, range-bound tendency, fewer institutional participants
• Quality Score: 0.40 (40% of peak quality)
• Strategy Implications: Fade extremes, expect ranges, smaller position sizes
• Best For: Mean-reversion setups, accumulation/distribution identification
London Session (03:00-12:00 ET)
• Characteristics: European institutional activity, volatility pickup, trend initiation
• Quality Score: 0.70 (70% of peak quality)
• Strategy Implications: Watch for trend development, breakouts more reliable
• Best For: Initial trend identification, structure breaks
New York Session (08:00-17:00 ET)
• Characteristics: Highest liquidity, US institutional activity, major moves
• Quality Score: 0.95 (95% of peak quality)
• Strategy Implications: Best environment for directional trades
• Best For: Trend continuation, momentum plays
London/NY Overlap (08:00-12:00 ET)
• Characteristics: Peak liquidity, both European and US participants active
• Quality Score: 1.0 (100%—maximum quality)
• Strategy Implications: Highest probability for successful breakouts and trends
• Best For: All signal types—this is prime time
Off-Hours
• Characteristics: Thin liquidity, erratic price action, gaps possible
• Quality Score: 0.30 (30% of peak quality)
• Strategy Implications: Avoid new positions, wider stops if holding
• Best For: Waiting
Smart Weekend Detection:
AMWT properly handles the Sunday evening futures open:
// Traditional (broken):
isWeekend = dayofweek == saturday OR dayofweek == sunday
// AMWT (correct):
anySessionActive = not na(asianTime) or not na(londonTime) or not na(nyTime)
isWeekend = calendarWeekend AND NOT anySessionActive
This ensures Sunday 6pm ET (when futures open) correctly shows "Asian Session" rather than "Weekend."
Session Transition Boosts:
Certain session transitions create trading opportunities:
• Asian → London transition: +15% confidence boost (volatility expansion likely)
• London → Overlap transition: +20% confidence boost (peak liquidity approaching)
• Overlap → NY-only transition: -10% confidence adjustment (liquidity declining)
• Any → Off-Hours transition: Signal suppression recommended
📈 TRADE MANAGEMENT SYSTEM
The Signal Spam Problem:
Many indicators generate signal after signal, creating confusion and overtrading. AMWT implements a complete trade lifecycle management system that prevents signal spam and tracks performance.
Trade Lock Mechanism:
Once a signal fires, the system enters a "trade lock" state:
Trade Lock Duration: Configurable (default 30 bars)
Early Exit Conditions:
• TP3 hit (full target reached)
• Stop Loss hit (trade failed)
• Lock expiration (time-based exit)
During lock:
• No new signals of same type displayed
• Opposite signals can override (reversal)
• Trade status tracked in dashboard
Target Levels:
Each signal generates three profit targets based on ATR:
TP1 (Conservative Target)
• Default: 1.0 × ATR
• Purpose: Quick partial profit, reduce risk
• Action: Take 30-40% off position, move stop to breakeven
TP2 (Standard Target)
• Default: 2.5 × ATR
• Purpose: Main profit target
• Action: Take 40-50% off position, trail stop
TP3 (Extended Target)
• Default: 5.0 × ATR
• Purpose: Runner target for trend days
• Action: Close remaining position or continue trailing
Stop Loss:
• Default: 1.9 × ATR from entry
• Purpose: Define maximum risk
• Placement: Below recent swing low (longs) or above recent swing high (shorts)
Invalidation Level:
Beyond stop loss, AMWT calculates an "invalidation" level where the wave hypothesis dies:
invalidation = entry - (ATR × INVALIDATION_MULT × 1.5)
If price reaches invalidation, the current market interpretation is wrong—not just the trade.
Visual Trade Management:
During active trades, AMWT displays:
• Entry arrow with grade label (▲A+, ▼B, etc.)
• TP1, TP2, TP3 horizontal lines in green
• Stop Loss line in red
• Invalidation line in orange (dashed)
• Progress indicator in dashboard
Persistent Execution Markers:
When targets or stops are hit, permanent markers appear:
• TP hit: Green dot with "TP1"/"TP2"/"TP3" label
• SL hit: Red dot with "SL" label
These persist on the chart for review and statistics.
💰 PERFORMANCE TRACKING & STATISTICS
Tracked Metrics:
• Total Trades: Count of all signals that entered trade lock
• Winning Trades: Signals where at least TP1 was reached before SL
• Losing Trades: Signals where SL was hit before any TP
• Win Rate: Winning / Total × 100%
• Total R Profit: Sum of R-multiples from winning trades
• Total R Loss: Sum of R-multiples from losing trades
• Net R: Total R Profit - Total R Loss
Currency Conversion System:
AMWT can display P&L in multiple formats:
R-Multiple (Default)
• Shows risk-normalized returns
• "Net P&L: +4.2R | 78 trades" means 4.2 times initial risk gained over 78 trades
• Best for comparing across different position sizes
Currency Conversion (USD/EUR/GBP/JPY/INR)
• Converts R-multiples to currency based on:
- Dollar Risk Per Trade (user input)
- Tick Value (user input)
- Selected currency
Example Configuration:
Dollar Risk Per Trade: $100
Display Currency: USD
If Net R = +4.2R
Display: Net P&L: +$420.00 | 78 trades
Ticks
• For futures traders who think in ticks
• Converts based on tick value input
Statistics Reset:
Two reset methods:
1. Toggle Reset
• Turn "Reset Statistics" toggle ON then OFF
• Clears all statistics immediately
2. Date-Based Reset
• Set "Reset After Date" (YYYY-MM-DD format)
• Only trades after this date are counted
• Useful for isolating recent performance
🎨 VISUAL FEATURES
Macro Channel:
Dynamic regression-based channel showing market boundaries:
• Upper/lower bounds calculated from swing pivot linear regression
• Adapts to current market structure
• Shows overall trend direction and potential reversal zones
Chop Boxes:
Semi-transparent overlay during high-chop periods:
• Purple/orange coloring indicates dangerous conditions
• Visual reminder to avoid new positions
Confluence Heat Zones:
Background shading indicating setup quality:
• Darker shading = higher confluence
• Lighter shading = lower confluence
• Helps identify optimal entry timing
EMA Ribbon:
Trend visualization via moving average fill:
• EMA 8/21/50 with gradient fill between
• Green fill when bullish aligned
• Red fill when bearish aligned
• Gray when neutral
Absorption Zone Boxes:
Marks potential accumulation/distribution areas:
• High volume + small body = absorption
• Boxes drawn at these levels
• Often act as support/resistance
Liquidity Pool Lines:
BSL/SSL levels with labels:
• Dashed lines at liquidity clusters
• "BSL" label above swing high clusters
• "SSL" label below swing low clusters
Six Professional Themes:
• Quantum: Deep purples and cyans (default)
• Cyberpunk: Neon pinks and blues
• Professional: Muted grays and greens
• Ocean: Blues and teals
• Matrix: Greens and blacks
• Ember: Oranges and reds
🎓 PROFESSIONAL USAGE PROTOCOL
Phase 1: Learning the System (Week 1)
Goal: Understand AMWT concepts and dashboard interpretation
Setup:
• Signal Mode: Balanced
• Display: All features enabled
• Grade Filter: C (see all signals)
Actions:
• Paper trade ONLY—no real money
• Observe HMM state transitions throughout the day
• Note when agents agree vs disagree
• Watch chop detection engage and disengage
• Track which grades produce winners vs losers
Key Learning Questions:
• How often do A+ signals win vs B signals? (Should see clear difference)
• Which agent tends to be right in current market? (Check dashboard)
• When does chop detection save you from bad trades?
• How do signals near liquidity events perform vs signals in vacuum?
Phase 2: Parameter Optimization (Week 2)
Goal: Tune system to your instrument and timeframe
Signal Mode Testing:
• Run 5 days on Aggressive mode (more signals)
• Run 5 days on Conservative mode (fewer signals)
• Compare: Which produces better risk-adjusted returns?
Grade Filter Testing:
• Track A+ only for 20 signals
• Track A and above for 20 signals
• Track B and above for 20 signals
• Compare win rates and expectancy
Chop Threshold Testing:
• Default (80%): Standard filtering
• Try 70%: More aggressive filtering
• Try 90%: Less filtering
• Which produces best results for your instrument?
Phase 3: Strategy Development (Weeks 3-4)
Goal: Develop personal trading rules based on system signals
Position Sizing by Grade:
• A+ grade: 100% position size
• A grade: 75% position size
• B grade: 50% position size
• C grade: 25% position size (or skip)
Session-Based Rules:
• London/NY Overlap: Take all A/A+ signals
• NY Session: Take all A+ signals, selective on A
• Asian Session: Only A+ signals with extra confirmation
• Off-Hours: No new positions
Chop Zone Rules:
• Chop >70%: Reduce position size 50%
• Chop >80%: No new positions
• Chop <50%: Full position size allowed
Phase 4: Live Micro-Sizing (Month 2)
Goal: Validate paper trading results with minimal risk
Setup:
• 10-20% of intended full position size
• Take ONLY A+ signals initially
• Follow trade management religiously
Tracking:
• Log every trade: Entry, Exit, Grade, HMM State, Chop Level, Agent Consensus
• Calculate: Win rate by grade, by session, by chop level
• Compare to paper trading (should be within 15%)
Red Flags:
• Win rate diverges significantly from paper trading: Execution issues
• Consistent losses during certain sessions: Adjust session rules
• Losses cluster when specific agent dominates: Review that agent's logic
Phase 5: Scaling Up (Months 3-6)
Goal: Gradually increase to full position size
Progression:
• Month 3: 25-40% size (if micro-sizing profitable)
• Month 4: 40-60% size
• Month 5: 60-80% size
• Month 6: 80-100% size
Scale-Up Requirements:
• Minimum 30 trades at current size
• Win rate ≥50%
• Net R positive
• No revenge trading incidents
• Emotional control maintained
💡 DEVELOPMENT INSIGHTS
Why HMM Over Simple Indicators:
Early versions used standard indicators (RSI >70 = overbought, etc.). Win rates hovered at 52-55%. The problem: indicators don't capture state. RSI can stay "overbought" for weeks in a strong trend.
The insight: markets exist in states, and state persistence matters more than indicator levels. Implementing HMM with state transition probabilities increased signal quality significantly. The system now knows not just "RSI is high" but "we're in IMPULSE_UP state with 70% probability of staying in IMPULSE_UP."
The Multi-Agent Evolution:
Original version used a single analytical methodology—trend-following. Performance was inconsistent: great in trends, destroyed in ranges. Added mean-reversion agent: now it was inconsistent the other way.
The breakthrough: use multiple agents and let the system learn which works . Thompson Sampling wasn't the first attempt—tried simple averaging, voting, even hard-coded regime switching. Thompson Sampling won because it's mathematically optimal and automatically adapts without manual regime detection.
Chop Detection Revelation:
Chop detection was added almost as an afterthought. "Let's filter out obviously bad conditions." Testing revealed it was the most impactful single feature. Filtering chop zones reduced losing trades by 35% while only reducing total signals by 20%. The insight: avoiding bad trades matters more than finding good ones.
Liquidity Anchoring Discovery:
Watched hundreds of trades. Noticed pattern: signals that fired after liquidity events (stop runs, volume spikes) had significantly higher win rates than signals in quiet markets. Implemented liquidity detection and anchoring. Win rate on liquidity-anchored signals: 68% vs 52% on non-anchored signals.
The Grade System Impact:
Early system had binary signals (fire or don't fire). Adding grading transformed it. Traders could finally match position size to signal quality. A+ signals deserved full size; C signals deserved caution. Just implementing grade-based sizing improved portfolio Sharpe ratio by 0.3.
🚨 LIMITATIONS & CRITICAL ASSUMPTIONS
What AMWT Is NOT:
• NOT a Holy Grail : No system wins every trade. AMWT improves probability, not certainty.
• NOT Fully Automated : AMWT provides signals and analysis; execution requires human judgment.
• NOT News-Proof : Exogenous shocks (FOMC surprises, geopolitical events) invalidate all technical analysis.
• NOT for Scalping : HMM state estimation needs time to develop. Sub-minute timeframes are not appropriate.
Core Assumptions:
1. Markets Have States : Assumes markets transition between identifiable regimes. Violation: Random walk markets with no regime structure.
2. States Are Inferable : Assumes observable indicators reveal hidden states. Violation: Market manipulation creating false signals.
3. History Informs Future : Assumes past agent performance predicts future performance. Violation: Regime changes that invalidate historical patterns.
4. Liquidity Events Matter : Assumes institutional activity creates predictable patterns. Violation: Markets with no institutional participation.
Performs Best On:
• Liquid Futures : ES, NQ, MNQ, MES, CL, GC
• Major Forex Pairs : EUR/USD, GBP/USD, USD/JPY
• Large-Cap Stocks : AAPL, MSFT, TSLA, NVDA (>$5B market cap)
• Liquid Crypto : BTC, ETH on major exchanges
Performs Poorly On:
• Illiquid Instruments : Low volume stocks, exotic pairs
• Very Low Timeframes : Sub-5-minute charts (noise overwhelms signal)
• Binary Event Days : Earnings, FDA approvals, court rulings
• Manipulated Markets : Penny stocks, low-cap altcoins
Known Weaknesses:
• Warmup Period : HMM needs ~50 bars to initialize properly. Early signals may be unreliable.
• Regime Change Lag : Thompson Sampling adapts over time, not instantly. Sudden regime changes may cause short-term underperformance.
• Complexity : More parameters than simple indicators. Requires understanding to use effectively.
⚠️ RISK DISCLOSURE
Trading futures, stocks, options, forex, and cryptocurrencies involves substantial risk of loss and is not suitable for all investors. Adaptive Market Wave Theory, while based on rigorous mathematical frameworks including Hidden Markov Models and multi-armed bandit algorithms, does not guarantee profits and can result in significant losses.
AMWT's methodologies—HMM state estimation, Thompson Sampling agent selection, and confluence-based grading—have theoretical foundations but past performance is not indicative of future results.
Hidden Markov Model assumptions may not hold during:
• Major news events disrupting normal market behavior
• Flash crashes or circuit breaker events
• Low liquidity periods with erratic price action
• Algorithmic manipulation or spoofing
Multi-agent consensus assumes independent analytical perspectives provide edge. Market conditions change. Edges that existed historically can diminish or disappear.
Users must independently validate system performance on their specific instruments, timeframes, and broker execution environment. Paper trade extensively before risking capital. Start with micro position sizing.
Never risk more than you can afford to lose completely. Use proper position sizing. Implement stop losses without exception.
By using this indicator, you acknowledge these risks and accept full responsibility for all trading decisions and outcomes.
"Elliott Wave was a first-order approximation of market phase behavior. AMWT is the second—probabilistic, adaptive, and accountable."
Initial Public Release
Core Engine:
• True Hidden Markov Model with online Baum-Welch learning
• Viterbi algorithm for optimal state sequence decoding
• 6-state market regime classification
Agent System:
• 3-Bandit consensus (Trend, Reversion, Structure)
• Thompson Sampling with true Beta distribution sampling
• Adaptive weight learning based on performance
Signal Generation:
• Quality-based confluence grading (A+/A/B/C)
• Four signal modes (Aggressive/Balanced/Conservative/Institutional)
• Grade-based visual brightness
Chop Detection:
• 5-factor analysis (ADX, Choppiness Index, Range Compression, Channel Position, Volume)
• 7 regime classifications
• Configurable signal suppression threshold
Liquidity:
• Volume spike detection
• Stop run (liquidity sweep) identification
• BSL/SSL pool mapping
• Absorption zone detection
Trade Management:
• Trade lock with configurable duration
• TP1/TP2/TP3 targets
• ATR-based stop loss
• Persistent execution markers
Session Intelligence:
• Asian/London/NY/Overlap detection
• Smart weekend handling (Sunday futures open)
• Session quality scoring
Performance:
• Statistics tracking with reset functionality
• 7 currency display modes
• Win rate and Net R calculation
Visuals:
• Macro channel with linear regression
• Chop boxes
• EMA ribbon
• Liquidity pool lines
• 6 professional themes
Dashboards:
• Main Dashboard: Market State, Consensus, Trade Status, Statistics
📋 AMWT vs AMWT-PRO:
This version includes all core AMWT functionality:
✓ Full Hidden Markov Model state estimation
✓ 3-Bandit Thompson Sampling consensus system
✓ Complete 5-factor chop detection engine
✓ All four signal modes
✓ Full trade management with TP/SL tracking
✓ Main dashboard with complete statistics
✓ All visual features (channels, zones, pools)
✓ Identical signal generation to PRO
✓ Six professional themes
✓ Full alert system
The PRO version adds the AMWT Advisor panel—a secondary dashboard providing:
• Real-time Market Pulse situation assessment
• Agent Matrix visualization (individual agent votes)
• Structure analysis breakdown
• "Watch For" upcoming setups
• Action Command coaching
Both versions generate identical signals . The Advisor provides additional guidance for interpreting those signals.
Taking you to school. - Dskyz, Trade with probability. Trade with consensus. Trade with AMWT.
Esmeralda.AiHow to read the new visuals:
Labels: When a signal appears, the label now calculates the exact price for your Stop Loss (SL) and Take Profit (TP).
Lines: You will see short horizontal lines appear at the signal bar.
Green Line: This is your target.
Red Line: This is where you exit if the trade goes against you.
The 90% Rule: To keep the win rate as high as possible, you can manually move your TP to the Yellow Mean Line if the market looks like it is losing steam.
Luxy VWAP Magic - MTF Projection EngineThis indicator transforms the classic VWAP into a comprehensive trading system. Instead of switching between multiple indicators, you get everything in one place: multi-timeframe analysis, statistical bands, momentum detection, volume profiling, session tracking, and divergence signals.
What Makes This Different
Traditional VWAP indicators show a single line. This tool treats VWAP as a foundation for complete market analysis. The indicator automatically detects your asset type (stocks, crypto, forex, futures) and adjusts its behavior accordingly. Crypto traders get 24/7 session tracking. Stock traders get proper market hours handling. Everyone gets institutional-grade analytics.
Anchor Period Options
The anchor period determines when VWAP resets and recalculates. You have three categories of options:
Time-Based Anchors:
Session - Resets at market open. Best for intraday stock trading where you want fresh VWAP each day.
Day - Resets at midnight UTC. Standard option for most traders.
Week / Month / Quarter / Year - Longer reset periods for swing traders and position traders who want broader context.
Rolling Window Anchors:
Rolling 5D - A sliding 5-day window that never resets. Solves the Monday problem where weekly VWAP equals daily VWAP on first day of week.
Rolling 21D - Approximately one month of trading data in continuous calculation. Excellent for crypto and forex markets that trade 24/7 without clear session breaks.
Event-Based Anchors:
Dividends - Resets on ex-dividend dates. Track institutional cost basis from dividend events.
Splits - Resets on stock split dates. Useful for analyzing post-split trading behavior.
Earnings - Resets on earnings report dates. See where volume-weighted trading occurred since last quarterly report.
Standard Deviation Bands
Three sets of bands surround the main VWAP line:
Band 1 (Aqua) - Plus and minus one standard deviation. Approximately 68% of price action occurs within this range under normal distribution. Touches suggest minor extension.
Band 2 (Fuchsia) - Plus and minus two standard deviations. Only 5% of trading should occur outside this range statistically. Touches here indicate significant overextension and high probability of mean reversion.
Band 3 (Purple) - Plus and minus three standard deviations. Touches are rare (0.3% probability) and represent extreme conditions. Often marks climax moves or panic selling/buying.
Each band can be toggled independently. Most traders show Band 1 by default and add Band 2 and 3 for specific setups or volatile instruments.
Multi-Timeframe VWAP System
The MTF section plots previous period VWAPs as horizontal support and resistance levels:
Daily VWAP - Previous day's final VWAP value. Key intraday reference level.
Weekly VWAP - Previous week's final VWAP. Important for swing traders.
Monthly VWAP - Previous month's final VWAP. Institutional benchmark level.
Quarterly VWAP - Previous quarter's final VWAP. Major support/resistance for position traders.
Previous Day VWAP - Yesterday's closing VWAP specifically, separate from current daily calculation.
The Confluence Zone percentage setting determines how close multiple VWAPs must be to trigger a confluence alert. When two or more timeframe VWAPs converge within this threshold, you get a high-probability support/resistance zone.
Session VWAPs for Global Markets
For forex, crypto, and futures traders who operate in 24/7 markets, the indicator tracks three major global sessions:
Asia Session - UTC 21:00 to 08:00. Gold colored line. Typically lower volatility, range-bound action that sets overnight levels.
London Session - UTC 08:00 to 17:00. Orange colored line. Often determines daily direction with high volume European participation.
New York Session - UTC 13:00 to 22:00. Blue colored line. Highest volume session globally. Sharp directional moves common.
Previous session VWAP values display as horizontal lines when each session closes, acting as intraday support and resistance. The table shows which sessions are currently active with checkmarks.
On-Chart Labels and Signals
The indicator plots several types of labels directly on price action when significant events occur:
Volume Spike Labels
Fire when current bar volume exceeds configurable thresholds relative to both the previous bar and the 20-bar average. Default settings require 300% of previous bar AND 200% of average volume. Green labels indicate bullish candles. Red labels indicate bearish candles. These spikes often mark institutional entry points.
Momentum Shift Labels
Appear when VWAP acceleration changes direction. The Slowing label warns when an active trend loses steam, often preceding reversal. The Accelerating label confirms trend continuation or potential bottom during downtrends. Filters available to show only reversal signals in existing trends.
VWAP Squeeze Labels
Detect when standard deviation bands contract relative to ATR (Average True Range). Low volatility compression often precedes explosive breakout moves. When the squeeze fires (releases), a label appears with directional prediction based on VWAP slope.
Divergence Labels
Mark price/volume divergences using CVD (Cumulative Volume Delta) analysis:
Bullish divergence: Price makes lower low, but CVD makes higher low. Hidden accumulation despite price weakness.
Bearish divergence: Price makes higher high, but CVD makes lower high. Hidden distribution despite price strength.
Dynamic VWAP Coloring
The main VWAP line changes color based on its slope direction:
Green - VWAP is rising. Institutional buying pressure. Volume-weighted price increasing.
Red - VWAP is falling. Institutional selling pressure. Volume-weighted price decreasing.
Gray - VWAP is flat. Consolidation or balance between buyers and sellers.
This coloring can be disabled for a static blue line if you prefer cleaner visuals. The VWAP label next to the line shows the current trend direction and delta percentage.
Calculated Projection Cone
One of the most powerful features is the Calculated Projection Cone. Unlike traditional extrapolation methods that simply extend a trend line forward, this system analyzes what actually happened in similar market conditions throughout the chart's history.
How It Works:
The system classifies each bar into one of 27 unique market states:
Z-Score Level - LOW (oversold), MID (fair value), or HIGH (overbought) based on configurable thresholds
Trend Direction - DOWN, FLAT, or UP based on VWAP slope
Volume Profile - LOW (below 80%), NORMAL (80-150%), or HIGH (above 150%) relative volume
When you look at the current bar, the indicator:
1. Identifies the current market state (e.g., LOW Z-Score + UP Trend + HIGH Volume)
2. Searches through all historical bars on the chart that had the same state
3. Calculates what happened in those bars X bars later (where X is your projection horizon)
4. Shows you the probability of up/down and the average move size
Visual Elements:
Probability Cone - Colored green (bullish probability above 55%), red (bearish below 45%), or gold (neutral). The cone width represents the historical range of outcomes (roughly the 20th to 80th percentile).
Center Line - Shows the average expected price based on historical outcomes in similar conditions.
Probability Label - Displays direction probability and average move. Example: "67% UP (+0.8%)" means 67% of similar past cases moved up, averaging 0.8% gain.
Fallback System:
When the exact 27-state match has insufficient historical data:
First fallback: Uses Z-Score plus Trend only (9 broader states, ignoring volume)
Second fallback: Uses Z-Score only (3 states)
When fallback is active, confidence automatically adjusts
Settings:
Projection Horizon - How many bars forward to analyze outcomes (5, 10, 15, or 20 bars, default 10)
Lookback Period - Historical data window in days (30-252, default 60)
Minimum Samples - Cases needed before using fallback (5-30, default 10)
Z-Score Threshold - Bucket boundary for LOW/MID/HIGH classification (1.0, 1.5, or 2.0 sigma)
Cloud Transparency - Adjust visibility (50-95%)
Colors - Customize bullish, bearish, and neutral cone colors
Confidence Levels:
HIGH - 30 or more similar historical cases found
MEDIUM - 15-29 similar cases
LOW - Fewer than 15 cases (more uncertainty)
IMPORTANT DISCLAIMER:
The Calculated Projection is based on past patterns only. It is NOT a price prediction or financial advice. Similar market states in the past do not guarantee similar outcomes in the future. The probability shown is historical frequency, not a guarantee. Always combine with other analysis and never rely solely on projections for trading decisions.
Alert Conditions
The indicator includes over 20 pre-built alert conditions:
Price vs VWAP:
Price crosses above VWAP
Price crosses below VWAP
Band Touches:
Price touches plus or minus one sigma band
Price touches plus or minus two sigma band (extreme)
Price touches plus or minus three sigma band (very extreme)
Z-Score Extremes:
Z-Score crosses above plus two (overbought extreme)
Z-Score crosses below minus two (oversold extreme)
Momentum and Trend:
Momentum slowing
Momentum accelerating
Trend turns bullish/bearish/neutral
Volume:
Volume spike detected
CVD Direction:
Buyers take control
Sellers take control
High Probability Signals:
Bullish reversal signal (oversold plus accelerating momentum)
Bearish reversal signal (overbought plus slowing momentum)
MTF and Special:
MTF confluence zone entry
VWAP squeeze fired
Bullish/Bearish divergence detected
Any significant signal (catch-all)
All signals use confirmed bar data to prevent false alerts from incomplete candles.
Settings Overview
Settings are organized into logical groups:
VWAP Settings
Anchor Period selection
Show/Hide VWAP line
Dynamic coloring toggle
VWAP label visibility
Bands Visibility
Toggle each of three bands independently
Info Table
Show/Hide table
Table position (9 options)
Text size
Volume spike label settings with adjustable thresholds
Momentum label settings with filters
Signal labels limited to 5 most recent (auto-managed)
Probability engine lookback period
Multi-Timeframe VWAP
Enable/Disable MTF system
Show MTF in table
Show MTF lines on chart
Individual timeframe toggles
Confluence zone threshold
Squeeze detection toggle
Session VWAPs
Enable/Disable session tracking
Apply to all assets option
Show session labels
Divergence Detection
Enable/Disable divergence
Pivot lookback period
Show divergence labels
Calculated Projection
Enable/Disable projection cone
Projection horizon (5, 10, 15, or 20 bars)
Lookback period in days (30-252)
Minimum samples threshold
Z-Score classification threshold (1.0, 1.5, or 2.0 sigma)
Cloud transparency adjustment
Bullish, bearish, and neutral colors
The Info Table - Your Trading Dashboard
The right side of your chart displays a compact table with up to twelve metrics.
Row-by-Row Breakdown:
Asset and Period - Shows what the indicator detected (US Stock, Crypto, Forex, etc.) and your selected anchor period. The detection happens automatically based on exchange data, so VWAP resets and calculations match your actual trading instrument.
Delta Percentage - How far current price sits from VWAP, expressed as a percentage. Positive means price trades above fair value. Negative means below. Large delta values (beyond 1-2%) often precede mean reversion moves. Day traders watch this for overextension.
Z-Score - Statistical deviation from VWAP measured in standard deviations. Unlike raw delta, Z-Score accounts for volatility. A 2% move in a volatile biotech stock differs from 2% in a stable utility. Z-Score normalizes this. Values beyond plus or minus two sigma occur only 5% of the time statistically.
Trend Direction - Whether VWAP itself is rising, falling, or flat. Rising VWAP means the volume-weighted average price is increasing, which indicates institutional accumulation. Falling VWAP suggests distribution. This differs from price trend since it weights by volume.
Momentum State - Is the trend accelerating or slowing down? This measures the rate of change in VWAP slope. When an uptrend shows slowing momentum, it often precedes reversal. Accelerating momentum in a downtrend can signal capitulation and potential bottom.
Relative Volume - Current bar volume compared to the 20-bar average, shown as percentage. Values above 150% indicate above-average activity. Spikes above 200-300% often mark institutional involvement. Low volume (below 80%) warns of potential fake moves.
MTF Bias - Four checkmarks or X marks showing whether price sits above or below Daily, Weekly, Monthly, and Quarterly VWAP. Four checkmarks means strong bullish alignment across all timeframes. Four X marks indicates bearish alignment. Mixed readings suggest consolidation or transition.
Band Probabilities - Historical statistics showing how often price touched each standard deviation band over your lookback period. This helps you understand if mean reversion or trend following works better for your specific instrument.
Session Status - Which global trading sessions are currently active (Asia, London, New York). Shows checkmarks for active sessions. Important for forex and crypto traders who need to know when major liquidity windows open and close.
Divergence State - Whether the indicator detects bullish or bearish divergence between price and cumulative volume delta. Bullish divergence occurs when price makes lower lows but buying pressure (CVD) makes higher lows, suggesting hidden accumulation.
Confidence Score - A weighted composite of all factors displayed as a progress bar and percentage. Combines MTF alignment, Z-Score, trend direction, volume delta, momentum, and relative volume into a single 0-100 score. Higher scores indicate stronger conviction setups.
Calculated Projection - When the Projection Cone is enabled, shows the historical probability of price direction and expected move. For example: "▲ 67% (+0.8%)" means in similar market states historically, price moved up 67% of the time with an average gain of 0.8%. The system analyzes 27 unique market states based on Z-Score, Trend, and Volume conditions.
Recommended Use Cases
Day Trading Stocks:
Use Session anchor with Band 1 visible. Watch for price returning to VWAP after morning move. Volume spikes near VWAP often mark institutional accumulation zones.
Swing Trading:
Use Weekly or Rolling 21D anchor. Enable MTF lines for Daily and Weekly levels. Trade pullbacks to these levels in direction of MTF bias.
Crypto and Forex:
Enable Session VWAPs. Use Rolling anchors to avoid artificial resets. Monitor session transitions for breakout opportunities.
Mean Reversion:
Focus on Z-Score reaching plus or minus two. Add Band 2 visibility. Combine with slowing momentum for highest probability reversals.
Trend Following:
Watch MTF bias alignment. Four checkmarks plus accelerating momentum plus high volume confirms trend continuation setups.
Projection Planning:
Enable the Calculated Projection to see what happened historically in similar market conditions. Use 5-10 bars for intraday setups, 15-20 bars for swing trade planning. Focus on high probability readings (above 60%) with HIGH confidence (30 or more samples). The cone shows the probable range of outcomes based on actual historical data. Combine with other factors like MTF alignment and volume for higher conviction setups.
Important Notes
The indicator does not repaint. MTF values use previous period's confirmed data.
Rolling VWAP works best on 15-minute timeframes and above due to bar lookback requirements.
Session VWAPs apply to global markets by default (forex, crypto, futures). Enable the all-assets option for stocks if desired.
Volume data for forex represents tick volume, not actual traded volume.
All alert conditions fire only on confirmed (closed) bars to prevent false signals.
The Calculated Projection updates each bar as market state changes. This is expected behavior. The projection shows probabilities based on similar past conditions, not a fixed prediction.
Q AND A
Q: Does this indicator repaint?
A: No. The main VWAP calculation uses standard TradingView VWAP methodology. Multi-timeframe values use previous period's confirmed data with appropriate lookahead settings. All alert signals require bar confirmation.
Q: Why does my Rolling VWAP look different on 1-minute versus 15-minute charts?
A: Rolling VWAP calculates across a fixed number of trading days. On very short timeframes, the bar lookback may hit TradingView limits. For best Rolling VWAP accuracy, use 15-minute or higher timeframes.
Q: Can I use this on any instrument?
A: Yes. The indicator automatically detects asset type and adjusts behavior. Stocks use standard market hours. Crypto uses 24/7 calculations. Forex uses tick volume. Everything adapts automatically.
Q: What does the Confidence Score actually measure?
A: The score combines six weighted factors: MTF alignment (25%), Z-Score position (20%), Trend direction (20%), CVD pressure (15%), Momentum state (10%), and Relative volume (10%). Higher scores indicate more factors aligned in one direction.
Q: Why are Session VWAPs not showing on my stock chart?
A: Session VWAPs apply to 24-hour markets by default (forex, crypto, futures). For stocks, enable the Use for All Assets option in Session VWAP settings.
Q: The Divergence labels appear delayed. Is this a bug?
A: Divergence detection requires pivot confirmation, which needs bars on both sides of the pivot point. The label appears at the actual pivot location (several bars back) once confirmed. This is intentional and prevents false signals.
Q: Can I change the band colors?
A: Yes. Each of the three bands has its own color input setting. You can customize Band 1, Band 2, and Band 3 colors to match your preferences. The defaults are Aqua, Fuchsia, and Purple. The main VWAP line color adapts dynamically based on slope direction or can be set to static blue.
Q: How do I set up alerts?
A: Right-click on the chart, select Add Alert, choose this indicator, and select your desired condition from the dropdown. All conditions include descriptive alert messages with relevant data.
Q: What is the Probability Engine lookback period?
A: This setting determines how many trading days the indicator analyzes to calculate band touch rates and mean reversion statistics. Default is 60 days (approximately 3 months). Longer periods provide more stable statistics but may miss recent behavior changes.
Q: Why do I see fewer labels than expected?
A: Signal labels (Volume, Momentum, Squeeze, Divergence) are limited to 5 most recent labels on the chart to keep it clean. When a new label appears, the oldest one is automatically removed. Additionally, momentum labels have several filters: check the slope multiplier setting (higher values require stronger trends) and the Only Reversal Signals option (when enabled, labels only appear for potential reversals, not trend confirmations).
Q: What is the Calculated Projection and how accurate is it?
A: The Calculated Projection analyzes what happened in past market conditions similar to the current state. It classifies each bar by Z-Score level, Trend direction, and Volume profile (27 unique states), then shows the historical probability of up vs down and the average move size. It is NOT a price prediction or guarantee. The probability shown is how often similar conditions led to up/down moves historically, not a future guarantee. Always use it as one input among many.
Q: Why does the Projection probability change?
A: The projection updates on each bar as market state changes. If Z-Score moves from LOW to MID, or trend shifts from UP to FLAT, the system looks up a different historical category. This is expected behavior. The projection shows what happened in similar past conditions to the current bar's state.
Q: The Projection shows LOW confidence. What does that mean?
A: Confidence levels indicate sample size: HIGH means 30 or more historical cases found, MEDIUM means 15-29 cases, LOW means fewer than 15 cases. When sample size is low, the system uses a fallback: first aggregating by Z-Score plus Trend only (ignoring volume), then by Z-Score only. LOW confidence means less statistical reliability, so weight other factors more heavily in your decision.
Q: Why does the cone sometimes show 50/50 probability?
A: A 50/50 reading means that in similar past market states, price moved up roughly half the time and down half the time. This indicates a neutral or balanced condition where historical patterns provide no directional edge. Consider waiting for a higher probability setup or using other analysis methods.
CREDITS AND ACKNOWLEDGMENTS
Methodology Foundation:
VWAP (Volume Weighted Average Price) - Standard institutional benchmark calculation, widely used since the 1980s for algorithmic execution and fair value assessment
Standard Deviation Bands - Statistical volatility measurement applying normal distribution principles to price deviation from mean
Z-Score Analysis - Classic statistical normalization technique for comparing values across different volatility regimes
Cumulative Volume Delta (CVD) - Order flow analysis concept measuring aggressive buying versus selling pressure
Concept Integration:
Mean reversion probability engine - Custom historical statistics tracking for band touch rates
Momentum acceleration detection - Second derivative analysis of VWAP slope changes
VWAP Squeeze - Volatility compression concept adapted from TTM Squeeze methodology applied to VWAP bands versus ATR
Confidence scoring system - Weighted composite scoring combining multiple technical factors
Calculated Projection Cone - Probability-based projection using 27-state market classification (Z-Score, Trend, Volume) with historical outcome analysis and weighted fallback system
All calculations use standard public domain formulas and TradingView built-in functions. No proprietary third-party code was used.
For questions, feedback, or feature requests, please comment below or send a private message.
Happy Trading!
CriptoAlert AutoPlot (parser robusto)CriptoAlert AutoPlot is a utility indicator designed for traders who receive structured trading signals and want to automatically plot entry zones, targets, and stop levels on their TradingView chart — without manually drawing horizontal lines.
This tool is ideal for users of Cripto.Alert or any trading methodology that outputs price levels in text format.
How It Works
Paste your full text-based trading signal into the input box, and the indicator automatically:
Parses the text
Extracts the following price levels:
Entry Min
Entry Max
Target 1
Target 2
Target 3
Stop
Draws horizontal dotted lines corresponding to each level
Adjusts dynamically whenever you replace the signal text
Allows you to hide all lines instantly using the “Clear values” toggle
Lines behave exactly like native TradingView horizontal lines — they stay fixed to price regardless of zoom level or time frame.
Supported Input Format
Paste the full signal in a single line or multi-line format.
The parser is flexible and recognizes the standard Cripto.Alert structure:
Entrada: 0.882438 até 1.029428
Alvos:
1- 0.560266 (41.39%)
2- 0.362432 (62.09%)
3- 0.164599 (82.78%)
Stop: 1.100001 (15.07%)
You may also place everything on one line:
Entrada: 0.882438 até 1.029428 Alvos: 1- 0.560266 | 2- 0.362432 | 3- 0.164599 Stop: 1.100001
Example of Extracted Values
After parsing, the indicator internally produces:
Entry Min: 0.882438
Entry Max: 1.029428
Target 1: 0.560266
Target 2: 0.362432
Target 3: 0.164599
Stop: 1.100001
These values are plotted automatically.
Features
Automatic parsing of trading signal text
Horizontal dotted lines with adjustable opacity
Layout-friendly design
Clear-all option for quick chart cleanup
Works on any market and any timeframe
Reliable even when zooming or scaling the chart
Ideal For
Cripto.Alert users
Professional and retail traders
Swing traders and scalpers using multiple price levels
Educators who want clean chart templates for teaching
Anyone who frequently plots multiple horizontal levels manually
Limitations
Only parses numbers in the standard Cripto.Alert signal format
Does not calculate risk/reward or validate signal quality
Does not provide buy/sell recommendations
This indicator is purely a visual aid to speed up your charting workflow.
Simulateur Carnet d'Ordres & Liquidité [Sese] - Custom🔹 Indicator Name
Order Book & Liquidity Simulator - Custom
🔹 Concept and Functionality
This indicator is a technical analysis tool designed to visually simulate market depth (Order Book) and potential liquidity zones.
It is important to adhere to TradingView's transparency rules: This script does not access real Level 2 data (the actual exchange order book). Instead, it uses a deductive algorithm based on historical Price Action to estimate where Buy Limit (Bid) and Sell Limit (Ask) orders might be resting.
Methodology used by the script:
Pivot Detection: The indicator scans for significant Swing Highs and Swing Lows over a user-defined lookback period (Length).
Level Projection: These pivots are projected to the right as horizontal lines.
Red Lines (Ask): Represent potential resistance zones (sellers).
Blue Lines (Bid): Represent potential support zones (buyers).
Liquidity Management (Absorption): The script is dynamic. If the current price crosses a line, the indicator assumes the liquidity at that level has been consumed (orders filled). The line is then automatically deleted from the chart.
Density Profile (Right Side): Horizontal bars appear to the right of the current price. These approximate a "Time Price Opportunity" or Volume Profile, showing where the market has spent the most time recently.
🔹 User Manual (Settings)
Here is how to configure the inputs to match your trading style:
1. Detection Algorithm
Lookback Length (Candles): Determines the sensitivity of the pivots.
Low value (e.g., 10): Shows many lines (scalping/short term).
High value (e.g., 50): Shows only major structural levels (swing trading).
Volume Factor: (Technical note: In this specific code version, this variable is calculated but the lines are primarily drawn based on geometric pivots).
2. Visual Settings
Show Price Lines (Bid/Ask): Toggles the horizontal Support/Resistance lines on or off.
Show Volume Profile: Toggles the heatmap-style bars on the right side of the chart.
Extend Lines: If checked, untouched lines will extend to the right towards the current price bar.
3. Colors and Transparency Management
Customize the aesthetics to keep your chart clean:
Bid / Ask Colors: Choose your base colors (Default is Blue and Red).
Line Transparency (%): Crucial for chart visibility.
0% = Solid, bright colors.
80-90% = Very subtle, faint lines (recommended if you overlay this on other tools).
Text Size: Adjusts the size of the price labels ("BUY LIMIT" / "SELL LIMIT").
🔹 How to Read the Indicator
Rejections: Unbroken lines act as potential walls. Watch for price reaction when approaching a blue line (support) or red line (resistance).
Breakouts/Absorption: When a line disappears, it means the level has been breached. The market may then seek the next liquidity level (the next line).
Density (Right-side boxes): More opaque/visible boxes indicate a price zone "accepted" by the market (consolidation). Empty gaps suggest an imbalance where price might move through quickly.
⚠️ Disclaimer
This script is for educational and technical analysis purposes only. It is a simulation based on price history, not real-time order book data. Past performance is not indicative of future results. Trading involves risk.
[ArchLabs] Support & Resitance Levels Support & Resistance Levels — SR-v1.100
Smart, auto-managed zones for clean market structure
⸻
🔍 What this indicator does
This script automatically finds and maintains high-quality support & resistance zones on your chart, so you don’t have to keep redrawing levels by hand.
It:
• Detects major swing highs and lows (pivots)
• Builds support and resistance zones (not just thin lines)
• Filters out overlapping / redundant levels
• Tracks how price interacts with those zones in real time
• Marks and alerts:
• ✅ Breakouts
• 🚨 False breakouts
• 🔁 Retests
• Flips broken support → resistance and resistance → support automatically
You get a clean structural map of the market, continuously updated.
⸻
🧠 How levels are built (conceptually)
1. The indicator looks back over a configurable window and finds significant highs and lows (pivots).
2. From each confirmed pivot, it creates:
• A core level price (horizontal line)
• A price area around it (shaded zone), sized relative to recent price range/volatility
3. It then checks for overlaps between existing levels and new candidates:
• If a new level is too close to an existing one (within your overlap threshold), it gets discarded.
• This keeps only the most meaningful, non-redundant levels on the chart.
4. A cap of around 10 levels per side (support / resistance) keeps the view readable.
The result: a curated set of zones that actually matter, not a wall of lines.
⸻
🎨 Visuals on the chart
You’ll see:
• Support zones
• Line: bullish color (default green)
• Area: semi-transparent band below/around the line
• Resistance zones
• Line: bearish color (default red)
• Area: semi-transparent band above/around the line
Colors are customizable for:
• Level line
• Zone area
• Breakout highlight
• Retest label
This makes it easy to visually separate support vs resistance and quickly spot key reactions.
⸻
⚡ Dynamic behavior & level lifecycle
Each level goes through a natural “life cycle,” which the indicator tracks for you:
1. Active zone
• The level is valid and extended to the right as long as price stays “engaged” with it (using smoothed highs/lows to avoid noise).
2. Extension / pause
• When price pulls away from the level far enough, the extension can temporarily stop so the level doesn’t stretch indefinitely without interaction.
• If price comes back into the zone with meaningful action, the level can resume extension.
3. Break & role reversal
• When price cleanly breaks the level (based on smoothed price, not just a wick), the zone is:
• Stopped and locked in place
• Marked as broken
• Immediately cloned and flipped:
• Broken support becomes a new resistance zone at the same area.
• Broken resistance becomes a new support zone.
This gives you automatic role-reversal levels without manually redrawing anything.
⸻
🧷 Event tags & alerts
The indicator tracks three key interactions with each zone:
1. Breakouts (optional)
When price decisively breaks a level:
• A small breakout label appears on/near the level:
• Support broken → bearish breakout style
• Resistance broken → bullish breakout style
• An alert message is fired (if alerts are enabled on the script)
Use this to catch true structural breaks that may signal trend continuation or regime change.
⸻
2. False breakouts (optional)
False breakouts are marked when price:
• Wicks through a level, but
• Fails to close beyond it and quickly returns inside the zone
When detected:
• A 🚨 FB label appears at the level
• The label tracks with price while the false breakout is active
• An alert can fire each time this behavior is confirmed
This is very useful for reversal traders and anyone fading failed breakouts.
⸻
3. Retests (optional)
Retests are detected when:
• Price re-enters a zone after previously moving away from it
• The candle comes back into the area for the first time in this new approach
The script:
• Marks the retest with a “T” label in a distinct color for support vs resistance
• Brings that level to the top of the internal priority list, keeping fresh retests visually and logically “hot”
Traders often use these as high-probability reaction points (e.g., breakout → retest → continuation).
⸻
⚙️ Key settings
All inputs are grouped for clarity:
Support / Resistance Levels
• Pivots Lookback
Controls how far back the indicator looks for swing highs/lows.
• Higher value → fewer, stronger levels
• Lower value → more reactive, more levels
• Overlap Multiplier (Pips)
Sets how aggressively overlapping levels are merged/ignored.
• Higher value → fewer levels, more consolidation
• Lower value → more granular levels
• Auto Overlap
When enabled, the script automatically adjusts the overlap threshold based on timeframe:
• Intraday lower timeframes → tighter filtering
• Higher/intra-session → more appropriate scaling
This lets you drop the indicator on multiple timeframes without constantly retuning.
⸻
Level Event Toggles
• Breakout Labels & Alerts (on/off)
• False Breakout Labels & Alerts (on/off)
• Retest Labels & Alerts (on/off)
Turn on only what fits your style.
Scalpers might want all three; swing traders may prefer only breakouts + retests.
⸻
Support / Resistance Colors
Separate color groups for:
• Line & area of support levels
• Line & area of resistance levels
• Visual styling for breakouts
• Visual styling for retests
You can match your existing chart theme or build a dedicated SR layout.
⸻
📈 How to use it in your trading
Here are a few practical ways to integrate this indicator:
• Context map
Use it as a structural overlay on any symbol/timeframe to see where price is likely to react.
• Breakout + retest setups
• Wait for a level to break with a breakout label.
• Then watch for a T (retest) label into the flipped zone.
• Combine with your own confirmation (price action, volume, oscillators, etc.).
• Mean-reversion & fade trades
• Hunt for false breakout (FB) labels on key levels.
• These are often good spots to fade aggressive moves that lose momentum.
• Confluence builder
• Combine zones with trend tools, VR/DC, moving averages, or higher timeframe structure.
• A breakout/retest at a level that also lines up with higher TF structure can be especially meaningful.
⸻
✅ Summary
Support & Resistance Levels (SR-v1.100) is designed to be:
• Clean – no cluttered spaghetti of lines
• Adaptive – zones evolve with the market and flip roles automatically
• Actionable – breakout, false breakout, and retest events are clearly marked and alert-ready
• Flexible – works on any market and timeframe with simple, intuitive inputs
Drop it on your chart, tune the lookback & overlap to your style, and let it handle the heavy lifting of structural mapping while you focus on decisions.
Power RSI Segment Runner [CHE] Power RSI Segment Runner — Tracks RSI momentum across higher timeframe segments to detect directional switches for trend confirmation.
Summary
This indicator calculates a running Relative Strength Index adapted to segments defined by changes in a higher timeframe, such as daily closes, providing a smoothed view of momentum within each period. It distinguishes between completed segments, which fix the final RSI value, and ongoing ones, which update in real time with an exponential moving average filter. Directional switches between bullish and bearish momentum trigger visual alerts, including overlay lines and emojis, while a compact table displays current trend strength as a progress bar. This segmented approach reduces noise from intra-period fluctuations, offering clearer signals for trend persistence compared to standard RSI on lower timeframes.
Motivation: Why this design?
Standard RSI often generates erratic signals in choppy markets due to constant recalculation over fixed lookback periods, leading to false reversals that mislead traders during range-bound or volatile phases. By resetting the RSI accumulation at higher timeframe boundaries, this indicator aligns momentum assessment with broader market cycles, capturing sustained directional bias more reliably. It addresses the gap between short-term noise and long-term trends, helping users filter entries without over-relying on absolute overbought or oversold thresholds.
What’s different vs. standard approaches?
- Baseline Reference: Diverges from the classic Wilder RSI, which uses a fixed-length exponential moving average of gains and losses across all bars.
- Architecture Differences:
- Segments momentum resets at higher timeframe changes, isolating calculations per period instead of continuous history.
- Employs persistent sums for ups and downs within segments, with on-the-fly RSI derivation and EMA smoothing.
- Integrates switch detection logic that clears prior visuals on reversal, preventing clutter from outdated alerts.
- Adds overlay projections like horizontal price lines and dynamic percent change trackers for immediate trade context.
- Practical Effect: Charts show discrete RSI endpoints for past segments alongside a curved running trace, making momentum evolution visually intuitive. Switches appear as clean, extendable overlays, reducing alert fatigue and highlighting only confirmed directional shifts, which aids in avoiding whipsaws during minor pullbacks.
How it works (technical)
The indicator begins by detecting changes in the specified higher timeframe, such as a new daily bar, to define segment boundaries. At each boundary, it finalizes the prior segment's RSI by summing positive and negative price changes over that period and derives the value from the ratio of those sums, then applies an exponential moving average for smoothing. Within the active segment, it accumulates ongoing ups and downs from price changes relative to the source, recalculating the running RSI similarly and smoothing it with the same EMA length.
Points for the running RSI are collected into an array starting from the segment's onset, forming a curved polyline once sufficient bars accumulate. Comparisons between the running RSI and the last completed segment's value determine the current direction as long, short, or neutral, with switches triggering deletions of old visuals and creation of new ones: a label at the RSI pane, a vertical dashed line across the RSI range, an emoji positioned via ATR offset on the price chart, a solid horizontal line at the switch price, a dashed line tracking current close, and a midpoint label for percent change from the switch.
Initialization occurs on the first bar by resetting accumulators, and visualization gates behind a minimum bar count since the segment start to avoid early instability. The trend strength table builds vertically with filled cells proportional to the rounded RSI value, colored by direction. All drawing objects update or extend on subsequent bars to reflect live progress.
Parameter Guide
EMA Length — Controls the smoothing applied to the running RSI; higher values increase lag but reduce noise. Default: 10. Trade-offs: Shorter settings heighten sensitivity for fast markets but risk more false switches; longer ones suit trending conditions for stability.
Source — Selects the price data for change calculations, typically close for standard momentum. Default: close. Trade-offs: Open or high/low may emphasize gaps, altering segment intensity.
Segment Timeframe — Defines the higher timeframe for segment resets, like daily for intraday charts. Default: D. Trade-offs: Shorter frames create more frequent but shorter segments; longer ones align with major cycles but delay resets.
Overbought Level — Sets the upper threshold for potential overbought conditions (currently unused in visuals). Default: 70. Trade-offs: Adjust for asset volatility; higher values delay bearish warnings.
Oversold Level — Sets the lower threshold for potential oversold conditions (currently unused in visuals). Default: 30. Trade-offs: Lower values permit deeper dips before signaling bullish potential.
Show Completed Label — Toggles labels at segment ends displaying final RSI. Default: true. Trade-offs: Enables historical review but can crowd charts on dense timeframes.
Plot Running Segment — Enables the curved polyline for live RSI trace. Default: true. Trade-offs: Visualizes intra-segment flow; disable for cleaner panes.
Running RSI as Label — Displays current running RSI as a forward-projected label on the last bar. Default: false. Trade-offs: Useful for quick reads; may overlap in tight scales.
Show Switch Label — Activates RSI pane labels on directional switches. Default: true. Trade-offs: Provides context; omit to minimize pane clutter.
Show Switch Line (RSI) — Draws vertical dashed lines across the RSI range at switches. Default: true. Trade-offs: Marks reversal bars clearly; extends both ways for reference.
Show Solid Overlay Line — Projects a horizontal line from switch price forward. Default: true. Trade-offs: Acts as dynamic support/resistance; wider lines enhance visibility.
Show Dashed Overlay Line — Tracks a dashed line from switch to current close. Default: true. Trade-offs: Shows price deviation; thinner for subtlety.
Show Percent Change Label — Midpoint label tracking percent move from switch. Default: true. Trade-offs: Quantifies progress; centers dynamically.
Show Trend Strength Table — Displays right-side table with direction header and RSI bar. Default: true. Trade-offs: Instant strength gauge; fixed position avoids overlap.
Activate Visualization After N Bars — Delays signals until this many bars into a segment. Default: 3. Trade-offs: Filters immature readings; higher values miss early momentum.
Segment End Label — Color for completed RSI labels. Default: 7E57C2. Trade-offs: Purple tones for finality.
Running RSI — Color for polyline and running elements. Default: yellow. Trade-offs: Bright for live tracking.
Long — Color for bullish switch visuals. Default: green. Trade-offs: Standard for uptrends.
Short — Color for bearish switch visuals. Default: red. Trade-offs: Standard for downtrends.
Solid Line Width — Thickness of horizontal overlay line. Default: 2. Trade-offs: Bolder for emphasis on key levels.
Dashed Line Width — Thickness of tracking and vertical lines. Default: 1. Trade-offs: Finer to avoid dominance.
Reading & Interpretation
Completed segment RSIs appear as static points or labels in purple, indicating the fixed momentum at period close—values drifting toward the upper half suggest building strength, while lower half implies weakness. The yellow curved polyline traces the live smoothed RSI within the current segment, rising for accumulating gains and falling for losses. Directional labels and lines in green or red flag switches: green for running momentum exceeding the prior segment's, signaling potential uptrend continuation; red for the opposite.
The right table's header colors green for long, red for short, or gray for neutral/wait, with filled purple bars scaling from bottom (low RSI) to top (high), topped by the numeric value. Overlay elements project from switch bars: the solid green/red line as a price anchor, dashed tracker showing pullback extent, and percent label quantifying deviation—positive for alignment with direction, negative for counter-moves. Emojis (up arrow for long, down for short) float above/below price via ATR spacing for quick chart scans.
Practical Workflows & Combinations
- Trend Following: Enter long on green switch confirmation after a higher high in structure; filter with table strength above midpoint for conviction. Pair with volume surge for added weight.
- Exits/Stops: Trail stops to the solid overlay line on pullbacks; exit if percent change reverses beyond 2 percent against direction. Use wait bars to confirm without chasing.
- Multi-Asset/Multi-TF: Defaults suit forex/stocks on 1H-4H with daily segments; for crypto, shorten EMA to 5 for volatility. Scale segment TF to weekly for daily charts across indices.
- Combinations: Overlay on EMA clouds for confluence—switch aligning with cloud break strengthens signal. Add volatility filters like ATR bands to debounce in low-volume regimes.
Behavior, Constraints & Performance
Signals confirm on bar close within segments, with running polyline updating live but gated by minimum bars to prevent flicker. Higher timeframe changes may introduce minor repaints on timeframe switches, mitigated by relying on confirmed HTF closes rather than intrabar peeks. Resource limits cap at 500 labels/lines and 50 polylines, pruning old objects on switches to stay efficient; no explicit loops, but array growth ties to segment length—suitable for up to 500-bar histories without lag.
Known limits include delayed visualization in short segments and insensitivity to overbought/oversold levels, as thresholds are inputted but not actively visualized. Gaps in source data reset accumulators prematurely, potentially skewing early RSI.
Sensible Defaults & Quick Tuning
Start with EMA length 10, daily segments, and 3-bar wait for balanced responsiveness on hourly charts. For excessive switches in ranging markets, increase wait bars to 5 or EMA to 14 to dampen noise. If signals lag in trends, drop EMA to 5 and use 1H segments. For stable assets like indices, widen to weekly segments; tune colors for dark/light themes without altering logic.
What this indicator is—and isn’t
This tool serves as a momentum visualization and switch detector layered over price action, aiding trend identification and confirmation in segmented contexts. It is not a standalone trading system, predictive model, or risk calculator—always integrate with broader analysis, position sizing, and stop-loss discipline. View it as an enhancement for discretionary setups, not automated alerts without validation.
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.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
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.
MA Signal IndicatorMA Signal Indicator
The MA Signal Indicator is a customizable designed to identify potential trading opportunities based on price interactions with a Simple Moving Average (SMA). It incorporates risk management features such as stop-loss (SL), take-profit (TP), and breakeven levels, calculated using the Average True Range (ATR). The indicator is visually intuitive, overlaying trade signals, price levels, and colored zones directly on the chart.
Key Features:
1. Moving Average-Based Signals:
• Generates buy (long) signals when the price crosses above a user-defined SMA (default: 55 periods).
• Generates sell (short) signals when the price crosses below the SMA.
• Long and short trades can be independently enabled or disabled via input settings.
2. Risk Management:
• Stop-Loss (SL): Set as a multiple of the ATR (default: 1x ATR) below the entry price for long trades or above for short trades.
• Take-Profit (TP): Set as a multiple of the ATR (default: 5x ATR) above the entry price for long trades or below for short trades.
• Breakeven Level: A trigger level (default: 2x ATR) where traders may choose to move their stop-loss to breakeven, optionally displayed on the chart.
3. Visual Feedback:
• SMA Line: Plotted in orange (default: 55-period SMA) for trend reference.
• Trade Zone: Highlights the area between the stop-loss and take-profit levels with a semi-transparent green (long) or red (short) background.
• Price Lines: Displays entry price (white), stop-loss (red), take-profit (green), and breakeven level (gray, optional) as horizontal lines during active trades.
• Signal Markers: Triangular markers indicate entry points (green triangle up for long, red triangle down for short).
• Exit Markers: Labels show when a trade hits the take-profit (green checkmark) or stop-loss (red cross).
4. Trade Logic:
• Only one trade is active at a time (long or short).
• Trades are exited when either the stop-loss or take-profit is hit, resetting the indicator for the next signal.
• Ensures signals are only triggered when not already in a trade, avoiding duplicate entries.
Inputs:
• MA Period: Length of the SMA (default: 55).
• ATR Period: Period for ATR calculation (default: 5).
• SL Multiplier: ATR multiplier for stop-loss (default: 1.0).
• TP Multiplier: ATR multiplier for take-profit (default: 5.0).
• Move to Breakeven After: ATR multiplier for breakeven trigger (default: 2.0).
• Show Break Even Line: Option to display the breakeven level (default: true).
• Allow Long Trades: Enable/disable long signals (default: true).
• Allow Short Trades: Enable/disable short signals (default: true).
Use Case:
This indicator is ideal for trend-following traders who want a clear, visual system for entering and exiting trades based on SMA crossovers, with predefined risk and reward levels. It suits both manual and automated trading strategies, providing flexibility to adjust parameters for different markets or timeframes.
Notes:
• The indicator is overlaid on the price chart for easy integration with other analysis tools.
• Users should test and adjust parameters (e.g., MA length, ATR multipliers) to suit their trading style and market conditions.
• The breakeven line is a visual guide; manual adjustment of stops is required as the indicator does not automatically modify trade positions.
This indicator provides a robust framework for disciplined trading with clear entry, exit, and risk management visuals.
First Candle🕯️ First Candle Indicator (First 5-Minute Candle High/Low)
The First Candle indicator automatically marks the high and low of the first 5-minute candle of the U.S. trading session . These levels can act as key intraday support and resistance zones, often used in breakout, scalping, or opening-range trading strategies.
📌 Key Features:
Automatic detection of the first candle of the U.S. session based on the selected timeframe (default is 5 minutes).
Horizontal lines are plotted at the high and low of that candle, with fully customizable colors and thickness.
Labels show the exact level and timeframe used for the high and low.
Resets daily, removing previous session data at the start of a new session.
Displays a visual marker (blue triangle) when the first candle is detected.
Allows users to select different timeframes for defining the "first candle" (e.g., 1, 5, 15 minutes).
⚙️ Customizable Inputs:
Show First Candle Lines: toggle the display of high/low lines.
Timeframe for Marking: choose the timeframe to detect the first candle (e.g., 5 minutes).
High Line Color / Low Line Color: set the color of each level line.
Line Thickness: adjust the width of the lines (1 to 5 pixels).
🧠 Strategic Applications:
Identify breakout zones right after the market opens.
Define opening range for pullback or continuation setups.
Set clear reference levels for intraday trading decisions.
SMI-DarknessIndicator Description: SMI-Darkness
The SMI-Darkness is an indicator based on the Stochastic Momentum Index (SMI), designed to help identify the strength and direction of an asset's trend, as well as potential buy and sell signals. It displays a smoothed SMI using multiple moving average options to customize the indicator’s behavior according to the user’s trading style.
Main Features
Smoothed SMI: Calculates the traditional SMI and smooths it using a user-configurable moving average, improving signal clarity.
Signal Line: Displays a smoothed signal line to identify crossovers with the SMI, generating potential entry or exit points.
Histogram: Shows the difference between the smoothed SMI and the signal line, visually highlighting trend strength. Blue bars indicate buying strength, while yellow bars indicate selling strength.
Horizontal Lines: Includes overbought (+40) and oversold (-40) levels, plus a neutral zero level to aid interpretation.
Indicator Parameters
SMI Short Period: Sets the short period used to calculate the SMI (default 5). Lower periods make the indicator more sensitive.
SMI Signal Period: Sets the period to smooth the signal line (default 5). Adjust to control the signal line's smoothness.
Moving Average Type: Choose the moving average type to smooth the SMI and signal line. Options include:
SMA (Simple Moving Average)
SMMA (Smoothed Moving Average)
EMA (Exponential Moving Average)
WMA (Weighted Moving Average)
HMA (Hull Moving Average)
JMA (Jurik Moving Average) — Note: This is not an original or proprietary moving average but a publicly available open-source version created by TradingView users.
VWMA (Volume-Weighted Moving Average)
KAMA (Kaufman Adaptive Moving Average)
How to Use
Trend Identification: Observe the position of the smoothed SMI relative to the signal line and the histogram values.
When the histogram is positive (blue bars), momentum is bullish.
When the histogram is negative (yellow bars), momentum is bearish.
Buy and Sell Signals:
A crossover of the smoothed SMI above the signal line may indicate a buy signal.
A crossover of the smoothed SMI below the signal line may indicate a sell signal.
Overbought/Oversold Levels:
SMI values above +40 suggest potential overbought conditions, signaling caution on long positions.
Values below -40 suggest potential oversold conditions, indicating possible buying opportunities.
Customization: Adjust the parameters to balance sensitivity and noise, choosing the moving average type that best fits your trading style.
Enigma Sniper 369The "Enigma Sniper 369" is a custom-built Pine Script indicator designed for TradingView, tailored specifically for forex traders seeking high-probability entries during high-volatility market sessions.
Unlike generic trend-following or scalping tools, this indicator uniquely combines session-based "kill zones" (London and US sessions), momentum-based candle analysis, and an optional EMA trend filter to pinpoint liquidity grabs and reversal opportunities.
Its originality lies in its focus on liquidity hunting—identifying levels where stop losses are likely clustered (around swing highs/lows and wick midpoints)—and providing visual entry zones that are dynamically removed once price breaches them, reducing clutter and focusing on actionable signals.
The name "369" reflects the structured approach of three key components (session timing, candle logic, and trend filter) working in harmony to snipe precise entries.
What It Does
"Enigma Sniper 369" identifies potential buy and sell opportunities by drawing two types of horizontal lines on the chart during user-defined London and US
session kill zones:
Solid Lines: Mark the swing low (for buys) or swing high (for sells) of a trigger candle, indicating a potential entry point where stop losses might be clustered.
Dotted Lines: Mark the 50% level of the candle’s wick (lower wick for buys, upper wick for sells), serving as a secondary confirmation zone for entries or tighter stop-loss placement.
These lines are plotted only when specific candle conditions are met within the kill zones, and they are automatically deleted once the price crosses them, signaling that the liquidity at that level has likely been grabbed. The indicator also includes an optional EMA filter to ensure trades align with the broader trend, reducing false signals in choppy markets.
How It Works
The indicator’s logic is built on a multi-layered approach:
Kill Zone Timing: Trades are only considered during user-defined London and US session hours (e.g., London from 02:00 to 12:00 UTC, as seen in the screenshots). These sessions are known for high volatility and liquidity, making them ideal for capturing institutional moves.
Candle-Based Momentum Logic:
Buy Signal: A candle must close above its midpoint (indicating bullish momentum) and have a lower low than the previous candle (suggesting a potential liquidity grab below the previous swing low). This is expressed as close > (high + low) / 2 and low < low .
Sell Signal: A candle must close below its midpoint (bearish momentum) and have a higher high than the previous candle (indicating a potential liquidity grab above the previous swing high), expressed as close < (high + low) / 2 and high > high .
These conditions ensure the indicator targets candles that break recent structure to hunt stop losses while showing directional momentum.
Optional EMA Filter: A 50-period EMA (customizable) can be enabled to filter signals based on trend direction.
Buy signals are only generated if the EMA is trending upward (ema_value > ema_value ), and sell signals require a downward EMA trend (ema_value < ema_value ). This reduces noise by aligning entries with the broader market trend.
Liquidity Levels and Deletion Logic:
For a buy signal, a solid green line is drawn at the candle’s low, and a dotted green line at the 50% level of the lower wick (from the candle body’s bottom to the low).
For a sell signal, a solid red line is drawn at the candle’s high, and a dotted red line at the 50% level of the upper wick (from the body’s top to the high).
These lines extend to the right until the price crosses them, at which point they are deleted, indicating the liquidity at that level has been taken (e.g., stop losses triggered).
Alerts: The indicator includes alert conditions for buy and sell signals, notifying traders when a new setup is identified.
Underlying Concepts
The indicator is grounded in the concept of liquidity hunting, a strategy often employed by institutional traders. Markets frequently move to levels where stop losses are clustered—typically just beyond swing highs or lows—before reversing in the opposite direction. The "Enigma Sniper 369" targets these moves by identifying candles that break structure (e.g., a lower low or higher high) during high-volatility sessions, suggesting a potential sweep of stop losses. The 50% wick level acts as a secondary confirmation, as this midpoint often represents a zone where tighter stop losses are placed by retail traders. The optional EMA filter adds a trend-following element, ensuring entries are taken in the direction of the broader market momentum, which is particularly useful on lower timeframes like the 15-minute chart shown in the screenshots.
How to Use It
Here’s a step-by-step guide based on the provided usage example on the GBP/USD 15-minute chart:
Setup the Indicator: Add "Enigma Sniper 369" to your TradingView chart. Adjust the London and US session hours to match your timezone (e.g., London from 02:00 to 12:00 UTC, US from 13:00 to 22:00 UTC). Customize the EMA period (default 50) and line styles/colors if desired.
Identify Kill Zones: The indicator highlights the London session in light green and the US session in light purple, as seen in the screenshots. Focus on these periods for signals, as they are the most volatile and likely to produce liquidity grabs.
Wait for a Signal: Look for solid and dotted lines to appear during the kill zones:
Buy Setup: A solid green line at the swing low and a dotted green line at the 50% lower wick level indicate a potential buy. This suggests the market may have grabbed liquidity below the swing low and is now poised to move higher.
Sell Setup: A solid red line at the swing high and a dotted red line at the 50% upper wick level indicate a potential sell, suggesting liquidity was taken above the swing high.
Place Your Trade:
For a buy, set a buy limit order at the dotted green line (50% wick level), as this is a more conservative entry point. Place your stop loss just below the solid green line (swing low) to cover the full swing. For example, in the screenshots, the market retraces to the dotted line at 1.32980 after a liquidity grab below the swing low, triggering a buy limit order.
For a sell, set a sell limit order at the dotted red line, with a stop loss just above the solid red line.
Monitor Price Action: Once the price crosses a line, it is deleted, indicating the liquidity at that level has been taken. In the screenshots, after the buy limit is triggered, the market moves higher, confirming the setup. The caption notes, “The market returns and tags us in long with a buy limit,” highlighting this retracement strategy.
Additional Context: Use the indicator to identify liquidity levels that may be targeted later. For example, the screenshot notes, “If a new session is about to open I will wait for the grab liquidity to go long,” showing how the indicator can be used to anticipate future moves at session opens (e.g., London open at 1.32980).
Risk Management: Always set a stop loss below the swing low (for buys) or above the swing high (for sells) to protect against adverse moves. The 50% wick level helps tighten entries, improving the risk-reward ratio.
Practical Example
On the GBP/USD 15-minute chart, during the London session (02:00 UTC), the indicator identifies a buy setup with a solid green line at 1.32901 (swing low) and a dotted green line at 1.32980 (50% wick level). The market initially dips below the swing low, grabbing liquidity, then retraces to the dotted line, triggering a buy limit order. The price subsequently rises to 1.33404, yielding a profitable trade. The user notes, “The logic is in the last candle it provides new level to go long,” emphasizing the indicator’s ability to identify fresh levels after a liquidity sweep.
Customization Tips
Adjust the EMA period to suit your timeframe (e.g., a shorter period like 20 for faster signals on lower timeframes).
Modify the session hours to align with your broker’s timezone or specific market conditions.
Use the alert feature to get notified of new setups without constantly monitoring the chart.
Why It’s Useful for Traders
The "Enigma Sniper 369" stands out by combining session timing, momentum-based candle analysis, and liquidity hunting into a single tool. It provides clear, actionable levels for entries and stop losses, removes invalid signals dynamically, and aligns trades with high-probability market conditions. Whether you’re a scalper looking for quick moves during London open or a swing trader targeting session-based reversals, this indicator offers a structured, data-driven approach to trading.
BTC Mining Income Oscillator Z-ScoreBTC Mining Income Oscillator (Z-Score)
Overview
The BTC Mining Income Oscillator (Z-Score) is a custom technical indicator that analyzes Bitcoin mining income to help traders identify overbought and oversold conditions. The indicator uses a Z-Score to track deviations in mining income, highlighting periods of high or low mining profitability.
This indicator is made up of:
Z-Score Line (Blue): Measures how far the current mining income deviates from its historical mean.
Mining Income Oscillator (Orange): A scaled value of mining income that oscillates within a specific range to indicate overbought and oversold conditions.
How the Indicator Works
1. Mining Income Calculation
The BTC Mining Income is determined using two main factors:
Block Reward: The number of BTC miners earn for each block mined (currently 3.125 BTC, adjustable in settings).
Transaction Fees: The average transaction fees per block (default is 0.3 BTC).
Blocks per Day: The number of blocks mined per day (default is 144).
The daily mining income in BTC is calculated as:
Mining Income
=
(
Block Reward
+
Transaction Fees
)
×
Blocks per Day
Mining Income=(Block Reward+Transaction Fees)×Blocks per Day
This value is then converted to USD by multiplying it by the current Bitcoin price.
2. Z-Score Calculation
The Z-Score measures how far the current mining income deviates from its mean over a set period (default is 90 days). The Z-Score helps identify when mining income is unusually high or low:
A high Z-Score indicates that the mining income is significantly above the historical mean, signaling overbought conditions.
A low Z-Score indicates that the mining income is significantly below the historical mean, signaling oversold conditions.
The Z-Score is calculated as follows:
Z-Score
=
(
Current Mining Income
−
Mean Income
)
Standard Deviation
Z-Score=
Standard Deviation
(Current Mining Income−Mean Income)
The result is then smoothed over a period (default is 5) to reduce noise and provide a more stable value.
3. Mining Income Oscillator
The mining income is scaled to oscillate between +20 and +90. This oscillation makes it easy to track overbought and oversold conditions in the market:
Values between 85 and 90 indicate overbought conditions (high mining profitability).
Values between 20 and 22 indicate oversold conditions (low mining profitability).
Values between 22 and 85 indicate neutral conditions, where mining profitability is normal.
The mining income oscillator helps traders spot extreme conditions (overbought or oversold) in mining profitability.
How to Read the Indicator
1. Z-Score Line (Blue)
The Z-Score represents how far current mining income is from the historical average.
Above +2: The mining income is unusually high, indicating an overbought market.
Below -2: The mining income is unusually low, indicating an oversold market.
Between -2 and +2: This range is neutral, where the mining income is within the average historical range.
2. Mining Income Oscillator (Orange)
The Mining Income Oscillator is scaled between 20 and 90.
85–90: Overbought conditions, indicating high mining profitability.
20–22: Oversold conditions, indicating low mining profitability.
22–85: Neutral conditions, indicating moderate mining profitability.
3. Background Shading
Red Shading (85–90): Indicates overbought conditions (mining income is unusually high).
Green Shading (20–22): Indicates oversold conditions (mining income is unusually low).
The shaded regions provide a visual guide to spot periods when the market is overbought or oversold.
4. Key Horizontal Lines
0 Line: Represents the neutral level for the Z-Score, where the mining income is at the historical mean.
+2 and -2 Lines: Indicate overbought and oversold conditions for the Z-Score.
90 and 20 Lines: Indicate the upper and lower bounds for the mining income oscillator.
Where the Data Comes From
Bitcoin Price: The current Bitcoin price is pulled directly from the chart.
Block Reward and Transaction Fees: These values are set manually by the user or can be updated dynamically.
Mining Income: Calculated based on the block reward, transaction fees, and current Bitcoin price.
Z-Score and Oscillator Calculations: Both are calculated based on mining income in USD over a defined look-back period.
Best Timeframe for This Indicator
This indicator is designed to work best on the 2-day chart (2D) timeframe. On the 2-day chart, the mining income data, Z-Score, and the oscillator are less sensitive to noise and short-term volatility, providing more reliable signals. While it can be used on other timeframes, the 2-day chart offers the clearest and most stable analysis.
